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Case Studies in Finance links managerial decisions to capital markets and the expectations of investors. At the core of almost all of the cases is a valuation task that requires students to look to financial markets for guidance in resolving the case problem. These cases also invite students to apply modern information technology to the analysis of managerial decisions. In the Seventh Edition, 25% of the cases are new with many dating from 2011–2012, ensuring that your students are learning from the most relevant and current sources.

Visit the Online Learning Center at www.mhhe.com/bruner7e to see a complete list of changes to the Seventh Edition and to access study and teaching tools.

Bruner Eades S chi l l

Case Studies in Finance

managing for corporate value creation

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Bruner Eades Schil l

Case Studies in Finance managing for corporate value creation

seventh edition

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Case Studies in Finance

Managing for Corporate Value Creation

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Case Studies in Finance

Managing for Corporate Value Creation

Seventh Edition

Robert F. Bruner Kenneth M. Eades Michael J. Schill

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CASE STUDIES IN FINANCE: MANAGING FOR CORPORATE VALUE CREATION, SEVENTH EDITION

Published by McGraw-Hill, a business unit of The McGraw-Hill Companies, Inc., 1221 Avenue of the Americas, New York, NY, 10020. Copyright © 2014 by The McGraw-Hill Companies, Inc. All rights reserved. Printed in the United States of America. Previous editions © 2002, 1989, and 1975. No part of this publication may be reproduced or distributed in any form or by any means, or stored in a database or retrieval system, without the prior written consent of The McGraw-Hill Companies, Inc., including, but not limited to, in any network or other electronic storage or transmission, or broad- cast for distance learning.

Some ancillaries, including electronic and print components, may not be available to customers outside the United States.

This book is printed on acid-free paper.

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ISBN 978-0-07-786171-1 MHID 0-07-786171-X

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Library of Congress Cataloging-in-Publication Data

Bruner, Robert F., 1949- Case studies in finance : managing for corporate value creation / Robert F. Bruner, Kenneth M. Eades,

Michael J. Scholl.––Seventh Edition. pages cm

Includes index. ISBN-13: 978-0-07-786171-1 (alk. paper) ISBN-10: 0-07-786171-X (alk. paper) 1. Corporations––Finance––Case studies. 2. International business enterprises––Finance––Case studies.

I. Eades, Ken M. II. Schill, Michael J. III. Title. HG4015.5.B78 2013 658.15––dc23 2012046392

The Internet addresses listed in the text were accurate at the time of publication. The inclusion of a website does not indicate an endorsement by the authors or McGraw-Hill, and McGraw-Hill does not guarantee the accuracy of the information presented at these sites.

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The McGraw-Hill/Irwin Series in Finance, Insurance and Real Estate

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INVESTMENTS

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Bodie, Kane, and Marcus Essentials of Investments Ninth Edition

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In dedication to our wives

Barbara M. Bruner Kathy N. Eades

Mary Ann H. Schill

and to our children

Dedication

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Robert F. Bruner is Dean of the Darden Graduate School of Business Administration, Distinguished Professor of Business Administration and Charles C. Abbott Professor of Business Administration at the University of Virginia. He has taught and written in various areas, including corporate finance, mergers and acquisitions, investing in emerg- ing markets, innovation, and technology transfer. In addition to Case Studies in Finance, his books include Finance Interactive, multimedia tutorial software in Finance (Irwin/ McGraw-Hill 1997), The Portable MBA (Wiley 2003), Applied Mergers and Acquisitions, (Wiley, 2004), Deals from Hell: M&A Lessons that Rise Above the Ashes (Wiley, 2005) and The Panic of 1907 (Wiley, 2007). He has been recognized in the United States and Europe for his teaching and case writing. BusinessWeek magazine cited him as one of the “masters of the MBA classroom.” He is the author or co-author of over 400 case studies and notes. His research has been published in journals such as Financial Man- agement, Journal of Accounting and Economics, Journal of Applied Corporate Finance, Journal of Financial Economics, Journal of Financial and Quantitative Analysis, and Journal of Money, Credit, and Banking. Industrial corporations, financial institutions, and government agencies have retained him for counsel and training. He has been on the faculty of the Darden School since 1982, and has been a visiting professor at various schools including Columbia, INSEAD, and IESE. Formerly he was a loan officer and investment analyst for First Chicago Corporation. He holds the B.A. degree from Yale University and the M.B.A. and D.B.A. degrees from Harvard University. Copies of his papers and essays may be obtained from his website, http://www.darden.virginia.edu/ web/Faculty-Research/Directory/Full-time/Robert-F-Bruner/. He may be reached via email at [email protected]

About the Authors

Kenneth M. Eades is Professor of Business Administration and Area Coordinator of the Finance Department of the Darden Graduate School of Business Administration at the University of Virginia. He has taught a variety of corporate finance topics including: capital structure, dividend policy, risk management, capital investments and firm valuation. His research interests are in the area of corporate finance where he has published articles in The Journal of Finance, Journal of Financial Economics, Journal of Financial and Quantitative Analysis, and Financial Management. In addition to Case Studies in Finance, his books include The Portable MBA (Wiley 2010) Finance Interactive, a multimedia tutorial software in Finance (Irwin/McGraw-Hill 1997) and Case Studies in Financial Decision Making (Dry- den Press, 1994). He has written numerous case studies as well as a web-based, interactive tutorial on the pricing of financial derivatives. He has received the Wachovia Award for Excellence in Teaching Materials and the Wachovia Award for Excellence in Research. Mr. Eades is active in executive education programs at the Darden School and has served as a consultant to a number of corporations and institutions; including many commercial banks and investment banks; Fortune 500 companies and the Internal Revenue Service. Prior to joining Darden in 1988, Professor Eades was a member of the faculties at The University

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of Michigan and the Kellogg School of Management at Northwestern University. He has a B.S. from the University of Kentucky and Ph.D. from Purdue University. His website is http://www.darden.virginia.edu/web/Faculty-Research/Directory/Full-time/Kenneth-M- Eades/ and he may be reached via email at [email protected]

Michael J. Schill is Associate Professor of Business Administration of the Darden Graduate School of Business Administration at the University of Virginia where he teaches corporate finance and investments. His research spans empirical questions in corporate finance, investments, and international finance. He is the author of numerous articles that have been published in leading finance journals such as Journal of Business, Journal of Finance, Journal of Financial Economics, and Review of Financial Studies, and cited by major media outlets such as The Wall Street Journal. Some of his recent research projects investigate the market pricing of firm growth and the corporate gains to foreign stock exchange listing or foreign currency borrowing. He has been on the faculty of the Darden School since 2001 and was previously with the University of California, Riverside, as well as a visiting professor at Cambridge and Melbourne. Prior to his doctoral work, he was a management consultant with Marakon Associates in Stamford and London. He continues to be active in consult- ing and executive education for major corporations. He received a B.S. degree from Brigham Young University, an M.B.A. from INSEAD, and a Ph.D. from University of Washington. More details are available from his website, http://www.darden.vir- ginia.edu/web/Faculty-Research/Directory/Full-time/ Michael-J-Schill/. He may be reached via email at [email protected]

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Dedication vii About the Authors viii Contents x Foreword xiii Preface xiv Note to the Student: How To Study and Discuss Cases xxv Ethics in Finance xxxii

Setting Some Themes 1. Warren E. Buffett, 2005 To think like an investor 3 2. Bill Miller and Value Trust Market efficiency 23 3. Ben & Jerry’s Homemade Value creation and governance 39 4. The Battle for Value, 2004: FedEx Corp. vs. Value creation and economic profit 53

United Parcel Service, Inc. 5. Genzyme and Relational Investors: Science Value creation, business strategy and activist investors 75

and Business Collide?

Financial Analysis and Forecasting 6. The Thoughtful Forecaster Forecasting principles 101 7. The Financial Detective, 2005 Ratio analysis 119 8. Krispy Kreme Doughnuts, Inc. Financial statement analysis 125 9. The Body Shop International PLC 2001: Introduction to forecasting 143

An Introduction to Financial Modeling 10. Value Line Publishing: October 2002 Financial ratios and forecasting 161 11. Horniman Horticulture Analysis of growth and bank financing 175 12. Guna Fibres, Ltd. Forecasting seasonal financing needs 181

Estimating the Cost of Capital 13. “Best Practices” in Estimating the Cost Estimating the cost of capital 193

of Capital: Survey and Synthesis” 14. Roche Holdings AG: Funding the Genentech Cost of debt capital 219

Acquisition 15. Nike, Inc.: Cost of Capital Cost of capital for the firm 235 16. Teletech Corporation, 2005 Business segments and risk-return tradeoffs 243 17. The Boeing 7E7 Project specific risk-return 257

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Capital Budgeting and Resource Allocation 18. The Investment Detective Investment criteria and discounted cash flow 283 19. Worldwide Paper Company Analysis of an expansion investment 285 20. Target Corporation Multifaceted capital investment decisions 289 21 Aurora Textile Company Analysis of an investment in a declining industry 311 22. Compass Records Analysis of working capital investment 323 23 The Procter and Gamble Company: Scenario analysis in a project decision 337

Investment in Crest Whitestrips Advanced Seal

24. Victoria Chemicals plc (A): Relevant cash flows 349 The Merseyside Project

25 Victoria Chemicals plc (B): The Merseyside Mutually exclusive investment opportunities 357 and Rotterdam Projects

26. Star River Electronics Ltd. Capital project analysis and forecasting 365 27. The Jacobs Division 2010 Strategic planning 373 28. University of Virginia Health System: Analysis of an investment in a not-for-profit 381

The Long-Term Acute Care Hospital organization Project

Management of the Firm’s Equity: Dividends and Repurchases 29. Gainesboro Machine Tools Corporation Dividend payout decision 393 30. AutoZone, Inc. Dividend and stock buyback decisions 409

Management of the Corporate Capital Structure 31. An Introduction to Debt Policy and Value Effects of debt tax shields 425 32. Structuring Corporate Financial Policy: Concepts in setting financial policy 431

Diagnosis of Problems and Evaluation of Strategies

33. California Pizza Kitchen Optimal leverage 449 34. The Wm. Wrigley Jr. Company: Capital Leveraged restructuring 467

Structure, Valuation, and Cost of Capital 35. Deluxe Corporation Financial flexibility 479 36. Horizon Lines, Inc. Bankruptcy/restructuring 497

Analysis of Financing Tactics: Leases, Options, and Foreign Currency 37. Carrefour S.A. Currency risk management 513 38. Baker Adhesives Hedging foreign currency cash flows 523 39. J&L Railroad Risk management and hedging commodity risk 529 40. Primus Automation Division, 2002 Economics of lease financing 541 41. MoGen, Inc. Convertible bond valuation and financial engineering 553

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8Valuing the Enterprise: Acquisitions and Buyouts42. Methods of Valuation for Mergers Valuation principles 569and Acquisitions43. American Greetings Firm valuation in stock repurchase decision 589 44. Arcadian Microarray Technologies, Inc. Evaluating terminal values 599 45. JetBlue Airways IPO Valuation Initial public offering valuation 617 46. Rosetta Stone: Pricing the 2009 IPO Initial public offering valuation 635 47. The Timken Company Financing an acquisition 655 48. Sun Microsystems Valuing a takeover opportunity 671 49. Hershey Foods Corporation: Bitter Corporate governance influence 693

Times in a Sweet Place 50. Flinder Valves and Controls Inc. Valuing the enterprise for sale 715 51. Palamon Capital Partners/TeamSystem Valuing a private equity investment 727

S.p.A. 52. Purinex, Inc. Financing the early-stage firm 745 53. Medfield Pharmaceuticals Valuing strategic alternatives 755

xii Contents

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The half-decade from 2008 to 2013 forced a series of “teachable moments” into the consciousness of leaders in both business and government. More such moments may be in the offing, given the unresolved issues stemming from the global financial crisis. What lessons shall we draw from these moments? And how shall we teach the lessons so that the next generation of leaders can implement wiser policies?

One theme implicit in most critiques and policy recommendations of this period entails the con- sequences of financial illiteracy. At few other times in financial history have we seen so strong an affir- mation of Derek Bok’s famous argument, “If you think education is expensive, try ignorance.” The actions and behavior of consumers, investors, financial intermediaries, and regulators suggest ignorance (naïve or otherwise) of such basic financial concepts as time value of money, risk-adjusted returns, cost of capital, capital adequacy, solvency, optionality, capital market efficiency, and so on. If ignorance is bliss, teachers of finance face a delirious world.

Now more than ever, the case method of teaching corporate finance is critical to meeting the diverse educational challenges of our day. The cases presented in this volume address the richness of the problems that practitioners face and help to develop the student in three critical areas:

• Knowledge. The conceptual and computational building blocks of finance are the necessary foun- dation for professional competence. The cases in this volume afford solid practice with the breadth and depth of this foundational knowledge. And they link the practical application of tools and con- cepts to a contextual setting for analysis. Such real-world linkage is an important advantage of case studies over textbook problem sets.

• Skills. Case studies demand decisions and recommendations. Too many analysts are content to calculate or estimate without helping a decision-maker fully understand the implications of the analysis. By placing the student in the position of the decision-maker, the case study promotes confidence and competence in making decisions. Furthermore, class discussions of cases promote skills in communication, selling and defending ideas, giving feedback, negotiating, and getting re- sults through teamwork—these are social skills that are best learned in face-to-face engagement.

• Attributes of character. Popular outrage over the crisis focused on shady ethics. The duty of agents, diligence in the execution of professional responsibilities, breaches of trust, the temptations of self- dealing, and outright fraud intrude into retrospective assessments of what might otherwise be dry and technical analyses of the last decade. It is no longer possible or desirable to teach finance as a purely technical subject devoid of ethical considerations. Ultimately, teaching is a moral act: by choosing worthy problems, modeling behavior, and challenging the thinking of students, the teacher strength- ens students in ways that are vitally important for the future of society. The case method builds attrib- utes of character such as work ethic and persistence; empathy for classmates and decision-makers; social awareness of the consequences of decisions and the challenging context for decision-makers; and accountability for one’s work. When students are challenged orally to explain their work, the ensuing discussion reveals the moral dilemmas that confront the decision maker. At the core of transformational teaching with cases is growth in integrity. As Aristotle said, “Character is destiny,” a truism readily apparent in the ruinous aftermath of the global financial crisis.

As with the sixth edition of this book, I must commend my colleagues, Kenneth Eades and Michael Schill, who brought this seventh edition to the public. They are accomplished scholars in Finance and masterful teachers—above all, they are devoted to the quality of the learning experience for students. Their efforts in preparing this volume will enrich the learning for countless students and help teachers world-wide to rise to the various challenges of the post-crisis world.

Robert F. Bruner Dean and Charles C. Abbott Professor of Business Administration Distinguished Professor of Business Administration Darden Graduate School of Business Administration University of Virginia Charlottesville, Virginia October 8, 2012

Foreword

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The inexplicable is all around us. So is the incomprehensible. So is the unintelligible. Interviewing Babe Ruth* in 1928, I put it to him “People come and ask what’s your system for hitting home runs—that so?” “Yes,” said the Babe, “and all I can tell ‘em is I pick a good one and sock it. I get back to the dugout and they ask me what it was I hit and I tell ‘em I don’t know except it looked good.”

—Carl Sandburg†

Managers are not confronted with problems that are independent of each other, but with dynamic situations that consist of complex systems of changing problems that interact with each other. I call such situations messes . . . Managers do not solve problems: they manage messes.

—Russell Ackoff‡

Orientation of the Book

Practitioners tell us that much in finance is inexplicable, incomprehensible, and unin- telligible. Like Babe Ruth, their explanations for their actions often amount to “I pick a good one and sock it.” Fortunately for a rising generation of practitioners, tools and concepts of Modern Finance provide a language and approach for excellent perform- ance. The aim of this book is to illustrate and exercise the application of these tools and concepts in a messy world.

Focus on Value The subtitle of this book is Managing for Corporate Value Creation. Economics teaches us that value creation should be an enduring focus of concern because value is the foundation of survival and prosperity of the enterprise. The focus on value also helps managers understand the impact of the firm on the world around it. These cases harness and exercise this economic view of the firm. It is the special province of finance to highlight value as a legitimate concern for managers. The cases in this book exercise valuation analysis over a wide range of assets, debt, equities, and options, and a wide range of perspectives, such as investor, creditor, and manager.

Linkage to Capital Markets An important premise of these cases is that managers should take cues from the cap- ital markets. The cases in this volume help the student learn to look at the capital markets in four ways. First, they illustrate important players in the capital markets such as individual exemplars like Warren Buffett and Bill Miller and institutions like

Preface

*George Herman “Babe” Ruth (1895–1948) was one of the most famous players in the history of American baseball, leading the league in home runs for 10 straight seasons, setting a record of 60 home runs in one season, and hitting 714 home runs in his career. Ruth was also known as the “Sultan of Swat.”

†Carl Sandburg, “Notes for Preface,” in Harvest Poems (New York: Harcourt Brace Jovanovich, 1960), p.11.

‡Russell Ackoff, “The Future of Operational Research is Past,” Journal of Operational Research Society, 30, 1 (Pergamon Press, Ltd., 1979): 93–104.

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investment banks, commercial banks, rating agencies, hedge funds, merger arbi- trageurs, private equity firms, lessors of industrial equipment, and so on. Second, they exercise the students’ abilities to interpret capital market conditions across the eco- nomic cycle. Third, they explore the design of financial securities, and illuminate the use of exotic instruments in support of corporate policy. Finally, they help students understand the implications of transparency of the firm to investors, and the impact of news about the firm in an efficient market.

Respect for the Administrative Point of View The real world is messy. Information is incomplete, arrives late, or is reported with error. The motivations of counterparties are ambiguous. Resources often fall short. These cases illustrate the immense practicality of finance theory in sorting out the issues facing managers, assessing alternatives, and illuminating the effects of any par- ticular choice. A number of the cases in this book present practical ethical dilemmas or moral hazards facing managers—indeed, this edition features a chapter, “Ethics in Finance” right at the beginning, where ethics belongs. Most of the cases (and teach- ing plans in the associated instructor’s manual) call for action plans rather than mere analyses or descriptions of a problem.

Contemporaneity All of the cases in this book are set in the year 2000 or after and 40 percent are set in 2006 or later. A substantial proportion (25 percent) of these cases and technical notes are new, or significantly updated. The mix of cases reflects the global business environment: 45 percent of the cases in this book are set outside the United States, or have strong cross-border elements. Finally the blend of cases continues to reflect the growing role of women in managerial ranks: 28 percent of the cases present women as key protagonists and decision-makers. Generally, these cases reflect the increasingly diverse world of business participants.

Plan of the Book

The cases may be taught in many different combinations. The sequence indicated by the table of contents corresponds to course designs used at Darden. Each cluster of cases in the Table of Contents suggests a concept module, with a particular orientation.

1. Setting Some Themes. These cases introduce basic concepts of value creation, assessment of performance against a capital market benchmark, and capital market efficiency that reappear throughout a case course. The numerical analysis required of the student is relatively light. The synthesis of case facts into an important framework or perspective is the main challenge. The case, “Warren E. Buffett, 2005,” sets the nearly universal theme of this volume: the need to think like an investor. “Bill Miller and Value Trust,” explores a basic question about performance measurement: what is the right benchmark against which to evaluate success? “Ben & Jerry’s Homemade, Inc.” invites a consideration of “value” and the ways to measure it. The case entitled, “The Battle for Value, 2004: FedEx Corp. vs. United Parcel Service, Inc.” uses

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“economic profit” (or EVA®) to explore the origins of value creation and destruction, and its competitive implications for the future. A new case, “Genzyme and Relational Investors: Science and Business Collide?”, poses the dilemma of managing a public company when the objectives of the shareholders are not always easily aligned with the long-term objectives of the company.

2. Financial Analysis and Forecasting. In this section, students are introduced to the crucial skills of financial-statement analysis, break-even analysis, ratio analysis, and financial statement forecasting. The section starts with a note, “The Thoughtful Forecaster”, that provides a helpful introduction to financial state- ment analysis and student guidance on generating rational financial forecasts. The case, “Value Line Publishing: October 2002”, provides students an exposure to financial modeling with electronic spreadsheets. “Horniman Horticulture” uses a financial model to build intuition for the relevancy of corporate cash flow and the financial effects of firm growth. The case, “Krispy Kreme Doughnuts, Inc.,” confronts issues regarding the quality of reported financial results. “Guna Fibres” asks the students to consider a variety of working capital decisions, including the impact of seasonal demand upon financing needs. Other cases address issues in the analysis of working-capital management, and credit analysis.

3. Estimating the Cost of Capital. This module begins with a discussion of “best practices” among leading firms. The cases exercise skills in estimating the cost of capital for firms and their business segments. The cases aim to exercise and solidify students’ mastery of the capital asset pricing model, the dividend-growth model, and the weighted average cost of capital formula. “Roche Holdings AG: Funding the Genentech Acquisition” is a new case that invites students to estimate the appropriate cost of debt in the largest debt issuance in history. The case provides an introduction to the concept of estimating required returns. “Nike, Inc.: Cost of Capital” presents an introductory exercise in the estimation of the weighted average cost of capital. “Teletech Corporation, 2005,” explores the implications of mean-variance analysis to business segments within a firm, and gives a useful foundation for discussing value-additivity. “The Boeing 7E7,” presents a dramatic exercise in the estimation of a discount rate for a major corporate project.

4. Capital Budgeting and Resource Allocation. The focus of these cases is the evaluation of investment opportunities and entire capital budgets. The analytical challenges range from simple time value of money problems (“The Investment Detective”) to setting the entire capital budget for a resource-constrained firm (“Target Corporation”). Key issues in this module include the estimation of Free Cash Flows, the comparison of various investment criteria (NPV, IRR, payback, and equivalent annuities), the treatment of issues in mutually exclusive invest- ments, and capital budgeting under rationing. This module features several new cases. The first is “The Procter and Gamble Company: Crest Whitestrips Ad- vanced Seal”, which asks the student to value a new product launch but then con- sider the financial implications of a variety of alternative launch scenarios. The second new case, “Jacobs Division”, presents students an opportunity to consider the implications of strategic planning processes. And finally, “UVa Hospital System: The Long-term Acute Care Hospital Project”, is an analysis of investment

xvi Preface

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decision within a not-for-profit environment. In addition to forecasting and valuing the project’s cash flows, students must assess whether NPV and IRR are appropriate metrics for an organization that does not have stockholders.

5. Management of the Firm’s Equity: Dividends and Repurchases. This module seeks to develop practical principles about dividend policy and share issues by drawing on concepts about dividend irrelevance, signaling, investor clienteles, bond- ing, and agency costs. The first case, “Gainesboro Machine Tools Corporation”, concerns a company that is changing its business strategy and considering a change in its dividend policy. The case serves as a comprehensive introduction to corporate financial policy and themes in managing the right side of the balance sheet. The sec- ond case is new to this edition. “AutoZone, Inc.” is a leading auto parts retailer that has been repurchasing shares over many years. The case serves as an excellent ex- ample of how share repurchases impact the balance sheet and presents the student with the challenge of assessing the impact upon the company’s stock price.

6. Management of the Corporate Capital Structure. The problem of setting capital structure targets is introduced in this module. Prominent issues are the use and creation of debt tax shields, the role of industry economics and technol- ogy, the influence of corporate competitive strategy, the tradeoffs between debt policy, dividend policy, and investment goals, and the avoidance of costs of distress. The case, “California Pizza Kitchen,” addresses the classic dilemma entailed in optimizing the use of debt tax shields and providing financial flexibility—this theme is extended in another case, “Deluxe Corporation” that asks how much flexibility a firm needs. “Horizon Lines, Inc.” is a new case about a company facing default on a debt covenant that will prompt the need for either Chapter 11 protection or a voluntary financial restructuring.

7. Analysis of Financing Tactics: Leases, Options, and Foreign Currency. While the preceding module is concerned with setting debt targets, this module addresses a range of tactics a firm might use to pursue those targets, hedge risk, and exploit market opportunities. Included are domestic and international debt offerings, leases, currency hedges, warrants, and convertibles. With these cases, students will exercise techniques in securities valuation, including the use of option-pricing theory. For example, “Baker Adhesives” explores the concept of exchange-rate risk and the management of that risk with a forward-contract hedge and a money-market hedge. “MoGen, Inc” presents the pricing challenges associ- ated with a convertible bond as well as a complex hedging strategy to change the conversion price of the convertible through the purchase of options and issuance of warrants. A new case, “J&L Railroad”, presents a commodity risk problem for which students are asked to propose a specific hedging strategy using financial contracts offered on the open market or from a commercial bank.

8. Valuing the Enterprise: Acquisitions and Buyouts. This module begins with an extensive introduction to firm valuation in the note “Methods of Valuation: Mergers and Acquisitions.” The focus of the note includes valuation using DCF and multiples. This edition features four new cases in this module. The first new case, “American Greetings”, is provides a straightforward firm valuation in the context of a repurchase decision and is designed to be an introduction to firm

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valuation. The second new case is “Rosetta Stone: Pricing the 2009 IPO”, provides an alternative IPO valuation case to the JetBlue case with additional focus on valuation with market multiples. “Sun Microsystems” is the third new addition to the module and presents traditional takeover valuation case with opportunities to evaluate merger synergies and cost of capital implications. Several of the cases demand an analysis that spans several stakeholders. For example, “Hershey Foods Corporation,” presents the high profile story of when the Hershey Trust Company put Hershey Foods up for sale. The case raises a number of challenging valuation and governance issues. “The Timken Company” deals with an acquisition that requires the student to conduct a challenging valua- tion analysis of Torrington as well as develop a financing strategy for the deal. The module also features a merger negotiation exercise (“Flinder Valves and Controls Inc.”) that provides an engaging venue for investigating the distribution of joint value in a merger negotiation. Thus, the comprehensive nature of cases in this module makes them excellent vehicles for end-of-course classes, student term papers, and/or presentations by teams of students.

This edition offers a number of cases that give insights about investing or financing decisions in emerging markets. These include “Guna Fibres Ltd.,” “Star River Elec- tronics Ltd.,” and “Baker Adhesives.”

Summary of Changes for this Edition

The seventh edition represents a substantial change from the sixth edition. This edition offers 13 new or significantly updated cases in this edition, or 25 percent

of the total. In the interest of presenting a fresh and contemporary collection, older cases have been updated and/or replaced with new case situations such that all the cases are set in 2000 or later and 40 percent are set in 2006 or later. Several of the favorite “classic” cases from the first six editions are available online from Irwin/McGraw-Hill, from where instructors who adopt this edition may copy them for classroom use. All cases and teach- ing notes have been edited to sharpen the opportunities for student analysis.

The book continues with a strong international aspect (24 of the cases, 45 percent, are set outside the United States or feature significant cross-border issues). Also, the collection continues to feature female decision-makers and protagonists prominently (15, or 28 percent, of the cases).

Supplements

The case studies in this volume are supported by various resources that help make student engagement a success:

• Spreadsheet files support student and instructor preparation of the cases. They are located on the book’s website at www.mhhe.com/bruner7e

• A guide to the novice on case preparation, “Note to the Student: How to Study and Discuss Cases” in this volume.

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• The instructor’s resource manual provides counterparty roles for two negotiation exercises and also presents detailed discussions of case outcomes, one of which is designed to be used as second class period for the case. These supplemental mate- rials can significantly extend student learning and expand the opportunities for classroom discussion.

• An instructor’s resource manual of about 800 pages in length containing teaching notes for each case. Each teaching note includes suggested assignment questions, a hypothetical teaching plan, and a prototypical finished case analysis.

• Website addresses in many of the teaching notes. These provide a convenient avenue for updates on the performance of undisguised companies appearing in the book.

• Notes in the instructor’s manual on how to design a case method course, on using computers with cases, and on preparing to teach a case.

• A companion book by Robert Bruner titled, Socrates’ Muse: Reflections on Excel- lence in Case Discussion Leadership (Irwin/McGraw-Hill, 2002), is available to instructors who adopt the book for classroom use. This book offers useful tips on case method teaching.

• Several “classic” cases and their associated teaching notes were among the most popular and durable cases in previous editions of Case Studies in Finance. Instructors adopting this volume for classroom use may request permission to reproduce them for their courses.

Acknowledgments

This book would not be possible without the contributions of many other people. Col- leagues at Darden who have taught, co-authored, contributed to, or commented on these cases are Brandt Allen, Yiorgos Allayannis, Sam Bodily, Karl-Adam Bonnier, Susan Chaplinsky, John Colley, Bob Conroy, Mark Eaker, Richard Evans, Bob Fair, Paul Farris, Jim Freeland, Sherwood Frey, Bob Harris, Jared Harris, Mark Haskins, Michael Ho, Marc Lipson, Elena Loutskina, Pedro Matos, Matt McBrady, Charles Meiburg, Jud Reis, William Sihler and Robert Spekman. We are grateful for their collegiality and for the support for our casewriting efforts from the Darden School Foundation, the L. White Matthews Fund for Finance Casewriting, the Batten Institute, the Citicorp Global Schol- ars Program, Columbia Business School, INSEAD, and the University of Melbourne.

Colleagues at other schools provided worthy insights and encouragement toward the development of the seven editions of Case Studies in Finance. We are grateful to the following persons (listed with the schools with which they were associated at the time of our correspondence or work with them):

Michael Adler, Columbia

Raj Aggarwal, John Carroll

Turki Alshimmiri, Kuwait Univ.

Ed Altman, NYU

James Ang, Florida State

Paul Asquith, M.I.T.

Bob Barnett, North Carolina State

Geert Bekaert, Stanford

Michael Berry, James Madison

Randy Billingsley, VPI&SU

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xx Preface

Gary Blemaster, Georgetown

Rick Boebel, Univ. Otago, New Zealand

Oyvind Bohren, BI, Norway

John Boquist, Indiana

Michael Brennan, UCLA

Duke Bristow, UCLA

Ed Burmeister, Duke

Kirt Butler, Michigan State

Don Chance, VPI&SU

Andrew Chen, Southern Methodist

Barbara J. Childs, Univ. of Texas at Austin

C. Roland Christensen, Harvard

Thomas E. Copeland, McKinsey

Jean Dermine, INSEAD

Michael Dooley, UVA Law

Barry Doyle, University of San Francisco

Bernard Dumas, INSEAD

Craig Dunbar, Western Ontario

Peter Eisemann, Georgia State

Javier Estrada, IESE

Ben Esty, Harvard

Thomas H. Eyssell, Missouri

Pablo Fernandez, IESE

Kenneth Ferris, Thunderbird

John Finnerty, Fordham

Joseph Finnerty, Illinois

Steve Foerster, Western Ontario

Günther Franke, Konstanz

Bill Fulmer, George Mason

Louis Gagnon, Queens

Dan Galai, Jerusalem

Jim Gentry, Illinois

Stuart Gilson, Harvard

Robert Glauber, Harvard

Mustafa Gultekin, North Carolina

Benton Gup, Alabama

Jim Haltiner, William & Mary

Rob Hansen, VPI&SU

Philippe Haspeslagh, INSEAD

Gabriel Hawawini, INSEAD

Pekka Hietala, INSEAD

Rocky Higgins, Washington

Pierre Hillion, INSEAD

Laurie Simon Hodrick, Columbia

John Hund, Texas

Daniel Indro, Kent State

Thomas Jackson, UVA Law

Pradeep Jalan, Regina

Michael Jensen, Harvard

Sreeni Kamma, Indiana

Steven Kaplan, Chicago

Andrew Karolyi, Western Ontario

James Kehr, Miami Univ. Ohio

Kathryn Kelm, Emporia State

Carl Kester, Harvard

Naveen Khanna, Michigan State

Herwig Langohr, INSEAD

Dan Laughhunn, Duke

Ken Lehn, Pittsburgh

Saul Levmore, UVA Law

Wilbur Lewellen, Purdue

Scott Linn, Oklahoma

Dennis Logue, Dartmouth

Paul Mahoney, UVA Law

Paul Malatesta, Washington

Wesley Marple, Northeastern

Felicia Marston, UVA (McIntire)

John Martin, Texas

Ronald Masulis, Vanderbilt

John McConnell, Purdue

Richard McEnally, North Carolina

Catherine McDonough, Babson

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Wayne Mikkelson, Oregon

Michael Moffett, Thunderbird

Nancy Mohan, Dayton

Ed Moses, Rollins

Charles Moyer, Wake Forest

David W. Mullins, Jr., Harvard

James T. Murphy, Tulane

Chris Muscarella, Penn State

Robert Nachtmann, Pittsburgh

Tom C. Nelson, University of Colorado

Ben Nunnally, UNC-Charlotte

Robert Parrino, Texas (Austin)

Luis Pereiro, Universidad Torcuato di Tella

Pamela Peterson, Florida State

Larry Pettit, Virginia (McIntire)

Tom Piper, Harvard

Gordon Philips, Maryland

John Pringle, North Carolina

Ahmad Rahnema, IESE

Al Rappaport, Northwestern

Allen Rappaport, Northern Iowa

Raghu Rau, Purdue

David Ravenscraft, North Carolina

Henry B. Reiling, Harvard

Lee Remmers, INSEAD

Jay Ritter, Michigan

Richard Ruback, Harvard

Jim Schallheim, Utah

Art Selander, Southern Methodist

Israel Shaked, Boston

Dennis Sheehan, Penn State

J.B. Silvers, Case Western

Betty Simkins, Oklahoma State

Luke Sparvero, Texas

Preface xxi

Richard Stapleton, Lancaster

Laura Starks, Texas

Jerry Stevens, Richmond

John Strong, William & Mary

Marti Subrahmanyam, NYU

Anant Sundaram, Thunderbird

Rick Swasey, Northeastern

Bob Taggart, Boston College

Udin Tanuddin, Univ. Surabaya, Indonesia

Anjan Thakor, Indiana

Thomas Thibodeau, Southern Methodist

Clifford Thies, Shenandoah Univ.

James G. Tompkins, Kenesaw State

Walter Torous, UCLA

Max Torres, IESE

Nick Travlos, Boston College

Lenos Trigeorgis, Cyprus

George Tsetsekos, Drexel

Peter Tufano, Harvard

James Van Horne, Stanford

Nick Varaiya, San Diego State

Theo Vermaelen, INSEAD

Michael Vetsuypens, Southern Methodist

Claude Viallet, INSEAD

Ingo Walter, NYU

Sam Weaver, Lehigh

J.F. Weston, UCLA

Peter Williamson, Dartmouth

Brent Wilson, Brigham Young

Kent Womack, Dartmouth

Karen Wruck, Ohio State

Fred Yeager, St. Louis

Betty Yobaccio, Framingham State

Marc Zenner, North Carolina

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Tom Adams, Rosetta Stone

Norm Bartczak, Center for Financial Strategy

Bo Brookby, First Wachovia

Alison Brown, Compass Records

W.L. Lyons Brown, Brown-Forman

Bliss Williams Browne, First Chicago

George Bruns, BankBoston

Ian Buckley, Henderson Investors

Ned Case, General Motors

Phil Clough, ABS Capital

Daniel Cohrs, Marriott

David Crosby, Johnson & Johnson

Jinx Dennett, BankBoston

Barbara Dering, Bank of New York

Ty Eggemeyer, McKinsey

Geoffrey Elliott, Morgan Stanley

Glenn Eisenberg, The Timken Company

Louis Elson, Palamon Capital Partners

Christine Eosco, BankBoston

Larry Fitzgerald, UVA Health System

Catherine Friedman, Morgan Stanley

Carl Frischkorn, Threshold Sports

Carrie Galeotafiore, Value Line Publishing

Charles Griffith, AlliedSignal

Ian Harvey, BankBoston

David Herter, Fleet Boston

Christopher Howe, Kleinwort Benson

Paul Hunn, Manufacturers Hanover

Kristen Huntley, Morgan Stanley

James Gelly, General Motors

Ed Giera, General Motors

Betsy Hatfield, Bank Boston

Denis Hamboyan, Bank Boston

John Hulbert, Target Corp.

Thomas Jasper, Salomon Brothers

Andrew Kalotay, Salomon Brothers

Lisa Levine, Equipment Leasing

Mary Lou Kelley, McKinsey

Francesco Kestenholz, UBS

Daniel Lentz, Procter and Gamble

Eric Linnes, Kleinwort Benson

Peter Lynch, Fidelity Investments

Dar Maanavi, Merrill Lynch

Mary McDaniel, SNL Securities

Jean McTighe, BankBoston

Frank McTigue, McTigue Associates

David Meyer, J.P. Morgan

Michael Melloy, Planet

Jeanne Mockard, Putnam Investments

Pascal Montiero de Barros, Planet

Lin Morison, BankBoston

John Muleta, PSINet

Dennis Neumann, Bank of New York

John Newcomb, BankBoston

Ralph Norwood, Polaroid

Marni Gislason Obernauer, J.P. Morgan

John Owen, JetBlue Airways

Michael Pearson, McKinsey

Nancy Preis, Kleinwort Benson

Joe Prendergast, First Wachovia

Luis Quartin-Bastos, Planet

Jack Rader, FMA

Christopher Reilly, S.G. Warburg

Emilio Rottoli, Glaxo

We are also grateful to the following practitioners (listed here with affiliated com- panies at the time of our work with them):

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Preface xxiii

Gerry Rooney, NationsBank

Craig Ruff, AIMR

Barry Sabloff, First Chicago

Linda Scheuplein, J.P. Morgan

Doug Scovanner, Target Corp.

Keith Shaughnessy, Bank Boston

Jack Sheehan, Johnstown

Katrina Sherrerd, AIMR

John Smetanka, Security Pacific

John Smith, General Motors

Raj Srinath, AMTRAK

Rick Spangler, First Wachovia

Kirsten Spector, BankBoston

Martin Steinmeyer, MediMedia

Bill Stilley, Adenosine Therapeutics

Stephanie Summers, Lehman Brothers

Sven-Ivan Sundqvist, Dagens Nyheter

Patrick Sweeney, Servervault

Henri Termeer, Genzyme

Ward J. Timken, Jr., The Timken Company

Peter Thorpe, Citicorp.

Katherine Updike, Excelsior

Tom Verdoorn, Land O’Lakes

Frank Ward, Corp. Performance Systems

David Wake Walker, Kleinwort Benson

Garry West, Compass Records

Ulrich Wiechmann, UWINC

Ralph Whitworth, Relational Investors

Scott Williams, McKinsey

Harry You, Salomon Brothers

Richard Zimmermann, Hershey Foods

Research assistants working under our direction have helped gather data and pre- pare drafts. Research assistants who contributed to various cases in this and previous editions include Darren Berry, Justin Brenner, Anna Buchanan, Anne Campbell, Drew Chambers, Jessica Chan, Vladimir Kolcin, Lucas Doe, Brett Durick, David Eichler, Ali Erarac, Rick Green, Daniel Hake, Dennis Hall, Jerry Halpin, Peter Hennessy, Nili Mehta, Casey Opitz, Katarina Paddack, Suprajj Papireddy, Chad Rynbrandt, John Sherwood, Elizabeth Shumadine, Jane Sommers-Kelly, Thien Pham, Carla Stiassni, Sanjay Vakharia, Larry Weatherford, and Steve Wilus. We give special acknowledge- ment to Sean Carr who played a multifaceted role in the production of the previous edition. It was his efforts that not only made the fifth edition a reality, but also posi- tioned us so well to complete this edition. We have supervised numerous others in the development of individual cases—those worthy contributors are recognized in the first footnote of each case.

A busy professor soon learns the wisdom in the adage, “Many hands make work light.” we are very grateful to the staff of the Darden School for its support in this project. Excellent editorial assistance at Darden was provided by Stephen Smith and Catherine Wiese (Darden’s nonpareil editors) and their associates in Darden Business Publishing and the Darden Case Collection, Sherry Alston, Amy Lemley, Heidi White, and Beth Woods. Ginny Fisher gave stalwart secretarial support. Valuable library research support was given by Karen Marsh King and Susan Norrisey. The patience, care, and dedication of these people are richly appreciated.

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At McGraw-Hill/Irwin, Chuck Synovec has served as Executive Editor for this book. Mike Junior, now Vice President, recruited Bob Bruner into this project years ago; the legacy of that early vision-setting continues in this edition. Lisa Bruflodt was the project manager, and Casey Rasch served as Editorial Coordinator on this edition.

Of all the contributors, our wives, Barbara M. Bruner, Kathy N. Eades, and Mary Ann H. Schill as well as our children have endured great sacrifices as the result of our work on this book. As Milton said, “They also serve who only stand and wait.” Development of this seventh edition would not have been possible without their fond patience.

All these acknowledgments notwithstanding, responsibility for these materials is ours. We welcome suggestions for their enhancement. Please let us know of your experience with these cases, either through McGraw-Hill/Irwin, or at the coordinates given below.

Robert F. Bruner Dean, Charles C. Abbott Professor of Business Administration and Distinguished Professor of Business Administration Darden Graduate School of Business University of Virginia [email protected]§

Kenneth M. Eades Paul Tudor Jones Research Professor of Business Administration Darden Graduate School of Business University of Virginia [email protected]*

Michael J. Schill Associate Professor of Business Administration Darden Graduate School of Business University of Virginia [email protected]*

Individual copies of all the Darden cases in this and previous editions may be obtained promptly from McGraw-Hill/Irwin’s Create (http://create.mcgraw-hill.com) or from Darden Business Publishing (telephone: 800-246-3367; https://store.darden. virginia.edu/). Proceeds from these case sales support case writing efforts. Please respect the copyrights on these materials.

§Students should know that we are unable to offer any comments that would assist their preparation of these cases without the prior express request of their instructors.

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This note was prepared by Robert F. Bruner. Copyright © 2001 by the University of Virginia Darden School Foundation, Charlottesville, VA. All rights reserved. To order copies, send an e-mail to [email protected] No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means—electronic, mechanical, photo- copying, recording, or otherwise—without the permission of the Darden School Foundation. Rev. 11/05.

Note to the Student: How to Study and Discuss Cases

Get a good idea and stay with it. Dog it and work at it until it’s done, and done right. —Walt Disney

You enroll in a “case-method” course, pick up the book of case studies or the stack of loose-leaf cases, and get ready for the first class meeting. If this is your first expe- rience with case discussions, the odds are that you are clueless and a little anxious about how to prepare for this course. That is fairly normal, but something you should try to break through quickly in order to gain the maximum benefit from your studies. Quick breakthroughs come from a combination of good attitude, good “infrastruc- ture,” and good execution—this note offers some tips.

Good Attitude Students learn best that which they teach themselves. Passive and mindless learning is ephemeral. Active, mindful learning simply sticks. The case method makes learn- ing sticky by placing you in situations that require the invention of tools and concepts in your own terms. The most successful case-method students share a set of charac- teristics that drive self-teaching:

1. Personal initiative, self-reliance: Case studies rarely suggest how to proceed. Professors are more like guides on a long hike: They can’t carry you, but they can show you the way. You must arrive at the destination under your own power. You must figure out the case on your own. To teach yourself means that you must sort ideas out in ways that make sense to you personally. To teach yourself is to give yourself two gifts: the idea you are trying to learn and greater self-confidence in your own ability to master the world.

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xxvi Note to the Student: How to Study and Discuss Cases

2. Curiosity, a zest for exploration as an end in itself: Richard P. Feynman, who won the Nobel Prize in Physics in 1965, was once asked whether his key discovery was worth it. He replied, “[The Nobel Prize is] a pain in the [neck]. . . . I don’t like honors. . . . The prize is the pleasure of finding the thing out, the kick in the discovery, the observation that other people use it [my work]—those are the real things; the honors are unreal to me.”1

3. A willingness to take risks: Risk-taking is at the heart of all learning. Usually, one learns more from failures than from successes. Banker Walter Wriston once said, “Good judgment comes from experience. Experience comes from bad judgment.”

4. Patience and persistence: Case studies are messy, a realistic reflection of the fact that managers don’t manage problems, they manage messes. Initially, reaching a solution will seem to be the major challenge. But once you reach a solution, you may discover other possible solutions and then face the choice among the best alternatives.

5. An orientation to community and discussion: Much of the power of the case method derives from a willingness to talk with others about your ideas and your points of confusion. This is one of the paradoxes of the case method: You must teach yourself, but not in a vacuum. The poet T. S. Eliot said, “There is no life not lived in community.” Talking seems like such an inefficient method of sorting through the case, but if exploration is an end in itself, then talking is the only way. Furthermore, talking is an excellent means of testing your own mastery of ideas, of rooting out points of confusion, and, generally, of preparing yourself for professional life.

6. Trust in the process: The learnings from a case-method course are impressive. They arrive cumulatively over time. In many cases, the learnings continue well after the course has finished. Occasionally, those learnings hit you with the force of a tsunami. But generally, the learnings creep in quietly but powerfully like the tide. After the case course, you will look back and see that your thinking, mastery, and appreciation have changed dramatically. The key point is that you should not measure the success of your progress on the basis of any single case discussion. Trust that, in the cumulative work over many cases, you will gain the mastery you seek.

Good Infrastructure “Infrastructure” consists of all the resources that the case-method student can call upon. Some of this is simply given to you by the professor: case studies, assignment questions, supporting references to textbooks or articles, and computer data or models. But you can go much further to help yourself. Consider these steps:

1. Find a quiet place to study. Spend at least 90 minutes there for each case study. Each case has subtleties to it that you will miss unless you can concentrate. After two or three visits, your quiet place will take on the attributes of a habit:

1Richard P. Feynman, The Pleasure of Finding Things Out (Cambridge, Mass.: Perseus Publishing, 1999), 12.

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Note to the Student: How to Study and Discuss Cases xxvii

You will slip into a working attitude more easily. Be sure to spend enough time in the quiet place to give yourself a chance to really engage the case.

2. Get a business dictionary. If you are new to business and finance, some of the terms will seem foreign; if English is not your first language, many of the terms will seem foreign, if not bizarre. Get into the habit of looking up terms that you don’t know. The benefit of this becomes cumulative.

3. Skim a business newspaper each day, read a business magazine, follow the markets. Reading a newspaper or magazine helps build a context for the case study you are trying to solve at the moment, and helps you make connections between the case study and current events. The terminology of business and finance that you see in the publications helps to reinforce your use of the dictionary, and hastens your mastery of the terms that you will see in the cases. Your learning by reading business periodicals is cumulative. Some students choose to follow a good business-news Web site on the Internet. Those Web sites have the virtue of being inexpensive and efficient, but they tend to screen too much. Having the printed publication in your hands and leafing through it help the process of discovery, which is the whole point of the exercise.

4. Learn the basics of spreadsheet modeling on a computer. Many case studies now have supporting data available for analysis in Microsoft Excel spreadsheet files. Analyzing the data on a computer rather than by hand both speeds up your work and extends your reach.

5. Form a study group. The ideas in many cases are deep; the analysis can get complex. You will learn more and perform better in class participation by discussing the cases together in a learning team. Your team should devote an average of an hour to each case. High-performance teams show a number of common attributes:

a. The members commit to the success of the team.

b. The team plans ahead, leaving time for contingencies.

c. The team meets regularly.

d. Team members show up for meetings and are prepared to contribute.

e. There may or may not be a formal leader, but the assignments are clear. Team members meet their assigned obligations.

6. Get to know your professor. In the case method, students inevitably learn more from one another than from the instructor. But the teacher is part of the learning infrastructure, too: a resource to be used wisely. Never troll for answers in advance of a case discussion. Do your homework; use classmates and learning teams to clear up most of your questions so that you can focus on the meatiest issues with the teacher. Be very organized and focused about what you would like to discuss. Remember that teachers like to learn, too: If you reveal a new insight about a case or bring a clipping about a related issue in current events, both the professor and the student can gain from their time together. Ultimately, the best payoff to the professor is the “aha” in the student’s eyes when he or she masters an idea.

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xxviii Note to the Student: How to Study and Discuss Cases

Good Execution Good attitude and infrastructure must be employed properly—one needs good execution. The extent to which a student learns depends on how the case study is approached. What can one do to gain the maximum from the study of those cases?

1. Reading the case. The very first time you read any case, look for the forest, not the trees. This requires that your first reading be quick. Do not begin taking notes on the first round; instead, read the case like a magazine article. The first few paragraphs of a well-constructed case usually say something about the problem— read those carefully. Then quickly read the rest of the case, mainly seeking a sense of the scope of the problems and what information the case contains to help resolve them. Leaf through the exhibits, looking for what information they hold rather than for any analytical insights. At the conclusion of the first pass, read any supporting articles or notes that your instructor may have recommended.

2. Getting into the case situation. Develop your “awareness.” With the broader perspective in mind, the second and more detailed reading will be more productive. The reason is that as you now encounter details, your mind will be able to organize them in some useful fashion rather than inventorying them randomly. Making links among case details is necessary for solving the case. At this point, you can take notes that will set up your analysis.

The most successful students project themselves into the position of the decision- maker because this perspective helps them link case details as well as develop a stand on the case problem. Assignment questions may help you do this, but it is a good idea to get into the habit of doing it yourself. Here are the kinds of questions you might try to answer in preparing every case:

• Who are the protagonists in the case? Who must take action on the problem? What do they have at stake? What pressures are they under?

• What business is the company in? What is the nature of its product? What is the nature of demand for that product? What is the firm’s distinctive compe- tence? With whom does it compete?2 What is the structure of the industry? Is the firm comparatively strong or weak? In what ways?

• What are the goals of the firm? What is the firm’s strategy in pursuit of those goals? (The goals and strategy may be explicitly stated, or they may be implicit in the way the firm does business.) What are the firm’s apparent functional policies in marketing (e.g., push versus pull strategy), production (e.g., labor relations, use of new technology, distributed production versus centralized), and finance (e.g., the use of debt financing, payment of dividends)? Financial

2Think broadly about competitors. In A Connecticut Yankee in King Arthur’s Court, Mark Twain wrote, “The best swordsman in the world doesn’t need to fear the second best swordsman in the world; no, the person for him to be afraid of is some ignorant antagonist who has never had a sword in his hand before; he doesn’t do the thing he ought to do, and so the expert isn’t prepared for him; he does the thing he ought not to do; and it often catches the expert out and ends him on the spot.”

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Note to the Student: How to Study and Discuss Cases xxix

and business strategies can be inferred from an analysis of the financial ratios and a sources-and-uses-of-funds statement.

• How well has the firm performed in pursuit of its goals? (The answer to this question calls for simple analysis using financial ratios, such as the DuPont system, compound growth rates, and measures of value creation.)

The larger point of this phase of your case preparation is to broaden your awareness of the issues. Warren Buffett, perhaps the most successful investor in history, said, “Any player unaware of the fool in the market probably is the fool in the market.” Awareness is an important attribute of successful managers.

3. Defining the problem. A common trap for many executives is to assume that the issue at hand is the real problem most worthy of their time, rather than a symptom of some larger problem that really deserves their time. For instance, a lender is often asked to advance funds to help tide a firm over a cash shortfall. Careful study may reveal that the key problem is not a cash shortfall, but rather product obsolescence, unexpected competition, or careless cost management. Even in cases where the decision is fairly narrowly defined (e.g., a capital-expenditure choice), the “problem” generally turns out to be the believability of certain key assumptions. Students who are new to the case method tend to focus narrowly in defining problems and often overlook the influence that the larger setting has on the problem. In doing that, the student develops narrow specialist habits, never achieving the general-manager perspective. It is useful and important for you to define the problem yourself and, in the process, validate the problem as suggested by the protagonist in the case.

4. Analysis: run the numbers and go to the heart of the matter. Virtually all finance cases require numerical analysis. This is good because figure-work lends rigor and structure to your thinking. But some cases, reflecting reality, invite you to explore blind alleys. If you are new to finance, even those explorations will help you learn.3 The best case students develop an instinct for where to devote their analysis. Economy of effort is desirable. If you have invested wisely in problem definition, economical analysis tends to follow. For instance, a student might assume that a particular case is meant to exercise financial forecasting skills and will spend two or more hours preparing a detailed forecast, instead of preparing a simpler forecast in one hour and conducting a sensitivity analysis based on key assumptions in the next hour. An executive rarely thinks of a situation as having to do with a forecasting method or discounting or any other technique, but rather thinks of it as a problem of judgment, deciding on which people or concepts or environmental conditions to bet. The best case analyses get down to the key bets on which the executive is wagering the prosperity of the firm and his or her career. Get to the business issues quickly, and avoid lengthy churning through relatively unimportant calculations.

3Case analysis is often iterative: An understanding of the big issues invites an analysis of details—then the details may restructure the big issues and invite the analysis of other details. In some cases, getting to the heart of the matter will mean just such iteration.

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xxx Note to the Student: How to Study and Discuss Cases

5. Prepare to participate: take a stand. To develop analytical insights without making recommendations is useless to executives and drains the case-study experience of some of its learning power. A stand means having a point of view about the problem, a recommendation, and an analysis to back up both of them. The lessons most worth learning all come from taking a stand. From that truth flows the educative force of the case method. In the typical case, the student is projected into the position of an executive who must do something in response to a problem. It is this choice of what to do that constitutes the executive’s stand. Over the course of a career, an executive who takes stands gains wisdom. If the stand provides an effective resolution of the problem, so much the better for all concerned. If it does not, however, the wise executive analyzes the reasons for the failure and may learn even more than from a success. As Theodore Roosevelt wrote:

The credit belongs to the man4 who is actually in the arena—whose face is marred by dust and sweat and blood . . . who knows the great enthusiasms, the great devotions—and spends himself in a worthy cause—who, at best, if he wins, knows the thrills of high achievement—and if he fails, at least fails while daring greatly so that his place shall never be with those cold and timid souls who know neither victory nor defeat.

6. In class: participate actively in support of your conclusions, but be open to new insights. Of course, one can have a stand without the world being any wiser. To take a stand in case discussions means to participate actively in the discussion and to advocate your stand until new facts or analyses emerge to warrant a change.5 Learning by the case method is not a spectator sport. A classic error many students make is to bring into the case-method classroom the habits of the lecture hall (i.e., passively absorbing what other people say). These habits fail miserably in the case-method classroom because they only guarantee that one absorbs the truths and fallacies uttered by others. The purpose of case study is to develop and exercise one’s own skills and judgment. This takes practice and participation, just as in a sport. Here are two good general suggestions: (1) defer significant note-taking until after class and (2) strive to contribute to every case discussion.

7. Immediately after class: jot down notes, corrections, and questions. Don’t overinvest in taking notes during class—that just cannibalizes “air time” in which you could be learning through discussing the case. But immediately after class, collect your learnings and questions in notes that will capture your thinking. Of course, ask a fellow student or your teacher questions to help clarify issues that still puzzle you.

4Today, a statement such as this would surely recognize women as well. 5There is a difference between taking a stand and pigheadedness. Nothing is served by clinging to your stand to the bitter end in the face of better analysis or common sense. Good managers recognize new facts and good arguments as they come to light and adapt.

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8. Once a week, flip through notes. Make a list of your questions, and pursue answers. Take an hour each weekend to review your notes from class discus- sions during the past week. This will help build your grasp of the flow of the course. Studying a subject by the case method is like building a large picture with small mosaic tiles. It helps to step back to see the big picture. But the main objective should be to make an inventory of anything you are unclear about: terms, concepts, and calculations. Work your way through this inventory with classmates, learning teams, and, ultimately, the instructor. This kind of review and follow-up builds your self-confidence and prepares you to participate more effectively in future case discussions.

Conclusion: Focus on Process and Results Will Follow View the case-method experience as a series of opportunities to test your mastery of techniques and your business judgment. If you seek a list of axioms to be etched in stone, you are bound to disappoint yourself. As in real life, there are virtually no “right” answers to these cases in the sense that a scientific or engineering problem has an exact solution. Jeff Milman has said, “The answers worth getting are never found in the back of the book.” What matters is that you obtain a way of thinking about business situations that you can carry from one job (or career) to the next. In the case method, it is largely true that how you learn is what you learn.6

6In describing the work of case teachers, John H. McArthur has said, “How we teach is what we teach.”

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Ethics in Finance The first thing is character, before money or anything else.

—J. P. Morgan (in testimony before the U.S. Congress)

The professional concerns himself with doing the right thing rather than making money, knowing that the profit takes care of itself if the other things are attended to.

—Edwin LeFevre, Reminiscences of a Stock Operator

Integrity is paramount for a successful career in finance and business, as practitioners remind us. One learns, rather than inherits, integrity. And the lessons are everywhere, even in case studies about finance. To some people, the world of finance is purely mechanical, devoid of ethical considerations. The reality is that ethical issues are pervasive in finance. Exhibit 1 gives a list of prominent business scandals around the turn of the twenty-first century. One is struck by the wide variety of industrial settings and especially by the recurrent issues rooted in finance and accounting. Still, the dis- belief that ethics matter in finance can take many forms.

“It’s not my job,” says one person, thinking that a concern for ethics belongs to a CEO, an ombudsperson, or a lawyer. But if you passively let someone else do your thinking, you expose yourself to complicity in the unethical decisions of others. Even worse is the possibility that if everyone assumes that someone else owns the job of ethical practice, then perhaps no one owns it and that therefore the enterprise has no moral compass at all.

Another person says, “When in Rome, do as the Romans do. It’s a dog-eat-dog world. We have to play the game their way if we mean to do business there.” Under that view, it is assumed that everybody acts ethically relative to his local environment so that it is inappropriate to challenge unethical behavior. This is moral relativism. The problem with this view is that it presupposes that you have no identity, that, like a chameleon, you are defined by the environment around you. Relativism is the enemy

This technical note was prepared by Robert F. Bruner and draws segments from two of his books, Applied Mergers and Acquisitions (John Wiley & Sons, copyright © 2004 by Robert F. Bruner) and Deals from Hell: Lessons That Rise Above the Ashes (John Wiley & Sons, copyright © 2005 by Robert F. Bruner). These segments are used here with his permission. Copyright © 2006 by the University of Virginia Darden School Foundation, Charlottesville, VA. All rights reserved. To order copies, send an e-mail to [email protected] No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means—electronic, mechanical, photo- copying, recording, or otherwise—without the permission of the Darden School Foundation.

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of personal identity and character. You must have a view, if you are rooted in any cul- tural system. Prepare to take a stand.

A third person says, “It’s too complicated. Civilization has been arguing about ethics for 3,000 years. You expect me to master it in my lifetime?” The response must be that we use complicated systems dozens of times each day without a full mastery of their details. Perhaps the alternative would be to live in a cave, which is a simpler life but much less rewarding. Moreover, as courts have been telling the business world for centuries, ignorance of the law is no defense. If you want to succeed in the field of finance, you must grasp the norms of ethical behavior.

There is no escaping the fact that ethical reasoning is vital to the practice of business and finance. Tools and concepts of ethical reasoning belong in the financial toolkit alongside other valuable instruments of financial practice.

Ethics and economics were once tightly interwoven. The patriarch of economics, Adam Smith, was actually a scholar of moral philosophy. Although the two fields may have diverged in the last century, they remain strong complements.1 Morality concerns norms and teachings. Ethics concerns the process of making morally good decisions or, as Andrew Wicks wrote, “Ethics has to do with pursuing—and achieving— laudable ends.”2 The Oxford English Dictionary defines moral as follows: “Of knowledge, opinions, judgments, etc.; relating to the nature and application of the distinction between right and wrong.”3 Ethics, however, is defined as the “science of morals.”4 To see how the decision-making processes in finance have ethical implications, consider the following case study.

Minicase: WorldCom Inc.5

The largest corporate fraud in history entailed the falsification of $11 billion in operating profits at WorldCom Inc. WorldCom was among the three largest long- distance telecommunications providers in the United States, the creation of a rollup acquisition strategy by its CEO, Bernard Ebbers. WorldCom’s largest acquisition, MCI Communications in 1998, capped the momentum-growth story. This, combined with the buoyant stock market of the late 1990s, increased the firm’s share price dramatically.

By early 2001, it dawned on analysts and investors that the United States was greatly oversupplied with long-distance telecommunications capacity. Much of that capacity had been put in place with unrealistic expectations of growth in Internet use. With the collapse of the Internet bubble, the future of telecom providers was suddenly in doubt.

1Sen (1987) and Werhane (1999) have argued that Smith’s masterpiece, Wealth of Nations, is incorrectly construed as a justification for self-interest and that it speaks more broadly about virtues such as prudence, fairness, and cooperation. 2Wicks (2003), 5. 3Oxford English Dictionary (1989), vol. IX, 1068. 4Oxford English Dictionary (1989), vol. V, 421. 5This case is based on facts drawn from Pulliam (2003), Blumenstein and Pulliam (2003), Blumenstein and Solomon (2003), and Solomon (2003).

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WorldCom had leased a significant portion of its capacity to both Internet service providers and telecom service providers. Many of those lessees declined and, starting in 2000, entered bankruptcy. In mid-2000, Ebbers and WorldCom’s chief financial officer (CFO), Scott Sullivan, advised Wall Street that earnings would fall below expectations. WorldCom’s costs were largely fixed—the firm had high operating leverage. With relatively small declines in revenue, earnings would decline sharply. In the third quarter of 2000, WorldCom was hit with $685 million in write-offs as its customers defaulted on capacity-lease commitments. In October 2000, Sullivan pressured three midlevel accounting managers at WorldCom to draw on reserve accounts set aside for other purposes to cover operating expenses, which reduced the reported operating expenses and increased profits. The transfer violated rules regarding the independence and purpose of reserve accounts. The three accounting managers acqui- esced, but later regretted their action. They considered resigning, but were persuaded to remain with the firm through its earnings crisis. They hoped or believed that a turn- around in the firm’s business would make their action an exception.

Conditions worsened in the first quarter of 2001. Revenue fell further, producing a profit shortfall of $771 million. Again, Sullivan prevailed on the three accounting managers to shift operating costs—this time, to capital-expenditure accounts. Again, the managers complied. This time, they backdated entries in the process. In the second, third, and fourth quarters of 2001, they transferred $560 million, $743 mil- lion, and $941 million, respectively. In the first quarter of 2002, they transferred $818 million.

The three accounting managers experienced deep emotional distress over their actions. In April 2002, when they discovered that WorldCom’s financial plan for 2002 implied that the transfers would continue until the end of the year, the three managers vowed to cease making transfers and to look for new jobs. But inquiries by the U.S. Securities and Exchange Commission (SEC) into the firm’s suspiciously positive financial performance triggered an investigation by the firm’s head of internal auditing. Feeling the heat of the investigation, the three managers met with representatives from the SEC, the U.S. Federal Bureau of Investigation (FBI), and the U.S. attorney’s office on June 24, 2002. The next day, WorldCom’s internal auditor disclosed to the SEC the discovery of $3.8 billion in fraudulent accounting. On June 26, the SEC charged WorldCom with fraud.

But the scope of the fraud grew. In addition to the $3.8 billion reallocation of oper- ating expenses to reserves and capital expenditures, WorldCom had shifted another $7.2 billion to its MCI subsidiary, which affected the tracking stock on that entity.

As news of the size of the fraud spread, WorldCom’s stock price sank. From its peak in late 2000 until it filed for bankruptcy in July 2002, about $180 billion of WorldCom’s equity-market value evaporated. In March 2003, WorldCom announced that it would write off $79.8 billion in assets following an impairment analysis: $45 billion of the write-off arose from the impairment of goodwill.

The three accounting managers had hoped that they would be viewed simply as witnesses. On August 1, they were named by the U.S. attorney’s office as unindicted co-conspirators in the fraud. WorldCom fired them immediately. Unable to cope with the prospect of large legal bills for their defense, they pleaded guilty to securities

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fraud and conspiracy to commit fraud. The charges carried a maximum of 15 years in prison.

Bernard Ebbers and Scott Sullivan were charged with fraud. A study conducted by the bankruptcy examiner concluded that Ebbers had played a role in inflating the firm’s revenues. One example cited in the report was the firm’s announcement of the acquisition of Intermedia Communications Inc. in February 2001. Even before WorldCom’s board had approved the deal, the firm’s lawyers made it look as if the board had approved the deal by creating false minutes.

WorldCom emerged from bankruptcy in 2004 with a new name, MCI Commu- nications. On March 2, 2004, Sullivan pleaded guilty to fraud. Ebbers continued to protest his innocence, arguing that the fraud was masterminded by Sullivan without Ebbers’s knowledge. A jury found Ebbers guilty on March 15, 2005. In the summer of 2005, MCI agreed to be acquired by Verizon, a large regional telephone company in the United States.

This case illustrates how unethical behavior escalates over time. Such behavior is costly to companies, investors, and employees. It damages investor confidence and trust—and it is invariably uncovered. Fraud and earnings management share a common soil: a culture of aggressive growth. Although growth is one of the foremost aims in business, the mentality of growth at any price can warp the thinking of otherwise honorable people.

The shields against fraud are a culture of integrity, strong governance, and strong financial monitoring. Yet in some circumstances, such shields fail to forestall unethical behavior. Michael Jensen (2005) explored an important circumstance associated with managerial actions: when the stock price of a firm is inflated beyond its intrinsic (or true) value. Jensen pointed to the scandals that surfaced during and after a period of overvaluation in share prices between 1998 and 2001. He argued that “society seems to overvalue what is new.” When a firm’s equity becomes overvalued, it motivates behavior that poorly serves the interests of those investors on whose behalf the firm is managed. Managers whose compensation is tied to increases in share price are motivated to “game the system” by setting targets and managing earnings in ways that yield large bonuses. This behavior is a subset of problems originating from target- based corporate-budgeting systems.

Jensen argues that the market for corporate control solves the problem of undervalued equity (i.e., firms operating at low rates of efficiency) with the instru- ments of hostile takeovers, proxy fights, leveraged buyouts, and so on. But he points out that there is little remedy for the opposite case, overvalued equity. Equity-based compensation—in the form of stock options, shares of stock, stock-appreciation rights, and so on—merely adds fuel to the fire.

Paradoxically, a high stock price would seem to be desirable. But occasionally, stock prices become detached from the fundamental basis for their valuation—that is, when the price exceeds the intrinsic value of the shares. Jensen defines overvalued stock as occurring when the performance necessary to produce that price cannot be attained except by good fortune. The problem is that managers fail to face the facts and explain to investors the overvaluation of shares. Instead, they take actions that prolong, or even worsen, the overvaluation. Those actions destroy value in the long

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run, even though they may appear to create or preserve value in the short run—as was the case with WorldCom. A little of this behavior begins to stimulate more; soon, a sense of proportion is lost and the organization eventually turns to fraud. The hope is to postpone the inevitable correction in price until after the executive has moved on to another firm or retired. Telling the truth to investors about overvaluation is extremely painful. The firm’s stock price falls, executive bonuses dwindle, and the directors listen to outraged investors.

What the tragedies of WorldCom and the other firms cited in Exhibit 1 share is that, like Peter Pan, those companies refused to grow up. They refused to admit frankly to their shareholders and to themselves that their very high rates of growth were unsustainable.

Why One Should Care about Ethics in Finance Managing in ethical ways is not merely about avoiding bad outcomes. There are at least five positive arguments for bringing ethics to bear on financial decision-making.

Sustainability. Unethical practices are not a foundation for enduring, sustainable enterprise. This first consideration focuses on the legacy one creates through one’s financial transactions. What legacy do you want to leave? To incorporate ethics into our finance mind-set is to think about the kind of world that we would like to live in and that our children will inherit.

One might object that, in a totally anarchic world, unethical behavior might be the only path in life. But this view only begs the point: We don’t live in such a world. Instead, our world of norms and laws ensures a corrective process against unethical behavior.

Ethical behavior builds trust. Trust rewards. The branding of products seeks to create a bond between producer and consumer: a signal of purity, performance, or other attributes of quality. This bond is built by trustworthy behavior. As markets reveal, successfully branded products command a premium price. Bonds of trust tend to pay. If the field of finance were purely a world of one-off transactions, it would seem ripe for opportunistic behavior. But in the case of repeated entry into financial markets and transactions by, for example, active buyers, intermediaries, and advisers, reputation can count for a great deal in shaping the expectations of counterparties. This implicit bond, trust, or reputation can translate into more effective and econom- ically attractive financial transactions and policies.

Surely, ethical behavior should be an end in itself. If you are behaving ethically only to get rich, then you are hardly committed to that behavior. But it is a useful encouragement that ethical behavior need not entail pure sacrifice. Some might even see ethical behavior as an imperfect means by which justice expresses itself.

Ethical behavior builds teams and leadership, which underpin process excel- lence. Standards of global best-practice emphasize that good business processes drive good outcomes. Stronger teams and leaders result in more agile and creative responses to problems. Ethical behavior contributes to the strength of teams and leadership by aligning employees around shared values and by building confidence and loyalty.

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An objection to this argument is that, in some settings, promoting ethical behavior is no guarantee of team-building. Indeed, teams might blow apart over disagreements about what is ethical or what action is appropriate to take. But typically, this is not the fault of ethics, but rather that of the teams’ processes for handling disagreements.

Ethics sets a higher standard than laws and regulations. To a large extent, the law is a crude instrument. It tends to trail rather than anticipate behavior. It contains gaps that become recreational exploitation for the aggressive businessperson. Justice may be neither swift nor proportional to the crime; as Andrew Wicks said, it “puts you in an adversarial posture with respect to others, which may be counterproductive to other objectives in facing a crisis.”6 To use only the law as a basis for ethical thinking is to settle for the lowest common denominator of social norms. As Richard Breeden, the former SEC chair, said, “It is not an adequate ethical standard to want to get through the day without being indicted.”7

Some might object to that line of thinking by claiming that, in a pluralistic society, the law is the only baseline of norms on which society can agree. Therefore, isn’t the law a “good-enough” guide to ethical behavior? Lynn Paine argued that this view leads to a “compliance” mentality and that ethics takes one further. She wrote, “Attention to law, as an important source of managers’ rights and responsibilities, is integral to, but not a substitute for, the ethical point of view—a point of view that is attentive to rights, responsibilities, relationships, opportunities to improve and enhance human well-being, and virtue and moral excellence.”8

Reputation and conscience. Motivating ethical behavior only by trumpeting its financial benefits without discussing its costs is inappropriate. By some estimates, the average annual income for a lifetime of crime (even counting years spent in prison) is large—it seems that crime does pay. If income were all that mattered, most of us would switch to this lucrative field. The business world features enough cheats and scoundrels who illustrate that there are myriad opportunities for any professional to break promises—or worse—for money. Ethical professionals decline those opportu- nities for reasons having to do with the kind of people they want to be. Amar Bhide and Howard Stevenson wrote:

The businesspeople we interviewed set great store on the regard of their family, friends, and the community at large. They valued their reputations, not for some nebulous financial gain but because they took pride in their good names. Even more important, since outsiders cannot easily judge trustworthiness, businesspeople seem guided by their inner voices, by their consciences. . . . We keep promises because it is right to do so, not because it is good business.9

6Wicks (2003), 11. 7K. V. Salwen, “SEC Chief’s Criticism of Ex-Managers of Salomon Suggests Civil Action is Likely,” Wall Street Journal, 20 November 1991, A10. 8Paine (1999), 194–195. 9Bhide and Stevenson (1990), 127–128.

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For Whose Interests Are You Working? Generally, the financial executive or deal designer is an agent acting on behalf of others. For whom are you the agent? Two classic schools of thought emerge.

• Stockholders. Some national legal frameworks require directors and managers to operate a company in the interests of its shareholders. This shareholder focus affords a clear objective: do what creates shareholder wealth. This approach would seem to limit charitable giving, “living-wage” programs, voluntary reduction of pollution, and enlargement of pension benefits for retirees, all of which can be loosely gathered under the umbrella of the social responsibility movement in business. Milton Friedman (1962), perhaps the most prominent exponent of the stockholder school of thought, has argued that the objective of business is to return value to its owners, and that to divert the objective to other ends is to expropriate shareholder value and threaten the survival of the enterprise. Also, the stockholder view would argue that, if all the companies deviated, the price system would cease to function well as a carrier of information about the allocation of resources in the economy. The stockholder view is perhaps dominant in the United States, the United Kingdom, and other countries in the Anglo-Saxon sphere.

• Stakeholders. The alternative view admits that stockholders are an important constituency of the firm, but that other groups such as employees, customers, suppliers, and the community also have a stake in the activities and the success of the firm. Edward Freeman (1984) argued that the firm should be managed in the interest of the broader spectrum of constituents. The manager would necessarily be obligated to account for the interests and concerns of the various constituent groups in arriving at business decisions. The aim would be to satisfy them all, or at least the most concerned stakeholders, on each issue. The complexity of that kind of decision-making can be daunting and slows the process. In addition, it is not always clear which stakeholder interests are relevant in making specific decisions. Such a definition seems to depend largely on the specific context, which would seem to challenge the ability to achieve equitable treatment of different stakeholder groups across time. But the important contribution of this view is to suggest a relational view of the firm and to stimulate the manager to consider the diversity of those relationships.

Adding complexity to the question of whose interests one serves is the fact that one often has many allegiances—not only to the firm or the client, but also to one’s community, family, etc. One’s obligations as an employee or as a professional are only a subset of one’s total obligations.

What is “Good”? Consequences, Duties, Virtues One confronts ethical issues when one must choose among alternatives on the basis of right versus wrong. The ethical choices may be stark where one alternative is truly right and the other truly wrong. But in professional life, the alternatives typically differ

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more subtly, as in choosing which alternative is more right or less wrong. Ernest Hemingway said that what is moral is what makes one feel good after and what is immoral is what makes one feel bad after. Because feelings about an action could vary tremendously from one person to the next, this simplistic test would seem to admit moral relativism as the only course, an ethical “I’m OK, you’re OK” approach. Fortunately 3,000 years of moral reasoning provide frameworks for a better definition of what is right and wrong.

Right and wrong as defined by consequences. An easy point of departure is to focus on outcomes. An action might be weighed in terms of its utility10 for society. Who is hurt or helped must be taken into consideration. Utility can be assessed in terms of the pleasure or pain for people. People choose to maximize utility. There- fore, the right action is that which produces the greatest good for the greatest number of people.

Utilitarianism has proven to be a controversial ideal. Some critics have argued that this approach might endorse gross violations of the norms that society holds dear, including the right to privacy, the sanctity of contracts, and property rights, when weighed against the consequences for all. And the calculation of utility might be subject to special circumstances or open to interpretation, making the assessment rather more situation-specific than some philosophers could accept.

Utilitarianism was the foundation for modern neoclassical economics. Utility has proved to be difficult to measure rigorously, and remains a largely theoretical idea. Yet utility-based theories are at the core of welfare economics, and underpin analyses of such widely varying phenomena as government policies, consumer preferences, and investor behavior.

Right and wrong as defined by duty or intentions. Immoral actions are ultimately self-defeating. The practice of writing bad checks, for instance, if practiced univer- sally, would result in a world without check-writing and probably very little credit, too. Therefore, you should act on rules that you would be required to apply univer- sally.11 You should treat a person as an end, never as a means. It is vital to ask whether an action would show respect for others and whether that action was something a rational person would do: “If everyone behaved this way, what kind of world would we have?”

Critics of that perspective argue that its universal view is too demanding, indeed, even impossible for a businessperson to observe. For instance, the profit motive focuses on the manager’s duty to just one company. But Norman Bowie responds, “Perhaps focusing on issues other than profits . . . will actually enhance the bottom line. . . . Perhaps we should view profits as a consequence of good business prac- tices rather than as the goal of business.”12

10The Utilitarian philosophers, Jeremy Bentham (1748–1832), James Mill (1773–1836), and John Stuart Mill (1806–1873), argued that the utility (or usefulness) of ideas, actions, and institutions could be measured in terms of their consequences. 11The philosopher Immanuel Kant (1724–1804) sought a foundation for ethics in the purity of one’s motives. 12Bowie (1999), 13.

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Right and wrong as defined by virtues. Finally, a third tradition13 in philosophy argues that the debate over values is misplaced. The focus should instead, be on virtues and the qualities of the practitioner. The attention to consequences or duty is fundamentally a focus on compliance. Rather, one should consider whether an action is consistent with being a virtuous person. This view argues that personal happiness flowed from being virtuous and not merely from comfort (utility) or observance (duty). It acknowledges that vices are corrupting. And it focuses on personal pride: “If I take this action, would I be proud of what I see in the mirror? If it were reported tomorrow in the newspaper, would I be proud of myself?” Warren Buffett, chief executive officer (CEO) of Berkshire Hathaway, and one of the most successful investors in modern history, issued a letter to each of his operating managers every year emphasizing the importance of personal integrity. He said that Berkshire could afford financial losses, but not losses in reputation. He also wrote, “Make sure everything you do can be reported on the front page of your local newspaper written by an unfriendly, but intel- ligent reporter.”14

Critics of virtue-based ethics raise two objections. First, a virtue to one person may be a vice to another. Solomon (1999) points out that Confucius and Friedrich Nietzsche, two other virtue ethicists, held radically different visions of virtue. Confucius extolled such virtues as respect and piety, whereas Nietzsche extolled risk-taking, war- making, and ingenuity. Thus, virtue ethics may be context-specific. Second, virtues can change over time. What may have been regarded as gentlemanly behavior in the nineteenth century might have been seen by feminists in the late twentieth century as insincere and manipulative.

A discrete definition of right and wrong remains the subject of ongoing discourse. But the practical person can abstract from those and other perspectives useful guide- lines toward ethical conduct:

• How will my action affect others? What are the consequences?

• What are my motives? What is my duty here? How does this decision affect them?

• Does this action serve the best that I can be?

What Can You Do to Promote Ethical Behavior in Your Firm? An important contributor to unethical business practices is the existence of a work environment that promotes such behavior. Leaders in corporate workplaces need to be proactive in shaping a high-performance culture that sets high ethical expectations. The leader can take a number of steps to shape an ethical culture.

Adopt a code of ethics. One dimension of ethical behavior is to acknowledge some code by which one intends to live. Corporations, too, can adopt codes of conduct that shape ethical expectations. Firms recognize the “problem of the commons” inherent in

13This view originated in ancient Greek philosophy, starting with Socrates, Plato, and Aristotle. 14Russ Banham, “The Warren Buffett School,” Chief Executive (December 2002): http://www.robertpmiles. com/BuffettSchool.htm (accessed on 19 May 2003).

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unethical behavior by one or a few employees. In 1909, the U.S. Supreme Court decided that a corporation could be held liable for the actions of its employees.15

Since then, companies have sought to set corporate expectations for employee behavior, including codes of ethics.16 Exhibit 2 gives an example of one such code, from General Electric Company. Those norms are one page of a 35-page document outlining the code, to whom it applies, special responsibilities for employees and leaders, specific codes of conduct with respect to customers and suppliers, government business, competition, health, safety, employment, and the protection of GE’s assets. Corporate codes are viewed by some critics as cynical efforts that seem merely to respond to executive liability that might arise from white-collar and other economic crimes. Companies and their executives may be held liable for an employee’s behavior, even if the employee acted contrary to the company’s instructions. Mere observance of guidelines in order to reduce liability is a legalistic approach to ethical behavior. Instead, Lynn Paine (1994) has urged firms to adopt an “integrity strategy” that uses ethics as the driving force within a corporation. Deeply held values would become the foundation for decision-making across the firm, and would yield a frame of reference that would integrate functions and businesses. By that view, ethics defines what a firm stands for.

In addition, an industry or a professional group can adopt a code of ethics. One example relevant to finance professionals is the Code of Ethics of the CFA Institute, the group that confers the Chartered Financial Analyst (CFA) designation on profes- sional securities analysts and portfolio managers. Excerpts from the CFA Institute’s Code of Ethics and Standards of Professional Conduct are given in Exhibit 3.

Talk about ethics within your team and firm. Many firms seek to reinforce a culture of integrity with a program of seminars and training in ethical reasoning. A leader can stimulate reflection through informal discussion of ethical developments (for example: indictments, convictions, civil lawsuits) in the industry or profession, or of ethical issues that the team may be facing. This kind of discussion (without preaching) signals that it is on the leader’s mind and is a legitimate focus of discussion. One executive regularly raises issues such as those informally over lunch or morning coffee. Leaders believe that ethical matters are important enough to be the focus of team discussions.

Reflect on your dilemmas. The challenge for many finance practitioners is that ethical dilemmas do not readily lend themselves to the structured analysis that one would apply to valuing a firm or balancing the books. Nevertheless, one can harness the questions raised in the field of ethics to lend some rigor to one’s reflections. Laura Nash (1981) abstracted a list of 12 questions on which the thoughtful practitioner might reflect in grappling with an ethical dilemma:

1. Have I defined the problem correctly and accurately?

2. If I stood on the other side of the problem, how would I define it?

15See New York Central v. United States, 212 U.S. 481. 16Murphy (1997) compiled 80 exemplary ethics statements.

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3. What are the origins of this dilemma?

4. To whom and to what am I loyal, as a person and as a member of a firm?

5. What is my intention in making this decision?

6. How do the likely results compare with my intention?

7. Can my decision injure anyone? How?

8. Can I engage the affected parties in my decision before I decide or take action?

9. Am I confident that my decision will be as valid over a long period as it may seem at this moment?

10. If my boss, the CEO, the directors, my family, or the community learned about this decision, would I have misgivings about my actions?

11. What signals (or symbols) might my decision convey, if my decision were under- stood correctly? If misunderstood?

12. Are there exceptions to my position, perhaps special circumstances under which I might make a different decision?

Act on Your Reflections This may be the toughest step of all. The field of ethics can lend structure to one’s thinking, but has less to say about the action to be taken. When confronting a problem of ethics within a team or an organization, one can consider a hierarchy of responses, from questioning and coaching to whistle-blowing (either to an internal ombudsperson or, if necessary, to an outside entity) and, possibly, leaving the organization.

Conclusion An analysis of finance’s ethical issues is vital. The cases of WorldCom and other major business scandals show that ethical issues pervade the financial environment. Ethics is one of the pillars on which stands success in finance—it builds sustainable enter- prise, trust, organizational strength, and personal satisfaction. Therefore, the financial decision-maker must learn to identify, analyze, and act on the ethical issues that may arise. Consequences, duties, and virtues stand out as three important benchmarks for ethical analysis. Nevertheless, the results of such analysis are rarely clear-cut. But real business leaders will take the time to sort through the ambiguities and do “the right thing” in the words of Edwin LeFevre. These and other ethical themes will appear throughout finance case studies and one’s career.

References and Recommended Readings Achampong, F., and W. Zemedkun. “An Empirical and Ethical Analysis of Factors

Motivating Managers’ Merger Decisions.” Journal of Business Ethics 14 (1995): 855–865.

Bhide, A., and H. H. Stevenson. “Why be Honest if Honesty Doesn’t Pay.” Harvard Business Review (September–October 1990): 121–129.

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Bloomenthal, Harold S. Sarbanes-Oxley Act in Perspective. (St. Paul, MN: West Group), 2002.

Blumenstein, R., and S. Pulliam. “WorldCom Report Finds Ebbers Played Role in Inflating Revenue.” Wall Street Journal. 6 June 2003, downloaded from http://online.wsj.com/article_print/0,,SB105485251027721500,00.html.

Blumenstein, R., and D. Solomon. “MCI is Expected to Pay Massive Fine in SEC Deal.” Wall Street Journal. 19 May 2003, downloaded from http://online.wsj .com/ article_print/0,,SB105329362774148600,00.html.

Boatright, J. R. Ethics in Finance. (Oxford: Blackwell Publishers), 1999. Bowie, N. E. “A Kantian Approach to Business Ethics.” in A Companion to Busi-

ness Ethics. R. E. Frederick, ed. (Malden, MA: Blackwell), 1999, 3–16. Carroll, A. B. “Ethics in Management.” in A Companion to Business Ethics. R. E.

Frederick, ed. (Malden, MA: Blackwell), 1999, 141–152. Frederick, R. E. A Companion to Business Ethics. (Oxford: Blackwell Publishers). Freeman, R. E. Strategic Management: A Stakeholder Approach. (Boston, MA:

Pittman), 1984. Friedman, M. Capitalism and Freedom. (Chicago, IL: University of Chicago

Press), 1962. General Electric Company. “Integrity: The Spirit and Letter of our Commitment.”

February 2004. http://www.ge.com/files/usa/en/commitment/social/integrity/ downloads/english.pdf.

Jensen, M. “The Agency Costs of Overvalued Equity.” Financial Management (Spring 2005): 5–19.

Kidder, R. “Ethics and the Bottom Line: Ten Reasons for Businesses to do Right.” Insights on Global Ethics (Spring 1997): 7–9.

Murphy, P. E. “80 Exemplary Ethics Statements.” in L. H. Newton, “A Passport for the Corporate Code: From Borg Warner to the Caux Principles.” in R. E. Frederick, ed. A Companion to Business Ethics. (Malden, MA: Blackwell), 1999, 374–385.

Nash, L. L. “Ethics without the Sermon,” Harvard Business Review (November–December 1981): 79–90.

Paine, L. S. “Managing for Organizational Integrity.” Harvard Business Review (March–April 1994): 106–117.

———. “Law, Ethics, and Managerial Judgment,” in R. E. Frederick, ed. A Com- panion to Business Ethics. (Malden, MA: Blackwell), 1999, 194–206.

Paine, L. S. Value Shift: Why Companies Must Merger Social and Financial Imperatives to Achieve Superior Performance. (New York: McGraw-Hill), 2003.

Pulliam, S. “A Staffer Ordered to Commit Fraud Balked, and then Caved.” Wall Street Journal. 23 June 2003, A1.

Sen, A. On Ethics and Economics. (Oxford: Blackwell Publishers), 1987.

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xliv Ethics in Finance

Shafer, W. “Effects of Materiality, Risk, and Ethical Perceptions on Fraudulent Reporting by Financial Executives.” Journal of Business Ethics 38, 3 (2002): 243–263.

Solomon, R. “Business Ethics and Virtue.” in R. E. Frederick, ed. A Companion to Business Ethics. (Malden, MA: Blackwell), 1999, 30–37.

Solomon, D. “WorldCom Moved Expenses to the Balance Sheet of MCI.” Wall Street Journal. 31 March 2003, http://online.wsj.com/article_print/ 0,,SB104907054486790100,00.html.

Werhane, P. “Two Ethical Issues in Mergers and Acquisitions.” Journal of Busi- ness Ethics 7 (1988): 41–45.

———. “Mergers, Acquisitions, and the Market for Corporate Control.” Public Affairs Quarterly 4, 1 (1990): 81–96.

———. “A Note on Moral Imagination.” Charlottesville, VA: University of Virginia Darden School of Business Case Collection (UVA-E-0114), 1997.

———. “Business Ethics and the Origins of Contemporary Capitalism: Econom- ics and Ethics in the Work of Adam Smith and Herbert Spencer.” in R. E. Frederick, ed. A Companion to Business Ethics. (Malden, MA: Blackwell), 1999, 325–341.

Wicks, A. “A Note on Ethical Decision Making.” Charlottesville, VA: University of Virginia Darden School of Business Case Collection (UVA-E-0242), 2003.

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EXHIBIT 1 | Prominent Business Scandals Revealed between 1998 and 2002

The companies and their alleged or admitted accounting issues are as follows:

• Adelphia (loans and looting) • Bristol-Myers (improper inflation of revenues through sue of sales incentives) • CMS Energy (overstatement of revenues through round-trip energy trades) • Computer Associates (inflation of revenues) • Dynegy (artificial increase of cash flow) • Elan (use of off-balance-sheet entities) • Enron (inflation of earnings and use of off-balance-sheet entities) • Global Crossing (artificial inflation of revenues) • Halliburton (improper revenue recognition) • Kmart (accounting for vendor allowances) • Lucent Technologies (revenue accounting and vendor financing) • Merck (revenue recognition) • MicroStrategy (backdating of sales contracts) • Network Associates (revenue and expense recognition) • PNC Financial Services (accounting for the transfer of loans) • Qwest (revenue inflation) • Reliance Resources (revenue inflation through round-trip energy trades) • Rite Aid (inflation of earnings) • Tyco International (improper use of “cookie jar” reserves and acquisition accounting) • Vivendi Universal (withholding information about liquidity troubles) • WorldCom (revenue and expense recognition) • Xerox (revenue and earnings inflation)

These cases and their points of controversy are summarized in Bloomenthal (2002), Appendices E-1 and E-2.

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EXHIBIT 2 | General Electric’s (GE) Code of Conduct

• Obey the applicable laws and regulations governing our business conduct worldwide. • Be honest, fair, and trustworthy in all your GE activities and relationships. • Avoid all conflicts of interest between work and personal affairs. • Foster an atmosphere in which fair employment practices extend to every member of the diverse GE community. • Strive to create a safe workplace and to protect the environment. • Through leadership at all levels, sustain a culture where ethical conduct is recognized, valued, and exemplified

by all employees.

Source: General Electric Company, “Integrity: The Spirit and Letter of Our Commitment,” February 2004, 5. A longer version of this resource is also available on the company’s Web site at http://www.ge.com/files/usa/en/commitment/social/integrity/downloads/ english.pdf.

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EXHIBIT 3 | Excerpts from the CFA Institute’s Code of Ethics and Standards of Professional Conduct: January 1, 2006

CFA Institute’s Code of Ethics • Act with integrity, competence, diligence, respect, and in an ethical manner with the public, clients, prospective

clients, employers, employees, colleagues in the investment profession, and other participants in the global capital markets.

• Place the integrity of the investment profession and the interests of clients above their own personal interests. • Use reasonable care and exercise independent professional judgment when conducting investment analysis,

making investment recommendations, taking investment actions, and engaging in other professional activities. • Practice and encourage others to practice in a professional and ethical manner that will reflect credit on them-

selves and the profession. • Promote the integrity of, and uphold the rules governing, capital markets. • Maintain and improve their professional competence and strive to maintain and improve the competence of

other investment professionals.

CFA Institute’s Standards of Professional Conduct (excerpts that suggest the scope and detail of the complete standards)

Members and candidates must: • Understand and comply with all applicable laws, rules, and regulations . . . • Use reasonable care and judgment to achieve and maintain independence and objectivity in their professional

activities. Members and candidates must not offer, solicit, or accept any gift, benefit, compensation, or consider- ation that reasonably could be expected to compromise their own or another’s independence and objectivity.

• Not knowingly make any misrepresentations relating to investment analysis, recommendations, actions, or other professional activities.

• Not engage in any professional conduct involving dishonesty, fraud, or deceit, or commit any act that reflects adversely on their professional reputation, integrity, or competence.

• Not act or cause others to act on the [material, nonpublic] information. • Not engage in practices that distort prices or artificially inflate trading volume with the intent to mislead market

participants. • Have a duty of loyalty to their clients and must act with reasonable care and exercise prudent judgment.

Members and candidates must act for the benefit of their clients and place their clients’ interests before their employer’s or their own interests. . . .

• Deal fairly and objectively with all clients. . . . • Keep information about current, former, and prospective clients confidential. . . . • Act for the benefit of their employer and not deprive their employer of the advantage of their skills and abilities,

divulge confidential information, or otherwise cause harm to their employer. • Not accept gifts, benefits, compensation, or consideration that competes with, or might reasonably be expected

to create a conflict of interest with, their employer’s interest. . . . • Make reasonable efforts to detect and prevent violations of applicable laws, rules, regulations, and the Code

and Standards by anyone subject to their supervision or authority. • Disclose to clients and prospective clients the basic format and general principles of the investment processes

used . . . Use reasonable judgment in identifying which factors are important to their investment analyses, rec- ommendations, or actions and include those factors in communications with clients and prospective clients. . . . Distinguish between fact and opinion in the presentation of investment analysis and recommendations. . . .

Source: CFA Institute, Code of Ethics and Standards of Professional Conduct (Charlottesville, VA: CFA Institute), 2006, http://www.cfainstitute.org/cfacentre/pdf/English2006CodeandStandards.pdf.

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xlviii Part One Part Title

xlviii

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Case Studies in Finance

Managing for Corporate Value Creation

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Setting Some Themes

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Warren E. Buffett, 2005 On May 24, 2005, Warren E. Buffett, the chairperson and chief executive officer (CEO) of Berkshire Hathaway Inc., announced that MidAmerican Energy Holdings Company, a subsidiary of Berkshire Hathaway, would acquire the electric utility PacifiCorp. In Buffett’s largest deal since 1998, and the second largest of his entire career, MidAmer- ican would purchase PacifiCorp from its parent, Scottish Power plc, for $5.1 billion in cash and $4.3 billion in liabilities and preferred stock. “The energy sector has long interested us, and this is the right fit,” Buffett said. At the announcement, Berkshire Hathaway’s Class A shares closed up 2.4% for the day, for a gain in market value of $2.55 billion.1 Scottish Power’s share price also jumped 6.28% on the news;2 the S&P 500 Composite Index closed up 0.02%. Exhibit 1 illustrates the recent share price performance for Berkshire Hathaway, Scottish Power, and the S&P 500 Index.

The acquisition of PacifiCorp renewed public interest in its sponsor, Warren Buffett. In many ways, he was an anomaly. One of the richest individuals in the world (with an estimated net worth of about $44 billion), he was also respected and even beloved. Though he had accumulated perhaps the best investment record in history (a compound annual increase in wealth for Berkshire Hathaway of 24% from 1965 to 2004),3 Berkshire paid him only $100,000 per year to serve as its CEO. While Buffett and other insiders controlled 41.8% of Berkshire Hathaway, he ran the company in the interests of all shareholders. “We will not take cash compensation, restricted stock, or option grants that would make our results superior to [those of Berkshire’s investors],” Buffett said. “I will keep well over 99% of my net worth in Berkshire. My wife and I have never sold a share nor do we intend to.”4

3

1CASE

1The per-share change in Berkshire Hathaway’s Class A share price at the date of the announcement was $2,010. The company had 1,268,783 Class A shares outstanding. 2The per-share change in Scottish Power’s share price at the date of the announcement was (British pounds) GBP27.75. The company had 466,112,000 shares outstanding. 3In comparison, the annual average total return on all large stocks from 1965 to the end of 2004 was 10.5%. Stocks, Bonds, Bills, and Inflation 2005 Yearbook (Chicago: Ibbotson Associates, 2005), 217. 4Warren Buffett, Annual Letter to Shareholders, 2001.

This case was prepared by Robert F. Bruner and Sean D. Carr as a basis for class discussion rather than to illustrate effective or ineffective handling of an administrative situation. Copyright © 2005 by the University of Virginia Darden School Foundation, Charlottesville, VA. All rights reserved. To order copies, send an e-mail to [email protected] No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means—electronic, mechanical, photocopying, recording, or otherwise—without the permission of the Darden School Foundation. Rev. 2/07.

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4 Part One Setting Some Themes

Buffett was the subject of numerous laudatory articles and at least eight biographies, yet he remained an intensely private individual. Though acclaimed by many as an intellectual genius, he shunned the company of intellectuals and preferred to affect the manner of a down-home Nebraskan (he lived in Omaha) and a tough-minded investor. In contrast to investing’s other “stars,” Buffett acknowledged his investment failures both quickly and publicly. Although he held an MBA from Columbia University and credited his mentor, Professor Benjamin Graham, with developing the philosophy of value-based investing that had guided Buffett to his success, he chided business schools for the irrelevance of their finance and investing theories.

Numerous writers sought to distill the essence of Buffett’s success. What were the key principles that guided Buffett? Could those principles be applied broadly in the 21st century, or were they unique to Buffett and his time? From an understanding of those principles, analysts hoped to illuminate the acquisition of PacifiCorp. What were Buffett’s probable motives in the acquisition? What did Buffett’s offer say about his valuation of PacifiCorp, and how would it compare with valuations for other reg- ulated utilities? Would Berkshire’s acquisition of PacifiCorp prove to be a success? How would Buffett define success?

Berkshire Hathaway Inc. Berkshire Hathaway was incorporated in 1889 as Berkshire Cotton Manufacturing, and eventually grew to become one of New England’s biggest textile producers, accounting for 25% of the United States’ cotton textile production. In 1955, Berkshire merged with Hathaway Manufacturing and began a secular decline due to inflation, technological change, and intensifying competition from foreign competitors. In 1965, Buffett and some partners acquired control of Berkshire Hathaway, believing that its financial decline could be reversed.

Berkshire Hathaway “Class A” vs. S&P 500 Composite Index

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Case 1 Warren E. Buffett, 2005 5

5A split was an increase in the number of a firm’s outstanding shares that did not cause a change in the shareholders’ equity. A two-for-one split would entail a 50% reduction in the stock’s price at the time of the split. Company directors authorized stock splits to make the company’s shares affordable to a broader range of investors. 6In 1996, Berkshire Hathaway issued Class B shares, which had an economic interest equal to 1/30th and a voting interest equal to 1/200th that of the firm’s Class A shares. 7Berkshire Hathaway Inc., 2004 Annual Report, 1.

Over the next 20 years, it became apparent that large capital investments would be required to remain competitive and that even then the financial returns would be mediocre. Fortunately, the textile group generated enough cash in the initial years to permit the firm to purchase two insurance companies headquartered in Omaha: National Indemnity Company and National Fire & Marine Insurance Company. Acqui- sitions of other businesses followed in the 1970s and 1980s; Berkshire Hathaway exited the textile business in 1985.

The investment performance of a share in Berkshire Hathaway had astonished most observers. In 1977, the firm’s year-end closing share price was $102; on May 24, 2005, the closing price on its Class A shares reached $85,500. Over the same period, the Stan- dard & Poor’s 500 Index grew from 96 to 1,194. Some observers called for Buffett to split5 the firm’s share price to make it more accessible to the individual investor. He steadfastly refused.6

In 2004, Berkshire Hathaway’s annual report described the firm as “a holding company owning subsidiaries engaged in a number of diverse business activities.”7

Berkshire’s portfolio of businesses included:

• Insurance: The largest component of Berkshire’s portfolio focused on property and casualty insurance, on both a direct and a reinsurance basis (for example, GEICO, General Re).

• Apparel: Manufacturing and distribution of a variety of footwear and clothing products, including underwear, active-wear, children’s clothes, and uniforms (for example, Fruit of the Loom, Garan, Fechheimer Brothers, H.H. Brown Shoe, Justin Brands).

• Building products: Manufacturing and distribution of a variety of building materials, and related products and services (for example, Acme Building Brands, Benjamin Moore, Johns Manville, MiTek).

• Finance and financial products: Proprietary investing, manufactured housing and related consumer financing, transportation equipment leasing, furniture leasing, life annuities and risk management products (for example, BH Finance, Clayton Homes, XTRA, CORT, Berkshire Hathaway Life, and General Re Securities).

• Flight services: Training to operators of aircraft and ships, and providing fractional ownership programs for general aviation aircraft (for example, FlightSafety, NetJets).

• Retail: Retail sales of home furnishings, appliances, electronics, fine jewelry, and gifts (for example, Nebraska Furniture Mart, R.C. Willey Home Furnishings, Star

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6 Part One Setting Some Themes

Furniture Company, Jordan’s Furniture, Borsheim’s, Helzberg Diamond Shops, Ben Bridge Jeweler).

• Grocery distribution: Wholesale distributing of groceries and nonfood items (for example, McLane Company).

• Carpet and floor coverings: Manufacturing and distribution of carpet and floor coverings under a variety of brand names (for example, Shaw Industries).

Berkshire also owned an assortment of smaller businesses8 generating about $3 billion in revenues. Exhibit 2 gives a summary of revenues, operating profits, capital expenditures, depreciation, and assets for Berkshire’s various business seg- ments. The company’s investment portfolio also included equity interests in numer- ous publicly traded companies, which are summarized in Exhibit 3. In addition, the company owned about $21.4 billion of foreign exchange contracts at year end, spread among 12 currencies. Prior to March 2002, neither Buffett nor Berkshire had ever traded in currencies, but Buffett had developed serious concerns about the United States’ large current account deficits, and he hoped that his currency bets would offset the growing pressure on the dollar.

Buffett’s Investment Philosophy Warren Buffett was first exposed to formal training in investing at Columbia University where he studied under Professor Benjamin Graham. A coauthor of the classic text Security Analysis, Graham developed a method of identifying undervalued stocks (that is to say, stocks whose prices were less than their intrinsic value). This became the cornerstone of modern value investing. Graham’s approach was to focus on the value of assets, such as cash, net working capital, and physical assets. Eventually, Buffett modified that approach to focus also on valuable franchises that were unrecognized by the market.

Over the years, Buffett had expounded his philosophy of investing in his chair- person’s letter to the shareholders in Berkshire Hathaway’s annual report. By 2005, those lengthy letters had accumulated a broad following because of their wisdom and their humorous, self-deprecating tone. The letters emphasized the following elements:

1. Economic reality, not accounting reality. Financial statements prepared by accountants conformed to rules that might not adequately represent the economic reality of a business. Buffett wrote:

. . . because of the limitations of conventional accounting, consolidated reported earnings may reveal relatively little about our true economic performance. Charlie [Munger,

8These included Scott Fetzer, a diversified manufacturer and distributor of commercial and industrial products; Buffalo News, a newspaper publisher in western New York; International Dairy Queen, which licensed and serviced a system of 6,000 Dairy Queen stores; See’s Candies, a manufacturer and distributor of boxed chocolates and other confectionery products; Larson-Juhl, which designed, manufactured, and distrib- uted custom picture-framing products; CTB International, a manufacturer of equipment and systems for the poultry, hog, egg production, and grain industries; and the Pampered Chef, a direct seller of kitchen tools.

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Case 1 Warren E. Buffett, 2005 7

Buffett’s business partner] and I, both as owners and managers, virtually ignore such consolidated numbers. . . . Accounting consequences do not influence our operating or capital-allocation process.9

Accounting reality was conservative, backward-looking, and governed by generally accepted accounting principles (GAAP). Investment decisions, on the other hand, should be based on the economic reality of a business. In economic reality, intan- gible assets, such as patents, trademarks, special managerial expertise, and reputa- tion might be very valuable, yet under GAAP, they would be carried at little or no value. GAAP measured results in terms of net profit; in economic reality, the results of a business were its flows of cash.

A key feature to Buffett’s approach defined economic reality at the level of the business itself, not the market, the economy, or the security—he was a funda- mental analyst of the business. His analysis sought to judge the simplicity of the business, the consistency of its operating history, the attractiveness of its long- term prospects, the quality of management, and the firm’s capacity to create value.

2. The cost of the lost opportunity. Buffett compared an investment opportunity against the next best alternative, the “lost opportunity.” In his business decisions, he demonstrated a tendency to frame his choices as either/or decisions rather than yes/no decisions. Thus, an important standard of comparison in testing the attractiveness of an acquisition was the potential rate of return from investing in the common stocks of other companies. Buffett held that there was no funda- mental difference between buying a business outright, and buying a few shares of that business in the equity market. Thus, for him, the comparison of an invest- ment against other returns available in the market was an important benchmark of performance.

3. Value creation: time is money. Buffett assessed intrinsic value as the present value of future expected performance:

[All other methods fall short in determining whether] an investor is indeed buying something for what it is worth and is therefore truly operating on the principle of obtaining value for his investments. . . . Irrespective of whether a business grows or doesn’t, displays volatility or smoothness in earnings, or carries a high price or low in relation to its current earnings and book value, the investment shown by the discounted-flows-of-cash calculation to be the cheapest is the one that the investor should purchase.10

Enlarging on his discussion of intrinsic value, Buffett used an educational example:

We define intrinsic value as the discounted value of the cash that can be taken out of a business during its remaining life. Anyone calculating intrinsic value necessarily comes up with a highly subjective figure that will change both as estimates of future cash flows are revised and as interest rates move. Despite its fuzziness, however, intrinsic value is all important and is the only logical way to evaluate the relative attractiveness of investments and businesses.

9Berkshire Hathaway Inc., 2004 Annual Report, 2. 10Berkshire Hathaway Inc., 1992 Annual Report, 14.

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8 Part One Setting Some Themes

To see how historical input (book value) and future output (intrinsic value) can diverge, let us look at another form of investment, a college education. Think of the education’s cost as its “book value.” If it is to be accurate, the cost should include the earnings that were foregone by the student because he chose college rather than a job. For this exercise, we will ignore the important non-economic benefits of an education and focus strictly on its economic value. First, we must estimate the earnings that the graduate will receive over his lifetime and subtract from that figure an estimate of what he would have earned had he lacked his education. That gives us an excess earnings figure, which must then be discounted, at an appropriate interest rate, back to graduation day. The dollar result equals the intrinsic economic value of the education. Some graduates will find that the book value of their education exceeds its intrinsic value, which means that whoever paid for the education didn’t get his money’s worth. In other cases, the intrinsic value of an education will far exceed its book value, a result that proves capital was wisely deployed. In all cases, what is clear is that book value is meaningless as an indicator of intrinsic value.11

To illustrate the mechanics of this example, consider the hypothetical case presented in Exhibit 4. Suppose an individual has the opportunity to invest $50 million in a business—this is its cost or book value. This business will throw off cash at the rate of 20% of its investment base each year. Suppose that instead of receiving any dividends, the owner decides to reinvest all cash flow back into the business—at this rate, the book value of the business will grow at 20% per year. Suppose that the investor plans to sell the business for its book value at the end of the fifth year. Does this investment create value for the individual? One determines this by discounting the future cash flows to the present at a cost of equity of 15%. Suppose that this is the investor’s opportunity cost, the required return that could have been earned elsewhere at comparable risk. Dividing the present value of future cash flows (i.e., Buffett’s intrinsic value) by the cost of the investment (i.e., Buffett’s book value) indicates that every dollar invested buys securities worth $1.23. Value is created.

Consider an opposing case, summarized in Exhibit 5. The example is similar in all respects, except for one key difference: the annual return on the investment is 10%. The result is that every dollar invested buys securities worth $0.80. Value is destroyed.

Comparing the two cases in Exhibits 4 and 5, the difference in value creation and destruction is driven entirely by the relationship between the expected returns and the discount rate: in the first case, the spread is positive; in the second case, it is negative. Only in the instance where expected returns equal the discount rate will book value equal intrinsic value. In short, book value or the investment outlay may not reflect the economic reality. One needs to focus on the prospective rates of return, and how they compare to the required rate of return.

4. Measure performance by gain in intrinsic value, not accounting profit. Buffett wrote:

11Berkshire Hathaway Inc., 1994 Annual Report, 7.

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Our long-term economic goal . . . is to maximize Berkshire’s average annual rate of gain in intrinsic business value on a per-share basis. We do not measure the economic significance or performance of Berkshire by its size; we measure by per-share progress. We are certain that the rate of per-share progress will diminish in the future—a greatly enlarged capital base will see to that. But we will be disappointed if our rate does not exceed that of the average large American corporation.12

The gain in intrinsic value could be modeled as the value added by a business above and beyond the charge for the use of capital in that business. The gain in intrinsic value was analogous to the economic-profit and market-value-added measures used by analysts in leading corporations to assess financial perform- ance. Those measures focus on the ability to earn returns in excess of the cost of capital.

5. Risk and discount rates. Conventional academic and practitioner thinking held that the more risk one took, the more one should get paid. Thus, discount rates used in determining intrinsic values should be determined by the risk of the cash flows being valued. The conventional model for estimating discount rates was the capital asset pricing model (CAPM), which added a risk premium to the long- term risk-free rate of return, such as the U.S. Treasury bond yield.

Buffett departed from conventional thinking by using the rate of return on the long-term (for example, 30 year) U.S. Treasury bond to discount cash flows.13

Defending this practice, Buffett argued that he avoided risk, and therefore should use a “risk-free” discount rate. His firm used almost no debt financing. He focused on companies with predictable and stable earnings. He or his vice chair, Charlie Munger, sat on the boards of directors, where they obtained a candid, inside view of the company and could intervene in managements’ decisions if necessary. Buffett once said, “I put a heavy weight on certainty. If you do that, the whole idea of a risk factor doesn’t make sense to me. Risk comes from not knowing what you’re doing.”14 He also wrote:

We define risk, using dictionary terms, as “the possibility of loss or injury.” Academics, however, like to define “risk” differently, averring that it is the relative volatility of a stock or a portfolio of stocks—that is, the volatility as compared to that of a large universe of stocks. Employing databases and statistical skills, these academics compute with precision the “beta” of a stock—its relative volatility in the past—and then build arcane investment and capital allocation theories around this calculation. In their hunger for a single statistic to measure risk, however, they forget a fundamental principle: it is better to be approxi- mately right than precisely wrong.15

Case 1 Warren E. Buffett, 2005 9

12Berkshire Hathaway Inc., 2004 Annual Report, 74. 13The yield on the 30-year U.S. Treasury bond on May 24, 2005, was 5.76%. The beta of Berkshire Hathaway was 0.75. 14Quoted in Jim Rasmussen, “Buffett Talks Strategy with Students,” Omaha World-Herald, 2 January 1994, 26. 15Berkshire Hathaway Inc., 1993 Annual Report. Republished in Andrew Kilpatrick, Of Permanent Value: The Story of Warren Buffett (Birmingham, AL: AKPE, 1994), 574.

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10 Part One Setting Some Themes

6. Diversification. Buffett disagreed with conventional wisdom that investors should hold a broad portfolio of stocks in order to shed company-specific risk. In his view, investors typically purchased far too many stocks rather than waiting for one exceptional company. Buffett said,

Figure businesses out that you understand and concentrate. Diversification is protection against ignorance, but if you don’t feel ignorant, the need for it goes down drastically.16

7. Investing behavior should be driven by information, analysis, and self-discipline, not by emotion or “hunch.” Buffett repeatedly emphasized awareness and infor- mation as the foundation for investing. He said, “Anyone not aware of the fool in the market probably is the fool in the market.”17 Buffett was fond of repeating a parable told to him by Benjamin Graham:

There was a small private business and one of the owners was a man named Market. Every day, Mr. Market had a new opinion of what the business was worth, and at that price stood ready to buy your interest or sell you his. As excitable as he was opinionated, Mr. Market presented a constant distraction to his fellow owners. “What does he know?” they would wonder, as he bid them an extraordinarily high price or a depressingly low one. Actually, the gentleman knew little or nothing. You may be happy to sell out to him when he quotes you a ridiculously high price, and equally happy to buy from him when his price is low. But the rest of the time, you will be wiser to form your own ideas of the value of your holdings, based on full reports from the company about its operation and financial position.18

Buffett used this allegory to illustrate the irrationality of stock prices as compared to true intrinsic value. Graham believed that an investor’s worst enemy was not the stock market, but oneself. Superior training could not compensate for the absence of the requisite temperament for investing. Over the long term, stock prices should have a strong relationship with the economic progress of the business. But daily market quotations were heavily influenced by momentary greed or fear, and were an unreliable measure of intrinsic value. Buffett said,

As far as I am concerned, the stock market doesn’t exist. It is there only as a reference to see if anybody is offering to do anything foolish. When we invest in stocks, we invest in businesses. You simply have to behave according to what is rational rather than according to what is fashionable.19

Accordingly, Buffett did not try to “time the market” (i.e., trade stocks based on expectations of changes in the market cycle)—his was a strategy of patient, long-term investing. As if in contrast to Mr. Market, Buffett expressed more

16Quoted in Forbes (19 October 1993). Republished in Andrew Kilpatrick, Of Permanent Value, 574. 17Quoted in Michael Lewis, Liar’s Poker (New York: Norton, 1989), 35. 18Originally published in Berkshire Hathaway Inc., 1987 Annual Report. This quotation was paraphrased from James Grant, Minding Mr. Market (New York: Times Books, 1993), xxi. 19Peter Lynch, One Up on Wall Street (New York: Penguin Books, 1990), 78.

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Case 1 Warren E. Buffett, 2005 11

contrarian goals: “We simply attempt to be fearful when others are greedy and to be greedy only when others are fearful.”20 Buffett also said, “Lethargy bordering on sloth remains the cornerstone of our investment style,”21 and “The market, like the Lord, helps those who help themselves. But unlike the Lord, the market does not forgive those who know not what they do.”22

Buffett scorned the academic theory of capital market efficiency. The efficient markets hypothesis (EMH) held that publicly known information was rapidly impounded into share prices, and that as a result, stock prices were fair in reflect- ing what was known about the company. Under EMH, there were no bargains to be had and trying to outperform the market would be futile. “It has been helpful to me to have tens of thousands turned out of business schools taught that it didn’t do any good to think,” Buffett said.23

I think it’s fascinating how the ruling orthodoxy can cause a lot of people to think the earth is flat. Investing in a market where people believe in efficiency is like playing bridge with someone who’s been told it doesn’t do any good to look at the cards.24

8. Alignment of agents and owners. Explaining his significant ownership interest in Berkshire Hathaway, Buffett said, “I am a better businessman because I am an investor. And I am a better investor because I am a businessman.”25

As if to illustrate this sentiment, he said:

A managerial “wish list” will not be filled at shareholder expense. We will not diversify by purchasing entire businesses at control prices that ignore long-term economic conse- quences to our shareholders. We will only do with your money what we would do with our own, weighing fully the values you can obtain by diversifying your own portfolios through direct purchases in the stock market.26

For four of Berkshire’s six directors, over 50% of their family net worth was represented by shares in Berkshire Hathaway. The senior managers of Berkshire Hathaway subsidiaries held shares in the company, or were compensated under incentive plans that imitated the potential returns from an equity interest in their business unit or both.27

20Berkshire Hathaway Inc., 1986 Annual Report, 16. 21Berkshire Hathaway Inc., 1990 Annual Report, 15. 22Berkshire Hathaway Inc., Letters to Shareholders, 1977–1983, 53. 23Quoted in Andrew Kilpatrick, Of Permanent Value, 353. 24Quoted in L. J. Davis, “Buffett Takes Stock,” New York Times, 1 April 1990, 16. 25Quoted in Forbes (19 October 1993). Republished in Andrew Kilpatrick, Of Permanent Value, 574. 26“Owner-Related Business Principles,” in Berkshire Hathaway’s 2004 Annual Report, 75. 27In April 2005, the U.S. Securities and Exchange Commission interviewed Warren Buffett in connection with an investigation into the insurance giant AIG and its dealings with Berkshire Hathaway’s General Re insurance unit. Buffett reported that he had questioned General Re’s CEO about the transactions with AIG, but that he never learned any details.

bru6171X_case01_001-022.qxd 11/24/12 2:23 PM Page 11

MidAmerican Energy Holdings Company MidAmerican Energy Holdings Company, a subsidiary of Berkshire Hathaway Inc., was a leader in the production of energy from diversified sources, including geothermal, natural gas, hydroelectric, nuclear power, and coal. Based in Des Moines, Iowa, the company was a major supplier and distributor of energy to over 5 million customers in the United States and Great Britain. Through its HomeServices of America division, MidAmerican also owned the second-largest full-service independent real-estate bro- kerage in the United States. Exhibit 6 provides condensed, consolidated financial statements for MidAmerican for the years 2000 through 2004.

Berkshire Hathaway took a major stake in MidAmerican on March 14, 2000, with a $1.24 billion investment in common stock and a nondividend-paying convert- ible preferred stock.28 This investment gave Berkshire about a 9.7% voting interest and a 76% economic interest in MidAmerican. “Though there are many regulatory constraints in the utility industry, it’s possible that we will make additional commit- ments in the field,” Buffett said, at the time. “If we do, the amounts could be large.”29

Subsequently, in March 2002, Berkshire acquired another 6.7 million shares of MidAmerican’s convertible stock for $402 million, giving Berkshire a 9.9% voting interest and an 83.7% economic interest in the equity of MidAmerican (80.5% on a diluted basis).

At the time of Berkshire’s initial investment in MidAmerican, Buffett explained that acquisitions in the electric utility industry were complicated by a variety of reg- ulations, including the Public Utility Holding Company Act of 1935 (PUHCA), which was intended to prevent conglomerates from owning utilities and to impede the for- mation of massive national utilities that regulators could not control. This regulation made it necessary for Berkshire to structure its investment in MidAmerican such that it would not have voting control. Buffett had said he was eager to have PUHCA scaled back, and that if it were repealed he would invest $10 billion to $15 billion in the electric utility industry.30

PacifiCorp For the past several years, Berkshire Hathaway had been unsuccessful in identifying attractive acquisition opportunities. In 2001, Buffett addressed the issue head-on in his annual letter to shareholders:

Some years back, a good $10 million idea could do wonders for us (witness our investment in the Washington Post in 1973 or GEICO in 1976). Today, the combination of ten such

12 Part One Setting Some Themes

28Berkshire acquired 900,942 shares of common stock and 34,563,395 shares of convertible preferred stock of MidAmerican. Convertible preferred stock was preferred stock that carried the right to be exchanged by the investor for common stock. The exchange, or conversion, right was like a call option on the common stock of the issuer. The terms of the convertible preferred stated the price at which common shares could be acquired in exchange for the principal value of the convertible preferred stock. 29Berkshire Hathaway Inc., 1999 Annual Report, 11. 30Rebecca Smith and Karen Richardson, Wall Street Journal, 25 May 2005, A1.

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ideas and a triple in the value of each would increase the net worth of Berkshire by only 1⁄4 of 1%. We need “elephants” to make significant gains now—and they are hard to find.31

By 2004, Berkshire’s fruitless search for “elephants” had begun to take its toll. In his annual letter that year, Buffett lamented his failure to make any multibillion- dollar acquisitions, and he bemoaned Berkshire’s large cash balance that had been accumulating since 2002. “We don’t enjoy sitting on $43 billion of cash equivalents that are earning paltry returns,” Buffett said. “What Charlie [Munger] and I would like is a little action now.”32

The announcement that Berkshire’s wholly owned subsidiary, MidAmerican Energy Holdings Company, would acquire PacifiCorp seemed to indicate that Buffett had found an “elephant.” PacifiCorp was a leading, low-cost energy producer and dis- tributor that served 1.6 million customers in six states in the western United States. Based in Portland, Oregon, PacifiCorp generated power through company-owned coal, hydrothermal, renewable wind power, gas-fired combustion, and geothermal facilities. The company had merged with Scottish Power in 1999. Exhibit 7 presents PacifiCorp’s most recent financial statements.

The PacifiCorp announcement renewed general interest in Buffett’s approach to acquisitions. Exhibit 8 gives the formal statement of acquisition criteria contained in Berkshire Hathaway’s 2004 Annual Report. In general, the policy expressed a tightly disciplined strategy that refused to reward others for actions that Berkshire Hathaway might just as easily take on its own. Analysts scrutinized the PacifiCorp deal for indi- cations of how it fit Berkshire’s criteria. Several noted that the timing of Berkshire Hathaway’s bid closely followed Duke Energy’s bid to acquire Cinergy for $9 billion. The PacifiCorp deal was expected to close after the federal and state regulatory reviews were completed, sometime in the next 12 to 18 months.

Exhibit 9 provides company descriptions and key financial data for comparable firms in the regulated electric utility business. Exhibit 10 presents a range of enterprise values and equity market values for PacifiCorp implied by the multiples of comparable firms.

Conclusion Conventional thinking held that it would be difficult for Warren Buffett to maintain his record of 24% annual growth in shareholder wealth. Buffett acknowledged that “a fat wallet is the enemy of superior investment results.”33 He stated that it was the firm’s goal to meet a 15% annual growth rate in intrinsic value. Would the PacifiCorp acquisition serve the long-term goals of Berkshire Hathaway? Was the bid price appro- priate? Because PacifiCorp was privately held by Scottish Power, how did Berkshire’s offer measure up against the company’s valuation implied by the multiples for comparable firms? What might account for the share price increase for Berkshire Hathaway at the announcement?

Case 1 Warren E. Buffett, 2005 13

31Berkshire Hathaway Inc., 2001 Annual Report, 17. 32Berkshire Hathaway Inc., 2001 Annual Report, 17. 33Quoted in Garth Alexander, “Buffett Spends $2bn on Return to His Roots,” Times (London), 17 August 1995.

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14 Part One Setting Some Themes

EXHIBIT 1 | Relative Share Price Performance of Berkshire Hathaway “Class A” & Scottish Power plc vs. S&P 500 Index (January 3, 2005–May 23, 2005)

Source of data: Datastream.

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16 Part One Setting Some Themes

EXHIBIT 3 | Major Investees of Berkshire Hathaway (dollars in millions)

% of Co. Cost1 Market Company Shares Owned ($mm) ($mm)

American Express Company2 151,610,700 12.1 $1,470 $ 8,546 17% The Coca-Cola Company2 200,000,000 8.3 1,299 8,328 16% The Gillette Company2 96,000,000 9.7 600 4,299 14% H&R Block, Inc. 14,350,600 8.1 223 703 32% M&T Bank Corporation 6,708,760 5.8 103 723 14% Moody’s Corporation 24,000,000 16.2 499 2,084 24% PetroChina “H” shares 2,338,961,000 1.3 488 1,249 39% The Washington Post Company 1,727,765 18.1 11 1,698 1% Wells Fargo & Company2 56,448,380 3.3 463 3,508 13% White Mountain Insurance 1,724,200 16.0 369 1,114 33% Others 3,531 5,465 65%

Total Common Stocks $9,056 $37,717

1This was both Berkshire’s actual purchase price and tax basis; GAAP “cost” differed in a few cases because of write-ups or write-downs that had been required. 2Buffett referred to this group of companies as Berkshire Hathaway’s “Big Four.” Berkshire invested $3.83 billion in the four through multiple transactions between May 1988 and October 2003; on a composite basis, Berkshire’s dollar-weighted purchase date was July 1992. By year-end 2004, Berkshire held these interests, on a weighted basis, for about 12.5 years.

Source of data: Berkshire Hathaway Inc., 2004 Annual Report, 16.

EXHIBIT 4 | Hypothetical Example of Value Creation

Assume:

• 5-year investment horizon, when you liquidate at “book” or accumulated investment value

• initial investment is $50 million • no dividends are paid, all cash flows are reinvested • return on equity ! 20% • cost of equity ! 15%

Year 0 1 2 3 4 5

Investment or book equity value 50 60 72 86 104 124 Market value (or intrinsic value) ! Present value @ 15% of 124 ! $61.65 Market/book ! $61.65/50.00 ! $1.23 Value created: $1.00 invested becomes $1.23 in market value.

Source: Case writer analysis.

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Case 1 Warren E. Buffett, 2005 17

EXHIBIT 5 | Hypothetical Example of Value Destruction

Assume:

• 5-year investment horizon, when you liquidate at “book” or accumulated investment value

• initial investment of $50 million • no dividends are paid, all cash flows are reinvested • return on equity ! 10% • cost of equity ! 15%

Year 0 1 2 3 4 5

Investment or book equity value 50 55 60 67 73 81 Market value (or intrinsic value) ! Present value @ 15% of $81 ! $40.30 Market/book ! $40.30/50.00 ! $0.80 Value destroyed: $1.00 invested becomes $0.80 in market value.

Source: Case writer analysis.

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18 Part One Setting Some Themes

EXHIBIT 6 | MidAmerican Energy Holdings Co.: Condensed Consolidated Financial Statements (dollars in millions)

2000 2001 2002 2003 2004

Balance sheets Assets:

Properties, plants, and equipment, net $ 5,349 $ 6,537 $10,285 $11,181 $11,607 Goodwill 3,673 3,639 4,258 4,306 4,307 Other assets 2,659 2,450 3,892 3,658 3,990

$11,681 $12,626 $18,435 $19,145 $19,904

Liabilities and shareholders’ equity: Debt, except debt owed to Berkshire $ 5,919 $ 7,163 $10,286 $10,296 $10,528 Debt owed to Berkshire 1,032 455 1,728 1,578 1,478 Other liabilities and minority interest 3,154 3,300 4,127 4,500 4,927

10,105 10,918 16,141 16,374 16,933 Shareholders’ equity 1,576 1,708 2,294 2,771 2,971

$11,681 $12,626 $18,435 $19,145 $19,904

Income statements Operating revenue and other income $ 4,013 $ 4,973 $ 4,903 $ 6,143 $ 6,727 Costs and expenses:

Cost of sales and operating expenses 3,100 3,522 3,092 3,913 4,390 Depreciation and amortization 383 539 530 603 638 Interest expense – debt held by Berkshire 40 50 118 184 170 Other interest expense 336 443 640 716 713

3,859 4,554 4,380 5,416 5,911

Earnings before taxes 154 419 523 727 816 Income taxes and minority interests 73 276 126 284 278

Earnings from continuing operations 81 143 397 443 538 Loss on discontinued operations — — (17) (27) (368) Net earnings $ 81 $ 143 $ 380 $ 416 $ 170

Source of data: Berkshire Hathaway regulatory filings.

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Case 1 Warren E. Buffett, 2005 19

EXHIBIT 7 | PacifiCorp Consolidated Financial Statements (dollars in millions)

Year Ended March 31,

2004 2005

Balance sheets Assets:

Current assets $ 756.4 $ 1,214.3 Properties, plants, and equipment, net 9,036.5 9,490.6 Other assets 1,884.2 1,816.0

$11,677.1 $12,520.9

Liabilities and shareholders’ equity: Current liabilities $ 1,074.3 $ 1,597.7 Deferred credits $ 3,706.3 $ 3,868.3 Long-term debt and capital lease obligations 3,520.2 3,629.0 Preferred stock subject to mandatory redemption 56.3 48.8

8,357.1 9,143.8 Shareholders’ equity 3,320.0 3,377.1

$11,677.1 $12,520.9

Income statements Operating revenue and other income $ 3,194.5 $ 3,048.8 Costs and expenses:

Operating expenses 2,147.8 1,955.5 Depreciation and amortization 428.8 436.9

Income from operations 617.9 656.4

Interest expense 224.4 236.2 Income from operations before income tax expense 393.5 420.2 Cumulative effect of accounting change (0.9) — Income tax expense 144.5 168.5

Net income $ 248.1 $ 251.7

Source of data: PacifiCorp 10-K regulatory filing.

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20 Part One Setting Some Themes

EXHIBIT 8 | Berkshire Hathaway Acquisition Criteria

We are eager to hear from principals or their representatives about businesses that meet all of the following criteria:

1. Large purchases (at least $75 million of pretax earnings unless the business will fit into one of our existing units). 2. Demonstrated consistent earning power (Future projections are of no interest to us, nor are “turnaround” situations.) 3. Businesses earning good returns on equity while employing little or no debt. 4. Management in place (We can’t supply it.) 5. Simple businesses (If there’s lots of technology, we won’t understand it.) 6. An offering price (We don’t want to waste our time or that of the seller by talking, even preliminarily, about a

transaction when price is unknown.)

The larger the company, the greater will be our interest: We would like to make an acquisition in the $5 billion to $20 billion range. We are not interested, however, in receiving suggestions about purchases we might make in the general stock market.

We will not engage in unfriendly takeovers. We can promise complete confidentiality and a very fast answer—customarily within five minutes—as to whether we’re interested. We prefer to buy for cash, but will consider issuing stock when we receive as much in intrinsic business value as we give. We don’t participate in auctions.

Charlie and I frequently get approached about acquisitions that don’t come close to meeting our tests: We’ve found that if you advertise an interest in buying collies, a lot of people will call hoping to sell you their cocker spaniels. A line from a country song expresses our feeling about new ventures, turnarounds, or auction-like sales: “When the phone don’t ring, you’ll know it’s me.”

Source: Berkshire Hathaway Inc., 2004 Annual Report, 28.

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Bill Miller and Value Trust Bill Miller’s success is so far off the charts that you have to ask whether it is superhuman. Quite simply, fund managers are not supposed to be this good. Is it mortal genius, or is it celestial luck?1

By the middle of 2005, Value Trust, an $11.2-billion mutual fund2 managed by William H. (Bill) Miller III, had outperformed its benchmark index, the Standard & Poor’s 500 Index (S&P 500), for an astonishing 14 years in a row. This record marked the longest streak of success for any manager in the mutual-fund industry; the next longest period of sustained performance was only half as long. For many fund managers, simply beating the S&P 500 in any single year would have been an accomplishment, yet Miller had achieved consistently better results during both the bull markets of the late 1990s and the bear markets of the early 2000s.

Over the previous 15 years, investors in Value Trust, one of a family of funds managed by the Baltimore, Maryland–based Legg Mason, Inc., could look back on the fund’s remarkable returns: an average annual total return of 14.6%, which sur- passed the S&P 500 by 3.67% per year. An investment of $10,000 in Value Trust at its inception, in April 1982, would have grown to more than $330,000 by March 2005. Unlike the fund’s benchmark, which was a capitalization-weighted index composed of 500 widely held common stocks, Value Trust only had 36 holdings, 10 of which accounted for nearly 50% of the fund’s assets. Exhibit 1 presents a summary of Legg Mason Value Trust, Inc., as it stood in August 2005.

While Miller rarely had the best overall performance among fund managers in any given year, and while some managers had beaten his results over short-term periods, no one had ever matched his consistent index-beating record. Miller’s results seemed to contradict conventional theories, which suggested that, in markets characterized by

23

2CASE

1James K. Glassman, “More Than Pure Luck,” Washington Post, 14 January 2004, F-01. 2A mutual fund was an investment vehicle that pooled the funds of individual investors to buy a portfolio of securities, stocks, bonds, and money-market instruments; investors owned a pro rata share of the overall investment portfolio.

This case was prepared by Sean D. Carr (MBA ‘03), under the supervision of Robert F. Bruner. It was written as a basis for class discussion rather than to illustrate effective or ineffective handling of an administrative situation. Copyright © (2005 by the University of Virginia Darden School Foundation, Charlottesville, VA. All rights reserved. To order copies, send an e-mail to [email protected] No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means—electronic, mechanical, photocopying, recording, or otherwise—without the permission of the Darden School Foundation.

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high competition, easy entry, and informational efficiency, it would be extremely dif- ficult to beat the market on a sustained basis. Observers wondered what might explain Miller’s performance.

The U.S. Mutual-Fund Market3

The U.S. mutual-fund market was the largest in the world, accounting for half of the $16.2 trillion in mutual-fund assets reported worldwide. The aggregate figures some- what masked the continual growth of mutual funds as an investment vehicle. Between 1995 and 2005, mutual-fund assets grew from $2.8 trillion to $8.1 trillion. Ninety-two million individuals, or nearly half of all households, owned mutual funds in 2004, com- pared with less than 6% in 1980. In 2004, individual investors held about 90% of all mutual-fund assets.

Mutual funds served several economic functions for investors. First, they afforded the individual investor the opportunity to diversify (own many different stocks) his or her portfolio efficiently without having to invest the sizable amount of capital usually necessary to achieve efficiency. Efficiency was also reflected in the ability of mutual funds to exploit scale economies in trading and transaction costs, economies unavailable to the typical individual investor. Second, in theory, mutual funds provided the individual investor with the professional expertise necessary to earn abnormal returns through successful analysis of securities. A third view was that the mutual-fund industry provided, according to one observer, “an insulating layer between the individual investor and the painful vicissitudes of the marketplace”:

This service, after all, allows individuals to go about their daily lives without spending too much time on the aggravating subject of what to buy and sell and when, and it spares them the even greater aggravation of kicking themselves for making the wrong decision. . . . Thus, the money management industry is really selling “more peace of mind” and “less worry,” though it rarely bothers to say so.4

Between 1970 and 2005, the number of all mutual funds grew from 361 to 8,044. This total included many different kinds of funds; each one pursued a specific invest- ment focus and was categorized into several acknowledged segments of the industry: aggressive growth (capital-appreciation-oriented), equity income, growth, growth and income, international, option, specialty, small company, balanced, and a variety of bond or fixed-income funds.5 Funds whose principal focus of investing was common stocks comprised the largest sector of the industry.

24 Part One Setting Some Themes

3Investment Company Fact Book, 45th ed. (Investment Company Institute, 2005). 4Contrarious, “Good News and Bad News,” Personal Investing (26 August 1987): 128. 5Aggressive growth funds sought to maximize capital gains, so current income was of little concern. Growth funds invested in better-known companies with steadier track records. Growth and income funds invested in companies with longer track records that were expected to increase in value and provide a steady income stream. International funds invested in foreign companies. Option funds sought to maximize current returns by investing in dividend-paying stocks on which call options were traded. Balanced funds attempted to conserve principal while earning both current income and capital gains.

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Case 2 Bill Miller and Value Trust 25

9,000

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U.S. Mutual Fund Industry: Total Number of Funds

To some extent, the growth in the number and types of mutual funds reflected the increased liquidity in the market and the demand by investors for equity. More impor- tantly, it reflected the effort by mutual-fund organizations to segment the market (i.e., to identify the specialized and changing needs of investors, and to create products to meet those needs). One important result was a broader customer base for the mutual- fund industry as well as a deeper penetration of the total market for financial services.

Another important result of this development was that it added a degree of com- plexity to the marketplace that altered the investment behavior of some equity investors. In particular, the breadth of mutual-fund alternatives tended to encourage fund switching, especially from one type of fund to another within a family of funds. This reflected the greater range of mutual funds from which to choose, the increased volatility in the market, and the increased trend toward timing-oriented investment strategies. In short, as the mutual-fund industry grew, mutual-fund money became “hotter” (tended to turn over faster).

Institutional investors that managed mutual funds, pension funds, and hedge funds6 on the behalf of individual investors dominated the market for common stocks in the United States in the mid 2000s. Indeed, at the end of 2004, mutual funds alone owned more than 20% of the outstanding stock of U.S. companies. The sheer domi- nance of those money managers appeared not only in the amount of assets held, but also in their trading muscle—their ability to move huge sums of money in and out of

Source: Investment Company Institute Fact Book 2005.

6Hedge funds, like mutual funds, pooled investors’ money and invested those funds in financial instruments to generate a positive return. Hedge-fund managers typically charged fees of 1% to 2% of the fund’s assets plus a performance fee of 20% of profits. Participation in a fund was usually limited to a small number of high net-worth individuals, who were required to “lock up” their invested capital for a year or more. Worldwide growth in hedge funds had exploded in recent years, rising from approximately 600 funds with $38 billion in assets in 1990, to more than 8,000 funds with $1 trillion in assets in 2004. Many hedge funds took specula- tive, value-driven trading positions, believed to enhance market volatility and liquidity. Traditionally, hedge funds had been little known and unregulated, but their recent growth as an investment vehicle had brought about increasing regulatory scrutiny in the United States.

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stocks on short notice. The rising dominance of institutional investors resulted in the growth of trading volume, average trade size, and, especially, block trading (individ- ual trades of more than 10,000 shares), which had increased from about 15% of all trading volume 30 years ago to about one-third in 2004. Accordingly, money man- agers were the principal price-setters (lead steers) in the stock market.

Mutual-Fund Basics When individuals invested in a mutual fund, their ownership was proportional to the number of shares purchased. The value of each share was called the fund’s net asset value (NAV). The NAV was computed as the fund’s total assets less liabilities, divided by the number of mutual-fund shares outstanding, or:

Net asset value (NAV) ! Market value of fund assets – Liabilities

Fund shares outstanding

The performance of a mutual fund could thus be measured as the increase or decrease in net asset value plus the fund’s income distributions (i.e., dividends and capital gains), expressed as a percentage of the fund’s NAV at the beginning of the investment period, or:

Annual !

Change in net asset value " Dividends " Capital-gain distributions total return NAV (at the beginning of the year)

Advisers, or managers, of mutual funds were compensated by investors through one-time transaction fees and annual payments. A fund’s transaction fees, or loads, cov- ered brokerage expenses and were rarely higher than 6% of an individual’s investment in the fund. Annual payments were calculated as a percentage of the fund’s total assets (called its expense ratio), and were charged to all shareholders proportionally. The expense ratio covered the fund’s management fees, administrative costs, and advertis- ing and promotion expenses. Expense ratios ranged from as low as 0.2% to as high as 2.0%. The average expense ratio was around 1.3% to 1.5%. Because the expense ratio was regularly deducted from the portfolio, it reduced the fund’s NAV, thereby lower- ing the fund’s gross returns. Depending on the magnitude of the fund’s expense ratio, the net effect of loads and expense ratios on shareholder returns could be dramatic.7

Another drag on shareholders’ returns was the fund’s tendency to keep about 8% of its assets in cash to meet redemptions or to invest in unexpected bargains. One observer of the industry, economist Henry Kaufman, warned that a sudden economy- wide shock from interest rates or commodity prices could spook investors into panic- style redemptions from mutual funds, which themselves would liquidate investments and send security prices into a tailspin. Unlike the banking industry, which enjoyed the liquidity afforded by the U.S. Federal Reserve System to respond to the effects of panic by depositors, the mutual-fund industry enjoyed no such government-backed reserve.

26 Part One Setting Some Themes

7For instance, suppose that you invested $10,000 in a fund that would appreciate at 10% annually, which you then sold out after three years. Also, suppose that the advisory firm had an expense ratio of 2% and a front-end load of 4%. The fees would cut your pretax profit by 35%—from $3,310 to $2,162.

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Performance of the Mutual-Fund Industry The two most frequently used measures of performance were (1) the percentage of annual growth rate of NAV assuming reinvestment (the total return on investment) and (2) the absolute dollar value today of an investment made at some time in the past. Those measures were then compared with the performance of a benchmark portfolio such as the Russell 2000 Index or the S&P 500 Composite Index. Exhibit 2 provides performance data on a range of mutual-fund categories and comparative indices. The Russell, S&P 500, Dow Jones, and Value Line indices offered benchmarks for the investment performance of hypothetical stock portfolios.8

Academicians criticized those performance measures because they failed to adjust for the relative risk of the mutual fund. Over long periods, as Exhibit 3 shows, dif- ferent types of securities yielded different levels of total return. Exhibit 4 shows that each of those types of securities was associated with differing degrees of risk (meas- ured as the standard deviation of returns). Thus, the relationship between risk and return was reliable both on average and over time. For instance, it should be expected that a conservatively managed mutual fund would yield a lower return—precisely because it took fewer risks.

After adjusting for the risk of the fund, academic studies reported that mutual funds were able to perform up to the market on a gross-returns basis; however, when expenses were factored in, they underperformed the market. For instance, Michael Jensen, in a paper published in 1968, reported that gross risk-adjusted returns were #0.4% and that net risk-adjusted returns (i.e., net of expenses) were #1.1%. In 1977, Main updated the study and found that, for a sample of 70 mutual funds, net risk-adjusted returns were essentially zero. Some analysts attributed this general result to the average 1.3% expense ratio of mutual funds and their desire to hold cash.

Most mutual-fund managers relied on some variation of the two classic schools of analysis:

Technical analysis: This involved the identification of profitable investment opportunities based on trends in stock prices, volume, market sentiment, Fibonacci numbers,9 etc.

Fundamental analysis: This approach relied on insights afforded by an analysis of the economic fundamentals of a company and its industry: supply and demand costs, growth prospects, etc.

Case 2 Bill Miller and Value Trust 27

8The Dow Jones indices of industrial companies, transportation companies, and utilities reflected the stocks of a small number (e.g., 30) of large, blue-chip companies, all traded on the New York Stock Exchange (NYSE) and the NASDAQ. The S&P 500 was an index of shares of the 500 largest companies, traded on both the New York and American Stock Exchanges. The Value Line Index was an equal-weighted stock index containing 1,700 companies from the NYSE, American Stock Exchange, NASDAQ, and over-the-counter market; it was also known as the Value Line Investment Survey. The Russell 2000 measured the performance of 2,000 of the smallest companies in the Russell 3000 index of the biggest U.S. stocks. As any index sample became larger, it reflected a greater weighting of smaller, high-growth companies. 9The sequence, named for Leonard Fibonacci (1175-1240), consisted of the numbers 1, 1, 2, 3, 5, 8, 13 and so on. Each number after the first two equals the sum of the two numbers before it. No academic research associates this sequence with a consistent ability to earn supernormal returns from investing in the market.

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While variations on those approaches often produced supernormal returns in cer- tain years, there was no guarantee that they would produce such returns consistently over time.

Burton Malkiel, an academic researcher, concluded that a passive buy-and-hold strategy (of a large, diversified portfolio) would do as well for the investor as the aver- age mutual fund:

Even a dart-throwing chimpanzee can select a portfolio that performs as well as one carefully selected by the experts. This, in essence, is the practical application of the theory of efficient markets. . . . The theory holds that the market appears to adjust so quickly to information about individual stocks and the economy as a whole, that no technique of selecting a portfolio—neither technical nor fundamental analysis—can consistently outperform a strategy of simply buying and holding a diversified group of securities such as those that make up the popular market averages. . . . [o]ne has to be impressed with the substantial volume of evidence suggesting that stock prices display a remarkable degree of efficiency. . . . If some degree of mispricing exists, it does not persist for long. “True value will always out” in the stock market.10

Many scholars accepted that view. They argued that the stock market followed a “random walk,” where the price movements of tomorrow were essentially uncorrelated with the price movements of today. In essence, this denied the possibility that there could be momentum in the movements of common stock prices. According to this view, technical analysis was the modern-day equivalent of alchemy. Fundamental analysis, too, had its academic detractors. They argued that capital markets’ information was efficient, and that the insights available to any one fundamental analyst were bound to be impounded quickly into share prices.

The notion that capital markets incorporated all the relevant information into existing securities’ prices was known as the efficient market hypothesis (EMH), and was widely, though not universally, accepted by financial economists. If EMH were correct and all current prices reflected the true value of the underlying securities, then arguably it would be impossible to beat the market with superior skill or intellect.

Economists defined three levels of market efficiency, which were distinguished by the degree of information believed to be reflected in current securities’ prices. The weak form of efficiency maintained that all past prices for a stock were impounded into today’s price; prices today simply followed a random walk with no correlation with past patterns. Semistrong efficiency held that today’s prices reflected not only all past prices, but also all publicly available information. Finally, the strong form of market efficiency held that today’s stock price reflected all the information that could be acquired through a close analysis of the company and the economy. “In such a market,” as one economist said, “we would observe lucky and unlucky investors, but we wouldn’t find any superior investment managers who can consis- tently beat the market.”11

28 Part One Setting Some Themes

10Burton G. Malkiel, A Random Walk Down Wall Street (New York: Norton, 1990), 186, 211. 11Richard A. Brealey, Stewart C. Myers, and Franklin Allen, Principles of Corporate Finance, 8th ed. (New York: McGraw-Hill Irwin, 2006), 337.

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By implication, proponents of those academic theories were highly critical of the services provided by active mutual-fund managers. Paul Samuelson, the Nobel Prize–winning economist, said:

[E]xisting stock prices already have discounted in them an allowance for their future prospects. Hence . . . one stock [is] about as good or bad a buy as another. To [the] passive investor, chance alone would be as good a method of selection as anything else.12

Various popular tests of this thinking seemed to support that view. For instance, Forbes magazine chose 28 stocks by throwing darts in June 1967 and invested $1,000 in each. By 1984, the $28,000 investment was worth $131,697.61, for a 9.5% compound rate of return. This beat the broad market averages and almost all mutual funds. Forbes concluded, “It would seem that a combination of luck and sloth beats brains.”13

Yet, the nagging problem remained that there were still some superstar money managers—like Bill Miller—who, over long periods, greatly outperformed the mar- ket. In reply, Malkiel suggested that beating the market was much like participating in a coin-tossing contest where those who consistently flip heads are the winners.14

In a coin-tossing game with 1,000 contestants, half will be eliminated on the first flip. On the second flip, half of those surviving contestants are eliminated. And so on, until, on the seventh flip, only eight contestants remain. To the naïve observer, the ability to flip heads consistently looks like extraordinary skill. By analogy, Malkiel suggested that the success of a few superstar portfolio managers could be explained as luck.

As might be expected, the community of money managers received those schol- arly theories with great hostility. And even in the ranks of academicians, dissension appeared in the form of the burgeoning field of “behavioral finance,” which suggested that greed, fear, and panic were much more significant factors in the setting of stock prices than the mainstream theory would permit. For instance, to many observers, the Internet bubble of the late 1990s seemed to be totally inconsistent with the view of markets as fundamentally rational and efficient. Professor Robert Shiller of Yale University said:

Evidence from behavioral finance helps us to understand . . . that the recent stock market boom, and then crash after 2000, had its origins in human foibles and arbitrary feedback relations and must have generated a real and substantial misallocation of resources. The challenge for economists is to make this reality a better part of their models.15

Similarly, the stock-market crash of October 1987 had also seemed to undermine the strength of the EMH. Professor Lawrence Summers of Harvard argued that the

Case 2 Bill Miller and Value Trust 29

12Malkiel, Random Walk, 182. 13Malkiel, Random Walk, 164. 14Malkiel, Random Walk, 175–176. 15Robert J. Shiller, “From Efficient Markets Theory to Behavioral Finance,” Journal of Economic Perspec- tives (winter 2003): 102.

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1987 crash was a “clear gap with the theory. If anyone did seriously believe that price movements are determined by changes in information about economic funda- mentals, they’ve got to be disabused of that notion by [the] 500-point drop.”16 Shiller said, “The efficient market hypothesis is the most remarkable error in the history of economic theory. This is just another nail in its coffin.”17

Academic research exposed other inconsistencies with the EMH. Those included apparently predictable stock-price patterns indicating reliable, abnormally positive returns in early January of each year (the “January effect”), and a “blue Monday” effect, where average stock returns were negative from the close of trading on Friday to the close of trading on Monday. Other evidence suggested that stocks with low price-to-earnings (P/E) multiples tended to outperform those with high P/E multiples. Finally, some evidence emerged for positive serial correlation (that is, momentum) in stock returns from week to week or from month to month. Those results were incon- sistent with a random walk of prices and returns. Yet, despite the existence of those anomalies, the EMH remained the dominant paradigm in the academic community.

Bill Miller and Value Trust Exhibit 5 presents a 10-year summary of the annual returns for Value Trust and eight other Legg Mason equity funds. Morningstar, the well-known statistical service for the investment community, gave Value Trust a five-star rating, its highest for invest- ment performance. Some observers attributed this success to the fund manager’s con- scious strategy of staying fully invested at all times rather than attempting to time the extent of market investments. Another popular explanation for the fund’s performance was the unusual skill of Bill Miller, the fund’s portfolio manager.

Miller started investing when he was about 9 years old; he later bought his first stock, RCA, when he was 16. During the Vietnam War, Miller served in military intel- ligence, and afterward earned a doctorate in philosophy from Johns Hopkins University. He eventually joined Legg Mason, Inc., in 1981. Miller was an adherent of fundamen- tal analysis, an approach to equity investing he had gleaned from a number of sources:

I had read a bunch of stuff on investing ever since I had gotten interested: Supermoney, about Ben Graham and Warren Buffett; Graham’s Intelligent Investor; Security Analysis; David Dreman’s Psychology in the Stock Market. Combine those books and those approaches, and what you have is basically a contrarian, value-based methodology, which, psychologically, was very compatible with the way I tended to think about things. I tend to think stocks are more attractive at lower prices rather than higher prices.18

Miller’s approach was research-intensive and highly concentrated. Nearly 50% of Value Trust’s assets were invested in just 10 large-capitalization companies. While

30 Part One Setting Some Themes

16B. Donnelly, “Efficient-Market Theorists Are Puzzled by Recent Gyrations in Stock Market,” Wall Street Journal, 23 October 1987, 7. 17B. Donnelly, “Efficient-Market Theorists.” 18Jack Otter, “Meet Mr. Market,” www.smartmoney.com, 5 May 2005, accessed 15 September 2005.

bru6171X_case02_023-038.qxd 11/24/12 2:24 PM Page 30

most of Miller’s investments were value stocks, he was not averse to taking large positions in the stocks of growth companies.19 Generally speaking, Miller’s style was eclectic and difficult to distill. “He almost takes pleasure in having people think he’s crazy,” one industry veteran said of him. “It means he’s doing well.”20 By the early 2000s, however, several key elements of Miller’s contrarian strategy had begun to emerge:

• Buy low-price, high intrinsic-value stocks: “We want to know how stock prices de- part from underlying value and why. That can be on the upside as we saw with the Internet, when most companies weren’t worth anything like what the market thought they were worth. What we want is the reverse—tremendous pessimism, people believing that a business is broken, scandal, something everybody is fleeing.”21

• Take heart in pessimistic markets: “Bargain prices do not occur when the consen- sus is cheery, the news is good, and investors are optimistic. Our research efforts are usually directed at precisely the area of the market the news media tells you has the least promising outlook, and we are typically selling those stocks that you are reading have the greatest opportunity for near-term gain.”22

• Remember that the lowest average cost wins: “For most investors, if a stock starts behaving in a way that is different from what they think it ought to be doing— say, it falls 15%—they will probably sell. In our case, when a stock drops and we believe in the fundamentals, the case for future returns goes up. Think of it like this: If the underlying business is worth $40, and the stock is $20, my rate of return is 100%. The lower the shares go, the higher the future rate of return and the more money you should invest in them.”23

• Be wary of valuation illusions: “I’ll give you two historical valuation illusions: Wal-Mart stores and Microsoft. From the day they came public, they looked expen- sive. Nonetheless, if you bought Wal-Mart when it went public at an expensive- looking 20" times earnings, you would have the returns of many thousands percent on that. The same goes for Microsoft. Until a couple of years ago, Microsoft went up an average 1% every week it was public, despite the fact that it looked expensive. Had we known the growth that was in front of it, we would have known it was actu- ally a bargain.”24

Case 2 Bill Miller and Value Trust 31

19The stock of a corporation that exhibited faster-than-average gains in earnings during recent periods was typically considered a growth stock. Growth stocks were generally riskier than the average stock, and they often had higher price-to-earnings ratios and paid little to no dividends. A value stock tended to trade at a lower price relative to its earnings, and it usually carried a high dividend yield and low price-to-book or price-to-earnings ratio. 20Christopher Davis, co-manager of the Davis Funds, quoted in Matthew Heimer, “Bill Miller,” www.smartmoney.com, 1 July 2005. 21“Miller’s Tale: Legg Mason’s Revered Fund Steward Talks about Value, Metrics, and His Optimism,” Barron’s (3 February 2003). 22Ian McDonald, “Miller Finds Value in Dreary Places,” Wall Street Journal, 16 May 2002. 23“Bill Miller: How to Profit from Falling Prices,” Fortune (3 September 2003). 24“Miller’s Tale.”

bru6171X_case02_023-038.qxd 11/24/12 2:24 PM Page 31

• Take the long view: “Portfolio turnover is over 100% for the average mutual fund, implying a 10- or 11-month holding period even though the short term is pretty well reflected in stock prices. The biggest opportunity for investors is really thinking out longer term. [P]eople need to think long term. People tend to react and not anticipate. And what they react to is what they wish they’d done a year ago, or two years ago.”25, 26

• Look for cyclical and secular underpricing: “Most value people tend to own stocks that are cyclically underpriced. Most growth people own stocks that are secularly underpriced: things that can grow for long periods of time. Our portfolios histori- cally tended to be, though I wouldn’t say they are now, better diversified along both cyclical and secular lines. And our portfolio tries to look at underpricing or mispric- ing along both of those dimensions so that we’re not caught in one or the other.”27

• Buy low-expectation stocks: “I think buying low-expectation stocks, buying higher dividend-yielding stocks, staying away from things with high expense ratios, and most important, the key thing would be—as Warren Buffett says—you need to be fearful when others are greedy, and greedy when others are fearful. So when the market’s been down for a while, and it looks bad, then you should be more aggres- sive, and when it’s been up for a while, then you should be less aggressive.”28

• Take risks: “As Earl Weaver29 used to say, you win more games on three-run homers than sacrifice bunts. That’s the thing people in the markets don’t under- stand as well as they should. A lot of people look to hit singles and sacrifice bunts and make small returns.30 But statistically you are far better off with huge gains because you are going to make mistakes. And if you are playing small ball and you make a few mistakes, you can’t recover.”31

Value Trust had earned a cumulative return of more than 830% over the previous 14 years, more than double that of its average peer and the index, according to Morn- ingstar. Even so, Miller remained modest about this record: “The evidence is pretty compelling that the market is pretty efficient and will beat most people most of the time.”32 He acknowledged that his much ballyhooed streak could just as easily have been an accident of the calendar. “If the year ended on different months, it wouldn’t

32 Part One Setting Some Themes

25McDonald, “Bill Miller Dishes on His Streak and His Strategy,” Wall Street Journal, 6 January 2005. 26Otter, “Meet Mr. Market.” 27Otter, “Meet Mr. Market.” 28Otter, “Meet Mr. Market.” 29Earl Sidney Weaver was a long-time manager of the Baltimore Orioles, an American baseball team. Dur- ing his tenure, the Orioles won six division titles, four league pennants, and the World Series championship. Bill Miller was widely known as an ardent Orioles fan. 30In American baseball, a homer (home run) was a hit that allowed a batter to circle all the bases and score a run. A bunt occurred when the batter hit the ball by positioning the bat in front of his body, rather than by swinging at it; a sacrifice bunt was a bunt that resulted in a base runner advancing and the batter being put out. A single was a batted ball that allowed a batter to reach first base only. 31“Bill Miller: How to Profit.” 32McDonald, “Bill Miller Dishes.”

bru6171X_case02_023-038.qxd 11/24/12 2:24 PM Page 32

be there, and at some point those mathematics will hit us,” Miller said. “We’ve been lucky. Well, maybe it’s not 100% luck. Maybe 95% luck.”33 According to Morningstar, Miller’s fund lagged behind the S&P 500 in 32 12-month periods out of a total of 152 12-month periods, from the beginning of the streak through July 2004.

Conclusion Judged from almost any perspective, Miller’s investment success was remarkable. His long-run, market-beating performance defied conventional academic theories. Investors, scholars, and market observers wondered about the sources of Miller’s superior per- formance and about its sustainability. As of the middle of 2005, was it rational for an equity investor to buy shares in Value Trust?

At 55, Bill Miller was hardly considered old. Warren Buffett was 74, and he remained an active and visible investor through his company, Berkshire Hathaway, Inc. (See UVA-F-1483, “Warren E. Buffett, 2005,” for additional information on Warren Buffett and Berkshire Hathaway.) But investors and other observers had begun to wonder how long Miller would remain at the helm of Value Trust and whether his successor could sustain his exemplary record.

In addition to managing the $11.2-billion Value Trust, Miller also guided the $3.2-billion Legg Mason Opportunity Trust and the $3.2-billion Legg Mason Special Investment Trust. In addition, Miller served as the chief executive officer of Legg Mason Capital Management, which had about $40 billion in assets under its management.

Case 2 Bill Miller and Value Trust 33

33McDonald, “Bill Miller Dishes.”

bru6171X_case02_023-038.qxd 11/24/12 2:24 PM Page 33

34 Part One Setting Some Themes

EXHIBIT 1 | Morningstar Report on Legg Mason Value Trust, Inc.

Market cap Giant Large Mid Small Micro

Value Measures Price/Earnings Price/Book Price/Sales Price/Cash Flow Dividend Yield % Growth Measures Long-Term Erngs Book Value Sales Cash Flow Historical Erngs

Rel Category

Info Software Hardware Media Telecom

Service Health Consumer Business Financial

Mfg Goods Ind Mtrls Energy Utilities

Composition

% 34.8 54.2 11.0 0.0 0.0

24.08 4.12 3.70 6.17

10.09

1.17 1.02 0.37 1.81 3.36

60.41 13.38 18.93 7.35

20.75

1.32 1.03 1.99 1.98 1.05

15.51 3.36 6.98 0.00 5.17

0.46 0.37 0.58 0.00 1.53

0.3 99.7 0.0 0.0 2.3

5 4 7

12

0 2 5

10

16 23 7

24

12 19 6

21

6 7 0 5

3 5 0 2

Current Investment Style Sector Weightings

% of Stocks

Rel S&P 500

S m

all

$

Avg $mil: 26,231

16.91 2.10 1.01 9.92 2.37

% 13.08 9.87 6.87

27.70 0.46

Rel Category 1.16 1.06 0.92 2.89 0.03

Profitability Return on Equity Return on Assets Net Margin

% 12.99 7.48 9.99

Rel Category 0.72 0.80 0.81

1.06 0.88 0.72 1.27 1.37

High 3 Year

Low

Cash Stocks Bonds Others Foreign (% of stock)

Value Blnd Growth

Large M

id

Legg Mason Value Prim Governance and Management

Stewardship Grade B

Portfolio Manager(s) Longtime manager Bill Miller has vastly outperformed his average peer and the index during his tenure. Assistant manager Nancy Dennin, who focused mostly on administrative tasks, recently stepped down. Some of her duties are being taken on by David Nelson, manager of American Leading Companies. The firm has hired a new research director. Ire Malis, and a chief strategist, Michael Mauboussin, along with a handful of new analysis.

Strategy Bill Miller looks for companies that are trading cheaply relative to his estimates of what they’re worth. This often leads him to beaten-down turnaround plays. Unlike many value managers, however, Miller is willing make fairly optimistic assumptions about growth, and he doesn’t shy away from owning companies in traditional growth sectors. In this portfolio, pricey Internet stocks rub elbows with bargain-priced financials and turnaround plays. Miller will also let favored names run, allowing top positions to soak up a large percentage of assets.

Performance 07.31.05

1st Qtr 2nd Qtr 3rd Qtr 4th Qtr Total 2001 #3.08 7.33 #20.01 9.02 #9.29 2002 #3.66 #13.73 #13.96 13.38 #18.92 2003 #2.91 25.48 3.54 13.79 43.53 2004 #1.22 4.59 #5.80 15.04 11.96 2005 #5.95 3.52 — — —

Trailing Total "$# "$# Russ % Rank Growth of Return % S&P 500 1000 Cat $10,000

3 Mo 11.31 4.14 3.30 5 11,131 6 Mo 5.45 0.00 #1.24 45 10,545 1 Yr 19.54 5.50 3.34 10 11,954 3 Yr Avg 19.87 7.26 6.41 1 17,224 5 Yr Avg 2.93 4.28 3.73 12 11,553

10 Yr Avg 15.96 5.98 5.79 1 43,962 15 Yr Avg 14.88 3.94 3.62 2 80,106

Tax Tax-Adj % Rank Tax-Cost % Rank Analysis Rtn % Cat Rat Cat

3 Yr (estimated) 19.87 1 0.00 1 5 Yr (estimated) 2.39 11 0.52 29

10 Yr (estimated) 14.88 1 0.93 28

Potential Capital Gain Exposure: 31% of assets

Morningstar’s Take by Christopher Traulsen 08-01-05

Rating and Risk Time Load-Adj Morningstar Morningstar Morningstar Period Return % Rtn vs Cat Risk vs Cat Risk-Adj Rating

1 Yr 19.54 3 Yr 19.87 High High ***** 5 Yr 2.93 "Avg High ****

10 Yr 15.96 High High ***** Incept 16.64

Other Measures Standard Index Best Fit Index S&P 500 Russ 1000

Alpha 3.6 2.4 Beta 1.31 1.33 R-Squared 88 89

Standard Deviation 18.25 Mean 19.87 Sharpe Ratio 1.00

Size isn’t yet a big problem for this fund, but we’re keeping an eye on the matter.

If you count all the money that manager Bill Miller and his team are running in this style, it totals $38 billion. That’s a sizable sum, particularly when one considers that other large offerings spread their assets over many more names than Miller does here. Indeed, the typical actively managed domestic stock mutual fund with at least $35 billion in assets holds 265 stocks and stashed 22% of assets in its top 10 holdings. As of March 31, 2005, the fund held just 36 stocks and squeezed 50% of its assets into its top 10 holdings.

The worry is that as the fund grows, Miller will be forced to deviate from those ideas he thinks have the highest probability of success because he already owns too much of them. Miller discounts this as a real negative, noting that he can just buy highly correlated names if need be. However, doing so still runs the risk that those names wont be as strong as the best

opportunities identified by his research. It’s worth noting, though, that other aspects of Miller’s style make him well-suited to running such a large portfolio. First, he usually isn’t competing for liquidity with the hordes of traders that a less contrarian manager might be. Miller also just doesn’t trade much: The fund’s turnover rate hasn’t cracked 30% since 1992.

It’s obvious that Miller is a brilliant portfolio manager—to glean that much, one just needs to look at his record and speak to him about how he thinks about investment opportunities. And we do not think the fund’s current size is cause for concern. However, Legg Mason’s recent deal with Citigroup means that a lot more brokers may suddenly be selling this fund (though it could also mean the share classes with cheaper ongoing expenses may become available). Add to that the fact that as CEO of the fund advisor, Miller has little incentive to close this offering and slow the growth of his group’s business, and we think the issue bears close watching.

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 07-05 History

19.04 25.19 32.99 42.74 61.58 75.27 55.44 50.06 40.59 58.26 65.23 66.32 NAV 1.39 40.76 38.43 37.05 48.04 26.71 #7.14 #9.29 #18.92 43.53 11.96 1.67 Total Return % 0.07 3.23 15.48 3.70 19.46 5.67 1.96 2.59 3.17 14.86 1.09 #1.21 "$#S&P 500 1.00 2.99 15.98 4.20 21.02 5.80 0.65 3.16 2.73 13.64 0.56 #2.33 "$#Russ 1000 0.27 0.93 0.66 0.11 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Income Return % 1.12 39.83 37.77 36.94 48.04 26.71 #7.14 #9.29 #18.92 43.53 11.96 1.67 Capital Return %

21 3 2 4 1 20 52 25 23 2 24 82 Total Rtn % Rank Cat 0.05 0.17 0.16 0.04 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Income $ 0.04 1.24 1.53 2.32 1.41 2.46 14.47 0.26 0.00 0.00 0.00 0.00 Capital Gains $ 1.82 1.81 1.82 1.77 1.73 1.69 1.68 1.69 1.68 1.72 1.70 1.68 Expense Ratio % 0.50 0.50 0.80 0.40 #0.10 #0.40 #0.60 #0.50 #0.50 #0.40 #0.60 0.77 Income Ratio %

26 20 20 10 13 19 20 27 24 25 4 9 Turnover Rate % 933 1,340 1,976 3,683 8,079 12,540 10,597 9,788 7,218 10,738 11,947 11,723 Net Assets $mil

Address: 100 Light St. Minimum Purchase: $1000 Add: $100 IRA: $1000 Baltimore MD 21203 Min Auto Inv Plan: $1000 Add: $50 800-577-8589 Sales Fees: 0.70%B, 0.25%S

Web Address: www.leggmason.com Management Fee: 0.7% Inception: 04-16-82 Actual Fees: Mgt:0.66% Dist:0.95% Advisor: Legg Mason Funds Expense Projections: 3Yr:$536 5Yr:$923 10Yr:$2009

Management Inc. Subadvisor: None Income Distrib: Annually

NTF Plans: DATALynx NTF, TD Waterhouse Ins NT

Portfolio Analysis 03-31-05 Share change since 12-04 Total Stocks:36 Sector PE Tot Ret % % Assets

Nextel Communications Telecom 13.3 15.96 7.57 | UnitedHealth Group Health 24.8 18.86 7.22

Tyco International Ind Mtrls 26.0 #14.20 6.96 AES Utilities 24.7 17.41 5.16

{ Amazon.com Consumer 36.1 1.94 4.88 { IAC/InterActiveCorp Consumer NMF #3.33 4.58 { J.P. Morgan Chase & Co. Financial 27.9 #7.32 3.98

Eastman Kodak Goods — #16.31 3.35 { Aetna Financial 18.3 24.09 3.18

McKesson Health — 43.48 2.97 | MGIC Investment Financial 11.0 #0.11 2.80 { eBay Consumer 68.5 #28.18 2.71 | Waste Management Business 17.5 #4.80 2.69 | Washington Mutual Financial 13.8 3.92 2.56

Electronic Arts Software 36.2 #6.61 2.54 { Qwest Communications Int Telecom — #13.96 2.49

Citigroup Financial 13.2 #7.12 2.45 { The Directv Group Media — #8.00 2.44

WPP Grp Business — — 2.34 Home Depot Consumer 18.6 2.31 2.31

© 2005 Marningstar, Inc. All rights reserved. The information herein is not represented or warranted to be accurate, correct, complete or timely. Past performance is no guarantee of future results. Access updated reports at mfb.morningstar.com. To order reprints, call 312-696-6100. Source: Morningstar, Inc.

Ticker LMVTX

Historical Profile

Yield 0.0%

NAV $66.32

Total Assets $18,208 mil

Load 12b-1 only

89%Return Risk Rating

93% 99% 99% 99% 98%100% 100% 100%

50.6 43.6 32.4 24.0 17.0

10.0

High High

Highest

Investment Style Equity Stock%

Growth of $10,000 Investment Values of Fund Investment Values of S&P 500

Performance Quartile (within Category)

Mstar Category Large Blend

Manager Change Partial Manager Change

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 07

bru6171X_case02_023-038.qxd 11/24/12 2:24 PM Page 34

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Case 2 Bill Miller and Value Trust 37

EXHIBIT 3 | Long-Term Cumulative Returns for Major Asset Categories

Investments in the U.S. Capital Markets Year-end 2004

Year-end 1925 ! $1.00 Small company stocks $12,968.48 Large company stocks $2,533.20 Long-term government bonds $65.72 Treasury bills $17.87 Inflation $10.62

Source of data: Stocks, Bonds, Bills, and Inflation 2005 Yearbook (Chicago: Ibbotson Associates, 2005), 28.

EXHIBIT 4 | Mean Returns and Standard Deviation of Returns by Major Asset Category

Series (from Geometric Arithmetic Standard 1926 to 2004) Mean Mean Deviation

Large company stocks 10.4% 12.4% 20.3% Small company stocks 12.7 17.5 33.1 Long-term corporate bonds 5.9 6.2 8.6 Long-term government 5.4 5.8 9.3 Intermediate-term government 5.4 5.5 5.7 U.S. Treasury bills 3.7 3.8 3.1 Inflation 3.0% 3.1% 4.3%

Source of data: Stocks, Bonds, Bills, and Inflation 2005 Yearbook (Chicago: Ibbotson Associates, 2005), 33.

EXHIBIT 5 | Average Annual Performance of Legg Mason Equity Funds

Average Annual Total Returns as of September 30, 2005 (%)

One Three Five Seven Ten Since Fund Name Year Year Year Year Year Inception

American Leading Companies Trust 17.87 19.75 4.22 6.93 9.83 9.37

Classic Valuation Fund 18.69 18.59 3.78 — — 5.21 Value Trust, Inc.* 14.25 21.86 2.07 9.41 15.04 16.39 Growth Trust 12.81 27.39 4.51 8.93 11.44 11.74 Special Investment Trust* 18.95 27.31 9.24 16.06 14.62 13.75 U.S. Small-Capitalization

Value Trust 15.02 22.23 16.24 12.11 — 8.01 Balanced Trust 9.31 10.15 1.94 2.97 — 4.34 Financial Services Fund 12.19 17.28 10.67 — — 8.99 Opportunity Trust* 24.36 34.02 9.31 — — 9.81

*Managed by Bill Miller.

Source of data: Company reports.

bru6171X_case02_023-038.qxd 11/24/12 2:24 PM Page 37

bru6171X_case02_023-038.qxd 11/24/12 2:24 PM Page 38

Ben & Jerry’s Homemade JERRY: What’s interesting about me and my role in the company is I’m just this

guy on the street. A person who’s fairly conventional, mainstream, accept- ing of life as it is.

BEN: Salt of the earth. A man of the people.

JERRY: But then I’ve got this friend, Ben, who challenges everything. It’s against his nature to do anything the same way anyone’s ever done it before. To which my response is always, “I don’t think that’ll work.”

BEN: To which my response is always, “How do we know until we try?”

JERRY: So I get to go through this leading-edge, risk-taking experience with Ben—even though I’m really just like everyone else.

BEN: The perfect duo. Ice cream and chunks. Business and social change. Ben and Jerry.

—Ben & Jerry’s Double-Dip

As Henry Morgan’s plane passed over the snow-covered hills of Vermont’s dairy land, through his mind passed the events of the last few months. It was late January 2000. Morgan, the retired dean of Boston University’s business school, knew well the trip to Burlington. As a member of the board of directors of Ben & Jerry’s Homemade for the past 13 years, Morgan had seen the company grow both in finan- cial and social stature. The company was now not only an industry leader in the super-premium ice cream market, but also commanded an important leadership posi- tion in a variety of social causes from the dairy farms of Vermont to the rainforests of South America.

Increased competitive pressure and Ben & Jerry’s declining financial perform- ance had triggered a number of takeover offers for the resolutely independent-minded company. Today’s board meeting had been convened to consider the pending offers.

39

3CASE

This case was prepared by Professor Michael J. Schill with research assistance from Daniel Burke, Vern Hines, Sangyeon Hwang, Wonsang Kim, Vincente Ladinez, and Tyrone Taylor. It was written as a basis for class discussion rather than to illustrate effective or ineffective handling of an administrative situation. Copyright © 2001 by the University of Virginia Darden School Foundation, Charlottesville, VA. All rights reserved. To order copies, send an e-mail to [email protected] No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means—electronic, mechanical, photocopying, recording, or otherwise—without the permission of the Darden School Foundation. Rev. 10/03.

bru6171X_case03_039-052.qxd 11/24/12 2:26 PM Page 39

Morgan expected a lively debate. Cofounders Ben Cohen and Jerry Greenfield knew the company’s social orientation required corporate independence. In stark contrast, chief executive Perry Odak felt that Ben and Jerry’s shareholders would be best served by selling out to the highest bidder.

Ben & Jerry’s Homemade Ben & Jerry’s Homemade, a leading distributor of super-premium ice creams, frozen yogurts, and sorbets, was founded in 1978 in an old gas station in Burlington, Vermont. Cohen and Greenfield recounted their company’s beginnings:

One day in 1977, we [Cohen and Greenfield] found ourselves sitting on the front steps of Jerry’s parents’ house in Merrick, Long Island, talking about what kind of business to go into. Since eating was our greatest passion, it seemed logical to start with a restau- rant. . . . We wanted to pick a product that was becoming popular in big cities and move it to a rural college town, because we wanted to live in that kind of environment. We wanted to have a lot of interaction with our customers and enjoy ourselves. And, of course, we wanted a product that we liked to eat. . . . We found an ad for a $5 ice- cream-making correspondence course offered through Penn State. Due to our extreme poverty, we decided to split one course between us, sent in our five bucks, read the ma- terial they sent back, and passed the open-book tests with flying colors. That settled it. We were going into the ice cream business.

Once we’d decided on an ice cream parlor, the next step was to decide where to put it. We knew college students eat a lot of ice cream; we knew they eat more of it in warm weather. Determined to make an informed decision (but lacking in technological and finan- cial resources), we developed our own low-budget “manual cross-correlation analysis.” Ben sat at the kitchen table, leafing through a U.S. almanac to research towns that had the highest average temperatures. Jerry sat on the floor; reading a guide to American colleges, searching for the rural towns that had the most college kids. Then we merged our lists. When we investigated the towns that came up, we discovered that apparently someone had already done this work ahead of us. All the warm towns that had a decent number of col- lege kids already had homemade ice-cream parlors. So we threw out the temperature crite- rion and ended up in Burlington, Vermont. Burlington had a young population, a significant college population, and virtually no competition. Later, we realized the reason why there was no competition. It’s so cold in Burlington for so much of the year, and the summer sea- son is so short, it was obvious (to everyone except us) that there was no way an ice cream parlor could succeed there. Or so it seemed.1

By January 2000, Cohen and Greenfield’s ice cream operation in Burlington, Ben & Jerry’s Homemade, had become a major premium ice cream producer with over 170 stores (scoop shops) across the United States and overseas, and had developed an important presence on supermarket shelves. Annual sales had grown to $237 mil- lion, and the company’s equity was valued at $160 million (Exhibits 1 and 2). The

40 Part One Setting Some Themes

1Ben Cohen and Jerry Greenfield, Ben & Jerry’s Double-Dip (New York: Simon & Schuster, 1997), 15–17.

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Case 3 Ben & Jerry’s Homemade 41

company was known for such zany ice cream flavors as Chubby Hubby, Chunky Monkey, and Bovinity Divinity. Exhibit 3 provides a selected list of flavors from its scoop-shop menu.

Ben & Jerry’s Social Consciousness Ben & Jerry’s was also known for its emphasis on socially progressive causes and its strong commitment to the community. Although unique during the company’s early years, Ben & Jerry’s community orientation was no longer that uncommon. Companies such as Patagonia (clothing), Odwalla (juice), The Body Shop (body-care products), and Tom’s of Maine (personal-care products) shared similar visions of what they termed “caring capitalism.”

Ben & Jerry’s social objective permeated every aspect of the business. One dimension was its tradition of generous donations of its corporate resources. Since 1985, Ben & Jerry’s donated 7.5% of its pretax earnings to various social foundations and community-action groups. The company supported causes such as Greenpeace International and the Vietnam Veterans of America Foundation by signing petitions and recruiting volunteers from its staff and the public. The company expressed cus- tomer appreciation with an annual free cone day at all of its scoop shops. During the event, customers were welcome to enjoy free cones all day.

Although the level of community giving was truly exceptional, what really made Ben & Jerry’s unique was its commitment to social objectives in its marketing, oper- ations, and finance policies. Cohen and Greenfield emphasized that their approach was fundamentally different from the self-promotion-based motivation of social causes supported by most corporations.

At its best, cause-related marketing is helpful in that it uses marketing dollars to help fund social programs and raise awareness of social ills. At its worst, it’s “greenwashing”—using philanthropy to convince customers the company is aligned with good causes, so the com- pany will be seen as good, too, whether it is or not. . . . They understand that if they dress themselves in that clothing, slap that image on, that’s going to move product. But instead of just slapping the image on, wouldn’t it be better if the company actually did care about its consumers and the community?2

An example of Ben & Jerry’s social-value-led marketing included its development of an ice cream flavor to provide demand for harvestable tropical-rainforest products. The product’s sidebar described the motivation:

This flavor combines our super creamy vanilla ice cream with chunks of Rainforest Crunch, a cashew & Brazil nut buttercrunch made for us by our friends at Community Products in Montpelier, Vermont. The cashews & Brazil nuts in this ice cream are har- vested in a sustainable way from tropical rainforests and represent an economically viable long-term alternative to cutting these trees down. Enjoy! —Ben & Jerry

2Ben Cohen and Jerry Greenfield, Ben & Jerry’s Double-Dip (New York: Simon & Schuster, 1997), 33.

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Financing decisions were also subject to community focus. In May of 1984, Ben & Jerry’s initiated its first public equity financing. Rather than pursue a broad tradi- tional public offering, the company issued 75,000 shares at $10.50 a share exclusively to Vermont residents. By restricting the offering to Vermonters, Cohen hoped to offer those who had first supported the company with the opportunity to profit from its suc- cess. To provide greater liquidity and capital, a traditional broad offering was later placed and the shares were then listed and traded on the NASDAQ. Despite Ben & Jerry’s becoming a public company, Cohen and Greenfield did not always follow tra- ditional investor-relations practices. “Chico” Lager, the general manager at the time, recalled the following Ben Cohen interview transcript that he received before its pub- lication in the Wall Street Transcript:

TWST: Do you believe you can attain a 15% increase in earnings each year over the next five years?

COHEN: I got no idea.

TWST: Umm-hmm. What do you believe your capital spending will be each year over the next five years?

COHEN: I don’t have any ideas as to that either.

TWST: I see. How do you react to the way the stock market has been treating you in general and vis-à-vis other companies in your line?

COHEN : I think the stock market goes up and down, unrelated to how a com- pany is doing. I never expected it to be otherwise. I anticipate that it will continue to go up and down, based solely on rumor and whatever sort of manipulation those people who like to manipulate the market can accomplish.

TWST : What do you have for hobbies?

COHEN : Hobbies. Let me think. Eating, mostly. Ping-Pong.

TWST : Huh?

COHEN : Ping-Pong.3

Solutions to corporate operating decisions were also dictated by Ben & Jerry’s interest in community welfare. The disposal of factory wastewater provided an example.

In 1985, when we moved into our new plant in Waterbury, we were limited in the amount of wastewater that we could discharge into the municipal treatment plant. As sales and production skyrocketed, so did our liquid waste, most of which was milky water. [We] made a deal with Earl, a local pig farmer, to feed our milky water to his pigs. (They loved every flavor except Mint with Oreo Cookies, but Cherry Garcia was their favorite.) Earl’s pigs alone couldn’t handle our volume, so eventually we loaned Earl $10,000 to buy 200 piglets. As far as we could tell, this was a win-win solution to a tricky environmental

42 Part One Setting Some Themes

3Fred “Chico” Lager, Ben & Jerry’s: The Inside Scoop (New York: Crown Publishers, 1994), 124–125.

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problem. The pigs were happy. Earl was happy. We were happy. The community was happy.4

Ben & Jerry’s social orientation was balanced with product and economic objec- tives. Its mission statement included all three dimensions, and stressed seeking new and creative ways of fulfilling each without compromising the others:

Product: To make, distribute, and sell the finest quality all-natural ice cream and related products in a wide variety of innovative flavors made from Vermont dairy products.

Economic: To operate the company on a sound financial basis of profitable growth, increasing value for our shareholders, and creating career opportunities and financial rewards for our employees.

Social: To operate the company in a way that actively recognizes the central role that business plays in the structure of society by initiating innovative ways to improve the quality of life of the broad community—local, national, and international.

Management discovered early on that the company’s three objectives were not always in harmony. Cohen and Greenfield told of an early example:

One day we were talking [about our inability to make a profit] to Ben’s dad, who was an accountant. He said, “Since you’re gonna make such a high-quality product . . . why don’t you raise your prices?” At the time, we were charging fifty-two cents a cone. Coming out of the ’60s, our reason for going into business was that ours was going to be “ice cream for the people.” It was going to be great quality products for everybody— not some elitist treat. . . . Eventually we said, Either we’re going to raise our prices or we’re going to go out of business. And then where will the people’s ice cream be? They’ll have to get their ice cream from somebody else. So we raised the prices. And we stayed in business.5

At other times, management chose to sacrifice short-term profits for social gains. Greenfield tells of one incident with a supplier:

Ben went to a Social Ventures Network meeting and met Bernie Glassman, a Jewish-Buddhist former nuclear-physicist monk. Bernie had a bakery called Greyston in inner-city Yonkers, New York. It was owned by a nonprofit religious institution; its purpose was to train and employ economically disenfranchised people [and] to fund low-income housing and other community-service activities. Ben said, “We’re looking for someone who can bake these thin, chewy, fudgy brownies. If you could do that, we could give you some business, and you could make us the brownies we need, and that would be great for both of us.” . . . The first order we gave Greyston was for a couple of tons. For us, that was a small order. For Greyston, it was a huge order. It caused their system to break down. The brownies were coming off the line so fast that they ended up getting packed hot. Then they needed to be

Case 3 Ben & Jerry’s Homemade 43

4Ben & Jerry’s Double-Dip, 154. 5Ben & Jerry’s Double-Dip, 154.

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frozen. Pretty soon, the bakery freezer was filled up with these steaming 50-pound boxes of hot brownies. The freezer couldn’t stay very cold, so it took days to freeze the brownies. By the time they were frozen, [they] had turned into 50-pound blocks of brownie. And that’s what Greyston shipped to us. So we called up Bernie and we said, “Those two tons you shipped us were all stuck together. We’re shipping them back.” Bernie said, “I can’t afford that. I need the money to meet my payroll tomorrow. Can’t you unstick them?” And we said, “Bernie, this really gums up the works over here.” We kept going back and forth with Greyston, trying to get the brownies right. Eventually we created a new flavor, Chocolate Fudge Brownie, so we could use the brownie blocks.6

Asset Control The pursuit of a nonprofit-oriented policy required stringent restrictions on corporate control. For Ben & Jerry’s, asset control was limited through elements of the com- pany’s corporate charter, differential stock-voting rights, and a supportive Vermont legislature.

Corporate Charter Restrictions At the 1997 annual meeting, Ben & Jerry’s shareholders approved amendments to the charter that gave the board greater power to perpetuate the mission of the firm. The amendments created a staggered board of directors, whereby the board was divided into three classes with one class of directors being elected each year for a three-year term. A director could only be removed with the approval of a two-thirds vote of all shareholders. Also, any vacancy resulting from the removal of a director could be filled by two-thirds vote of the directors who were then in office. Finally, the stock- holders increased the number of votes required to alter, amend, repeal, or adopt any provision inconsistent with those amendments to at least two-thirds of shareholders. See Exhibit 4 for a summary of the current board composition.

Differential Voting Rights Ben & Jerry’s had three equity classes: class A common, class B common, and class A preferred. The holders of class A common were entitled to one vote for each share held. The holders of class B common, reserved primarily for insiders, were entitled to 10 votes for each share held. Class B common was not transferable, but could be converted into class A common stock on a share-for-share basis and was transferable thereafter. The company’s principals—Ben Cohen, Jerry Greenfield, and Jeffrey Furman—effectively held 47% of the aggregate voting power, with only 17% of the aggregate common equity outstanding. Nonboard members, however, still maintained 51% of the voting power (see Exhibit 5). The class A preferred stock was held exclu- sively by the Ben & Jerry’s Foundation, a community-action group. The class A pre- ferred gave the foundation a special voting right to act with respect to certain business combinations and the authority to limit the voting rights of common stockholders in

44 Part One Setting Some Themes

6Ben & Jerry’s Double-Dip, 154.

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certain transactions such as mergers and tender offers, even if the common stock- holders favored such transactions.

Vermont Legislature In April 1998, the Vermont Legislature amended a provision of the Vermont Business Corporation Act, which gave the directors of any Vermont corporation the authority to consider the interests of the corporation’s employees, suppliers, creditors, and cus- tomers when determining whether an acquisition offer or other matter was in the best interest of the corporation. The board could also consider the economy of the state in which the corporation was located and whether the best interests of the company could be served by the continued independence of the corporation.

Those and other defense mechanisms strengthened Ben & Jerry’s ability to remain an independent, Vermont-based company, and to focus on carrying out the threefold corporate mission, which management believed was in the best interest of the com- pany, its stockholders, employees, suppliers, customers, and the Vermont community at large.

The Offers Morgan reviewed the offers on the table. Discussion with potential merger partners had been ongoing since the previous summer. In August 1999, Pillsbury (maker of the premium ice cream Haagen-Dazs) and Dreyer’s announced the formation of an ice cream joint venture. Under past distribution agreements, Pillsbury-Dreyer’s would become the largest distributor of Ben & Jerry’s products. In response, the Ben & Jerry’s board had authorized Odak to pursue joint-venture and merger discussions with Unilever and Dreyer’s. By December, the joint-venture arrangements had broken down, but the discussions had resulted in takeover offers for Ben & Jerry’s of between $33 and $35 a share from Unilever, and an offer of $31 a share from Dreyer’s. Just yesterday, Unilever had raised its offer to $36, and two private invest- ment houses, Meadowbrook Lane Capital and Chartwell Investments, had made two separate additional offers. The offer prices represented a substantial premium over the preoffer-announcement share price of $21.7 See Exhibit 6 for a comparison of investor-value measures for Ben & Jerry’s and the select competitors.

Dreyer’s Grand Ice Cream Dreyer’s Grand Ice Cream sold premium ice cream and other frozen desserts under the Dreyer’s and Edy’s brands and some under nonbranded labels. The Dreyer’s and

Case 3 Ben & Jerry’s Homemade 45

7Recent food-company acquisitions included Kraft’s $270-million acquisition of Balance Bar and Kellogg’s $308-million acquisition of Worthington Foods. Balance Bar and Worthington—both health-food companies—sold at takeover premia of 76% and 88%, respectively. The mean acquisition premium offered by successful bidders in a large sample of U.S. multiple-bid contests was found to be 70%. See S. Betton and B. E. Eckbo, “Toeholds, Bid Jumps, and Expected Payoffs in Takeovers,” Review of Financial Studies 13, 4 (winter 2000): 841–882.

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Edy’s lines were distributed through a direct store-delivery system. Total sales were over $1 billion, and company stock traded at a total capitalization of $450 million. Dreyer’s was also involved in community-service activities. In 1987, the company established the Dreyer’s Foundation to provide focused community support, particularly for youth and K–12 public education.

Unilever Unilever manufactured branded consumer goods, including foods, detergents, and other home- and personal-care products. The company’s ice cream division included the Good Humor, Breyers, Klondike, Dickie Dee, and Popsicle brands, and was the largest producer of ice cream in the world. Good Humor-Breyers was headquartered in Green Bay, Wisconsin, with plants and regional sales offices located throughout the United States. Unilever had a total market capitalization of $18 billion.

Meadowbrook Lane Capital Meadowbrook Lane Capital was a private investment fund that portrayed itself as socially responsible. The firm was located in Northampton, Massachusetts. The Mead- owbrook portfolio included holdings in Hain Foods, a producer of specialty health- oriented food products. Meadowbrook proposed acquiring a majority ownership interest through a tender offer to Ben & Jerry’s shareholders.

Chartwell Investments Chartwell Investments was a New York City private-equity firm that invested in growth financings and management buyouts of middle-market companies. Chartwell proposed investing between $30 million and $50 million in Ben & Jerry’s in exchange for a convertible preferred-equity position that would allow Chartwell to obtain majority representation on the board of directors.

Morgan summarized the offers as follows:

46 Part One Setting Some Themes

Bidder Offering Price Main Proposal

Dreyer’s $31 (stock) • Maintain B&J management team Grand • Operate B&J as a quasi-autonomous business unit

• Encourage some social endeavors Unilever $36 (cash) • Maintain select members of B&J management team

• Integrate B&J into Unilever’s frozen desserts division • Restrict social commitments and interests

Meadowbrook $32 (cash) • Install new management team Lane • Allow B&J to operate as an independent company

controlled under the Meadowbrook umbrella • Maintain select social projects and interests

Chartwell Minority • Install new management team interest • Allow B&J to continue as an independent company

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Conclusion Henry Morgan doubted that the social mission of the company would survive a takeover by a large traditional company. Despite his concern for Ben & Jerry’s social interests, Morgan recognized that, as a member of the board, he had been elected to represent the interests of the shareholders. A financial reporter, Richard McCaffrey, expressed the opinion of many shareholders:

Let’s jump right into the fire and suggest, depending upon the would-be acquiring com- pany’s track record at creating value, that it makes sense for the company [Ben & Jerry’s] to sell. Why? At $21 a share, Ben & Jerry’s stock has puttered around the same level, more or less, for years despite regular sales and earnings increases. For a company with a great brand name, about a 45% share of the super-premium ice cream market, successful new- product rollouts, and decent traction in its international expansion efforts, the returns should be better. Some of the reasons for underperformance, such as the high price of cream and milk, aren’t factors the company can control. That’s life in the ice cream busi- ness. But Ben & Jerry’s average return on shareholders’ equity, a measure of how well it’s employing shareholders’ money, stood at 7% last year, up from 5% in 1997. That’s lousy by any measure, although it’s improved this year and now stands at about 9%. This isn’t helped by the company’s charitable donations, of course, but if you’re an investor in Ben & Jerry’s you knew that going in—it’s an ironclad part of corporate culture, and has served the company well. Still, Ben & Jerry’s has to find ways to create value.8

The plane banked over icy Lake Champlain and began its descent into Burlington as Morgan collected his thoughts for what would undoubtedly be an emotional and spirited afternoon meeting.

Case 3 Ben & Jerry’s Homemade 47

8Richard McCaffrey, “In the Hunt for Ben & Jerry’s,” Fool.com (2 December 1999).

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48 Part One Setting Some Themes

EXHIBIT 1 | Ben & Jerry’s Homemade Financial Statements and Financial Ratios (in millions, except for per-share figures)

1999 1998 1997 1996 1995 1994

1 Net sales $237.0 $209.2 $174.2 $167.2 $155.3 $148.8 2 Cost of sales 145.3 136.2 114.3 115.2 109.1 109.8 3 Gross profit 91.8 73.0 59.9 51.9 46.2 39.0 4 Selling, general, & administrative expenses 82.9* 63.9 53.5 45.5 36.4 36.3 5 Earnings before interest and taxes 8.9* 9.1 6.4 6.4 9.8 2.8 6 Net income 8.0* 6.2 3.9 3.9 5.9 (1.9)

7 Working capital $ 42.8 $ 48.4 $ 51.4 $ 50.1 $ 51.0 $ 37.5 8 Total assets 150.6 149.5 146.5 $136.7 131.1 120.3 9 Long-term debt and obligations 16.7 20.5 25.7 31.1 32.0 32.4

10 Stockholders’ equity 89.4 90.9 86.9 82.7 78.5 72.5

Per-share figures: Sales $31.34 Earnings $ 1.06* Book equity $11.82

Gross margin (3/1) 38.7% 34.9% 34.4% 31.0% 29.7% 26.2% Operating margin (5/1) 3.8%* 4.3% 3.7% 3.8% 6.3% 1.9% Net income margin (6/1) 3.4%* 3.0% 2.2% 2.3% 3.8% !1.3% Asset turnover (1/9) 1.6 1.4 1.2 1.2 1.2 1.2 Working capital turnover (1/8) 5.5 4.3 3.4 3.3 3.0 4.0

ROA (5 " [1 ! 40%]/9) 3.5%* 3.7% 2.6% 2.8% 4.5% 1.4%

ROE (6/11) 8.9%* 6.8% 4.5% 4.7% 7.5% !2.6%

Yield to maturity on 30-year U.S. Treasury bonds (DataStream) 6.5% 5.1% 5.9% 6.6% 6.0% 7.9%

*Adjusted by case writer for 50% of 1999 $8.6-million special charge for asset write-off and employee severance associated with frozen novelty manufacturing facility.

Source: SEC filings.

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49

EXHIBIT 2 | Ben & Jerry’s Homemade Stock-Price Performance

40

35

30

25

20

15

10

5

0

P ri

ce

Ja n-

96

Ma r-9

6

Ma y-9

6 Ju

l-9 6

Se p-

96

No v-9

6

Ja n-

97

Ma r-9

7

Ma y-9

7 Ju

l-9 7

Se p-

97

No v-9

7

Ja n-

98

Ma r-9

8

Ma y-9

8 Ju

l-9 8

Se p-

98

No v-9

8

Ja n-

99

Ma r-9

9

Ma y-9

9 Ju

l-9 9

Se p-

99

No v-9

9

S&P 500 (adjusted to Ben & Jerry's Jan. 1996)

Ben & Jerry's Homemade

Industry Portfolio (includes Dreyer's, Eskimo Pie, TCBY, and Yocream

adjusted to Ben & Jerry's January 1996)

EXHIBIT 3 | Ben & Jerry’s Selected List of Flavors (January 2000)

Bovinity Divinity Milk-chocolate ice cream and white-chocolate cows swirled with white-chocolate ice cream and dark fudge cows

Cherry Garcia Cherry ice cream with cherries and fudge flakes Chocolate Chip Cookie Dough Vanilla ice cream with gobs of chocolate-chip cookie dough Chocolate Fudge Brownie Chocolate ice cream with fudgy brownies Chubby Hubby Chocolate-covered, peanut-butter-filled pretzels in vanilla-malt ice cream

with fudge and peanut-butter swirls Chunky Monkey Banana ice cream with walnuts and chocolate chunks Coconut Almond Fudge Chip Coconut ice cream with almonds and fudge chips Coffee, Coffee, BuzzBuzzBuzz! Coffee ice cream with espresso-fudge chunks Deep Dark Chocolate Very chocolaty ice cream New York Super Fudge Chunk Chocolate ice cream with white- and dark-chocolate chunks, pecans,

walnuts, and chocolate-covered almonds Peanut Butter Cup Peanut-butter ice cream with peanut-butter cups Phish Food Milk-chocolate ice cream with marshmallow nougat, caramel swirls, and

fudge fish Pistachio Pistachio Pistachio ice cream with pistachios S’mores Chocolate low-fat ice cream with marshmallow swirls and graham-cracker

wedges Southern Pecan Pie Brown-sugar ice cream with roasted pecans, chunks of pecan-pie pieces,

and a pecan-caramel swirl

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50 Part One Setting Some Themes

EXHIBIT 4 | Composition of Board of Directors

Name Age Office Year Elected

Jerry Greenfield 48 Chairperson, Director 1990 Ben Cohen 48 Vice Chairperson, Director 1977 Perry Odak 54 Chief Executive Officer, President, and Director 1997 Pierre Ferrari 49 Director, Self-Employed Consultant 1997 Jeffrey Furman 56 Director, Self-Employed Consultant 1982 Jennifer Henderson 46 Director, President of leadership-consulting firm– 1996

Strategic Interventions Frederick A. Miller 53 Director, President of management-consulting firm– 1992

Kaleel Jamison Consulting Group Henry Morgan 74 Director, Dean Emeritus of Boston 1987

University School of Management Bruce Bowman 47 Senior Director of Operations 1995 Charles Green 45 Senior Director of Sales and Distribution 1996 Michael Sands 35 Chief Marketing Officer 1999 Frances Rathke 39 Chief Financial Officer and Secretary 1990

*Occupations of directors who were neither employed at Ben & Jerry’s nor the Ben & Jerry’s Foundation, Inc., as of March 25, 1999, are as follows:

Ben Cohen: Cofounder of Ben & Jerry’s, and served as a director at Blue Fish Clothing, Community Products, Inc., Social Venture Network, and Greenpeace International.

Pierre Ferrari: President of Lang International, a marketing-consulting firm. Jeffrey Furman: Self-employed consultant. Jennifer Henderson: Director of Training at the Center for Community Change, and President of Strategic Interventions, a leadership-

and management-consulting firm. Frederick A. Miller: President of Kaleel Jamison Consulting Group, a strategic-culture-change and management-consulting firm. Henry Morgan: Dean Emeritus of the Boston University School of Management. Also served as a director at Cambridge Bancorpora-

tion, Southern Development Bancorporation, and Cleveland Development Bancorporation.

Source: SEC filings.

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Case 3 Ben & Jerry’s Homemade 51

EXHIBIT 5 | Beneficial-Ownership Structure of Ben & Jerry’s Homemade

Class A Common Stock Class B Common Stock Preferred Stock

% Outstanding % Outstanding % Outstanding # Shares Shares # Shares Shares # Shares Shares

Ben Cohen 413,173 6.1% 488,486 60.9% — — Jerry Greenfield 130,000 1.9% 90,000 11.2% — — Jeffrey Furman 17,000 * 30,300 3.8% — — Perry Odak 368,521 5.5% — — — — Pierre Ferrari 8,121 * — — — — Jennifer Henderson 1,138 * — — — — Frederick A. Miller 4,345 * — — — — Henry Morgan 5,845 * — — — — Bruce Bowman 46,064 * — — — — Charles Green 17,809 * — — — — Frances Rathke 51,459 * — — — — Credit Suisse Asset

Management 860,500 12.7% — — — — Dimensional Fund

Advisors 359,000 5.3% — — — — All officers &

directors as a group of 15 persons 1,115,554 16.5% 608,786 75.9% — —

Ben & Jerry’s Foundation, Inc. — — — — 900 100.0%

Total shares outstanding (12/25/1999) 6,759,276 801,813 900

*Less than 1%.

Source: SEC filings.

EXHIBIT 6 | Investor-Value Measures: Ben & Jerry’s and Industry Comparables

Price/Earnings Price/Book

Dreyer’s Grand 47.2 7.8 Eskimo Pie 30.7 1.1 TCBY Enterprises 12.5 1.2 Yocream International 9.4 1.8 Ben & Jerry’s 19.8 1.8

Source: Case writer analysis.

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The Battle for Value, 2004: FedEx Corp. vs. United Parcel Service, Inc.

FedEx will produce superior financial returns for shareowners by providing high value-added supply chain, transportation, business, and related information services through focused operating companies competing collectively, and managed collaboratively, under the respected FedEx brand.

FedEx Mission Statement (Excerpt)

We serve the evolving distribution, logistics, and commerce needs of our customers worldwide, offering excellence and value in all we do. We sustain a financially strong company, with broad employee ownership, that provides a long-term competitive return to our shareowners.

UPS Mission Statement (Excerpt)

On June 18, 2004, the United States and China reached a landmark air-transportation agreement that quintupled the number of commercial cargo flights between the two countries. The agreement also allowed for the establishment of air-cargo hubs in China and landing rights for commercial airlines at any available airport. The pact represented the most dramatic liberalization of air traffic in the history of the two nations, and FedEx Corporation and United Parcel Service, Inc. (UPS), the only U.S. all-cargo carriers then permitted to serve the vast Chinese market,1 were certain to be the primary beneficiaries of this opportunity.

News of the transportation agreement did not come as a major surprise to most observers as U.S. and Chinese negotiators had been in talks since at least February. The stock prices of both companies had been rising steadily since those talks began,

53

4CASE

1Northwest Airlines served China through both all-cargo and all-passenger services.

This case was prepared by Robert F. Bruner and Sean D. Carr as a basis for classroom discussion rather than to illustrate effective or ineffective management. The case complements “Battle for Value: Federal Express Corporation vs. United Parcel Service of America, Inc.” (UVA-F-1115), prepared by Robert F. Bruner and Derick Bulkley. Copyright © 2005 by the University of Virginia Darden School Foundation, Charlottesville, VA. All rights reserved. To order copies, send an e-mail to [email protected] No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means—electronic, mechanical, photocopying, recording, or otherwise—without the permission of the Darden School Foundation. Rev 07/08

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but FedEx’s share price had rocketed at a rate nearly five times faster than UPS’s.2

Exhibit 1 presents an illustration of recent stock-price patterns for the two firms relative to the S&P 500 Index. FedEx had the largest foreign presence in China, with 11 weekly flights—almost twice as many as UPS. The company served 220 Chinese cities, and flew directly to Beijing, Shenzhen, and Shanghai. FedEx’s volumes in China had grown by more than 50% between 2003 and 2004.

While UPS lagged behind FedEx in the Chinese market, it was still the world’s largest package-delivery company and the dominant parcel carrier in the United States. UPS had been active in China since 1988 and was the first carrier in the industry to offer nonstop service from the United States. By 2003, UPS had six weekly Boeing 747 flights to China, with direct flights to Beijing and Shanghai, serving nearly 200 cities. UPS reported a 60% growth in traffic on its principal U.S.–Shanghai route since initiating that service in 2001, and it predicted that peak-season demand would exceed its capacity.

As the U.S. package-delivery segment matured, the international markets—and espe- cially China—became a battleground for the two package-delivery giants. FedEx had vir- tually invented customer logistical management, and was widely perceived as innovative, entrepreneurial, and an operational leader. Historically, UPS had a reputation for being big, bureaucratic, and an industry follower, but “Big Brown” was aggressively shed- ding its plodding image, as it too became an innovator and a tenacious adversary. UPS had recently undergone a major overhaul of its image, and was repositioning itself as a leading provider of logistics and supply-chain management services.

The 2004 air-transportation agreement between China and the United States was a watershed moment for the international package-delivery business—more than 100 new weekly all-cargo flights were up for grabs with the United States’ largest trading partner. There was, however, no guarantee for exactly how those new cargo routes would be allocated between UPS and FedEx, companies that had been battling each other for dominance for more than 30 years. Moreover, the eventual assignment to the region of other carriers would test each company’s ability to fend off emerging competitive threats.

Against this backdrop, industry observers wondered how the titanic struggle between FedEx and UPS would develop, particularly for investors in the two firms. Was the performance of the companies in recent years predictive of the future? Success in China was widely seen as the litmus test for corporate survival in the new millennium. Which company was better positioned to attract the capital necessary to win this competitive battle?

FedEx Corporation FedEx first took form as Fred Smith’s undergraduate term paper for a Yale University economics class. Smith’s strategy dictated that FedEx would purchase the planes that it required to transport packages, whereas all other competitors used the cargo space

54 Part One Setting Some Themes

2Between February 18 and June 18, 2004, FedEx’s stock price rose 13.9%, whereas UPS’s grew 3.1%.

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available on passenger airlines. In addition to using his own planes, Smith’s key inno- vation was a hub-and-spoke distribution pattern, which permitted cheaper and faster service to more locations than his competitors could offer. In 1971, Smith invested his $4-million inheritance, and raised $91 million in venture capital to launch the firm—the largest venture-capital start-up at the time.

In 1973, on the first night of continuous operation, 389 FedEx employees deliv- ered 186 packages overnight to 25 U.S. cities. In those early years FedEx, then known as Federal Express Corporation, experienced severe losses, and Smith was nearly ousted from his chair position. By 1976, FedEx finally saw a modest profit of $3.6 million on an average daily volume of 19,000 packages. Through the rest of the 1970s, FedEx continued to grow by expanding services, acquiring more trucks and aircraft, and raising capital. The formula was successful. In 1981, FedEx generated more revenue than any other U.S. air-delivery company.

By 1981, competition in the industry had started to rise. Emery Air Freight began to imitate FedEx’s hub system and to acquire airplanes, and UPS began to move into the overnight air market. The United States Postal Service (USPS) positioned its overnight letter at half the price of FedEx’s, but quality problems and FedEx’s “absolutely positively overnight” ad campaign quelled that potential threat. In 1983, FedEx reached $1 billion in revenues and seemed poised to own the market for express delivery.

During the 1990s, FedEx proved itself as an operational leader, even receiving the prestigious Malcolm Baldrige National Quality Award from the President of the United States. FedEx was the first company ever to win in the service category. Part of this success could be attributed to deregulation and to operational strategy, but credit could also be given to FedEx’s philosophy of “People-Service-Profit,” which reflected its emphasis on customer focus, total quality management, and employee participation. Extensive attitude surveying, a promote-from-within policy, effective grievance procedures that sometimes resulted in a chat with Fred Smith himself, and an emphasis on personal responsibility and initiative not only earned FedEx a reputation as a great place to work, but also helped to keep the firm largely free of unions.

FedEx’s growth occurred within the context of fundamental change in the busi- ness environment. Deregulation of the domestic airline industry permitted larger planes to replace smaller ones, thereby permitting FedEx to purchase several Boeing 727s, which helped reduce its unit costs. Trucking industry deregulation also permitted FedEx to establish an integrated regional trucking system that lowered its unit costs on short-haul trips, enabling the company to compete more effectively with UPS. Rising inflation and global competitiveness compelled manufacturers to manage inventories more closely and to emulate the just-in-time (JIT) supply programs of the Japanese, creating a heightened demand for FedEx’s rapid and carefully moni- tored movement of packages. And, finally, technological innovations enabled FedEx to achieve important advances in customer ordering, package tracking, and process monitoring.

By the end of 2003, FedEx had nearly $15.4 billion in assets and net income of $830 million on revenues of about $22.5 billion. Exhibit 2 provides FedEx’s

Case 4 The Battle for Value, 2004: FedEx Corp. vs. United Parcel Service, Inc. 55

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financial and analytical ratios. The company had about 50,000 ground vehicles, 625 air- craft, 216,500 full- and part-time employees, and shipped more than 5.4 million pack- ages daily.

United Parcel Service, Inc. Founded in 1907, United Parcel Service, Inc., was the largest package-delivery com- pany in the world. Consolidated parcel delivery, both on the ground and through the air, was the primary business of the company, although increasingly the company offered more specialized transportation and logistics services.

Known in the industry as Big Brown, UPS had its roots in Seattle, Washington, where 19-year-old Jim Casey started a bicycle-messenger service called American Messenger Company. After merging with a rival firm, Motorcycle Delivery Company, the company focused on department-store deliveries, and that remained true until the 1940s. Renamed United Parcel Service of America, UPS started an air-delivery serv- ice in 1929 by putting packages on commercial passenger planes. The company entered its strongest period of growth during the post–World War II economic boom and, by 1975, UPS had reached a milestone when it could promise package delivery to every address in the continental United States. That same year the company expanded outside the country with its first delivery to Ontario, Canada. The following year, UPS began service in West Germany with 120 of its trademark-brown delivery vans.

The key to the success of UPS, later headquartered in Atlanta, Georgia, was effi- ciency. According to BusinessWeek, “Every route is timed down to the traffic light. Each vehicle was engineered to exacting specifications. And the drivers . . . endure a daily routine calibrated down to the minute.”3 But this demand for machinelike pre- cision met with resistance by UPS’s heavily unionized labor force. Of those demands, UPS driver Mark Dray said:

. . . drivers are expected to keep precise schedules (with hours broken down into hundredths) that do not allow for variables such as weather, traffic conditions, and package volume. If they’re behind, they’re reprimanded, and if they’re ahead of schedule, their routes are lengthened.4

In its quest for efficiency, UPS experienced several major strikes resulting from changes in labor practices and driver requirements. In August 1997, the 190,000 team- sters employed at UPS went on strike for 15 days before agreeing to a new five-year contract. In addition to large wage increases, the new agreement called for the cre- ation of 10,000 new full-time jobs and the shifting of 10,000 part-time workers into full-time positions. The strike cost UPS $700 million in lost revenue, resulting in less than 1% sales growth for the year (1996) and a decline in profits to $909 million from $1.15 billion.

56 Part One Setting Some Themes

3Todd Vogel and Chuck Hawkins, “Can UPS Deliver the Goods in a New World?” BusinessWeek (4 June 1990). 4Jill Hodges, “Driving Negotiations; Teamsters Survey Says UPS Drivers among Nation’s Most Stressed Workers,” Star Tribune (9 June 1993).

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For most of the company’s history, UPS stock was owned solely by UPS’s man- agers, their families, former employees, or charitable foundations owned by UPS. The company acted as the market-maker in its own shares, buying or selling shares at a fair market value5 determined by the board of directors each quarter. By the end of the millennium, however, having shrugged off the lingering effects of the strike and having emerged as a newly revitalized company with strong forward momentum, company executives determined that UPS needed the added flexibility of publicly traded stock in order to pursue a more aggressive acquisition strategy.

In November 1999, UPS initiated a two-for-one stock split, whereby the company exchanged each existing UPS share for two Class A shares. The company then sold 109.4 million newly created Class B shares on the New York Stock Exchange in an initial public offering (IPO) that raised $5.266 billion, net of issuance costs. UPS used the majority of these proceeds to repurchase 68 million shares of the Class A stock. Following a holding period after the IPO, Class A shares were convertible to Class B, and could be traded or sold accordingly. Although both shares of stock had the same economic interest in the company, Class A shares entitled holders to ten votes per share while the Class B shareowners were entitled to one vote.

Until the stock split and IPO in 1999, the financially and operationally conser- vative company had been perceived as slow and plodding. Although much larger than FedEx, UPS had not chosen to compete directly in the overnight delivery mar- ket until 1982, largely because of the enormous cost of building an air fleet. But after going public UPS initiated an aggressive series of acquisitions, beginning with a Miami-based freight carrier operating in Latin America and a franchise-based chain of stores providing packing, shipping, and mail services called Mail Boxes Etc. (later renamed the UPS Store) with more than 4,300 domestic and international locations.

More assertive than ever before, the UPS of the new millennium was the product of extensive reengineering efforts and a revitalized business focus. While the company had traditionally been the industry’s low-cost provider, in recent years the company had been investing heavily in information technology, aircraft, and facilities to support service innovations, maintain quality, and reduce costs. In early 2003, the company revamped its logo for the first time since 1961, and emphasized its activities in the wider supply-chain industry. “The small-package market in the United States is about a $60-billion market. The worldwide supply-chain market is about a $3.2-trillion market,” said Mike Eskew, UPS’s chair and CEO. “It’s everything from the moment something gets made until it gets delivered for final delivery, and then after market, it’s parts replacement.”6

Case 4 The Battle for Value, 2004: FedEx Corp. vs. United Parcel Service, Inc. 57

5In setting its share price, the board considered a variety of factors, including past and current earnings, earnings estimates, the ratio of UPS’s common stock to its debt, the business and outlook of UPS, and the general economic climate. The opinions of outside advisers were sometimes considered. The stock price had never decreased in value. The employee stock purchases were often financed with stock hypothecation loans from commercial banks. As the shares provided the collateral for those loans, the assessment made by the outside lenders provided some external validation for the share price. 6Harry R. Weber, “UPS, FedEx Rivalry: A Study in Contrasts,” Associated Press Newswires, 21 May 2004.

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By 2003, UPS offered package-delivery services throughout the United States and in more than 200 countries and territories, and moved more than 13 million packages and documents through its network every day. Domestic package operations accounted for 76% of revenues in 2002; international (15%); nonpackage (9%). In the United States, it was estimated that the company’s delivery system carried goods having a value in excess of 6% of the U.S. gross domestic product.7 The company employed 360,000 people (of whom 64% were unionized), and owned 88,000 ground vehicles and 583 aircraft.

At year-end 2003, UPS reported assets, revenues, and profits of $28.9 billion, $33.4 billion, and $2.9 billion, respectively. Exhibit 3 provides UPS’s financial and analytical ratios. The company’s financial conservatism was reflected in its AAA bond rating.

Competition in the Express-Delivery Market The $45-billion domestic U.S. package-delivery market could be segmented along at least three dimensions: weight, mode of transit, and timeliness of service. The weight categories consisted of letters (weighing 0–2.0 pounds), packages (2.0–70 pounds), and freight (over 70 pounds). The mode of transit categories were simply air and ground. Finally, time categories were overnight, deferred delivery (second-day), three-day delivery, and, lastly, regular delivery, which occurred four or more days after pickup.

The air-express segment was a $25-billion portion of the U.S. package-delivery industry, and was concentrated in letters and packages, overnight and deferred, and air or air-and-ground. While virtually all of FedEx’s business activities were in the air-express segment of the package-delivery industry, only about 22% of UPS’s revenues were derived from its next-day air business. FedEx and UPS’s competition for dominance of the $25-billion domestic air-express delivery market foreshadowed an unusually challenging future.

Exhibit 4 provides a detailed summary of the major events marking the com- petitive rivalry between FedEx and UPS. Significant dimensions of this rivalry included the following:

• Customer focus. Both companies emphasized their focus on the customer. This meant listening carefully to the customer’s needs, providing customized solutions rather than standardized products, and committing to service relationships.

• Price competition. UPS boldly entered the market by undercutting the price of FedEx’s overnight letter by half. But by the late 1990s, both firms had settled into a predictable pattern of regular price increases. Exhibit 5 provides a summary of recent rate increases.

• Operational reengineering. Given the intense price competition, the reduction of unit costs became a priority. Cost reduction was achieved through the exploitation

58 Part One Setting Some Themes

7“United Parcel Service, Inc.– SWOT Analysis,” Datamonitor Company Profiles (16 July 2004).

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of economies of scale, investment in technology, and business-process reengineering, which sought to squeeze unnecessary steps and costs out of the service process.

• Information technology. Information management became central to the opera- tions of both UPS and FedEx. Every package handled by FedEx, for instance, was logged into COSMOS (Customer, Operations, Service, Master On-line System), which transmitted data from package movements, customer pickups, invoices, and deliveries to a central database at the Memphis, Tennessee, head- quarters. UPS relied on DIADs (Delivery Information Acquisition Devices), which were handheld units that drivers used to scan package barcodes and record customer signatures.

• Service expansion. FedEx and UPS increasingly pecked at each other’s service offerings. FedEx, armed with volume discounts and superb quality, went after the big clients that had previously used UPS without thought. UPS copied FedEx’s customer interfaces by installing 11,500 drop-off boxes to compete with FedEx’s 12,000 boxes, 165 drive-through stations, and 371 express-delivery stores. UPS also began Saturday pickups and deliveries to match FedEx’s schedule. FedEx bought $200 million in ground vehicles to match UPS.

• Logistics services. The largest innovations entailed offering integrated logistics services to large corporate clients. These services were aimed at providing total inventory control to customers, including purchase orders, receipt of goods, order entry and warehousing, inventory accounting, shipping, and accounts receivable. The London design-company Laura Ashley, for instance, retained FedEx to store, track, and ship products quickly to individual stores worldwide. Similarly, Dell Computer retained UPS to manage its total inbound and outbound shipping.

The impact of the fierce one-upmanship occurring between FedEx and UPS was clearly reflected in their respective investment expenditures. Between 1992 and 2003, capital expenditures for FedEx and UPS rose at an annualized rate of 34.64% and 36.78%, respectively. During this period, the two companies matched each other’s investments in capital almost exactly. (Exhibit 6 provides a graphical representation of the firms’ cumulative capital-investment expenditures.)

International Package-Delivery Market By 2004, express cargo aircraft carried nearly 50% of all international trade, measured by value.8 Yet throughout the 1990s, international delivery had remained only a small part of the revenues for UPS and FedEx. After making significant investments in devel- oping European delivery capabilities, FedEx eventually relinquished its hub in Europe in 1992 by selling its Brussels, Belgium, operation to DHL. Analysts estimated that FedEx had lost $1 billion in Europe since its entry there in 1984. FedEx would con- tinue to deliver to Europe, but relied on local partners. In 1995, FedEx expanded its routes in Latin America and the Caribbean, and later introduced FedEx AsiaOne, a

Case 4 The Battle for Value, 2004: FedEx Corp. vs. United Parcel Service, Inc. 59

8Alexandara Harney and Dan Roberts, “Comment & Analysis,” Financial Times, 9 August 2004.

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next-business-day service between Asian countries and the United States via a hub in Subic Bay, Philippines.

UPS did not break into the European market in earnest until 1988, with the acqui- sition of 10 European courier services. To enhance its international delivery systems, UPS created a system that coded and tracked packages and automatically billed customers for customs’ duties and taxes. UPS hoped that its international service would account for one-third of total revenue by 2000. In May 1995, it announced that it would spend more than $1 billion to expand its European operations during the next five years. Exhibit 7 presents international and domestic (U.S.) segment data for FedEx and UPS.

According to economic and industry experts, China would become the world’s second-largest economy within 11 years and the largest by 2039. It was already the world’s largest market for mobile phones and a key center for the production of textiles, computer chips, and other high-tech products. According to recent economic projections, inter-Asia trade was projected to grow at a rate of 16.8% annually through 2005.9

The overall market for air cargo in China had been growing at 30% a year and was expected to increase at nearly that pace for the next five years.10 FedEx and UPS focused primarily on the import/export package market and not the intra-China domestic market, using local partners to pick up and deliver parcels within the country (although, by December 2005, each company would be permitted to own completely package operations in China). One industry source believed the domestic parcel market was approximately $800 million, while China’s export-import market was nearly $1 billion. “As it becomes the workshop of the world,” one observer noted, “teeming factories along the Pearl and Yangtze river deltas represent both the start of the world’s supply chain and the source of some of its biggest transport bottlenecks.”11

The newly announced U.S.–China air-service agreement would allow an additional 195 weekly flights for each country—111 by all-cargo carriers and 84 by passenger airlines—resulting in a total of 249 weekly flights by the end of a six-year phase-in period. The two countries also agreed to allow their carriers to serve any city in the other country. Until that time, Chinese carriers were limited to twelve U.S. cities, and U.S. pas- senger carriers could fly to only five Chinese cities. The agreement also provided that when carriers established cargo hubs in the other country, they would be granted a high degree of operating flexibility. According to U.S. Transportation Secretary Norman Mineta, “This agreement represents a giant step forward in creating an international air-transportation system that meets the needs of the new global marketplace.”

UPS and FedEx both welcomed the news. “This provides an extraordinary oppor- tunity for strengthening commercial supply chains that support growing international trade between the United States and China and throughout the world,” said Mike Eskew, UPS chair and CEO, who added that the hub provision in the agreement would

60 Part One Setting Some Themes

9UPS press release, 4 November 2004. 10Morgan Stanley, 6 April 2004. 11Alexandara Harney and Dan Roberts, “Comment & Analysis,” Financial Times, 9 August 2004.

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facilitate that process. Fred Smith, chair and CEO of FedEx, said, “We think China is a huge opportunity for the company. We have significant expansion plans in the country, reflecting its fantastic growth and unique position as one of the world’s top manufacturing centers.”12

Performance Assessment Virtually all interested observers—customers, suppliers, investors, and employees— watched the competitive struggle between UPS and FedEx for hints about the next stage of the drama. The conventional wisdom was that if a firm were operationally excellent, strong financial performance would follow. Indeed, FedEx had set a goal of producing “superior financial returns,” while UPS targeted “a long-term competi- tive return.” Had the two firms achieved their goals? Moreover, did the trends in finan- cial performance suggest whether strong performance could be achieved in the future? In pursuit of the answers to those questions, the following exhibits afford several pos- sible avenues of analysis.

EPS, Market Values, and Returns Exhibit 8 presents the share prices, earnings per share (EPS), and price-earnings ratios for the two firms. Also included is the annual total return from holding each share (percentage gain in share price plus dividend yield). Some analysts questioned the appropriateness of using UPS’s fair market-value share price before the 1999 IPO, because it had been set by the board of directors rather than in an open market.

Ratio Analysis Exhibits 2 and 3 present a variety of analytical ratios computed from the financial statements of each firm.

Economic Profit (Economic Value Added, or EVA™) Analysis EVA reflects the value created or destroyed each year by deducting a charge for capital from the firm’s net operating profit after taxes (NOPAT).

The capital charge was determined by multiplying the cost of capital, K, by the capital employed in the business or operation. This computation could be done by either of two methods, both of which would yield the same answer; they are presented in the exhibits for the sake of illustration. The operating approach works with the asset side of the balance sheet, and computes NOPAT directly from the income state- ment. The capital approach works with the right-hand side of the balance sheet, and computes NOPAT indirectly (i.e., by adjusting net income).

! NOPAT " 1K # Capital2 EVA ! Operating profits " Capital charge

Case 4 The Battle for Value, 2004: FedEx Corp. vs. United Parcel Service, Inc. 61

12Dan Roberts, “FedEx Plans Expanded Services in China,” Financial Times, 23 June 2004.

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Estimating Capital Exhibits 9 and 10 calculate the actual amount of capital from both an operating and a capital approach. Included in capital are near-capital items that represent economic value employed on behalf of the firm, such as the present value of operating leases, amortized goodwill, and losses. The rationale for including losses and write-offs in continuing capital is that such losses represent unproductive assets or a failed investment. Were they excluded from the capital equation, the sum would only count successful efforts and would not accurately reflect the performance of the firm.

Estimating NOPAT Exhibits 9 and 10 calculate NOPAT with a similar regard for losses and write-offs. Here, the aim is to arrive at the actual cash generated by the concern. To do so, the exhibits add increases in deferred taxes back into income because it is not a cash expense, and calculate the interest expense of the leased oper- ating assets as if they were leased capital assets.

Estimating Cost of Capital The capital charge applied against NOPAT should be based on a blend of the costs of all the types of capital the firm employs, or the weighted-average cost of capital (WACC). The cost of debt (used for both debt and leases) is the annual rate consistent with each firm’s bond rating (BBB for FedEx and AAA for UPS). The cost of equity may be estimated in a variety of ways. In the analysis here, the capital asset pricing model (CAPM)13 was employed. FedEx’s beta and cost of equity are used in estimating FedEx’s cost of capital. Because UPS’s beta was unobservable, the analysis that follows uses the average annual betas for UPS’s publicly held peer firms: FedEx, Air Express, Airborne Freight, Roadway, Yellow Transport, and J.B. Hunt Transport.

Estimating EVA and MVA In Exhibits 9 and 10, the stock of capital and the flow of cash are used to calculate the actual return and, with the introduction of the WACC, to calculate the EVA. These exhibits present the EVA calculated each year and cumu- latively over time. The panel at the bottom of each exhibit estimates the market value created or destroyed (or the market value added [MVA]) over the observation period. MVA is calculated as the difference between the current market value of the company and its investment base. The market value created could be compared with cumula- tive EVA. In theory, the following relationships would hold:

Thus,

Market value ! Capital $ Present value of all future EVA

MVA ! Market value of debt and equity " Capital

MVA ! Present value of all future EVA

62 Part One Setting Some Themes

13The CAPM describes the cost of equity as the sum of the risk-free rate of return and a risk premium. The risk premium is the average risk premium for a large portfolio of stocks times the risk factor (beta) for the company. A beta equal to 1.0 suggests that the company is just as risky as the market portfolio; less than 1.0 suggests lower risk; greater than 1.0 implies greater risk.

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Case 4 The Battle for Value, 2004: FedEx Corp. vs. United Parcel Service, Inc. 63

In other words, maximizing the present value of EVA would amount to maxi- mizing the market value of the firm.

Outlook for FedEx and UPS About 70%14 of FedEx’s common shares were held by institutional investors that, it could be assumed, were instrumental in setting the prices for the company’s shares. Typically, those investors absorbed the thinking of the several securities analysts who followed FedEx and UPS in 2004. Exhibit 11 contains excerpts from various equity reports, which indicate the outlook held by those analysts.

Observers of the air-express package-delivery industry pondered the recent per- formance of the two leading firms and their prospects. What had been the impact of the intense competition between the two firms? Which firm was doing better? The companies faced a watershed moment with the dramatic liberalization of the oppor- tunities in China. Might their past performance contain clues about the prospects for future competition?

14Officers, directors, and employees of FedEx owned 7% of the shares; the remainder, about 23%, was owned by individual investors not affiliated with the company.

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64 Part One Setting Some Themes

EXHIBIT 1 | UPS and FedEx Price Patterns June 2003 to June 2004

Source of data: Datastream (case writer’s analysis).

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66

bru6171X_case04_053-074.qxd 11/24/12 2:27 PM Page 66

Case 4 The Battle for Value, 2004: FedEx Corp. vs. United Parcel Service, Inc. 67

EXHIBIT 4 | Timeline of Competitive Developments

FedEx Corp. United Parcel Service, Inc.

• Offers 10:30 A.M. delivery 1982 • Establishes next-day air service • Acquires Gelco Express and launches 1984

operations in Asia-Pacific • Establishes European hub in Brussels 1985 • Begins intercontinental air service

between United States and Europe • Introduces handheld barcode scanner 1986

to capture detailed package information • Offers warehouse services for IBM, 1987

National Semiconductor, Laura Ashley 1988 • Establishes UPS’s first air fleet

• Offers automated customs service • Acquires Tiger International to expand its 1989 • Expands international air service to 180

international presence countries • Wins Malcolm Baldrige National 1990 • Introduces 10:30 A.M. guarantee for

Quality Award next-day air 1991 • Begins Saturday delivery

• Offers electronic-signature tracking • Offers two-day delivery 1992 • Expands delivery to over 200 countries

1993 • Provides supply-chain solutions through UPS Logistics Group

• Launches Web site for package tracking 1994 • Launches Web site for package tracking • Acquires air routes serving China 1995 • Offers guaranteed 8 A.M. overnight delivery • Establishes Latin American division • Creates new hub at Roissy–Charles de 1999 • Makes UPS stock available through a public

Gaulle Airport in France offering • Launches business-to-consumer 2000 • Acquires all-cargo air service in Latin America

home-delivery service • Carries U.S. Postal Service packages 2001 • Acquires Mail Boxes Etc. retail franchise • Acquires American Freightways Corp. • Begins direct flights to China • Expands home delivery to cover 100% of 2002 • Offers guaranteed next-day home delivery

the U.S. population • Acquires Kinko’s retail franchise 2003 • Contracts with Yangtze River Express for • Establishes Chinese headquarters package delivery within China

• Reduces domestic ground-delivery time

bru6171X_case04_053-074.qxd 11/24/12 2:27 PM Page 67

EXHIBIT 6 | Cumulative Capital Expenditures for FedEx and UPS

Sources of data: Company regulatory filings.

19 92

19 93

19 94

19 95

19 96

19 97

19 98

19 99

20 00

20 01

20 02

20 03

B ill

io ns

(U S

$)

$25.0

$15.0

$20.0

$10.0

$ 5.0

$ 0.0

FedEx Corp

United Parcel Service

EXHIBIT 5 | Summary of Announced List-Rate Increases

UPS 1998 1999 2000 2001 2002 2003 2004 Average

Date implemented 2/8/02 2/9/03 2/8/04 2/6/05 1/8/06 1/7/07 1/6/08

UPS ground 3.6% 2.5% 3.1% 3.1% 3.5% 3.9% 1.9% 3.1% U.S. domestic air 3.3% 2.5% 3.5% 3.7% 4.0% 3.2% 2.9% 3.3% U.S. export 0.0% 0.0% 2.9% 2.9% 3.9% 2.9% 2.9% 2.2% Residential premium1 $1.00 $1.00 $1.00 $1.05 $1.10 $1.15 $1.40 Commercial premium2 N/A N/A N/A N/A N/A N/A $1.00

FedEx 1998 1999 2000 2001 2002 2003 2004 Average

Date implemented 2/16/02 2/9/03 2/2/04 2/2/05 1/8/06 1/7/07 1/6/08

FedEx ground 3.6% 2.5% 3.1% 3.1% 3.5% 3.9% 1.9% 3.1% U.S. domestic air 3.5% 2.8% 0.0% 4.9% 3.5% 3.5% 2.5% 3.0% U.S. export 0.0% 0.0% 0.0% 2.9% 3.5% 3.5% 2.5% 1.8% Residential premium-express2 N/A N/A N/A N/A $1.35 $1.40 $1.75 Residential premium-ground 2 N/A N/A N/A $1.30 $1.35 $1.40 $1.75 Residential premium-home delivery 2 N/A N/A N/A $1.05 $1.10 $1.15 $1.40 Commercial premium-express2 N/A N/A N/A N/A $1.50 $1.75 $1.00 Commercial premium-ground 2 N/A N/A N/A N/A N/A N/A $1.00

Sources of data: UPS, FedEx, and Morgan Stanley. 1The residential premium was an additional charge for deliveries of express letters and packages to residential addresses, a price distinction UPS had applied to residential ground deliveries for the previous 10 years to offset the higher cost of providing service to them. 2The commercial premium was applied to products shipped to remote locations and/or select zip codes.

68 Part One Setting Some Themes

bru6171X_case04_053-074.qxd 11/24/12 2:27 PM Page 68

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63 $1

5. 38

$2 0.

00 $6

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$5 8.

75 $5

4. 50

$6 3.

08 $7

4. 55

D iv

id en

ds p

er s

ha re

1 $0

.2 5

$0 .2

5 $0

.2 8

$0 .3

2 $0

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$0 .3

5 $0

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$0 .5

8 $0

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$0 .7

6 $0

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P S

, b as

ic in

cl .

ex tr

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m s1

$0 .4

4 $0

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$0 .8

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$1 .0

0 $0

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$1 .5

9 $0

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$2 .5

4 $2

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$2 .8

4 $2

.5 7

P /E

m ul

tip le

21 .2

6 14

.8 2

14 .4

2 14

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14 .5

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12 .5

8 87

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23 .1

3 25

.5 9

22 .2

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pp re

ci at

io n

12 .1

6% 13

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11 .7

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5. 13

% 30

.0 8%

24 5.

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(1 4.

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) (7

.2 3%

) 15

.7 4%

18 .1

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um ul

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po un

d an

nu al

r et

ur n2

12 .1

6% 27

.0 3%

41 .8

9% 58

.1 1%

66 .2

2% 11

6. 22

% 64

5. 95

% 53

5. 14

% 48

9. 19

% 58

1. 95

% 70

5. 95

%

Fe dE

x C

or p.

19 92

19 93

19 94

19 95

19 96

19 97

19 98

19 99

20 00

20 01

20 02

20 03

S to

ck p

ric e,

D ec

em be

r 31

$1 0.

19 $1

2. 25

$1 9.

13 $1

4. 97

$1 9.

16 $2

6. 19

$3 2.

06 $5

4. 81

$3 5.

50 $4

0. 00

$5 3.

95 $6

3. 98

D iv

id en

ds p

er s

ha re

$0 .0

0 $0

.0 0

$0 .0

0 $0

.0 0

$0 .0

0 $0

.0 0

$0 .0

0 $0

.0 0

$0 .0

0 $0

.0 0

$0 .0

0 $0

.2 0

E P

S , b

as ic

in cl

. e xt

ra it

em s

($ 0.

53 )

$0 .2

5 $0

.9 1

$1 .3

2 $1

.3 5

$1 .5

6 $1

.7 2

$2 .1

3 $2

.3 6

$2 .0

2 $2

.3 8

$2 .7

9 P

/E m

ul tip

le nm

f 50

.0 0

20 .9

6 11

.3 6

14 .2

2 16

.7 9

18 .7

0 25

.7 3

15 .0

4 19

.8 0

22 .6

7 22

.9 3

C ap

ita l a

pp re

ci at

io n

20 .2

5% 56

.1 2%

(2 1.

73 %

) 27

.9 7%

36 .7

0% 22

.4 3%

70 .9

6% (3

5. 23

% )

12 .6

8% 34

.8 8%

18 .5

9% C

um ul

. c om

po un

d an

nu al

r et

ur n2

20 .2

5% 87

.7 3%

46 .9

3% 88

.0 4%

15 7.

06 %

21 4.

72 %

43 8.

04 %

24 8.

47 %

29 2.

64 %

42 9.

57 %

52 8.

02 %

S ta

nd ar

d &

P oo

r’ s

50 0

In de

x 19

92 19

93 19

94 19

95 19

96 19

97 19

98 19

99 20

00 20

01 20

02 20

03

In de

x le

ve l

43 5.

71 46

6. 45

45 9.

27 61

5. 93

74 0.

74 97

0. 43

1, 22

9. 23

1, 46

9. 25

1, 32

0. 28

1, 14

8. 08

87 9.

82 1,

11 1.

92 A

nn ua

l r et

ur n

7. 06

% (1

.5 4%

) 34

.1 1%

20 .2

6% 31

.0 1%

26 .6

7% 19

.5 3%

(1 0.

14 %

) (1

3. 04

% )

(2 3.

37 %

) 26

.3 8%

C um

ul . c

om po

un d

an nu

al r

et ur

n2 7.

06 %

5. 41

% 41

.3 6%

70 .0

1% 12

2. 72

% 18

2. 12

% 23

7. 21

% 20

3. 02

% 16

3. 50

% 10

1. 93

% 15

5. 20

%

C um

ul . M

ar ke

t- A

dj us

te d

R et

ur ns

19 93

19 94

19 95

19 96

19 97

19 98

19 99

20 00

20 01

20 02

20 03

U P

S 5.

11 %

21 .6

2% 0.

53 %

(1 1.

90 %

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6. 51

% )

(6 5.

90 %

) 40

8. 74

% 33

2. 12

% 32

5. 69

% 48

0. 02

% 55

0. 75

%

F ed

E x

13 .1

9% 82

.3 2%

5. 57

% 18

.0 3%

34 .3

3% 32

.6 0%

20 0.

83 %

45 .4

5% 12

9. 14

% 32

7. 64

% 37

2. 83

%

S ou

rc e

of d

at a:

S ta

nd ar

d &

P oo

r’s R

es ea

rc h

In si

gh t,

an nu

al r

ep or

ts .

1 T

he se

d at

a ha

ve b

ee n

ad ju

st ed

fo r

th e

tw o-

fo r-

on e

st oc

k sp

lit a

nd in

iti al

p ub

lic o

ffe rin

g co

m pl

et ed

b y

U P

S in

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em be

r 19

99 . P

rio r

to 1

99 9,

U P

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ha re

s w

er e

no t p

ub lic

ly tr

ad ed

a nd

th e

co m

pa ny

a ct

ed a

s a

m ar

ke t-

m ak

er fo

r its

o w

n st

oc k.

2 C

om po

un d

an nu

al r

et ur

n ca

lc ul

at io

n: (

C ur

re nt

y ea

r pr

ic e–

B eg

in ni

ng y

ea r

pr ic

e) /B

eg in

ni ng

y ea

r pr

ic e.

bru6171X_case04_053-074.qxd 11/24/12 2:27 PM Page 70

71

E X

H IB

IT 9

| E

co no

m ic

P ro

fit A

na ly

si s

fo r

Fe dE

x

Fe dE

x C

or p.

19 92

19 93

19 94

19 95

19 96

19 97

19 98

19 99

20 00

20 01

20 02

20 03

R et

ur n

on N

et A

ss et

s (R

O N

A )

N et

o pe

ra tin

g pr

ofi t a

fte r

ta x

($ m

m )

$1 87

$1 76

$3 63

$4 05

$4 19

$4 99

$7 27

$7 26

$8 66

$7 50

$8 81

$1 ,4

18 B

eg in

ni ng

c ap

ita l (

$m m

) $4

,0 78

$4 ,3

44 $4

,4 56

$4 ,6

55 $5

,0 81

$5 ,6

63 $6

,8 82

$7 ,8

63 $8

,6 36

$1 0,

09 0

$1 0,

87 0

$1 2,

05 0

R O

N A

(N O

P A

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eg in

ni ng

c ap

ita l)

4. 59

% 4.

05 %

8. 16

% 8.

70 %

8. 25

% 8.

82 %

10 .5

6% 9.

23 %

10 .0

3% 7.

43 %

8. 10

% 11

.7 7%

W ei

gh te

d- A

ve ra

ge C

os t o

f C

ap ita

l ( W

A C

C )

Lo ng

-t er

m d

eb t (

$m m

) $1

,7 98

$1 ,8

82 $1

,6 32

$1 ,3

25 $1

,3 25

$1 ,3

98 $1

,3 85

$1 ,3

60 $1

,7 76

$1 ,9

00 $1

,8 00

$1 ,7

09 S

ha re

s ou

ts ta

nd in

g (m

m )

21 6

21 9

22 4

22 5

22 8

23 0

29 5

29 8

28 4

29 7

29 8

29 9

S ha

re p

ric e

($ )

$1 0

$1 2

$1 9

$1 5

$1 9

$2 6

$3 2

$5 5

$3 6

$4 0

$5 4

$6 4

M ar

ke t v

al ue

o f e

qu ity

( $m

m )

$2 ,2

05 $2

,6 82

$4 ,2

74 $3

,3 63

$4 ,3

59 $6

,0 18

$9 ,4

53 $1

6, 33

3 $1

0, 09

8 $1

1, 89

3 $1

6, 08

7 $1

9, 10

4 T

ax r

at e

(% )

23 %

46 %

46 %

43 %

43 %

43 %

45 %

41 %

39 %

37 %

38 %

38 %

Lo ng

-t er

m U

.S . g

ov ’t.

b on

ds (

% )

7. 97

% 6.

80 %

7. 53

% 7.

01 %

7. 07

% 6.

89 %

5. 94

% 5.

79 %

6. 19

% 5.

65 %

5. 55

% 4.

76 %

S en

io r

B aa

-r at

ed d

eb t (

% )

9. 20

% 8.

11 %

8. 71

% 8.

27 %

8. 46

% 8.

16 %

7. 33

% 7.

69 %

8. 87

% 7.

94 %

7. 96

% 6.

58 %

R is

k pr

em iu

m (

% )

5. 6%

5. 6%

5. 6%

5. 6%

5. 6%

5. 6%

5. 6%

5. 6%

5. 6%

5. 6%

5. 6%

5. 6%

B et

a 1.

10 1.

15 1.

20 1.

20 1.

40 1.

35 1.

30 1.

15 1.

20 1.

20 1.

20 1.

10 C

os t o

f e qu

ity 1 (%

) 14

.1 3%

13 .2

4% 14

.2 5%

13 .7

3% 14

.9 1%

14 .4

5% 13

.2 2%

12 .2

3% 12

.9 1%

12 .3

7% 12

.2 7%

10 .9

2% W

A C

C 10

.9 9%

9. 72

% 11

.6 1%

11 .1

8% 12

.5 6%

12 .6

1% 12

.0 5%

11 .6

4% 11

.7 9%

11 .3

5% 11

.5 3%

10 .3

6%

E co

no m

ic V

al ue

A dd

ed (E

V A

) R

O N

A (

N O

P A

T /b

eg in

ni ng

c ap

ita l)

4. 59

% 4.

05 %

8. 16

% 8.

70 %

8. 25

% 8.

82 %

10 .5

6% 9.

23 %

10 .0

3% 7.

43 %

8. 10

% 11

.7 7%

W A

C C

10 .9

9% 9.

72 %

11 .6

1% 11

.1 8%

12 .5

6% 12

.6 1%

12 .0

5% 11

.6 4%

11 .7

9% 11

.3 5%

11 .5

3% 10

.3 6%

S pr

ea d

(6 .3

9% )

(5 .6

7% )

(3 .4

6% )

(2 .4

8% )

(4 .3

0% )

(3 .7

9% )

(1 .4

8% )

(2 .4

1% )

(1 .7

5% )

(3 .9

2% )

(3 .4

3% )

1. 41

% X

b eg

in ni

ng c

ap ita

l ( $m

m )

$4 ,0

78 $4

,3 44

$4 ,4

56 $4

,6 55

$5 ,0

81 $5

,6 63

$6 ,8

82 $7

,8 63

$8 ,6

36 $1

0, 09

0 $1

0, 87

0 $1

2, 05

0

E V

A (a

nn ua

l) ($

26 1)

($ 24

6) ($

15 4)

($ 11

5) ($

21 9)

($ 21

5) ($

10 2)

($ 19

0) ($

15 1)

($ 39

6) ($

37 3)

$1 70

E V

A (c

um ul

at iv

e) ($

26 1)

($ 50

7) ($

66 1)

($ 77

7) ($

99 5)

($ 1,

21 0)

($ 1,

31 2)

($ 1,

50 2)

($ 1,

65 3)

($ 2,

04 9)

($ 2,

42 2)

($ 2,

25 2)

M ar

ke t V

al ue

A dd

ed (M

V A

) M

ar ke

t v al

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f e qu

ity (

$m m

) $2

,2 05

$2 ,6

82 $4

,2 74

$3 ,3

63 $4

,3 59

$6 ,0

18 $9

,4 53

$1 6,

33 3

$1 0,

09 8

$1 1,

89 3

$1 6,

08 7

$1 9,

10 4

Lo ng

-t er

m d

eb t (

$m m

) 1,

79 8

1, 88

2 1,

63 2

1, 32

5 1,

32 5

1, 39

8 1,

38 5

1, 36

0 1,

77 6

1, 90

0 1,

80 0

1, 70

9

C ap

ita l (

m ar

ke t v

al ue

) ($

m m

) 4,

00 2

4, 56

5 5,

90 7

4, 68

7 5,

68 4

7, 41

6 10

,8 38

17 ,6

93 11

,8 74

13 ,7

93 17

,8 87

20 ,8

13

B oo

k va

lu e

of e

qu ity

( $m

m )

1, 58

0 1,

67 1

1, 92

5 2,

24 6

2, 57

6 2,

96 3

3, 96

1 4,

66 4

4, 78

5 5,

90 0

6, 54

5 7,

28 8

Lo ng

-t er

m d

eb t (

$m m

) 1,

79 8

1, 88

2 1,

63 2

1, 32

5 1,

32 5

1, 39

8 1,

38 5

1, 36

0 1,

77 6

1, 90

0 1,

80 0

1, 70

9

C ap

ita l (

bo ok

v al

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($ m

m )

3, 37

8 3,

55 4

3, 55

7 3,

57 0

3, 90

1 4,

36 0

5, 34

6 6,

02 3

6, 56

1 7,

80 1

8, 34

5 8,

99 7

M V

A (m

ar ke

t v al

ue -

b oo

k va

lu e)

$6 25

$1 ,0

11 $2

,3 50

$1 ,1

17 $1

,7 83

$3 ,0

56 $5

,4 92

$1 1,

67 0

$5 ,3

13 $5

,9 93

$9 ,5

42 $1

1, 81

6

S ou

rc es

o f d

at a:

V al

ue L

in e

In ve

st m

en t S

ur ve

y, S

ta nd

ar d

& P

oo r’s

R es

ea rc

h In

si gh

t, B

lo om

be rg

L P

, D at

as tr

ea m

. 1 T

he c

os t o

f e qu

ity w

as d

er iv

ed u

si ng

th e

ca pi

ta l a

ss et

p ric

in g

m od

el (

C A

P M

).

bru6171X_case04_053-074.qxd 11/24/12 2:27 PM Page 71

72

E X

H IB

IT 1

0 |

E co

no m

ic P

ro fit

A na

ly si

s fo

r U

P S

U ni

te d

P ar

ce l S

er vi

ce , I

nc .

19 92

19 93

19 94

19 95

19 96

19 97

19 98

19 99

20 00

20 01

20 02

20 03

R et

ur n

on N

et A

ss et

s (R

O N

A )

N et

o pe

ra tin

g pr

ofi t a

fte r

ta x

($ m

m )

$9 14

$8 88

$9 44

$1 ,4

48 $1

,5 45

$1 ,3

79 $1

,9 09

$3 ,2

15 $2

,9 55

$2 ,8

46 $2

,5 89

$3 ,3

09 B

eg in

ni ng

c ap

ita l (

$m m

) $6

,9 32

$7 ,1

95 $8

,2 80

$9 ,6

79 $1

1, 79

6 $1

2, 51

4 $1

3, 35

0 $1

8, 84

5 $1

7, 16

1 $2

0, 00

7 $2

0, 80

2 $2

3, 39

1 R

O N

A (N

O P

A T

/b eg

in ni

ng c

ap ita

l) 13

.1 9%

12 .3

4% 11

.4 0%

14 .9

6% 13

.1 0%

11 .0

2% 14

.3 0%

17 .0

6% 17

.2 2%

14 .2

3% 12

.4 5%

14 .1

5%

W ei

gh te

d- A

ve ra

ge C

os t o

f C ap

ita l(

W A

C C

) Lo

ng -t

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d eb

t ( $m

m )

$8 62

$8 52

$1 ,1

27 $1

,7 29

$2 ,5

73 $2

,5 83

$2 ,1

91 $1

,9 12

$2 ,9

81 $4

,6 48

$3 ,4

95 $3

,1 49

S ha

re s

ou ts

ta nd

in g1

(m m

) 1,

19 0

1, 16

0 1,

16 0

1, 14

0 1,

14 0

1, 12

4 1,

09 5

1, 21

1 1,

13 5

1, 12

1 1,

12 3

1, 12

9 S

ha re

p ric

e1 ($

) $9

$1 0

$1 2

$1 3

$1 5

$1 5

$2 0

$6 9

$5 9

$5 5

$6 3

$7 5

M ar

ke t v

al ue

o f e

qu ity

1 ($

m m

) $1

1, 00

8 $1

2, 03

5 $1

3, 63

0 $1

4, 96

3 $1

6, 67

3 $1

7, 28

2 $2

1, 89

6 $8

3, 53

8 $6

6, 66

3 $6

1, 06

8 $7

0, 83

9 $8

4, 16

7 T

ax r

at e

(% )

40 %

43 %

40 %

39 %

40 %

41 %

40 %

58 %

39 %

38 %

35 %

34 %

Lo ng

-t er

m U

.S . g

ov ’t.

b on

ds (

% )

7. 97

% 6.

80 %

7. 53

% 7.

01 %

7. 07

% 6.

89 %

5. 94

% 5.

79 %

6. 19

% 5.

65 %

5. 55

% 4.

76 %

S en

io r

B aa

-r at

ed d

eb t (

% )

8. 34

% 7.

36 %

8. 08

% 7.

71 %

7. 78

% 7.

53 %

6. 71

% 6.

90 %

7. 99

% 7.

16 %

6. 66

% 5.

47 %

R is

k pr

em iu

m (

% )

5. 6%

5. 6%

5. 6%

5. 6%

5. 6%

5. 6%

5. 6%

5. 6%

5. 6%

5. 6%

5. 6%

5. 6%

B et

a2 1.

24 1.

13 1.

16 1.

18 1.

18 1.

14 1.

08 1.

15 1.

11 1.

09 0.

95 0.

80 C

os t o

f e qu

ity 3 (%

) 14

.9 2%

13 .1

5% 14

.0 2%

13 .6

4% 13

.6 8%

13 .2

7% 11

.9 9%

12 .2

3% 12

.4 1%

11 .7

5% 10

.8 7%

9. 24

% W

A C

C 14

.2 0%

12 .5

8% 13

.3 2%

12 .7

2% 12

.4 7%

12 .1

2% 11

.2 6%

12 .0

2% 12

.0 9%

11 .2

3% 10

.5 6%

9. 04

%

E co

no m

ic V

al ue

A dd

ed (E

V A

) R

O N

A (

N O

P A

T /b

eg in

ni ng

c ap

ita l)

13 .1

9% 12

.3 4%

11 .4

0% 14

.9 6%

13 .1

0% 11

.0 2%

14 .3

0% 17

.0 6%

17 .2

2% 14

.2 3%

12 .4

5% 14

.1 5%

W A

C C

14 .2

0% 12

.5 8%

13 .3

2% 12

.7 2%

12 .4

7% 12

.1 2%

11 .2

6% 12

.0 2%

12 .0

9% 11

.2 3%

10 .5

6% 9.

04 %

S pr

ea d

(1 .0

1% )

(0 .2

4% )

(1 .9

1% )

2. 24

% 0.

63 %

(1 .1

0% )

3. 04

% 5.

04 %

5. 13

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Case 4 The Battle for Value, 2004: FedEx Corp. vs. United Parcel Service, Inc. 73

Morgan Stanley’s J.J. Valentine, April 6, 2004

Value Line Investment Survey’s W.R. Perkowitz Jr., Dec. 12, 2003

It was refreshing to hear FedEx’s management highlight some of the risks in China as we sense these issues are too often overlooked by the bulls. Some of these issues include:

• lack of legal framework • different interpretations of laws by regional and local governments • nonperforming loans that put pressure on China’s banking sector • liability by government for retirement program of state-owned enterprises • widening gap between the urban and the rural standard of living • government that often dictates commercial relationships

One issue that’s not as much a risk as it is a challenge is finding skilled, educated labor. This was a recurring theme that we heard during our visit to Asia, namely that China has a large unskilled workforce to produce cheap products, but it is becoming increasingly difficult to find skilled labor for the service industry, such as parcel delivery or logistics.

The international business should drive long-term growth. Unlike the domestic express business, which has reached maturity, the international market remains in the growth stage. Indeed, growth rates in this sector mirror the rate of domestic expansion in the late 1980s. Furthermore, demand for this service should rise going forward, as a greater amount of manufacturing capacity is outsourced to Asia. Finally, since a large portion of FedEx’s cost structure is fixed, and it has ample capacity to serve additional business, any increases in volume should flow directly to the bottom line.

EXHIBIT 11 | Equity Analysts’ Outlook for FedEx and UPS

FedEx Corporation

Analyst Comments

Value Line Investment Survey’s D.Y. Fung, Dec. 12, 2003

United Parcel Service’s third-quarter 2003 results were better than we expected. . . . This gain was driven by record-breaking results in the international and nonpackage segments. Indeed, both units experienced advances in volume and margins, which led to bottom-line increases of 171% and 61% respectively. Importantly, growth of these two businesses has resulted in greater earnings diversity at UPS. This has helped to protect investors from the cyclical downturn in the U.S. economy in the past two years. Going forward, we believe international and nonpackage will continue along their posi- tive growth trajectory, while generating a higher portion of the company’s net earnings.

United Parcel Service Inc.

Analyst Comments

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Genzyme and Relational Investors: Science and Business Collide?

For Marblehead Neck, Massachusetts, it was an unusually warm morning in April 2009, so Henri Termeer decided to take a leisurely walk on the beach. Termeer had some serious issues to consider and often found that the fresh sea air and solitude did wonders for his thought process. For more than 20 years, Termeer had been the chair- man and CEO of Genzyme Corporation, based in Cambridge, Massachusetts. Under his watch, Genzyme had grown from an entrepreneurial venture into one of the coun- try’s top-five biotechnology firms (Exhibit 1 shows Genzyme’s financial statements).

There were bumps along the way accompanying Termeer’s achievements, and a recent event was one of them. The week before, Termeer had sat in a presentation by Ralph Whitworth, cofounder and principal of a large activist investment fund, Relational Investors (RI). Whitworth’s company now had a 2.6% stake1 in Genzyme (Exhibit 2 shows Genzyme’s top 10 shareholders). Whitworth had a history of engagements with the board of directors of numerous companies, and in several instances, the CEO had been forced to resign. In January, when RI had announced its initial 1% investment in Termeer’s company, the two men had met for a meeting at the JP Morgan Healthcare Conference, and the discussion had been amicable. Whitworth and his team then trav- eled in April to Genzyme’s headquarters and talked about Genzyme’s core business, value creation, and the lack of transparency in some of the company’s communications.

Termeer was proud of his company’s accomplishments, shown by the number of peo- ple with rare diseases who had been successfully treated with Genzyme’s products. He was also pleased with the long-term growth in the price of Genzyme’s stock, which had easily outperformed the market over the last several years. In fact, the company had just

75

5CASE

1Relational Investors Form 13F, March 31, 2009.

This case was prepared by Rick Green under the supervision of Professors Kenneth Eades and Pedro Matos. It was written as a basis for class discussion rather than to illustrate effective or ineffective handling of an administrative situation. Copyright 2011 by the University of Virginia Darden School Foundation, Charlottesville, VA. All rights reserved. To order copies, send an e-mail to [email protected] No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or trans- mitted in any form or by any means ––electronic, mechanical, photocopying, recording, or otherwise–– without the permission of the Darden School Foundation.

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76 Part One Setting Some Themes

posted record revenues of $4.6 billion for 2008. Although the 2007–08 financial crisis had affected the stock market overall, Genzyme, along with the biotechnology industry, was faring better than most (see Exhibit 3 for charts on Genzyme’s stock performance).

But a bigger blow came about a month after Termeer’s first introduction to Whitworth. An operational problem surfaced in the company’s plant in Allston, Massachusetts, followed by an official warning letter from the U.S. Food and Drug Administration (FDA) on February 27, 2009. The company responded to the FDA by publicly disclosing its manufacturing issues. Genzyme began conducting a quality assessment of its system, and Whitworth had expressed his confidence in the com- pany’s actions to address the issues. Recent news on the impending health care reform bill also hit companies in the health care sector hard. Genzyme’s stock price, which had declined by 21% over five trading days, had yet to recover.

On top of handling Whitworth’s demands, Termeer had to prepare for the share- holders’ annual meeting scheduled for May 21. As Termeer mulled over the sequence of past events, the name of Whitworth’s RI fund suggested to him that relationship building was its modus operandi and that perhaps Whitworth genuinely wanted to help Genzyme increase its performance. Up to this time, Termeer had not considered RI to be a threat, but if there were other corporate activists or hedge funds monitoring his company and looking to set its corporate policy, then maybe he should take note that Genzyme now had an “activist” investor. What should he do?

Biotechnology Cheeses, beer, and wine have at least one thing in common: the application of bio- logical science in the form of bacteria processing. The use of living organisms to stim- ulate chemical reactions had been taking place for thousands of years. But since the mid-20th century, when revolutionary research in genetics led to the description of the structure of DNA, molecular biology had been transformed into a thriving industry. Products among the 1,200-plus biotechnology companies in 2008 included innova- tions in the treatment of multiple sclerosis, rheumatoid arthritis, cancer, autoimmune disorders, and diabetes.

Biotechnology drugs were normally far more complex to produce than the chemical-based blockbuster drugs developed by Big Pharma companies. The U.S. Supreme Court recognized patent rights on genetically altered life forms in the early 1980s, and the U.S. Congress passed the Orphan Drug Act in 1983. Intended to attract investment for research and development (R&D) in the treatment of rare diseases (those affecting less than 200,000 people), the act gave companies that brought successful drugs to market a seven-year monopoly on sales.2

This exclusive sales incentive was not a free lunch, however; its purpose was to offset the numerous uncertainties in biotechnology development. Many of these uncer- tainties pertained to the U.S. drug approval process itself, one of the most rigorous in the world. In addition to the extremely high cost of R&D, a lengthy process was required to get new products to market. After a particular disease was targeted, its treat- ment went through a series of chemical tests to determine therapeutic effectiveness and

2Steven Silver, “Biotechnology,” Standard and Poor’s Industry Surveys (August 19, 2010): 9.

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Case 5 Genzyme and Relational Investors: Science and Business Collide? 77

to uncover potential side effects. Preclinical studies were then done by testing animals over a period of years. Only then could the company submit an investigational new drug application to the FDA to begin clinical testing on humans.

Clinical trials on humans consisted of three phases: (1) testing the drug’s safety by giving small doses to relatively healthy people; (2) administering the drug to patients suffering from the targeted disease or condition; and (3) employing random double-blind tests to eliminate bias in the process. Typically, one group of patients was given the potential drug, and the other group was given an inert substance or placebo. Due to the rigorous nature of the clinical trials, only about 5% to 10% of drugs that reached the testing stage ultimately received approval for marketing.3 Not surprisingly, the biotechnology industry’s R&D spending as a percentage of revenues was among the highest of any U.S. industry group.

The level of R&D expenditures made it crucial to get new drugs to market quickly. The FDA’s Center for Drug Evaluation and Research was responsible for reviewing therapeutic biological products and chemical-based drugs. Unfortunately, inadequate funding and staffing of the FDA resulted in missed deadlines and a low level of final approvals. In 2008, the regulator approved 24 new drugs, out of which only six were biologic.4 By 2009, it was estimated that, on average, new products took more than eight years to get through the clinical development and regulatory process.

The industry weathered the financial storms in 2007–08 relatively well, as demand for biotechnology products depended more on the population’s health than the econ- omy (see Exhibit 4 for financial metrics for Genzyme and its major competitors). This was particularly true for large-cap companies with strong cash flows that did not need to access capital markets. Of more importance to some industry observers was that strong biotechnology companies might come under increased merger and acquisition (M&A) pressure from Big Pharma because these companies faced patent expirations on key blockbuster drugs in the coming years.5

Genzyme Corporation Henry Blair, a Tufts University scientist, and Sheridan Snyder founded Genzyme in 1981 to develop products based on enzyme technologies.6 Using venture capital funding, they purchased a small company, Whatman Biochemicals Ltd., which was absorbed into Genzyme. In 1983 (the same year that the Orphan Drug Act was passed), they recruited Henri Termeer to be president, joining the other 10 employees. Termeer had spent the previous 10 years with Baxter Travenol (later Baxter Interna- tional), including several years running its German subsidiary. He left his lucrative position at Baxter to join the start-up. Shortly after Termeer became CEO, Genzyme raised $28.5 million in its 1986 IPO and began trading on the NASDAQ (ticker: GENZ).

3Silver, 6. 4Silver, 5. 5Silver, 9. 6An enzyme is basically one of a number of proteins produced by the body that functions as a catalyst for a biochemical process.

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78 Part One Setting Some Themes

An accidental meeting between Termeer and a former Baxter colleague turned into a masterful acquisition for Genzyme. On a return flight from Chicago to Boston in 1989, Termeer and Robert Carpenter, chairman and CEO of Integrated Genetics (IG), based in Framingham, Massachusetts, discussed the businesses and finances of the two companies. Several months later, Genzyme purchased IG with its own stock for the equivalent of $31.5 million or less than $3 per share. Overnight Genzyme’s expertise received a considerable boost in several areas of biotechnology: molecular biology, protein and nuclear acid chemistry, and enzymology.7 Carpenter served as executive vice president of Genzyme for the next two years and was elected to the board of directors in 1994 (Exhibit 5 lists Genzyme board members).

Avoiding the glamorous blockbuster drug industry, Termeer established Gen- zyme’s footprint in the treatment of genetic disorders. His goal was to create targeted drugs to completely cure these diseases, despite the statistically small populations that were afflicted. In the company’s formative years, Termeer focused R&D on lysoso- mal storage disorders (LSDs). Commonalities among LSD patients were inherited life- threatening enzyme deficiencies that allowed the buildup of harmful substances. Cures were aimed at creating the genetic material to generate the deficient enzymes natu- rally in these patients.

Genzyme’s most rewarding product was the first effective long-term enzyme replacement therapy for patients with a confirmed diagnosis of Type I Gaucher’s disease. This inherited disease was caused by deficiency of an enzyme necessary for the body to metabolize certain fatty substances. The deficiency produced several crippling con- ditions such as bone disease, enlarged liver or spleen, anemia, or thrombocytopenia (low blood platelet count).

Initially, the product was known as Ceredase and received a great deal of atten- tion for its life-saving treatment. It was approved by the FDA in 1991 and protected by the Orphan Drug Act, but its success was not without controversy. The price for Ceredase was $150,000 per patient, per year, making it one of the most expensive drugs sold at the time. Genzyme argued that the price reflected the extraordinary expense of production; a year’s supply for a single patient required enzyme extrac- tion from approximately 20,000 protein-rich placentas drawn from a multitude of hos- pitals around the world.8 By 1994, however, Genzyme’s laboratories had developed Cerezyme, a genetically engineered replacement for Ceredase that was administered via intravenous infusion. Cerezyme was approved by the FDA in 1995 and also qual- ified for protection under the Orphan Drug Act.

Further successes against LSDs included Fabrazyme (to treat Fabry disease) and Myozyme (to treat Pompe disease). Fabry disease was caused by GL-3, a substance in cells lining the blood vessels of the kidney. Pompe disease shrank a patient’s mus- cles, eventually affecting the lungs and heart. These two drugs, along with Cerezyme, formed the core business of the company and were developed and sold by its genetic disease segment (GD).

7Bruce P. Montgomery, updated by Steven Meyer and Jeffrey L. Covell, “Genzyme Corporation,” Interna- tional Directory of Company Histories, ed. Jay P. Pederson, 77 (Detroit: St. James Press), 165. 8Montgomery, 166.

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Case 5 Genzyme and Relational Investors: Science and Business Collide? 79

Termeer was particularly proud of Genzyme’s scientific team for developing Myozyme. Pompe disease was a debilitating illness that affected both infants and adults. The symptoms for adults included a gradual loss of muscle strength and ability to breathe. Depending on the individual, the rate of decline varied, but patients even- tually needed a wheelchair and ultimately died prematurely most often because of res- piratory failure. The symptoms were similar for infants, but progressed at a faster rate, so death from cardiac or respiratory failure occurred within the first year of life. The first human trials for Myozyme were conducted on a small sample of newborns and resulted in 100% of the infants surviving their first year. This success was so dramatic that the European regulators approved the drug for infants and for adults.

Concurrent with the company’s focus on genetic disorders, it also invested in the development of hyaluronic acid-based drugs to reduce the formation of postoperative adhesions. Initially, it raised funds in 1989 through a secondary stock offering and an R&D limited partnership. The research the company conducted was significantly advanced by the acquisition of Biomatrix, Inc., in 2000, forming the biosurgery segment (BI).

Termeer also searched for nascent biotechnology research companies that had good products but limited capital or marketing capabilities. As a result, he created numerous alliances and joint ventures, providing funding in exchange for a share of future revenue streams. As one example, Genzyme formed a joint venture in 1997 with GelTex Pharmaceuticals, which specialized in the treatment of conditions in the gastrointestinal tract. GelTex’s first drug, RenaGel, bound dietary phosphates in patients with chronic kidney dysfunction.

After 1997, Termeer completed a host of acquisitions. To some extent, the oppor- tunity for these acquisitions resulted from the economic woes of other biotechnology firms whose clinical failures affected their funding abilities, resulting in research cuts and layoffs. Smaller start-up firms were vulnerable to economic stress if their flag- ship drug failed to succeed in time. These conditions suited Termeer, who had begun a broad strategy to diversify. But his strategy was not without risks because even drugs acquired in late-stage development had not yet been approved by the FDA.

Many of Genzyme’s acquisitions were new drugs in various stages of develop- ment (Exhibit 6 shows Genzyme’s major acquisitions). They were generally consid- ered to be incomplete biotechnologies that required additional research, development, and testing before reaching technological feasibility. Given the risk that eventual reg- ulatory approval might not be obtained, the technology may not have been considered to have any alternative future use. In those cases, Genzyme calculated the fair value of the technology and expensed it on the acquisition date as in-process research and development (IPR&D).

Over time, Genzyme reorganized or added business segments based on its own R&D results and the addition of acquired firms. By December 2008, the company was organized into four major segments: GD, cardiometabolic and renal (CR), BI, and hematologic oncology (HO). (Exhibit 7 displays segment product offerings and the fraction of 2008 revenues generated by each product).

In its presentation, RI had analyzed the performance of Genzyme’s business segments using a metric called cash flow return on investment or CFROI. The idea was

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to quantify the profit generated with respect to the capital that was invested in each busi- ness line (Exhibit 8 shows the CFROI estimates by RI for 2008). Termeer asked Gen- zyme’s CFO to review the analysis. He believed the performance of the GD division was correct, but he was not sure about the low performance of the other segments.

The goal of Termeer’s diversification strategy was to create solutions for curing more common diseases and to broaden the groups of patients who benefited.9 Termeer was also a member of the board of directors of Project HOPE, an international non- profit health education and humanitarian assistance organization. Through a partner- ship with Project HOPE, Genzyme provided life-saving treatment at no cost to patients in developing countries, particularly those with inadequate health care services or medical plans.

Like most biotechnology firms, Genzyme did not pay dividends to its sharehold- ers. As it stated, “We have never paid a cash dividend on our shares of stock. We currently intend to retain our earnings to finance future growth and do not anticipate paying any cash dividends on our stock in the foreseeable future.”10 The company had repurchased shares of its common stock amounting to $231.5 million in 2006 and $143 million in 2007, but these were offset by issuances of shares to honor option exercises. There was no open market share repurchase program.

In terms of operations, the $200 million manufacturing facility Genzyme had built in Allston produced the company’s primary genetic drugs, Cerezyme, Fabrazyme, and Myozyme. A new facility was being constructed in Framingham, and major interna- tional facilities were located in England, Ireland, and Belgium. Administrative activ- ities, sales, and marketing were all centered in Cambridge and Framingham. All was well until the first quarter of 2009, when Termeer received the FDA warning letter in February outlining deficiencies in the Allston plant. The “significant objectionable conditions” fell into four categories: maintenance of equipment, computerized sys- tems, production controls, and failure to follow procedures regarding the prevention of microbiological contamination.11 The problems in the Allston plant could be traced back to Termeer’s decision to stretch the production capacity of the plant to meet an unanticipated demand for Myozyme. Production had increased, but the strain placed on the complex processes eventually led to the problems cited by the FDA. Anything that disrupted the production of the plant concerned Termeer because it produced Gen- zyme’s best-selling products, and those medications were critical to the well-being of the patients who used them.

Relational Investors If only one word were used to describe 52-year-old Ralph Whitworth, cofounder of Relational Investors, it would be “performance.” While attending high school in Nevada, he raced his red 1965 Pontiac GTO against friends on the desert roads near

80 Part One Setting Some Themes

9Geoffrey Gagnon, “So This Is What a Biotech Tycoon Looks Like,” Boston Magazine, June 2008. 10Genzyme Corporation, 10-K filing, 2009. 11David Armstrong, “FDA Warns Genzyme on Plant Conditions–Agency’s Critique of Production Could Further Delay Biotech Company’s Pompe Drug,” Wall Street Journal, March 11, 2009.

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his home town of Winnemucca, outperforming them all. After obtaining a JD from Georgetown University Law Center, Whitworth accepted a job with T. Boone Pickens, the famous “corporate raider” of the 1980s, and gained what he called “a PhD in cap- italism” in the process.12 He left Pickens in 1996 to found RI with David Batchelder whom he had met while working for Pickens. The largest initial investment was the $200 million that came from the California Public Employees’ Retirement System (CalPERS). In recognition of RI’s performance, CalPERS had invested a total of $1.3 billion in RI by 2008. (Exhibit 9 illustrates RI’s annual performance.)

RI was commonly classified by observers as an “activist” investment fund. The typical target firm was a company whose discounted cash flow analysis provided a higher valuation than the company’s market price. Whitworth trained his executives to view the gap between a company’s intrinsic value and its market price as the result of an entrenched management taking care of itself at the expense of its shareholders.13

Specifically, Whitworth felt the value gap came primarily from two sources: (1) money not being spent efficiently enough to earn adequate returns, and/or (2) the company suffered from major corporate governance issues.14 Common causes of underperfor- mance were firm diversification strategies that were not providing an adequate return to shareholders, poor integration results with a merger partner or acquisition, or the misalignment of management incentives.

Once a firm was targeted, RI typically took a 1% to 10% stake in it and then engaged management with questions backed up by an RI detailed analysis. Depend- ing upon the particular responses from executives and directors, Whitworth would follow one of several paths. For example, he might request certain changes or consider making criticisms public. Resistance might result in isolated pressure on one or more executives or board members. In other instances, Whitworth might request a seat on the board, suggest a change in executive management or board composition, or initiate a proxy fight.15 Management and board compensation was a favorite target of RI criticism—one that was never well received by the target firm. Similar to most people’s view of an athlete, Whitworth had no objections regarding high compensa- tion for executives, so long as they performed. (Exhibit 10 illustrates some of RI’s major corporate governance engagements in the past.)

As one example, in late 2006, Whitworth and Batchelder contacted the board of Home Depot requesting changes in the company’s strategy. By then, RI had purchased $1 billion of Home Depot stock. Specifically, they criticized CEO Robert Nardelli’s decision to shift the company’s focus to a lower-margin commercial supply business, which Nardelli considered a growth opportunity. This proved to be commercially unsuccessful. As a result, Nardelli had increased revenues, which was in keeping with his board-approved incentive contract, but earnings suffered. After the engagement of RI, Batchelder joined the board, and Nardelli was ousted.

Case 5 Genzyme and Relational Investors: Science and Business Collide? 81

12Francesco Guerrera and James Politi, “The Lone Ranger of Boardroom Battles,” Financial Times, February 25, 2008. 13Jonathan R. Laing, “Insiders, Look Out!,” Barron’s, February 19, 2007. 14Aaron Bernstein and Jeffery M. Cunningham, “The Alchemist,” Directorship, June/July 2007. 15Laing, “Insiders, Look Out!”

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82 Part One Setting Some Themes

In another instance, this time with Sovereign Bancorp, corporate governance was the key issue. One director was found to have executed private transactions in branch offices. Another had an undisclosed ownership in a landscaping company that the bank hired. Instead of the more normal compensation of $80,000 paid to board members of similarly sized banks, Sovereign Bancorp’s board members received $320,000 a year.16 After uncovering these events and fighting with the board, Whitworth suc- ceeded in being elected to it, and the CEO Jay Sidhu was ousted.

At its peak, RI’s engagements comprised a total portfolio of $8.4 billion at the end of third quarter 2007. Given the drop in share prices following the financial cri- sis and the impact of several redemptions from investors, RI’s portfolio value had been reduced to $4.3 billion by the end of March 2009. (Exhibit 11 lists the amount of RI’s engagements as of September 30 for each year since 2001 as well as the active engagements that RI had as of March 31, 2009.)

Which Path to Follow? When Termeer finished his walk on the beach, he returned to the office, where he reviewed Whitworth’s presentation slides. The main slide illustrated RI’s calculation of the present value of each of Genzyme’s divisions plus its R&D pipeline. The sum of these, representing RI’s valuation of Genzyme, is compared to the company’s cur- rent stock price (Exhibit 12 shows RI’s valuation analysis of Genzyme). It showed that Genzyme’s share price was trading at $34 below its fundamental value—a sig- nificant discount. RI then offered recommendations as to how Genzyme could address this:

1. Improve capital allocation decision making to ensure that spending would be focused on the investment with the highest expected return.

2. Implement a share-buyback or dividend program.

3. Improve board composition by adding more members with financial expertise.

4. Focus executive compensation on the achievement of performance metrics.

Termeer reflected on the first two items on the RI list. During his presentation, Whitworth stated how impressed he was with Genzyme’s growth and complemented Termeer on how well he had been able to create significant shareholder value. But Whitworth anticipated that the years of successful growth were about to lead to high positive cash flow for several years. (Exhibit 13 shows how RI expected Genzyme to generate significant cash flow in the coming years.) That positive cash flow would create new challenges for Termeer. Whitworth explained that CEOs often failed to realize that value-adding investment opportunities were not available at the level of the cash flows being produced. As the CEOs continued to invest the large cash flows into lower-return investments, the market would eventually react negatively to the overinvestment problem and cause the share price to decline. Whitworth argued that

16Bernstein and Cunningham, 13.

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Case 5 Genzyme and Relational Investors: Science and Business Collide? 83

it was better for management to distribute the newly found cash flow as part of a share repurchase program. Moreover, he thought Genzyme could leverage its share repur- chases by obtaining external funding because Genzyme’s balance sheet could support a significant increase in debt.

Termeer realized it would be difficult for him to change his conservative views about leverage, particularly in light of the fact that he had been so successful in build- ing the company without relying on debt.17 The thought of using debt to enhance a share repurchase program was doubly difficult for him to accept. But even more important was his opinion that one had to take a long-term view to succeed in biotechnology. Whitworth seemed to see investments as simply a use of cash, whereas Termeer saw investments as being critical to the business model and survival of Genzyme. In fact, the higher cash flow level would make it easier to fund the investments because it would reduce or eliminate the need to access capital markets. Termeer had always envisioned a future where diagnostics and therapeutics would be closer together, and now he recognized that this future would require Genzyme to pursue a variety of technologies on an on-going basis.

Then Termeer’s eyes caught the third item on the list about adding board mem- bers with financial expertise. This brought to mind the earlier demands by another activist investor, Carl Icahn, who had purchased 1.5 million shares of Genzyme during third quarter 2007.18 Termeer had strongly protested Icahn’s involvement, and with the support of the board made a public plea to shareholders that ultimately led Icahn to sell his Genzyme shares and turn his attention to Biogen Idec, another major biotechnology company.19

In Termeer’s mind, Icahn was more than just an activist investor. During his long career, Icahn had earned the title of “corporate raider” by taking large stakes in com- panies that often culminated in a takeover or, at a minimum, in a contentious proxy fight. Earlier in the year, Icahn had taken a large position in MedImmune, Inc., and helped arrange the sale of the company to AstraZeneca PLC. Were the current cir- cumstances such that Icahn would see another opportunity to target Genzyme again? Where would Whitworth stand on this? “After all, at the end of the day, both Icahn and Whitworth are just after the cash flow,” said Termeer.

Other recent events were on Termeer’s mind as well. Genentech, the second- largest U.S. biotechnology firm and one of Genzyme’s competitors, had just lost a bitterly contested hostile takeover from Roche Holding AG at the start of 2009. This takeover reminded Termeer of the possibility that some Big Pharma companies were looking to expand their operations into biotechnology.

As Termeer reflected on the last 26 years spent creating and building Genzyme, he realized that Whitworth’s RI fund had been a shareholder for less than a year and held only 2.6% of the shares. It was no surprise these two men held such different viewpoints of what Genzyme had to offer to its owners and to society. Termeer, aware

17Geoffrey Gagnon, “So This Is What a Biotech Tycoon Looks Like.” 18Capital IQ, “Genzyme Corporation,” Public Ownership, Detailed, History—Carl Icahn LLC. 19Gagnon, “Biotech Tycoon.”

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84 Part One Setting Some Themes

that he needed a strategy for dealing with Whitworth, had identified three different approaches he could take:

1. Fight Whitworth as he had fought Icahn. To do this, he would need to enlist the board to join him in what would be a public relations battle for shareholder support.

2. Welcome Whitworth onto the board to reap the benefits of his experience in how to create shareholder value. In this regard, he could think of Whitworth as a free consultant.

3. Manage Whitworth by giving him some items on his list of demands but nothing that would compromise the core mission of Genzyme.

He had arranged for a phone call with Whitworth in the following week. Regardless of his approach, Termeer expected that Whitworth would probably request a hearing at the board meeting, which was scheduled two days before the annual shareholders’ meeting on May 21. The prospect of such a meeting with the board only served to emphasize the importance of Termeer’s having a strategy for the upcoming call with Whitworth and making decisions that would be in the best interest of his company.

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Case 5 Genzyme and Relational Investors: Science and Business Collide? 85

EXHIBIT 1 | Income Statements

Amounts in $ thousands 2006 2007 2008

Revenue Net product sales $2,887,409 $3,457,778 $4,196,907 Net service sales 282,118 326,326 366,091 Research & development revenue 17,486 29,415 42,041

Total revenues 3,187,013 3,813,519 4,605,039

Operating Costs Cost of products and services sold 735,671 927,330 1,148,562 Selling and administrative expenses 1,010,400 1,187,184 1,338,190 Research & development 649,951 737,685 1,308,330 Amortization of goodwill 209,355 201,105 226,442 Purchase of in-process R&D 552,900 106,350 0 Charges for impaired assets 219,245 0 2,036

Other operating expenses 3,377,522 3,159,654 4,023,560

Operating income (loss) (190,509) 653,865 581,479

Investment income 56,001 70,196 51,260 Interest expense (15,478) (12,147) (4,418) Equity method investments 88,935 20,465 (3,139) All other income (expense) 8,373 3,295 356

Total other income (expenses) 137,831 81,809 44,059

Income before income taxes (52,678) 735,674 625,538 Provision for income taxes 35,881 (255,481) (204,457)

Net income (loss) ($16,797) $480,193 $421,081

Earnings per share Basic ($0.06) $1.82 $1.57 Diluted ($0.06) $1.74 $1.50

Data Source: Genzyme Corporation, 10-K filing, 2008.

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86 Part One Setting Some Themes

EXHIBIT 1 | Balance Sheets (Continued)

Amounts in $ thousands 2006 2007 2008

Assets Cash and equivalents $492,170 $867,012 $572,106 Short-term investments 119,894 80,445 57,507 Accounts receivable 746,746 904,101 1,036,940 Inventory 374,644 439,115 453,437 Other current assets 256,047 331,158 396,145

Total current assets 1,989,501 2,621,831 2,516,135

Property, plant & equipment—net 1,610,593 1,968,402 2,306,567 Investments—long term 740,103 602,118 427,403 Goodwill 1,298,781 1,403,828 1,401,074 Other intangibles 1,492,038 1,555,652 1,654,698 Other long-term assets 60,172 162,544 365,399

Total Assets $7,191,188 $8,314,375 $8,671,276

Liabilities Accounts payable $98,063 $128,380 $127,869 Accrued expenses payable 532,295 645,645 765,386 Current portion—long-term debt 6,226 696,625 7,566 Other short-term liabilities 14,855 13,277 13,462

Current Liabilities 651,439 1,483,927 914,283

Long-term debt 809,803 113,748 124,341 Other liabilities 69,235 103,763 326,659

Total Liabilities 1,530,477 1,701,438 1,365,283

Shareholders’ Equity (a) Common stock and paid-in capital 5,108,904 5,387,814 5,783,460 Retained earnings 551,807 1,225,123 1,522,533

Total Equity 5,660,711 6,612,937 7,305,993 Total Liabilities and Shareholders’ Equity $7,191,188 $8,314,375 $8,671,276

Shares outstanding at December 31 (000) 263,026 266,008 270,704

Data Source: Genzyme Corporation, 10-K filings, 2007 and 2008.

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Case 5 Genzyme and Relational Investors: Science and Business Collide? 87

EXHIBIT 1 | Statement of Cash Flows (Continued)

Amounts in $ thousands 2006 2007 2008

Cash from operations Net income ($16,797) $480,193 $421,081 Depreciation & amortization 331,389 338,196 374,664 Stock-based compensation 208,614 190,070 187,596 Change in operating assets (73,311) (117,862) (90,615) Purchase of in-process R&D 552,900 106,350 0 Charge for impaired assets 219,243 0 2,036 Deferred income tax benefit (279,795) (106,140) (195,200) Other operating cash flows (53,674) 27,865 59,613

Cash from operations 888,569 918,672 759,175

Cash from investing Capital expenditure (333,675) (412,872) (597,562) Acquisitions, net of acquired cash (568,953) (342,456) (16,561) Net sale (purchase) of investments 13,168 205,614 188,127 Net sale (purchase) of equity securities 132,588 (1,282) (80,062) Other investing activities (79,540) (40,060) (75,482)

Cash from investing (836,412) (591,056) (581,540)

Cash from financing Net long-term debt issued/repaid (4,501) (5,909) (693,961) Issuance of common stock 158,305 285,762 318,753 Repurchase of common stock 0 (231,576) (143,012) Other financing activities (5,751) (1,051) 45,679

Cash from financing 148,053 47,226 (472,541)

Net change in cash & equivalents $200,210 $374,842 ($294,906)

Data Source: Genzyme Corporation, 10-K filing, 2008.

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88 Part One Setting Some Themes

EXHIBIT 2 | Top 10 Shareholders, March 31, 2009

Shares Held %

Clearbridge Advisors, LLC 15,103,597 5.7% Barclays Global Investors, UK, Ltd. 11,974,523 4.5% Wellington Management Co., LLP 10,790,760 4.0% State Street Global Advisors, Inc. 9,326,639 3.5% The Vanguard Group, Inc. 9,066,174 3.4% Sands Capital Management, LLC 8,372,483 3.1% UBS Global Asset Management 7,722,011 2.9% Fidelity Investments 6,995,691 2.6% Relational Investors LLC 6,942,506 2.6% PRIMECAP Management Company 6,330,985 2.4% SG Gestion 5,804,357 2.2% Massachusetts Financial Services Company 5,522,034 2.1%

Total shares outstanding: 267,019,462

Data Source: Forms 13F filed by investors.

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89

EXHIBIT 3 | Genzyme (GENZ) vs. S&P 500 (S&P) and NASDAQ Biotechnology Index (NBI), Weekly Close—Base ! 1/1/20030

Genzyme Daily Closing Price (GENZ)

-50%

0%

50%

100%

150%

200%

GENZ NBI S&P

Jan-2003 Jan-2004 Jan-2005 Jan-2006 Jan-2007 Jan-2008 Jan-2009

1-Oct-08 1-Nov-08 1-Dec-08 1-Jan-09 1-Feb-09 1-Mar-09 1-Apr-09

GENZ

$50

$60

$55

$65

$75

$70

$80

$85

April 9, 2009: $56.38

Data Source: Bloomberg.

bru6171X_case05_075-098.qxd 12/12/12 4:07 PM Page 89

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bru6171X_case05_075-098.qxd 12/12/12 4:07 PM Page 90

Case 5 Genzyme and Relational Investors: Science and Business Collide? 91

Henri A.Termeer (1983)

Charles L. Cooney (1983)

Douglas A. Berthiaume (1988)

Robert J. Carpenter (1994)

Victor J. Dzau, MD (2000)

Senator Connie Mack III (2001)

Gail K. Boudreaux (2004)

Richard F. Syron (2006)

Chairman of Genzyme since 1988; deputy chairman of the Federal Re- serve Bank of Boston; worked for Bax- ter laboratories for 10 years.

Distinguished professor of chemical and biochemical engineering at MIT (joined in 1970). Principal of BioInforma- tion Associates, Inc., a consulting firm.

Chairman, president, and CEO of Waters Corporation since 1994 (manufacturer of high-performance liquid chromatography instrumentation).

President of Boston Medical Investors, Inc. (invests in health care companies); chairman of Hydra Biosciences (ion-channel-based drugs); chairman of Peptimmune Inc. from 2002–07 (treatment of autoimmune diseases); cofounder of GelTex in 1991; CEO of Integrated Genetics until purchased by Genzyme in 1989.

Chancellor for Health Affairs and president and CEO of Duke University Health System.

Served as senior policy advisor at two law firms (King & Spalding LLP and Shaw Pittman); U.S. senator from Florida from 1989 to 2001.

EVP, United Healthcare Group (since May 2008). Former president of Blue Cross and Blue Shield of Illinois; held various positions over 20 years at Aetna Group Insurance.

Chairman and CEO of FHLMC (Freddie Mac) from 2003 to 2008; held executive positions at Thermo Electron from 1999 to 2003 (developed technology instruments).

Note: Date in parentheses is the first year elected to the board.

Data Source: Genzyme Corporation, 14A filing, April 13, 2009.

Compensation (Chairman); Corporate Governance

Audit (Chairman); Compensation

Compensation

Corporate Governance; Compensation

Corporate Governance (Chairman); Audit

Audit

Corporate Governance; Audit

EXHIBIT 5 | Board of Directors, March 31, 2009

Director Committee Experience

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92 Part One Setting Some Themes

EXHIBIT 6 | Acquisitions: 1997–2007 (in millions of dollars)

In-process Date Value R&D Company Acquired Drug or Business Acquired Segment

1997 $112 $0 PharmaGenics, Inc. Created Genzyme molecular oncology HO 2000 1,284 118 GelTex Obtained RenaGel (formerly a joint venture) CR 2000 875 82 Biomatrix, Inc. Became Genzyme Biosurgery division BI 2001 17 17 Focal Surgical biomaterials BI 2003 596 158 SangStat Medical Immune system treatment— Other

Corp. Thymoglobulin 2004 1,030 254 Ilex Oncology, Inc. Cancer drugs—Campath and Clolar HO 2005 659 12 Bone Care Int’l Treatment of kidney disease—Hectorol CR 2005 50 9 Verigen Cartilage repair—MACI (launch in 2012) BI 2005 12 7 Avigen AV201—Parkinson’s disease (launch GD

in 2016) 2006 589 553 AnorMED Mozobil—stem cell transplant HO

(approved 12/2008) 2007 $350 $106 Bioenvision Evoltra (launch 2010–13) HO

Data Sources: LexisNexis, “Genzyme Corporation” Mergers and Acquisitions; Genzyme Corporation 10-K filings, 2000–07; Montgomery, 165.

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Case 5 Genzyme and Relational Investors: Science and Business Collide? 93

Genetic Diseases (GD): The core business of the company focused on products to treat patients with genetic and other chronic debilitating diseases.

Cardiometabolic and Renal (CR): Treatment of renal, endocrine, and cardiovascular diseases.

Biosurgery (BI): Orthopaedic products; formed via purchase of Biomatrix, Inc., in 2000.

Hematologic Oncology (HO): cancer treatment products Other product revenue 11.1% (Other)

Cerezyme: Enzyme replacement therapy for Type 1 29.5% Gaucher’s Disease; launched in 1995 Fabrazyme: intended to replace the missing enzyme alpha- 11.8% Galactosidase in patients with the inherited Fabry disease; launched in 2001. Myozyme: Lysosomal glycogen-specific enzyme for use in 7.1% patients with infantile-onset of Pompe disease; launched in 2006. Aldurazyme: for treatment of Mucopolysaccharidosis I (MPS I), 3.6% a deficiency of a lysosomal enzyme, alpha-L-iduronidase; launched in 2003. Other genetic diseases 1.1% Renagel/ Renvela: Used by patients with chronic kidney 16.1% disease on dialysis for the control of serum phosphorus. Hectorol: Treatment of secondary hyperparathyroidism in 3.1% patients with stage 3 or 4 chronic kidney disease and on dialysis. Acquired via purchase of Bone Care in 2005. Thyrogen: Treatment for thyroid cancer to allow patients to 3.5% avoid traditional hypothyroidism treatment. Other cardiometabolic and renal 0.0% Synvisc: a local therapy to reduce osteoporosis knee pain, 6.3% facilitating increased mobility. Sepra: a family of products used by to prevent adhesions after 3.2% abdominal and pelvic open surgery, including a C-section, hysterectomy, myomectomy, colectomy, or hernia repair. Other biosurgery 1.2%

2.4%

Data Source: Genzyme Corporation, 10-K filings, 2008 and 2009.

EXHIBIT 7 | Main Products by Segment

% of 2008 Total Segment Product Revenues

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94 Part One Setting Some Themes

EXHIBIT 8 | Genzyme—Estimates of CFROI by Segment (2008)

30%

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Rest of Genzyme 8.8%

Total Company Cash ROIC = 14.2%

Strategic Partnerships

Bayer Healthcare FOVEA

Acquisitions

Partnerships & Acquisitions Isis Osiris PTC Ceregene Verigen

ILEX Bioenvision Bayer Healthcare Avigen - Gene Therapy

GelTex Bone Care SangStat DCL Biomatrix AnorMED Wyntek Genetrix IMPATH

R&D Pipeline (8.3%)

Note: Cash ROIC = Adjusted Cash Profits/Average Invested Capital.

Source: Relational Investors.

EXHIBIT 9 | Relational Investors—Calendar Year Performance (%)

2002 2003 2004 2005 2006 2007 2008

Relational Investors 0.55% 40.77 16.49 9.89 9.29 "10.01 "40.01% S&P "22.12% 28.69 10.87 4.89 15.81 5.54 "37.01% Alpha 22.67% 12.08 5.62 5.00 "6.52 "15.55 "4.00%

Note: RI was not required to disclose publicly its performance results. CalPERS disclosed its investment returns in RI’s Corporate Governance Fund, and this serves as a good proxy for RI’s performance.

Data Source: “Performance Analysis for the California Public Employers’ Retirement System,” Wilshire Consulting (Santa Monica, CA), September 30, 2010.

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bru6171X_case05_075-098.qxd 12/12/12 4:07 PM Page 95

96 Part One Setting Some Themes

Total Invested ($ millions)

2001 $554 2002 $1,062 2003 $1,878 2004 $3,199 2005 $6,910 2006 $5,974 2007 $8,063 2008 $4,974 2009* $4,282

* March 31, 2009.

Data source: Relational Investors, Form 13F.

EXHIBIT 11 | Relational Investors—Portfolio Investments

Total market value of equity positions held by RI (as of Sept. 30 each year)

List of RI’s active engagements (as of 3/31/2009)

Value ($000) % of % Owned Company 3/31/2009 RI’s Total by RI

The Home Depot, Inc. $856,826 22.1% 2.1% Baxter International Inc. 568,012 14.6% 1.8% Genzyme Corporation 412,315 10.6% 2.6% Unum Group 398,879 10.3% 9.6% Occidental Petroleum Corp. 292,752 7.5% 0.6% Yahoo! Inc. 269,789 7.0% 1.5% National Semiconductor Corp. 231,011 6.0% 9.8% Burlington Northern 211,631 5.5% 1.0% SPDR Trust Series 1 204,733 5.3% 0.3% Freeport-McMoran 100,610 2.6% 0.6% Others (under $100 million each) 334,000 8.6% n/a

Total Investments $3,880,558 100.0%

Data Source: Relational Investors, Form 13F.

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Case 5 Genzyme and Relational Investors: Science and Business Collide? 97

EXHIBIT 12 | Relational Investors’ Fundamental Valuation of Genzyme

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bru6171X_case05_075-098.qxd 12/12/12 4:07 PM Page 97

98 Part One Setting Some Themes

EXHIBIT 13 | Relational Investors’ Estimates of Genzyme’s Free Cash Flow

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PART

Financial Analysis and Forecasting

2

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The Thoughtful Forecaster Every day, fortunes are won and lost on the backs of business-performance forecasts. Investors who successfully anticipate business development are rewarded handsomely. Investors who fail to anticipate such development pay the penalty. This note exam- ines principles in the art and science of thoughtful financial forecasting. In particular, it reviews the importance of (1) understanding the financial relationships of a busi- ness enterprise, (2) grounding business forecasts in the reality of the industry and macroenvironment, (3) modeling a base-case forecast that incorporates the expecta- tions for business strategy, and (4) recognizing the potential for cognitive bias in the forecasting process. Forecasting is not the same as fortune-telling; unanticipated events have a way of making certain that specific forecasts are never completely correct. This note purports, however, that thoughtful forecasts aid understanding of the key bets in any forecast and the odds associated with success. It closes with an example of financial forecasting based on the Maytag Corporation, a U.S. appliance manufacturer.

Understanding the Financial Relationships of the Business Enterprise Financial statements provide information on the financial activities of an enterprise. Much like the performance statistics from an athletic contest, financial statements provide an array of identifying data on various historical strengths and weaknesses across a broad spectrum of business activities. The income statement, or profit-and- loss statement, measures flows of costs, revenue, and profits over a defined period of time. The balance sheet provides a snapshot of business investment and financing at a particular point in time. Both statements combine to provide a rich picture of a business’s financial performance. Thorough analysis of financial statements is one important way of understanding the mechanics of the systems that make up business operations.

101

6CASE

This technical note was prepared by Professor Michael J. Schill. Special thanks go to Vladimir Kolcin for data-collection assistance and to Lee Ann Long-Tyler and Ray Nedzel for technical assistance. Copyright © 2005 by the University of Virginia Darden School Foundation, Charlottesville, VA. All rights reserved. To order copies, send an e-mail to [email protected] No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means— electronic, mechanical, photocopying, recording, or otherwise—without the permission of the Darden School Foundation.

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Interpreting Financial Ratios Financial ratios provide a useful way to identify and compare relationships across financial-statement line items.1 Trends in the relationships captured by financial ratios are particularly helpful in modeling a financial forecast. The comparison of ratios across time or with similar firms provides diagnostic tools for assessing the health of the various systems in the enterprise. We review below common financial ratios for examining business-operating performance. An understanding of the current condition of the business can be used to anticipate prospective performance.

Growth Rates Growth rates capture the year-on-year percentage change in a par- ticular line item. For example, if total revenue for a business increases from $1.8 mil- lion to $2.0 million, the total revenue growth for the business is said to be 11.1% [(2.0 ! 1.8)"1.8]. Total revenue growth can be further decomposed into two other growth measures: unit growth (the growth in revenue due to an increase in units sold) and price growth (the growth in revenue due to an increase in the price of each unit). In the above example, if unit growth for the business is 5.0%, the remaining 6.1% of total growth can be attributed to price growth or price inflation.

Margins Margin ratios capture the percentage of revenue accounted for by profit or, alternatively, the percentage of revenue not consumed by business costs. For example, if operating profit2 is $0.2 million and total revenue is $2.0 million, the operating margin is 10% (0.2"2.0). Thus, for each revenue dollar, $0.90 is consumed by oper- ating expenses and an operating profit of $0.10 is generated. The margin also meas- ures the cost structure of the business. Common definitions of margin include the following:

Gross margin # Gross profit"Total revenue

Operating margin # Operating profit"Total revenue

Net profit margin # Net income"Total revenue

Turnover Turnover ratios measure the productivity, or efficiency, of business assets. The turnover ratio is constructed by dividing a related measure of volume from the income statement by a measure of investment from the balance sheet. For example, if total revenue is $2.0 million and total assets are $2.5 million, the asset-turnover measure is 0.8 times (2.0"2.5). Thus, each dollar of total asset investment is produc- ing $0.80 in revenue or, alternatively, total assets are turning over 0.8 times a year

102 Part Two Financial Analysis and Forecasting

1The analogy of athletic-performance statistics is again useful in understanding how ratios provide additional meaningful information. In measuring the effectiveness of a batter in baseball, the batting average (number of hits $ number of at-bats) may be more useful than simply knowing the number of hits. In measuring the suc- cess of a running back in football, the ratio of “rushing yards gained per carry” may be more useful than simply knowing the total rushing yards gained. 2Operating profit is also commonly referred to as earnings before interest and taxes (EBIT).

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through the operations of the business. Productive or efficient assets produce high levels of asset turnover. Common measures of turnover include the following:

Receivable turnover # Total revenue"Accounts receivable

Inventory turnover3 # Cost of goods sold"Inventory

PPE turnover # Total revenue"Net property, plant, equipment

Asset turnover # Total revenue"Total assets

Total capital turnover # Total revenue"Total capital

Payable turnover3 # Cost of goods sold"Accounts payable

An alternative and equally informative measure of asset productivity is a “days” measure, which is computed as the investment amount divided by the volume amount multiplied by 365 days. This measure captures the average number of days in a year that an investment item is held by the business. For example, if total revenue is $2.0 million and accounts receivable is $0.22 million, the accounts-receivable days are cal- culated as 40.2 days (0.22/2.0 % 365). In other words, the average receivable is held by the business for 40.2 days before being collected. The lower the days measure, the more efficient is the investment item. The days measure does not actually provide any information not already contained in the respective turnover ratio, as it is simply the inverse of the turnover measure multiplied by 365 days. Common days measures include the following:

Receivable days # Accounts receivable"Total revenue % 365 days

Inventory days # Inventory"Cost of goods sold % 365 days

Payable days # Accounts payable"Cost of goods sold % 365 days

Return on Investment Return on investment captures the profit generated per dollar of investment. For example, if operating profit is $0.2 million and total assets are $2.5 mil- lion, pretax return on assets is calculated as operating profit divided by total assets (0.2/2.5), or 8%. Thus, the total dollars invested in business assets are generating pre- tax operating-profit returns of 8%. Common measures of return on investment include the following:

Pretax return on assets # Operating profit"Total assets

Return on capital (ROC) # Operating profit % (1 ! Tax rate)"Total capital

(where Total capital # Total assets ! Non-interest-bearing current liabilities)

Return on equity (ROE) # Net income/Shareholders’ equity

It is worth observing that return on investment can be decomposed into a margin effect and a turnover effect. This relationship means that the same level of business profitability can be attained by a business with high margins and low turnover (e.g.,

3For inventory turnover and payable turnover, it is customary to use cost of sales as the volume measure because inventory and purchases are on the books at cost rather than at the expected selling price.

Case 6 The Thoughtful Forecaster 103

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Nordstrom) as by a business with low margins and high turnover (e.g., Wal-Mart). This decomposition can be shown algebraically for pretax return on assets:

Notice that the equality holds because the quantity for total revenue cancels out across the two right-hand ratios.

Using Financial Ratios in Financial Models Financial ratios are particularly helpful when forecasting financial statements because financial ratios capture relationships across financial-statement line items that tend to be preserved over time. For example, rather than forecasting explicitly the gross-profit dollar amount for next year, it may be easier to forecast a revenue growth rate and a gross margin that, when applied to current-year revenue, give an implicit dollar fore- cast for gross profit. Thus, if we estimate revenue growth at 5% and operating mar- gin at 24%, we can apply these ratios to last year’s total revenue of $2.0 million to derive an implicit gross-profit forecast of $0.5 million [2.0 % (1 & 0.05) % 0.24]. Given some familiarity with the financial ratios of a business, the ratios are generally easier to forecast than the expected dollar values. In effect, we model the future finan- cial statements based on assumptions about future financial ratios.

Financial models can be helpful in identifying the impact of particular assump- tions on the forecast. For example, models easily allow us to see the financial impact on dollar profits of a difference of one percentage point in operating margin. To facil- itate such a scenario analysis, financial models are commonly built in electronic- spreadsheet packages such as Excel. Good financial-forecast models make the fore- cast assumptions highly transparent. To achieve transparency, assumption cells for the forecast should be prominently displayed in the spreadsheet (e.g., total-revenue- growth-rate assumption cell, operating-margin assumption cell), and then those cells should be referenced in the generation of the forecast. In this way, it becomes easy not only to vary the assumptions for different forecast scenarios, but also to scruti- nize the forecast assumptions.

Grounding Business Forecasts in the Reality of the Industry and Macroenvironment Good financial forecasts recognize the impact of the business environment on the per- formance of the business. Financial forecasting should be grounded in an apprecia- tion for industry- and economy-wide pressures. Because business performance tends to be correlated across the economy, information regarding macroeconomic business trends should be incorporated into a business’s financial forecast. If, for example, price increases for a business are highly correlated with economy-wide inflation trends, the financial forecast should incorporate price-growth assumptions that capture the

Operating profit

Total assets #

Operating profit Total revenue

% Total revenue Total assets

Pretax ROA # Operating margin % Asset turnover

104 Part Two Financial Analysis and Forecasting

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TABLE 1 | Most profitable and least profitable U.S. industries, 1994–2004. Ranking of two-digit SIC code industries based on median pretax ROAs for all public firms followed by Compustat from 1994 to 2004.

Median Median Most Profitable Industries Firm ROA Least Profitable Industries Firm ROA

Apparel and accessory stores 12.1% Metal mining !1.4% Building-construction contractors 11.0% Chemicals and allied products 0.0% Furniture and fixture manufacturers 10.7% Business services 0.3% Leather/leather-products manufacturers 10.5% Banking 2.1% Petroleum refining 10.0% Insurance carriers 2.5%

available information on expected inflation. If the economy is in recession, the fore- cast should be consistent with that economic reality.

Thoughtful forecasts should also recognize “industry reality.” Business prospects are dependent on the structure of the industry in which the business operates. Some industries tend to be more profitable than others. Microeconomic theory provides some explanations for the variation in industry profitability. Profitability within an industry is likely to be greater if (1) barriers to entry discourage industry entrants, (2) ease of industry exit facilitates redeployment of assets for unprofitable players, (3) industry participants exert bargaining power over buyers and suppliers, or (4) industry consolidation reduces price competition.4 Table 1 shows the five most profitable industries and the five least profitable industries in the United States based on median pretax ROAs for all public firms from 1994 to 2004. Based on the evi- dence, firms operating in the apparel and accessory retail industry should have sys- tematically generated more profitable financial forecasts over that period than did firms in the metal-mining industry. One explanation for the differences in industry profitability is the ease of industry exit. In the retail industry, unprofitable businesses are able to sell their assets easily for redeployment elsewhere. In the metal-mining industry, where asset redeployment is much more costly, industry capacity may have dragged down industry profitability.

Being within a profitable industry, however, does not ensure superior business performance. Business performance also depends on the competitive position of the firm within the industry. Table 2 shows the variation of profitability for firms within the U.S. apparel and accessory industry from 1994 to 2004. Despite being the most prof- itable industry in Table 1, there is large variation in profitability within the industry; in fact, three firms generated median ROAs that were actually negative (Harold’s, Syms, and Stage Stores). Good forecasting considers the ability of a business to sus- tain performance given the structure of its industry and its competitive position within that industry.

Case 6 The Thoughtful Forecaster 105

4Michael E. Porter, “How Competitive Forces Shape Strategy,” Harvard Business Review 57, no. 2 (March–April 1979): 137–45.

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Year 0 1

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3

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Year 0 1

5

4

3

R an

ki ng

Q ui

nt ile

2

Year 1 Year After Ranking

High Growth Group

Low Growth Group

Year 2 Year 3

Sales Growth

FIGURE 1 | Firm-ranking transition matrix by profitability and sales growth. Firms are sorted for each year into five groups by either annual pretax ROA or sales growth. For example, in the ROA panel, Group 1 comprises the firms with the lowest 20% of ROA for the year; Group 5 comprises the firms with the highest 20% of ROA for the year. The figure plots the mean ranking number for all U.S. public firms followed by Compustat from 1994 to 2004.

TABLE 2 | Most and least profitable firms within the apparel and accessory retail industry, 1994–2004. Ranking of firms based on median pretax ROAs for all public firms in the apparel and accessory retail industry followed by Compustat from 1994 to 2004.

Median Median Most Profitable Firms Firm ROA Least Profitable Firms Firm ROA

Chico’s 35.3% Harold’s !9.7% Abercrombie & Fitch 35.2% Syms !2.1% Christopher & Banks 32.1% Stage Stores !1.2% American Eagle Outfitters 28.0% Guess 1.9% Hot Topic 26.9% United Retail 2.7%

Abnormal profitability is difficult to sustain over time. Competitive pressure tends to bring abnormal performance toward the mean. To show this effect, we sort all U.S. public companies for each year from 1994 to 2004 into five groups (Group 1 [low profits] through Group 5 [high profits]) based on their annual ROAs and sales growth. We then follow what happens to the composition of these groups over the next three years. The results of this exercise are captured in Figure 1. The ROA graph shows the mean group rankings for firms in subsequent years. For example, firms that rank in Group 5 (top ROA) at Year 0 tend to have a mean group ranking of 4.5 in Year 1,

106 Part Two Financial Analysis and Forecasting

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4.2 in Year 2, and 3.7 in Year 3. Firms that rank in Group 1 (bottom ROA) at Year 0 tend to have a mean group ranking of 1.5 in Year 1, 1.8 in Year 2, and 2.3 in Year 3. There is a systematic drift toward average performance (3.0) over time. The effect is even stronger vis-à-vis sales growth. Figure 1 provides the transition matrix for aver- age groups sorted by sales growth. Here we see that, by Year 2, the average sales- growth ranking for the high-growth group is virtually indistinguishable from that of the low-growth group.

Figure 1 illustrates that business is fiercely competitive. It is naïve to assume that superior business profitability or growth can continue unabated for an extended period of time. Abnormally high profits attract competitive responses that eventually return profits to normal levels.

Modeling a Base-Case Forecast That Incorporates Expectations for Business Strategy With a solid understanding of the business’s historical financial mechanics and of the environment in which the business operates, the forecaster can incorporate the firm’s oper- ating strategy into the forecast in a meaningful way. All initiatives to improve revenue growth, profit margin, and asset efficiency should be explicitly reflected in the financial forecast. The forecast should recognize, however, that business strategy does not play out in isolation. Competitors do not stand still. A good forecast recognizes that business strategy also begets competitive response. All modeling of the effects of business strategy should be tempered with an appreciation for the effects of aggressive competition.

One helpful way to temper the modeling of the effects of business strategy is to complement the traditional “bottom-up” approach to financial forecasting with a “top-down” approach. The top-down approach starts with a forecast of industry sales and then works back to the particular business of interest. The forecaster models firm sales by modeling market share within the industry. Such a forecast makes more explicit the challenge that sales growth must come from either overall industry growth or market-share gain. A forecast that explicit, demanding a market-share gain of, say, 20%–24%, is easier to scrutinize from a competitive perspective than a forecast that simply projects sales growth without any context (e.g., at an 8% rate).

Another helpful forecasting technique is to articulate business perspectives into a coherent qualitative “view” on business performance. This performance view encour- ages the forecaster to ground the forecast in a qualitative vision of how the future will play out. In blending qualitative and quantitative analyses into a coherent story, the forecaster develops a richer understanding of the relationships between the financial fore- cast and the qualitative trends and developments in the enterprise and its industry.

Forecasters can better understand their models by identifying the forecast’s “value drivers,” which are those assumptions that strongly affect the overall outcome. For example, for some businesses the operating-margin assumption may have a dramatic impact on overall business profitability, whereas the assumption for inventory turnover may make little difference. For other businesses, the inventory turnover may have a tremendous impact and thus be a value driver. In varying the assumptions, the forecaster can better appreciate which assumptions matter and thus channel resources to improve

Case 6 The Thoughtful Forecaster 107

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the forecast’s precision by shoring up a particular assumption or altering business strategy to improve the performance of a particular line item.

Lastly, good forecasters understand that it is more useful to think of forecasts as ranges of possible outcomes than as precise predictions. A common term for forecast is “base case.” A forecast represents the “best-guess” outcome or “expected value” of the forecast’s line items. In generating forecasts, it is also important to have an unbi- ased appreciation for the range of possible outcomes, which is commonly done by estimating a high-side and a low-side scenario. In this way, the forecaster can bound the forecast with a relevant range of outcomes and can best appreciate the key bets in a financial forecast.

Recognizing the Potential for Cognitive Bias in the Forecasting Process A substantial amount of research suggests that human decision making can be sys- tematically biased. Bias in financial forecasts creates systematic problems in manag- ing and investing in the business. Two elements of cognitive bias that play a role in financial forecasting are optimism bias and overconfidence bias. This note defines opti- mism bias as systematic positive error in the expected value of an unknown quantity, and defines overconfidence bias as systematic negative error in the expected variance of an unknown quantity. The definitions of these two terms are shown graphically in Figure 2. The dark curve shows the true distribution of the sales-growth rate. The real- ization of the growth rate is uncertain, with a higher probability of its being in the cen- tral part of the distribution. The expected value for the sales-growth rate is g*; thus,

108 Part Two Financial Analysis and Forecasting

FIGURE 2 | Optimism bias and overconfidence bias in forecasting sales-growth rate.

P ro

ba bi

lit y

Sales Growth Rate

g* g’

True Distribution

Forecast Distribution

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the proper base-case forecast for the sales-growth rate is precisely g*. The light curve shows the distribution expected by the average forecaster. This distribution is biased for two reasons. First, the expected value is too high. The forecaster expects the base-case sales-growth rate to be g’, rather than g*. Such positive bias for expected value is termed optimistic. Second, the dispersion of the distribution is too tight. This dispersion is captured by the variance (or standard-deviation) statistic. Because the fore- cast dispersion is tighter than the true dispersion, the forecaster exhibits negative vari- ance bias, or overconfidence—the forecaster believes that the forecast is more precise than it really is.

To test for forecasting bias among business-school forecasters, an experiment was performed in 2005 with the 300 first-year MBA students at the Darden Graduate School of Business Administration at the University of Virginia. Each student was randomly assigned both a U.S. public company and a year between 1980 and 20005—that is, some students were assigned the same company, but no students were assigned the same company and the same year. The students were asked to forecast sales growth and operating margin for their assigned company for the subsequent three years. The students based their forecasts on the following information: industry name, firm sales growth and operating margin for the previous three years, historical and three-year prospective industry average growth and margins, and certain macroeconomic histori- cal and three-year forecast data (real GNP growth, inflation rates, and the prevailing Treasury-bill yield). To avoid biasing the forecasts based on subsequent known out- comes, students were given the name of their firm’s industry but not the firm’s name. For the same reason, students were not given the identity of the current year. Responses were submitted electronically and anonymously. Forecast data from students who agreed to allow their responses to be used for research purposes were aggregated and analyzed. Summary statistics from the responses are presented in Figure 3.

The median values for the base-case forecast of expected sales growth and operat- ing margin are plotted in Figure 3. The sales-growth panel suggests that students tended to expect growth to continue to improve over the forecast horizon (Years 1 through 3). The operating-margin panel suggests that students expected near-term performance to be constant, followed by later-term improvement. To benchmark the forecast, we com- pared the students’ forecasts with the actual growth rates and operating margins real- ized by the companies. We expected that if students were unbiased in their forecasting, the distribution of the forecasts should be similar to the distribution of the actual results. Figure 3 also plots the median value for the actual realizations. We observe that sales growth for these randomly selected firms did not improve but stayed fairly constant, whereas operating margins tended to decline over the extended term. The gap between

Case 6 The Thoughtful Forecaster 109

5More precisely, the population of sample firms was all U.S. firms followed by Compustat and the Value Line Investment Survey. To ensure meaningful industry forecast data, we required that each firm belong to a mean- ingful industry (i.e., multiform, industrial services, and diversified industries were not considered). We also required that Value Line report operating profit for each firm. To maintain consistency in the representation of firms over time, the sample began with a random identification of 25 firms per year. The forecast data were based on Value Line forecasts during the summer of the first year of the forecast. All historical financial data were from Compustat.

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FIGURE 3 | Median expected and actual financial-forecast values for a random sample of U.S. companies. This figure plots the median forecast and actual company realization for sales growth and operating margin over the three-year historical period and the three- year forecast period based on the responses from MBA students in an experiment.

0 0%

!1!2 1 2 3 Forecast Year

Actual

Forecast

Sales Growth

1% 2% 3% 4% 5% 6% 7% 8% 9%

10%

0 10%

!1!2 1 2 3 Forecast Year

Actual

Forecast

Operating Margin

11%

12%

13%

14%

15%

the two lines represents the systematic bias in the students’ forecasts. Because the bias in both cases is positive, the results are consistent with systematic optimism in the stu- dents’ forecasts. By the third year, the optimism bias is a large 4 percentage points for the sales-growth forecast and almost 2 percentage points for the margin forecast.

Although the average student tended to exhibit an optimistic bias, there was vari- ation in the bias across groups of students. The forecast bias was further examined across two characteristics: gender and professional training. For both sales growth and operating margin, the test results revealed that males and those with professional back- grounds outside finance exhibited the most optimistic bias. For example, the bias in the third-year margin forecast was 0.7% for those with professional finance back- grounds and 1.9% for those outside finance; and 2.6% for the male students and just 0.8% for the female students.

In generating forecasts, it is also important to have an unbiased appreciation for the precision of the forecast, which is commonly done by estimating a high-side and a low-side scenario. To determine whether students were unbiased in appreciating the risk in forecast outcomes, they were asked to provide a high-side and a low-side sce- nario. The high-side scenario was defined explicitly as the 80th percentile level. The low-side scenario was defined as the 20th percentile level. Figure 4 plots the median high-side and low-side scenarios, as well as the expected base-case forecast presented in Figure 3. For the three-year horizon, the median high-side forecast was 4 per- centage points above the base case and the low-side forecast was 4 percentage points below the base case. The actual 80th percentile performance was 8 percentage points above the base case and the actual 20th percentile was 12 percentage points below the base case. The results suggest that the true variance in sales growth is substantially greater than that estimated by the students. The same is also true of the operating mar- gin. The estimates provided by the students are consistent with strong overconfidence (negative variance bias) in the forecast.

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1 2 3 Forecast Year

Low-side Forecast

High-side Forecast

Base Case Forecast

Actual 20th Percentile

Actual 80th Percentile

Sales Growth 20%

15%

10%

5%

0%

!5% 1 2 3

Forecast Year

Low-side Forecast

High-side Forecast Base Case Forecast

Actual 20th Percentile

Actual 80th Percentile

Operating Margin 25%

20%

15%

10%

5%

FIGURE 4 | Median base-case, high-side, and low-side forecasts versus the actual 20th and 80th per- formance percentiles for sales growth and operating margin. This figure plots the median base-case, high-side, and low-side forecasts for sales growth and operating margin over the three-year forecast period based on the responses from MBA students in an experi- ment. The actual company 20th and 80th performance percentiles for sales growth and operating margin are also plotted. In the experiment, the low-side and high-side perform- ance levels were defined as the students’ belief in the 20th and 80th percentile levels.

Maytag: An Example The Maytag Corporation is a $4.7-billion home- and commercial-appliance company headquartered in Newton, Iowa. Suppose that in early 2004 we need to forecast the financial performance of the Maytag Corporation for the end of 2004. We suspect that one sensible place to start is to look at the company’s performance over the past few years. The company’s annual report provides information from its income statement and balance sheet (Exhibit 1).

One approach is to forecast each line item independently. Such an approach, how- ever, ignores the important relationships among the different line items (e.g., costs and revenues tend to grow together). To gain an appreciation for these relationships, we calculate a variety of ratios, from sales growth to return on assets (Exhibit 1). In calculating the ratios, we notice some interesting patterns. First, sales growth declined sharply in 2003, from 11.5% to 2.7%. The sales decline was also accompanied by a decline in profitability margins; operating margin declined from 7.7% to 4.8%. Mean- while, the asset ratios showed modest improvement; total asset turnover improved only slightly, from 1.5% to 1.6%. The steadiness of asset turnover was relatively constant across the various classes of assets (e.g., inventory days improved slightly in 2003, from 46.7 days to 43.5 days; PPE turnover also improved slightly, from 4.4% to 4.6%). The picture suggests that in 2003 Maytag experienced eroding sales growth and margins, while improvements in current asset efficiency kept asset turnover constant. Because return on assets comprises both a margin effect and an asset-productivity effect, we can attribute the 2003 decline in return on assets wholly to Maytag’s margin decline. To be even more precise, because the operating expense as a percentage of sales actually

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declined, the margin (and ROA) decline is actually wholly due to a decline in gross margin. The historical-ratio analysis gives us some sense of the trends in business performance.

A common way to begin a financial forecast is to extrapolate current ratios into the future. For example, a simple starting point would be to assume that the 2003 financial ratios hold in 2004. If we make that simplifying assumption, we generate the financial forecast presented in Exhibit 2. We recognize this forecast as naïve, but it provides a “straw-man” forecast with which the relationships captured in the finan- cial ratios can be scrutinized. In generating the forecast, all the line-item figures are built on the ratios used in the forecast. The ratios that drive the forecast are bolded in Exhibit 2. The financial line-item forecasts are computed as referenced to the right of each figure. The nonbolded ratios are computed as before. This forecast is known as a “financial model.” The design of the model is thoughtful. By linking the dollar figures with the financial ratios, the model can be easily adjusted to accommodate different ratio assumptions.

We now augment our model with qualitative and quantitative research on the com- pany, its industry, and the overall economy. In early 2004, Maytag was engaged in an important company-wide effort to consolidate its divisional headquarters. Maytag was made up of five major business units: Maytag (major appliances), Amana (major appli- ances), Jenn-Air (kitchen appliances), Hoover (floor cleaning), and Dixie-Narco (vending-machine equipment). The company expected this initiative to save $150 million in annual operating expenses. Maytag was also engaged in a plant-efficiency exercise. The company was introducing major new lines in its Maytag and Hoover units that it expected to compete with the best products in the industry.

The U.S. major-appliance industry had historically been made up of four primary players: General Electric, Whirlpool, Maytag, and Electrolux. Recently, these compa- nies had experienced several challenges. First, the dramatic increase in steel prices, purportedly due to massive real investment in China, had increased industry produc- tion costs. Second, Asian manufacturers had begun to compete aggressively in their market. Third, products were becoming less easy to differentiate, leading to increased price competition. Tempering these effects, the buoyancy of the U.S. housing market had provided strong growth across the industry. Whirlpool had been particularly aggressive in its expansion efforts. In 2003, its sales growth was almost 11%, while operating margin was 6.8% and asset turnover was 1.7. In 2003, Whirlpool generated better ratios than Maytag across most dimensions.

Based on the business and environmental assessment, we take the view that Maytag will maintain its position in a deteriorating industry. We can adjust the naïve 2004 forecast (Exhibit 3) based on this assessment. We suspect that the increased entry by foreign competition and a stalling of the recent sales growth in the U.S. housing market will lead to zero sales growth for Maytag in 2004. We also expect the increased price competition and steel-price effect to lead to a further erosion of gross margins (to 16.0%). Although the company’s efforts to reduce overhead costs are under way, we expect that Maytag will not see any benefits from these efforts until 2005. Conse- quently, we estimate that operating expenses will return to their 2002 percentage of sales (13.8%). These assumptions give us an operating-margin estimate of 2.2%. We

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expect the increased competition and housing-market decline to reduce Maytag’s ability to work its current assets. We expect AR days to increase to 47.0, inventory turnover to decrease to 7.2%, and other-current-assets percentage to stay at 5%. Finally, we expect the productivity efforts to generate a small improvement in fixed-asset turnover. We project PPE turnover at 5.0% and other-noncurrent-asset turnover at 7.1%. These assumptions lead to an implied financial forecast. The resulting projected after-tax ROA is 2.2%. The forecast is thoughtful. It captures a coherent view of Maytag based on the company’s historical financial relationships, a grounding in the macroeconomic and industry reality, and incorporation of Maytag’s specific business strategy.

We recognize that we cannot anticipate all the events of 2004. Our forecast will inevitably be wrong. Nevertheless, we suspect that, by being thoughtful in our analy- sis, our forecast will provide a reasonable, unbiased expectation of future perform- ance. Exhibit 4 gives the actual 2004 results for Maytag. The big surprise was the substantial effect on sales growth and margin of an even more dramatic increase in steel prices. Maytag’s realized sales growth was actually negative, and gross margin dropped from 22% and 18% in 2002 and 2003, respectively, to 14% in 2004. Our asset assumptions were fairly close to the outcome. Although we did not complete a high-side and a low-side scenario in this simple example, we can hope that, had we done so, we could have appropriately assessed the sources and level of uncertainty of our forecast.

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EXHIBIT 1 | Financial Statements for Maytag Corporation (in millions of dollars)

2002 2003

(1) Sales 4,666 4,792 (2) Cost of sales 3,661 3,932

(3) Gross profit 1,005 860 (4) Operating expenses 645 631

(5) Operating profit 360 229

(6) Accounts receivable 586 597 (7) Inventory 468 468 (8) Other current assets 268 239 (9) Net property, plant, & equipment 1,066 1,047

(10) Other noncurrent assets 715 673

(11) Total assets 3,104 3,024

Sales growth 11.5% 2.7% Gross margin (3"1) 21.5% 17.9% Operating exp/Sales (4"1) 13.8% 13.2% Operating margin (5"1) 7.7% 4.8%

Receivable turnover (1"6) 8.0 8.0 Accounts receivable days (6"1*365 days) 45.9 45.5 Inventory turnover (2"7) 7.8 8.4 Inventory days (7"2*365 days) 46.7 43.5 Other current assets/Sales (8"1) 5.7% 5.0% PPE turnover (1/9) 4.4 4.6 Other noncurrent asset turnover (1/10) 6.5 7.1 Total asset turnover (1/11) 1.5 1.6 Return on assets (5*(1!.35)/11) 7.5% 4.9%

Note: Although including both turnover and days ratios is redundant, doing so illustrates the two perspectives.

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EXHIBIT 2 | Naïve Financial Forecast for Maytag Corporation (in millions of dollars)

2002 2003 2004E

(1) Sales 4,666 4,792 4,921 Sales03 * (1 & Sales growth) (2) Cost of sales 3,661 3,932 4,038 Sales04 ! Gross profit

(3) Gross profit 1,005 860 883 Sales04 * Gross margin (4) Operating expenses 645 631 648 Sales04 * Operating

exp/Sales (5) Operating profit 360 229 235 Gross profit ! Operating

expenses

(6) Accounts receivable 586 597 613 Sales04 * AR days/365 (7) Inventory 468 468 585 Cost of sales/Inv turnover (8) Other current assets 268 239 245 Sales04 * Other curr

assets/Sales (9) Net property, plant, &

equipment 1,066 1,047 1,075 Sales04"PPE turnover (10) Other noncurrent assets 715 673 691 Sales04"Other NC

asset turnover

(11) Total assets 3,104 3,024 3,210

Sales growth 11.5% 2.7% 2.7% Estimate Gross margin (3/1) 21.5% 17.9% 17.9% Estimate Operating exp/Sales (4/1) 13.8% 13.2% 13.2% Estimate Operating margin (5/1) 7.7% 4.8% 4.8%

Receivable turnover (1/6) 8.0 8.0 8.0 Accounts receivable days

(6/1*365 days) 45.9 45.5 45.5 Estimate Inventory turnover (2/7) 7.8 8.4 6.9 Estimate Inventory days

(7/2*365 days) 46.7 43.5 52.9 Other current assets/

Sales (8/1) 5.7% 5.0% 5.0% Estimate PPE turnover (1/9) 4.4 4.6 4.6 Estimate Other noncurrent asset

turnover (1/10) 6.5 7.1 7.1 Estimate Total asset turnover (1/11) 1.5 1.6 1.5 Return on assets

(5*(1!.35)/11) 7.5% 4.9% 4.8%

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EXHIBIT 3 | Revised Financial Forecast for Maytag Corporation (in millions of dollars)

2002 2003 2004E

(1) Sales 4,666 4,792 4,792 Sales03 * (1 & Sales growth) (2) Cost of sales 3,661 3,932 4,025 Sales04 ! Gross profit

(3) Gross profit 1,005 860 767 Sales04 * Gross margin (4) Operating expenses 645 631 661 Sales04 * Operating

exp"Sales

(5) Operating profit 360 229 105 Gross profit ! Operating expenses

(6) Accounts receivable 586 597 617 Sales04 * AR days/365 (7) Inventory 468 468 559 Cost of sales/Inv turnover (8) Other current assets 268 239 239 Sales04 * Other

curr assets/Sales (9) Net property, plant, &

equipment 1,066 1,047 958 Sales04"PPE turnover (10) Other noncurrent 715 673 675 Sales04"Other

assets NC asset turnover

(11) Total assets 3,104 3,024 3,048

Sales growth 11.5% 2.7% 0.0% Estimate Gross margin (3/1) 21.5% 17.9% 16.0% Estimate Operating exp/Sales (4/1) 13.8% 13.2% 13.8% Estimate Operating margin (5/1) 7.7% 4.8% 2.2%

Receivable turnover (1/6) 8.0 8.0 7.8 Accounts receivable days

(6/1*365 days) 45.9 45.5 47.0 Estimate Inventory turnover (2/7) 7.8 8.4 7.2 Estimate Inventory days

(7/2*365 days) 46.7 43.5 50.7 Other current assets/

Sales (8/1) 5.7% 5.0% 5.0% Estimate PPE turnover (1/9) 4.4 4.6 5.0 Estimate Other noncurrent asset

turnover (1/10) 6.5 7.1 7.1 Estimate Total asset turnover (1/11) 1.5 1.6 1.6 Return on assets

(5*(1 ! .35)/11) 7.5% 4.9% 2.2%

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EXHIBIT 4 | Actual Financial Performance of Maytag Corporation (in millions of dollars)

2002 2003 2004

(1) Sales 4,666 4,792 4,722 (2) Cost of sales 3,661 3,932 4,062

(3) Gross profit 1,005 860 660 (4) Operating expenses 645 631 625

(5) Operating profit 360 229 35

(6) Accounts receivable 586 597 630 (7) Inventory 468 468 515 (8) Other current assets 268 239 300 (9) Net property, plant, & equipment 1,066 1,047 921

(10) Other noncurrent assets 715 673 653

(11) Total assets 3,104 3,024 3,019

Sales growth 11.5% 2.7% !1.5% Gross margin (3/1) 21.5% 17.9% 14.0% Operating exp/Sales (4/1) 13.8% 13.2% 13.2% Operating margin (5/1) 7.7% 4.8% 0.7%

Receivable turnover (1/6) 8.0 8.0 7.5 Accounts receivable days (6/1*365 days) 45.9 45.5 48.7 Inventory turnover (2/7) 7.8 8.4 7.9 Inventory days (7/2*365 days) 46.7 43.5 46.3 Other current assets/Sales (8/1) 5.7% 5.0% 6.4% PPE turnover (1/9) 4.4 4.6 5.1 Other noncurrent asset turnover (1/10) 6.5 7.1 7.2 Total asset turnover (1/11) 1.5 1.6 1.6 Return on assets (5*(1 ! .35)/11) 7.5% 4.9% 0.8%

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The Financial Detective, 2005

Financial characteristics of companies vary for many reasons. The two most promi- nent drivers are industry economics and firm strategy.

Each industry has a financial norm around which companies within the industry tend to operate. An airline, for example, would naturally be expected to have a high proportion of fixed assets (airplanes), while a consulting firm would not. A steel manufacturer would be expected to have a lower gross margin than a pharmaceutical manufacturer because commodities such as steel are subject to strong price competi- tion, while highly differentiated products like patented drugs enjoy much more pricing freedom. Because of unique economic features of each industry, average financial statements will vary from one industry to the next.

Similarly, companies within industries have different financial characteristics, in part, because of the diverse strategies that can be employed. Executives choose strate- gies that will position their company favorably in the competitive jockeying within an industry. Strategies typically entail making important choices in how a product is made (e.g., capital intensive versus labor intensive), how it is marketed (e.g., direct sales versus the use of distributors), and how the company is financed (e.g., the use of debt or equity). Strategies among companies in the same industry can differ dra- matically. Different strategies can produce striking differences in financial results for firms in the same industry.

The following paragraphs describe pairs of participants in a number of different industries. Their strategies and market niches provide clues as to the financial condition and performance that one would expect of them. The companies’ common-sized financial statements and operating data, as of early 2005, are presented in a standardized format in Exhibit 1. It is up to you to match the financial data with the company descriptions. Also, try to explain the differences in financial results across industries.

119

7CASE

This case was prepared by Sean Carr, under the direction of Robert F. Bruner. It was written as a basis for class discussion rather than to illustrate effective or ineffective handling of an administrative situation. Copyright © 2005 by the University of Virginia Darden School Foundation, Charlottesville, VA. All rights reserved. To order copies, send an e-mail to [email protected] No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means—electronic, mechanical, photocopying, recording, or otherwise—without the permission of the Darden School Foundation.

bru6171X_case07_119-124.qxd 11/24/12 2:31 PM Page 119

Zhang Cathy
Zhang Cathy
Zhang Cathy
Zhang Cathy

Health Products Companies A and B manufacture and market health-care products. One firm is the world’s largest prescription-pharmaceutical company. This firm has a very broad and deep pipeline of ethical pharmaceuticals, supported by a robust research and devel- opment budget. In recent years, the company has divested several of its nonpharma- ceutical businesses, and it has come to be seen as the partner of choice for licensing deals with other pharmaceutical and biotechnology firms.

The other company is a diversified health-products company that manufactures and mass markets a broad line of prescription pharmaceuticals, over-the-counter reme- dies (i.e., nonprescription drugs), consumer health and beauty products, and medical diagnostics and devices. For its consumer segment, brand development and manage- ment are a major element of this firm’s mass-market-oriented strategy.

Beer Of the beer companies, C and D, one is a national brewer of mass-market consumer beers sold under a variety of brand names. This company operates an extensive network of breweries and distribution systems. The firm also owns a number of beer-related businesses, such as snack and aluminum-container manufacturing, and several major theme parks.

The other company produces seasonal and year-round beers with smaller produc- tion volume and higher prices. This company outsources most of its brewing activity. The firm is financially conservative, and has recently undergone a major cost-savings initiative to counterbalance the recent surge in packaging and freight costs.

Computers Companies E and F sell computers and related equipment. One company focuses exclusively on mail-order sales of built-to-order PCs, including desktops, laptops, notebooks, servers, workstations, printers, and handheld devices. The company is an assembler of PC components manufactured by its suppliers. The company allows its customers to design, price, and purchase through its Web site.

The other company sells a highly differentiable line of computers, consumer- oriented electronic devices, and a variety of proprietary software products. Led by its charismatic founder, the company has begun to recover from a dramatic decline in its market share. The firm has an aggressive retail strategy intended to drive traffic through its stores and to expand its installed base of customers by showcasing its products in a user-friendly retail atmosphere.

Books and Music The book and music retailers are companies G and H. One focuses on selling pri- marily to customers through a vast retail-store presence. The company is the leader in traditional book retailing, which it fosters through its “community store” concept

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and regular discount policy. The firm also maintains an online presence and owns a publishing imprint.

The other company sells books, music, and videos solely through its Internet Web site. While more than three-quarters of its sales are media, it also sells electronics and other general merchandise. The firm has only recently become profitable, and it has followed an aggressive strategy of acquiring related online businesses in recent years.

Paper Products Companies I and J are both paper manufacturers. One company is the world’s largest maker of paper, paperboard, and packaging. This vertically integrated company owns timberland; numerous lumber, paper, paperboard, and packing-products facilities; and a paper-distribution network. The company has spent the last few years rationalizing capacity by closing inefficient mills, implementing cost-containment initiatives, and selling nonessential assets.

The other firm is a small producer of printing, writing, and technical specialty papers, as well as towel and tissue products. Most of the company’s products are mar- keted under branded labels. The company purchases the wood fiber used in its paper- making process on the open market.

Hardware and Tools Companies K and L manufacture and sell hardware and tools. One of the companies is a global manufacturer and marketer of power tools and power-tool accessories, hardware and home-improvement products, and fastening systems. The firm sells pri- marily to retailers, wholesalers, and distributors. Its products appear under a variety of well-known brand names and are geared for the end user.

The other tool company manufactures and markets high-quality precision tools and diagnostic-equipment systems for professional users. The firm offers a broad range of products, which it sells via its own technical representatives and mobile fran- chise dealers. The company also provides financing for franchisees and for customers’ large purchases.

Retailing Companies M and N are two large discount retailers. One firm carries a wide variety of nationally advertised general merchandise. The company is known for its low prices, breadth of merchandise, and volume-oriented strategy. Most of its stores are leased and are located near the company’s expanding network of distribution centers. The company has begun to implement plans to expand both internationally and in large urban areas.

The other firm is a rapidly growing chain of upscale discount stores. The company competes by attempting to match other discounters’ prices on similar merchandise and by offering deep discounts on its differentiated items. Additionally, the company has partnerships with several leading designers. Recently, the firm has divested several

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nondiscount department-store businesses. To support sales and earnings growth, this company offers credit to qualified customers.

Newspapers Companies O and P own newspapers. One is a diversified media company that generates most of its revenues through newspapers sold around the country and around the world. Because the company is centered largely on one product, it has strong central controls. Competition for subscribers and advertising revenues in this firm’s segment is fierce. The company has also recently built a large office building for its headquarters.

The other firm owns a number of newspapers in relatively small communities throughout the Midwest and the Southwest. Some analysts view this firm as holding a portfolio of small local monopolies in newspaper publishing. This company has a significant amount of goodwill on its balance sheet, stemming from acquisitions. Key to this firm’s operating success is a strategy of decentralized decision making and administration.

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EXHIBIT 1 | Common-Sized Financial Data and Ratios

Health Prod. Beer Computers Books & Music Paper Tools Retail Newspapers

Assets A B C D E F G H I J K L M N O P

Cash & Short-Term Investments 24.2 16.1 1.4 55.6 42.2 67.9 54.8 16.2 7.6 5.9 9.3 6.5 4.6 7.0 0.6 1.1 Receivables 12.8 8.1 4.3 11.9 19.0 13.0 nmf 2.3 8.8 10.9 18.9 23.7 1.4 17.0 4.6 9.9 Inventories 7.0 5.4 4.3 11.7 2.0 1.3 14.8 38.6 7.9 14.4 17.8 14.9 24.5 16.7 0.8 0.8 Current Assets-Other 7.2 2.5 1.3 2.4 9.5 5.5 8.6 2.6 3.0 1.4 7.0 6.9 1.5 2.5 0.7 3.8 Current Assets-Total 51.2 32.1 11.2 81.7 72.8 87.6 78.2 59.7 27.2 32.6 52.9 52.1 32.0 43.1 6.6 15.5 Net Fixed Assets 19.6 14.9 54.7 16.0 7.3 8.8 7.6 24.4 50.8 62.5 13.6 13.7 57.0 52.2 14.1 34.6 Assets-Other 6.9 3.8 7.2 1.0 1.3 2.4 9.3 4.9 5.4 3.1 11.8 8.9 2.0 4.0 0.1 7.2 Intangibles 22.2 46.1 7.4 1.3 0.0 1.2 4.4 11.1 14.6 1.9 21.4 22.3 9.0 0.6 76.8 37.1 Investments & Advances 0.1 3.1 2.9 0.0 18.6 0.0 0.0 0.0 0.0 0.0 0.0 3.0 0.0 0.0 0.7 0.0 Assets-Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Liabilities & Equity

Accounts Payable 9.8 2.2 7.4 9.1 38.3 18.0 35.1 22.6 6.7 8.5 8.4 8.5 18.0 17.9 1.4 4.8 Debt in Current Liabilities 0.5 9.1 0.0 0.0 0.0 0.0 0.1 0.0 1.5 0.0 3.5 5.6 6.5 1.6 0.8 14.9 Income Taxes Payable 2.8 1.6 0.9 1.7 0.0 0.0 0.0 0.0 0.0 1.2 0.9 1.0 1.1 0.9 0.3 nmf Current Liabilities-Other 13.0 8.5 3.8 13.7 22.6 15.3 14.7 17.6 6.1 7.1 19.5 14.4 10.1 5.1 5.1 8.7 Current Liabilities-Total 26.1 21.4 12.2 24.4 60.9 33.3 49.9 40.2 14.2 16.7 32.4 29.4 35.7 25.5 7.5 28.3 LT Debt 4.8 5.9 51.2 0.0 2.2 0.0 56.9 7.4 41.3 18.3 21.7 8.9 19.7 28.0 14.4 11.9 Deferred Taxes 0.8 10.2 10.7 1.9 0.0 0.0 nmf 5.9 5.0 12.0 3.1 3.3 nmf 3.0 15.0 3.3 Liabilities-Other 8.6 7.3 9.5 0.7 8.9 3.7 0.2 11.0 10.9 12.4 14.6 8.9 2.5 3.2 0.7 17.5 Liabilities-Total 40.3 44.8 83.5 27.1 72.1 36.9 107.0 64.7 75.9 59.5 71.8 51.5 58.9 59.7 37.5 64.5 Stockholders’ Equity 59.7 55.2 16.5 72.9 27.9 63.1 (7.0) 35.3 24.1 40.5 28.2 48.5 41.1 40.3 62.5 35.5 Total Liabilities & Equity 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Income/Expenses

Sales-Net 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Cost of Goods Sold 23.9 11.1 53.9 38.5 81.0 70.9 75.8 69.5 75.3 82.9 61.0 51.6 75.3 67.1 49.7 40.5 Gross Profit 76.1 88.9 46.1 61.5 19.0 29.1 24.2 30.5 24.7 17.1 39.0 48.4 24.7 32.9 50.3 59.5 SG&A Expense 44.5 46.7 17.3 50.5 9.7 23.1 16.9 21.8 12.0 7.3 24.8 38.9 17.9 22.5 23.0 39.7 Depreciation 4.5 9.7 6.2 2.0 0.7 1.8 1.1 3.7 6.1 5.8 2.6 2.5 1.5 2.7 7.0 4.1 Earnings Before Interest &Taxes 27.2 32.5 22.5 9.0 8.6 4.2 6.2 5.0 6.6 4.0 11.7 6.9 5.3 7.7 20.2 15.6 Nonoperating Income (Expense) 0.7 1.1 2.9 0.3 0.4 0.7 0.3 0.1 0.4 0.1 0.6 0.1 0.8 0.0 1.3 0.4 Interest Income (Expense) (0.7) 0.7 2.9 0.0 0.0 0.0 1.5 0.3 3.3 1.0 1.1 1.0 0.5 1.0 1.9 1.6 Special Items-Income (Expense) (0.0) (6.3) 0.2 0.0 0.0 (0.3) 0.1 (0.3) (0.8) 0.0 0.0 (1.0) 0.0 (0.2) 0.0 (0.1) Pretax Income 27.1 26.7 22.8 9.2 9.0 4.6 5.1 4.5 2.9 3.1 11.2 5.1 5.6 6.5 19.7 14.4 Income Taxes-Total 9.1 5.1 7.8 3.5 2.8 1.3 (3.4) 1.9 0.8 1.2 3.0 1.6 2.0 2.4 7.1 5.6 Net Income (Loss) 18.0 21.6 15.0 5.8 6.2 3.3 8.5 2.9 (0.1) 2.0 8.4 3.4 3.6 6.8 12.6 8.9

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EXHIBIT 1 | Common-Sized Financial Data and Ratios (Continued)

Health Prod. Beer Computers Books & Music Paper Tools Retail Newspapers

Market Data A B C D E F G H I J K L M N O P

Beta 0.65 0.85 0.55 0.60 1.20 1.05 1.70 0.51 1.15 1.10 1.00 1.00 0.85 1.10 0.85 0.90 Price/Earnings 22.29 22.32 16.85 19.73 30.48 41.85 27.32 21.63 30.97 33.78 13.64 23.01 18.97 24.19 20.54 13.29 Price to Book 5.93 3.08 13.99 2.56 17.46 5.13 nmf 2.36 1.91 1.80 4.65 1.85 4.23 3.64 2.07 3.09 Dividend Payout 38.21 46.28 33.16 0.00 0.00 0.00 0.00 0.00 101.46 86.16 15.30 70.62 21.56 14.85 37.53 30.81

Liquidity

Current Ratio 1.96 1.50 0.92 3.35 1.20 2.63 1.57 1.49 1.91 1.94 1.63 1.77 0.90 1.69 0.88 0.55 Quick Ratio 1.42 1.13 0.47 2.77 1.01 2.43 nmf 0.46 1.15 1.00 0.87 1.03 0.17 0.94 0.69 0.39

Asset Management

Inventory Turnover 3.08 0.93 12.60 7.44 67.96 74.78 13.56 2.42 6.75 7.11 3.89 3.59 7.69 5.86 33.35 43.48 Receivables Turnover 7.06 5.47 21.87 18.68 12.23 8.28 nmf 72.11 8.68 11.64 5.82 4.42 192.73 8.31 10.98 8.50 Fixed Assets Turnover 4.67 2.86 1.72 12.67 30.68 12.03 29.42 6.54 1.43 1.86 7.63 7.50 4.50 2.77 3.43 2.59

Debt Management

Total Debt/Total Assets 5.34 14.99 51.19 0.00 2.18 0.00 56.94 7.42 42.78 18.36 25.21 14.45 26.16 29.54 15.22 26.81 LT Debt/Shareholders’ Equity 8.06 10.66 310.28 0.00 7.79 0.00 nmf 21.01 171.21 45.32 77.03 18.29 47.92 69.34 23.04 33.66 Interest Coverage After Tax 27.34 32.57 6.25 nmf 191.19 93.00 6.49 9.52 1.56 2.98 8.62 4.55 8.86 4.92 7.83 6.69

DuPont Analysis

Net Profit Margin 17.97 21.58 15.00 5.76 6.18 3.33 8.50 2.53 1.87 1.96 8.17 3.39 3.59 4.02 12.65 8.86 Asset Turnover 0.93 0.44 0.97 2.23 2.31 1.11 2.56 1.43 0.73 1.20 1.11 1.09 2.54 1.47 0.48 0.85 Return on Equity 26.75 16.64 83.97 15.95 46.92 5.44 nmf 10.58 5.79 5.71 28.30 7.36 20.79 14.47 9.86 20.89

Sources of data: S&P’s Research Insight; Value Line Investment Survey.

nmf = not a meaningful figure.

124

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Krispy Kreme Doughnuts, Inc. As the millennium began, the future for Krispy Kreme Doughnuts, Inc., smelled sweet. Not only could the company boast iconic status and a nearly cultlike follow- ing, it had quickly become a darling of Wall Street. Less than a year after its initial public offering, in April 2000, Krispy Kreme shares were selling for 62 times earn- ings and, by 2003, Fortune magazine had dubbed the company “the hottest brand in America.” With ambitious plans to open 500 doughnut shops over the first half of the decade, the company’s distinctive green-and-red vintage logo and unmistakable “Hot Doughnuts Now” neon sign had become ubiquitous.

At the end of 2004, however, the sweet story had begun to sour as the company made several accounting revelations, after which its stock price sank. From its peak in August 2003, Krispy Kreme’s stock price plummeted more than 80% in the next 16 months. Investors and analysts began asking probing questions about the com- pany’s fundamentals, but even by the beginning of 2005, many of those questions remained unanswered. Exhibits 1 and 2 provide Krispy Kreme’s financial statements for fiscal-years 2000 through 2004. Was this a healthy company? What had happened to the company that some had thought would become the next Starbucks? If almost everyone loved the doughnuts, why were so many investors fleeing the popular doughnut maker?

Company Background Krispy Kreme began as a single doughnut shop in Winston-Salem, North Carolina, in 1937, when Vernon Rudolph, who had acquired the company’s special dough- nut recipe from a French chef in New Orleans, started making and selling dough- nuts wholesale to supermarkets. Within a short time, Rudolph’s products became so popular that he cut a hole in his factory’s wall to sell directly to customers— thus was born the central Krispy Kreme retail concept: the factory store. By the late 1950s, Krispy Kreme had 29 shops in 12 states, many of which were operated by franchisees.

125

8CASE

This case was prepared by Sean Carr (MBA ’03), under the direction of Robert F. Bruner of the Darden Graduate School of Business Administration. It was written as a basis for class discussion rather than to illustrate effective or ineffective handling of an administrative situation. Copyright © 2005 by the University of Virginia Darden School Foundation, Charlottesville, VA. All rights reserved. To order copies, send an e-mail to [email protected] No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means—electronic, mechanical, photocopying, recording, or otherwise—without the permission of the Darden School Foundation.

bru6171X_case08_125-142.qxd 11/24/12 2:32 PM Page 125

After Rudolph’s death, in 1973, Beatrice Foods bought the company and quickly expanded it to more than 100 locations. Beatrice introduced other products, such as soups and sandwiches, and cut costs by changing the appearance of the stores and substituting cheaper ingredients in the doughnut mixture. The business languished, however, and by the early 1980s, Beatrice put the company up for sale.

A group of franchisees led by Joseph McAleer, who had been the first Krispy Kreme franchisee, completed a leveraged buyout of the company for $24 million in 1982. McAleer brought back the original doughnut formula and the company’s traditional logo. It was also around this time that the company introduced the “Hot Doughnuts Now” neon sign, which told customers when fresh doughnuts were coming off the line. The company still struggled for a while, but by 1989, Krispy Kreme had become debt- free and had slowly begun to expand. The company focused on its signature dough- nuts and added branded coffee in 1996. Scott Livengood, who became CEO in 1998 and chair the following year, took the company public in April 2000 in what was one of the largest initial public offerings (IPO) in recent years; one day after the offering, Krispy Kreme’s share price was $40.63, giving the firm a market capitalization of nearly $500 million.

Krispy Kreme’s Business After the company’s IPO, Krispy Kreme announced an aggressive strategy to expand the number of stores from 144 to 500 over the next five years. In addition, the com- pany planned to grow internationally, with 32 locations planned for Canada and more for the United Kingdom, Mexico, and Australia. Exhibit 3 provides an overview of the company’s store openings.

Krispy Kreme Doughnuts generated revenues through four primary sources: on-premises retail sales at company-owned stores (accounting for 27% of rev- enues); off-premises sales to grocery and convenience stores (40%); manufactur- ing and distribution of product mix and machinery (29%); and franchisee royalties and fees (4%). In addition to the traditional domestic retail locations, the company sought growth through smaller “satellite concepts,” which relied on factory stores to provide doughnuts for reheating, as well as the development of the international market.

• On-premises sales: Each factory store allowed consumers to see the production of doughnuts; Krispy Kreme’s custom machinery and doughnut-viewing areas cre- ated what the company called a “doughnut theater.” In that way, Krispy Kreme attempted to differentiate itself from its competition by offering customers an ex- perience rather than simply a product. Each factory store could produce between 4,000-dozen and 10,000-dozen doughnuts a day, which were sold both on- and off-premises.

• Off-premises sales: About 60% of off-premises sales were to grocery stores, both in stand-alone cases and on store shelves. The remainder were sold to convenience stores (a small percentage were also sold as private label). The company main- tained a fleet of delivery trucks for off-premises sales.

126 Part Two Financial Analysis and Forecasting

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• Manufacturing and distribution: Krispy Kreme’s Manufacturing and Distribution (KKM&D) division provided the proprietary doughnut mixes and doughnut- making equipment to every company-owned and franchised factory store. This vertical integration allowed the company to maintain quality control and prod- uct consistency throughout the system. The company maintained its own manu- facturing facilities for its mixes and machines, and it provided quarterly service for all system units. All franchisees were required to buy mix and equipment from Krispy Kreme. KKM&D also included the company’s coffee-roasting operation, which supplied branded drip coffee to both company-owned and franchised stores.

• Franchise royalties and fees: In exchange for an initial franchise fee and annual royalties, franchisees received assistance from Krispy Kreme with operations, advertising and marketing, accounting, and other information-management systems. Franchisees that had relationships with the company before the IPO in 2000 were called Associates, and they typically had locations in heritage markets in the south- eastern United States. Associates were not responsible for opening new stores. New franchisees were called Area Developers, and they were responsible for de- veloping new sites and building in markets with high potential. Area Developers typically paid $20,000 to $50,000 in initial franchise fees and between 4.5% and 6% in royalties. Franchisees also contributed 1% of their annual total sales to the corporate advertising fund.

Roughly 60% of sales at a Krispy Kreme store were derived from the company’s signature product, the glazed doughnut. This differed from Dunkin’ Donuts, the com- pany’s largest competitor, for which the majority of sales came from coffee.

Holes in the Krispy Kreme Story On May 7, 2004, for the first time in its history as a public company, Krispy Kreme announced adverse results. The company told investors to expect earnings to be 10% lower than anticipated, claiming that the recent low-carbohydrate diet trend in the United States had hurt wholesale and retail sales. The company also said it planned to divest Montana Mills, a chain of 28 bakery cafés acquired in January 2003 for $40 million in stock, and would take a charge of $35 million to $40 million in the first quarter. In addition, Krispy Kreme indicated that its new Hot Doughnut and Coffee Shops were falling short of expectations and that it had plans to close three of them (resulting in a charge of $7 million to $8 million). Krispy Kreme’s shares closed down 30%, at $22.51 a share.

Then, on May 25, the Wall Street Journal published a story describing aggressive accounting treatment for franchise acquisitions made by Krispy Kreme.1 According to

Case 8 Krispy Kreme Doughnuts, Inc. 127

1Mark Maremont and Rick Brooks, “Krispy Kreme Franchise Buybacks May Spur New Concerns,” Wall Street Journal, 25 May 2004.

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the article, in 2003, Krispy Kreme had begun negotiating to purchase a struggling seven-store Michigan franchise. The franchisee owed the company several million dol- lars for equipment, ingredients, and franchise fees and, as part of the deal, Krispy Kreme asked the franchisee to close two underperforming stores and to pay Krispy Kreme the accrued interest on past-due loans. In return for those moves, Krispy Kreme promised to raise its purchase price on the franchise.

According to the Journal, Krispy Kreme recorded the interest paid by the fran- chisee as interest income and, thus, as immediate profit; however, the company booked the purchase cost of the franchise as an intangible asset, under reacquired franchise rights, which the company did not amortize. Krispy Kreme also allowed the Michigan franchise’s top executive to remain employed at the company after the deal, but shortly after the deal was completed, that executive left. In accordance with a severance agree- ment, this forced Krispy Kreme to pay the executive an additional $5 million, an expense the company also rolled into the unamortized-asset category as reacquired franchise rights.

The company denied any wrongdoing with this practice, maintaining it had accounted for its franchise acquisitions in accordance with generally accepted accounting principles (GAAP). On July 29, however, the company disclosed that the U.S. Securities and Exchange Commission (SEC) had launched an informal investigation related to “franchise reacquisitions and the company’s previously announced reduction in earnings guidance.” Observers remained skeptical. “Krispy Kreme’s accounting for franchise acquisitions is the most aggressive we have found,” said one analyst at the time. “We surveyed 18 publicly traded companies with franchise operations, four of which had reacquired franchises, and they had amortized them. That clearly seems like the right thing to do.”2 Over the previous three years, Krispy Kreme had recorded $174.5 million as intangible assets (reac- quired franchise rights), which the company was not required to amortize. On the date of the SEC announcement, Krispy Kreme’s shares fell another 15%, closing at $15.71 a share.

Analysts’ Reactions Since the heady days of 2001, when 80% of the equity analysts following Krispy Kreme were making buy recommendations for the company’s shares, the conventional wisdom about the company had changed. By the time the Wall Street Journal pub- lished the article about Krispy Kreme’s franchise-reacquisition accounting practices in May 2004, only 25% of the analysts following Krispy Kreme were recommending the company as a buy; another 50% had downgraded the stock to a hold. Exhibits 4 and 5 provide tables of aggregate analysts’ recommendations and EPS (earnings per share) estimates. As Krispy Kreme’s troubles mounted during the second half of 2004, analysts became increasingly pessimistic about the stock:

128 Part Two Financial Analysis and Forecasting

2“Did Someone Say Doughnuts? Yes, the SEC,” New York Times, 30 July 2004.

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As the headlines about the SEC investigation and Krispy Kreme’s other man- agement issues continued (e.g., Krispy Kreme’s chief operating officer stepped down on August 16, 2004), observers looked more critically at the fundamentals of Krispy Kreme’s business. In September, the Wall Street Journal published an article that focused attention on the company’s growth:

The biggest problem for Krispy Kreme may be that the company grew too quickly and di- luted its cult status by selling its doughnuts in too many outlets, while trying to impress Wall Street. The number of Krispy Kreme shops has nearly tripled since early 2000, with 427 stores in 45 states and four foreign countries. Some 20,000 supermarkets, convenience stores, truck stops, and other outside locations also sell the company’s doughnuts.

Another issue is that Krispy Kreme has relied for a significant chunk of profits on high profit-margin equipment that it requires franchisees to buy for each new store. Its profits have also been tied to growth in the number of franchised stores, because of the upfront fee each must pay.3

Case 8 Krispy Kreme Doughnuts, Inc. 129

Analyst Comment Date

John Ivankoe, In addition to the possibility of an earnings restatement, we believe many July 29, 2004 J.P. Morgan fundamental problems persist, exclusive of any “low-carb” impact. Securities, Inc. Declining new-store volumes are indicative of a worsening investment

model, and we believe restructured store-development contracts, a smaller store format, and reduced fees charged for equipment and ingredients sold to franchises are necessary.

Jonathan M. We believe that the challenges KKD faces, including margin compression, Oct. 12, 2004 Waite, lower returns, an SEC investigation, and product saturation, currently KeyBanc Capital outweigh the company’s positive drivers. In addition, shares of KKD are Markets trading at 16.6! CY05 earnings versus its 15% growth rate. As such,

we rate KKD shares HOLD.

John S. Glass, Krispy Kreme’s balance sheet became bloated over the past two years by Nov. 8, 2004 CIBC World acquisition goodwill that will likely need to be written down. As a result, Markets KKD’s return on invested capital has plunged to about 10% versus

18% two years ago prior to these acquisitions. We’d view a balance sheet write-down, including eliminating a significant portion of the $170" million in “reacquired franchise rights,” as a first step in the right direction.

Glenn M. Guard, In our opinion, management was not focused on operations the way it Nov. 23, 2004 Legg Mason should have been. As a result, too many units were opened in poor

locations as the company tripled its unit base since 2000. Additionally, we believe that franchisees were not trained properly as to how best to run their off-premises business. As a result, we believe many units are losing money off-premises, and franchisees are not motivated to grow that business. It also appears to us that basic blocking and tackling, execution, and cost discipline were seriously lacking in both the company and franchise systems, resulting in inefficiencies.

3“Sticky Situation,” Wall Street Journal, 3 September 2004.

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In September 2004, Krispy Kreme announced that it would reduce its number of new stores for the year to about 60 from the previously announced 120.

Restatement Announced On January 4, 2005, Krispy Kreme’s board of directors announced that the company’s previously issued financial statements for the fiscal year ended February 1, 2004 (FY2004) would be restated to “correct certain errors.” The board determined that the adjustments, which principally related to the company’s “accounting for the acquisitions of certain franchisees,” would reduce pretax income for FY2004 by between $6.2 mil- lion and $8.1 million. The company also expected to restate its financial statements for the first and second quarters of FY2005.

Krispy Kreme also said it would delay the filing of its financial reports until the SEC’s investigation had been resolved and the company’s own internal inquiry was complete. However, the failure of the company to provide its lenders with finan- cial statements by January 14, 2005, could constitute a default under the company’s $150-million credit facility. In the event of such a default, Krispy Kreme’s banks had the right to terminate the facility and to demand immediate payment for any out- standing amounts. Krispy Kreme’s failure to file timely reports also placed the company at risk of having its stock delisted from the New York Stock Exchange (NYSE). By the end of the next day, Krispy Kreme’s shares were trading at less than $10 a share.

Most analysts felt that Krispy Kreme’s lenders would grant the company a waiver on its credit-facility default, and few felt the company was truly at risk of being delisted from the NYSE. The board’s announcement, however, served only to raise more questions about the company. Since August 2003, the company had lost nearly $2.5 billion in its market value of equity. Exhibit 6 illustrates the stock-price patterns for Krispy Kreme relative to the S&P 500 Composite Index. Were the revelations about the company’s franchise accounting practices sufficient to drive that much value out of the stock? Were there deeper issues at Krispy Kreme that deserved scrutiny? Exhibits 7, 8, and 9 provide analytical financial ratios for Krispy Kreme and a group of comparable companies in the franchise food-service industry.

130 Part Two Financial Analysis and Forecasting

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132 Part Two Financial Analysis and Forecasting

EXHIBIT 2 | Balance Sheets

Fiscal Year Three Months Ended Ended

Jan. 30, Jan. 28, Feb. 3, Feb. 2, Feb. 1, May 2, Aug. 1, (in thousands) 2000 2001 2002 2003 2004 2004 2004

ASSETS Current Assets: Cash and cash equivalents 3,183 7,026 21,904 32,203 20,300 13,715 19,309 Short-term investments 0 18,103 15,292 22,976

Accounts receivable 17,965 19,855 26,894 34,373 45,283 47,434 44,329 Accounts receivable, affiliates 1,608 2,599 9,017 11,062 20,482 20,740 19,933 Other receivables 794 2,279 2,771 884 2,363 3,169 4,868 Notes receivable, affiliates 0 0 0 0 458 4,404 5,440 Inventories 9,979 12,031 16,159 24,365 28,573 32,974 33,076 Prepaid expenses 3,148 1,909 2,591 3,478 5,399 4,675 6,749 Income taxes refundable 861 2,534 1,963 7,946 7,449 8,139 Deferred income taxes 3,500 3,809 4,607 9,824 6,453 13,280 20,005 Assets held for sale 36,856 3,374 3,325

Total current assets 41,038 67,611 101,769 141,128 174,113 151,214 165,173 Property and equipment, net 60,584 78,340 112,577 202,558 281,103 301,160 297,154 Deferred income taxes 1,398 0 0 0 0 Long-term investments 0 17,877 12,700 4,344 0 Long-term notes receivable, affiliates 0 0 0 1,000 7,609 2,988 2,925 Investments in unconsolidated joint ventures 2,827 3,400 6,871 12,426 10,728 9,921 Reacquired franchise rights, goodwill, other intangibles 0 0 16,621 49,354 175,957 176,078 176,045 Other assets 1,938 4,838 8,309 5,232 9,456 12,315 10,390

Total assets 104,958 171,493 255,376 410,487 660,664 654,483 661,608

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EXHIBIT 2 | Balance Sheets (continued)

Fiscal Year Three Months Ended Ended

Jan. 30, Jan. 28, Feb. 3, Feb. 2, Feb. 1, May 2, Aug. 1, (in thousands) 2000 2001 2002 2003 2004 2004 2004

LIABILITIES AND SHAREHOLDERS’ EQUITY Current Liabilities: Accounts payable 13,106 8,211 12,095 14,055 18,784 18,866 18,817 Book overdraft 0 5,147 9,107 11,375 8,123 12,670 13,107 Accrued expenses 14,080 21,243 26,729 20,981 23,744 27,107 32,249 Arbitration award 0 0 0 9,075 0 Revolving line of credit 0 3,526 3,871 0 0 Current maturities of long-term debt 2,400 0 731 3,301 2,842 4,663 5,566 Short-term debt 0 0 0 900 0 Income taxes payable 0 41 0 0 0

Total current liabilities 29,586 38,168 52,533 59,687 53,493 63,306 69,739 Deferred income taxes 0 579 3,930 9,849 6,374 16,468 25,564 Compensation deferred (unpaid) 990 1,106 0 0 0 Revolving lines of credit 0 0 0 7,288 87,000 72,000 62,000 Long-term debt, net of current portion 20,502 0 3,912 49,900 48,056 58,469 50,135 Accrued restructuring expenses 4,259 3,109 0 0 0 Other long-term obligations 1,866 1,735 4,843 5,218 11,211 10,774 12,078

Total long-term liabilities 27,617 6,529 12,685 72,255 152,641 157,711 149,777

Minority interest 1,117 2,491 5,193 2,323 2,815 2,593

SHAREHOLDERS’ EQUITY: Common stock, no par value, 300,000 shares authorized; issued and outstanding 85,060 121,052 173,112 294,477 296,812 299,865 Common stock, 10 par value, 1,000 shares authorized; issued and outstanding 4,670 Paid-in capital 10,805 Unearned compensation (188) (186) (119) (62) (47) (31) Notes receivable, employees (2,547) (2,349) (2,580) (558) (383) (383) (383) Nonqualified employee benefit plan assets (126) (138) (339) (369) (264) (264) Nonqualified employee benefit plan liability 126 138 339 369 264 264 Accumulated other comprehensive income (loss) 609 456 (1,486) (1,315) (783) (768) Retained earnings 34,827 42,547 68,925 102,403 159,490 135,052 140,816

Total shareholders’ equity 47,755 125,679 187,667 273,352 452,207 430,651 439,499 Total liabilities and

shareholders’ equity 104,958 171,493 255,376 410,487 660,664 654,483 661,608

Source of data: Company filings with the Securities and Exchange Commission (SEC).

Case 8 Krispy Kreme Doughnuts, Inc. 133

bru6171X_case08_125-142.qxd 11/24/12 2:32 PM Page 133

EXHIBIT 3 | Store Growth

Jan. 30, Jan. 28, Feb. 3, Feb. 2, Feb. 1, Store growth 2000 2001 2002 2003 2004

Total company factory stores Beginning of period 61 58 63 75 99 Stores openings 2 8 7 14 28 Store closings (5) (3) (2) (3) (2) Stores acquired from franchisees 0 0 7 13 16 End of period 58 63 75 99 141 Net change (3) 5 12 24 42 % year-over-year growth 9% 19% 32% 42%

Total franchised factory stores Beginning of period 70 86 111 143 177 Unit openings 19 28 41 49 58 Unit closings (3) (3) (2) (2) (3) Stores transferred to company 0 0 (7) (13) (16) End of period 86 111 143 177 216 Net change 16 25 32 34 39 % year-over-year growth 29% 29% 24% 22%

Total factory stores Beginning of period 131 144 174 218 276 Store openings 21 36 48 63 86 Store closings (8) (6) (4) (5) (5) End of period 144 174 218 276 357 Net change 13 30 44 58 81 % year-over-year growth 21% 25% 27% 29%

% of total stores Company-owned 40.3% 36.2% 34.4% 35.9% 39.5% Franchised 59.7% 63.8% 65.6% 64.1% 60.5%

Source of data: Company reports, case writer’s analysis.

134 Part Two Financial Analysis and Forecasting

bru6171X_case08_125-142.qxd 11/24/12 2:32 PM Page 134

EXHIBIT 4 | Analysts’ Recommendations

Percentage Recommending:

Period Buy Sell Hold

14-Jun-01 80.0% 20.0% 0.0% 19-Jul-01 80.0% 20.0% 0.0%

16-Aug-01 80.0% 20.0% 0.0% 20-Sep-01 80.0% 20.0% 0.0% 18-Oct-01 80.0% 20.0% 0.0% 15-Nov-01 80.0% 20.0% 0.0% 20-Dec-01 80.0% 20.0% 0.0% 17-Jan-02 66.7% 33.3% 0.0% 14-Feb-02 57.1% 28.6% 14.3% 14-Mar-02 71.4% 28.6% 0.0% 18-Apr-02 66.7% 33.3% 0.0%

16-May-02 66.7% 33.3% 0.0% 20-Jun-02 71.4% 28.6% 0.0% 18-Jul-02 71.4% 28.6% 0.0%

15-Aug-02 71.4% 28.6% 0.0% 19-Sep-02 66.7% 33.3% 0.0% 17-Oct-02 57.1% 28.6% 14.3% 14-Nov-02 57.1% 28.6% 14.3% 19-Dec-02 50.0% 12.5% 37.5% 16-Jan-03 50.0% 12.5% 37.5% 20-Feb-03 62.5% 12.5% 25.0% 20-Mar-03 62.5% 12.5% 25.0% 17-Apr-03 62.5% 12.5% 25.0%

15-May-03 55.6% 11.1% 33.3% 19-Jun-03 66.7% 0.0% 33.3% 17-Jul-03 80.0% 0.0% 20.0%

14-Aug-03 83.3% 0.0% 16.7% 18-Sep-03 66.7% 16.7% 16.7% 16-Oct-03 66.7% 16.7% 16.7% 20-Nov-03 66.7% 16.7% 16.7% 18-Dec-03 42.9% 14.3% 42.9% 15-Jan-04 42.9% 14.3% 42.9% 19-Feb-04 28.6% 14.3% 57.1% 18-Mar-04 28.6% 14.3% 57.1% 15-Apr-04 37.5% 25.0% 37.5%

20-May-04 25.0% 25.0% 50.0% 17-Jun-04 25.0% 25.0% 50.0% 15-Jul-04 33.3% 11.1% 55.6%

19-Aug-04 28.6% 28.6% 42.9% 16-Sep-04 25.0% 37.5% 37.5% 14-Oct-04 14.3% 42.9% 42.9% 18-Nov-04 14.3% 42.9% 42.9% 16-Dec-04 14.3% 57.1% 28.6% 20-Jan-05 14.3% 57.1% 28.6%

Source of data: I/B/E/S (Thomson Financial /First Call).

Case 8 Krispy Kreme Doughnuts, Inc. 135

bru6171X_case08_125-142.qxd 11/24/12 2:32 PM Page 135

EXHIBIT 5 | Consensus EPS Estimates

Estimate (Mean) Estimate Date

$ 0.38 2-Jul-01 $ 0.43 24-Aug-01 $ 0.41 25-Oct-01 $ 0.44 16-Nov-01 $ 0.43 21-Dec-01 $ 0.62 8-Mar-02 $ 0.63 24-May-02 $ 0.63 3-Jun-02 $ 0.63 1-Jul-02 $ 0.64 29-Aug-02 $ 0.64 3-Sep-02 $ 0.63 8-Oct-02 $ 0.66 22-Nov-02 $ 0.65 10-Jan-03 $ 0.66 14-Feb-03 $ 0.87 20-Mar-03 $ 0.89 29-May-03 $ 0.90 30-Jul-03 $ 0.90 21-Aug-03 $ 0.91 15-Sep-03 $ 0.91 17-Dec-03 $ 0.92 27-Jan-04 $ 1.17 10-Mar-04 $ 1.00 7-May-04 $ 0.99 26-May-04 $ 0.98 24-Jun-04 $ 0.92 16-Aug-04 $ 0.59 27-Aug-04 $ 0.69 10-Sep-04 $ 0.65 13-Sep-04 $ 0.58 3-Nov-04 $ 0.45 23-Nov-04

Source of data: I/B/E/S (Thomson Financial/First Call).

136 Part Two Financial Analysis and Forecasting

bru6171X_case08_125-142.qxd 11/24/12 2:32 PM Page 136

EXHIBIT 6 | Stock-Price Patterns Relative to the S&P 500 Composite Index

Ap r-0

0

Ju n-

00

Au g-

00

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0

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0

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01

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In de

x (4

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0 !

1 .0

0)

S&P 500

Krispy Kreme

Source of data: Datastream.

Case 8 Krispy Kreme Doughnuts, Inc. 137

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bru6171X_case08_125-142.qxd 11/24/12 2:32 PM Page 138

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EXHIBIT 9 | Common-Sized Financial Statements: Limited-Service Restaurant Averages and Krispy Kreme (KKD)

2001 2002 2003 KKD 2003

Balance Sheet: Assets (%) Cash & equivalents 12.8 12.4 13.7 3.1 Trade receivables (net) 1.6 0.9 1.4 10.4 Inventory 4.0 3.3 3.8 4.3 All other current 2.6 2.6 3.5 8.6 Total current 21.0 19.2 22.4 26.4 Fixed assets (net) 54.7 57.0 55.0 42.5 Intangibles (net) 13.3 14.2 12.6 26.6 All other noncurrent 11.0 9.6 10.0 4.5 Total assets 100.0 100.0 100.0 100.0

Balance Sheet: Liabilities & Equity (%) Notes payable, short-term 4.7 5.6 5.8 0.0 Current maturity, long-term debt 6.1 6.0 6.8 0.4 Trade payables 9.2 7.4 9.3 2.8 Income taxes payable 0.2 0.2 0.3 0.0 All other current 13.9 16.9 14.0 4.8 Total current 34.1 36.1 36.4 8.1 Long-term debt 40.2 45.6 41.9 7.3 Deferred taxes 0.1 0.2 0.1 1.0 All other non-current 4.7 8.3 8.7 14.9 Shareholders’ equity 20.9 9.9 12.9 68.4 Total liabilities & equity 100.0 100.0 100.0 100.0

Income Statement (%) Net sales 100.0 100.0 100.0 100.0 Operating expenses 56.3 55.6 58.1 76.2 Operating profit 4.0 4.7 4.0 15.3 All other expenses (net) 1.3 1.6 1.5 1.1 Profit before taxes 2.7 3.0 2.5 14.2

Source of data: Annual Statement Studies: 2004–2005, The Risk Management Association.

Case 8 Krispy Kreme Doughnuts, Inc. 141

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The Body Shop International PLC 2001: An Introduction to Financial Modeling

Finance bored the pants off me. I fell asleep more times than not.1

—Anita Roddick, founder, The Body Shop International

Roddick, as self-righteous as she is ambitious, professes to be unconcerned [with financial results]. . . . “Our business is about two things: social change and action, and skin care,” she snaps. “Social change and action come first. You money-conscious people . . . just don’t understand.” Well, maybe we don’t, but we sure know this: Roddick is one hell of a promoter. . . . She and her husband, Gordon, own shares worth just under $300 million. Now that’s social action.2

One of our greatest frustrations at The Body Shop is that we’re still judged by the media and the City by our profits, by the amount of product we sell, whereas we want and have always wanted to be judged by our actions in the larger world, by the positive difference we make.3

—Anita Roddick

In the late 1990s, The Body Shop International PLC, previously one of the fastest growing manufacturer-retailers in the world, ran aground. Although the firm had an annual revenue growth rate of 20% in the early to middle 1990s, by the late 1990s, revenue growth slowed to around 8%. New retailers of the naturally based skin- and hair-care products entered the market, bringing intense competition for The Body

143

9CASE

1Anita Roddick, Body and Soul (London: Ebury Press, 1991), 105. 2Jean Sherman Chatzky, “Changing the World,” Forbes (2 March 1992): 87. 3Anita Roddick, Business as Unusual (London: Thorsons, 2000), 56.

This case was prepared by Susan Shank and John Vaccaro under the direction of Robert F. Bruner and Robert Conroy. It was written as a basis for class discussion rather than to illustrate effective or ineffective handling of an administrative situation. The financial support of the Batten Institute for case development is gratefully acknowledged. Copyright © 2001 by the University of Virginia Darden School Foundation, Charlottesville, VA. All rights reserved. To order copies, send an e-mail to [email protected] No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means—electronic, mechanical, photocopying, recording, or otherwise—without the permission of the Darden School Foundation.

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Shop. Amidst the competition, The Body Shop failed to maintain its brand image by becoming something of a mass-market line as it expanded into “almost every mall in America, as well as virtually every corner on Britain’s shopping streets.”4

Anita Roddick, founder of The Body Shop, stepped down as chief executive offi- cer (CEO) in 1998,5 after numerous unsuccessful attempts to reinvent the company. Patrick Gournay, an executive from the French food giant Danone SA came on board as CEO. However, problems persisted despite the management change. In fiscal year 2001, revenue grew 13%, but pretax profit declined 21%. Gournay said of the results, “This is below our expectations, and we are disappointed with the outcome.”6

Nonetheless, Gournay was confident that a newly implemented strategy would produce improved results. The strategy consisted of three principal objectives: “To enhance The Body Shop Brand through a focused product strategy and increased investment in stores; to achieve operational efficiencies in our supply chain by reduc- ing product and inventory costs; and to reinforce our stakeholder culture.”7

Suppose that Anita Roddick, the Shop’s founder and cochair of the board of direc- tors, and Patrick Gournay, CEO, came to you in the spring of 2001, looking for assis- tance in short- and long-term planning for The Body Shop. As a foundation for this work, you will need to estimate The Body Shop’s future earnings and financial needs. The chal- lenge of this advisory work should not be underestimated. Anita Roddick is a strong- willed decision-maker with little taste for finance or financial jargon. Your projections must not only be technically correct, but they must also yield practical insights and be straightforward. What you have to say and how you say it are equally important.

If you feel comfortable using Exhibit 8 to prepare the next three years of finan- cial statements and to demonstrate The Body Shop’s debt financing needs, you might be better served by scanning the next few sections on basic financial modeling and concentrating on the last section of the case (Roddick Wants to Know). From expe- rience, however, a vast number of students have found the following exercises to be invaluable in their early understanding of financial modeling.

An Overview of Financial Forecasting In seeking to respond to Roddick’s request, you can draw on at least two classic fore- casting methods and a variety of hybrids that use some of each method. The two classic forecasting methods are as follows:

T-account forecasting: This method starts with a base year of financial statements, such as last year’s. Entries through double-entry bookkeeping determine how each account will change and what the resulting new balances will be. While

144 Part Two Financial Analysis and Forecasting

4Sarah Ellisan, “Body Shop Seeks a Makeover—U.K. Cosmetics Retailer Confirms Sale Talks with Mexico’s Grupo Omnilife—A Long and Difficult Fall from Grace,” Wall Street Journal Europe, 8 June 2001. 5Anita Roddick remained on the company’s board of directors and, together with her husband Gordon Roddick, served as cochair. 6CEO report (The Body Shop International PLC’s preliminary results for the 53 weeks to March 3, 2001). 7CEO report (3 March 2001).

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exactly true to the mechanics of how funds flow through the firm, this method is cumbersome and may require a degree of forecast information about transac- tions that are unavailable to many analysts outside (and even inside) the firm.

Percentage-of-sales forecasting: This method starts with a forecast of sales and then estimates other financial statement accounts based on some presumed relation- ship between sales and that account. While simple to execute, this technique is easily misused. For instance, some naive analysts may assume that operational capacity can increase in fractional amounts parallel to increases in sales, but can an airline company really buy only half a jumbo jet? Operational capacity usually increases in lump amounts, rather than in smooth amounts. The lesson here is that when you use this technique, you should scrutinize the percentage- of-sales relationships to make sure they are reasonable.

The most widely used approach is a hybrid of these two. For instance, T-accounts are used to estimate shareholders’ equity and fixed assets. Percentage-of-sales is used to estimate income statements, current assets, and current liabilities, because these latter items may credibly vary with sales. Other items will vary as a percentage of accounts other than sales. Tax expense will usually be a percentage of pretax income, while dividends will vary with after-tax income, and depreciation will usually vary with gross fixed assets.

A Pencil-and-Paper Forecast As an introduction to financial modeling, we will walk through the construction of a forecasted income statement and balance sheet, first with pencil and paper (just visu- alizing the steps may suffice) and later with a spreadsheet. In either case, you are preparing a pro forma, or projected, income statement and balance sheet for The Body Shop for 2002 (income statement for the entire year and balance sheet for year-end). All values should be in British pounds (GBP). Use the following assumptions as a guide:

Sales: GBP422.733 million (a 13% increase over 2001) Cost of goods sold (COGS): 38% of sales Operating expenses: 50% of sales Interest expense: 6% of debt (about the current interest rate) Profit before tax: Sales ! COGS ! Depreciation and amortization (D&A) !

Interest Tax: 30% of profit before tax (the going corporate tax rate in Britain) Dividends: GBP10.9 million (same as the three previous years) Earnings retained: Profit after tax ! Dividends Current assets: 32% of sales Fixed assets: GBP110.6 million Total assets: Current assets " Fixed assets Current liabilities: 28% of sales Debt: Total assets ! Current liabilities " Shareholders’ equity Common equity: GBP121.6 million " Retentions to earnings

Case 9 The Body Shop International PLC 2001: An Introduction to Financial Modeling 145

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Income statement: Begin with sales, and use it to estimate COGS and operating expenses. For the time being, leave interest expense at zero, since we do not yet know the amount of debt. Estimate profit before tax, tax expense, profit after tax, dividends, and earnings retained.

Balance sheet: Estimate current assets as 32% of sales and add that to GBP110.6 million to get an estimate for total assets. Next, estimate current liabilities as 28% of sales and common equity. Debt becomes the “plug” figure that makes the two sides of the balance sheet balance. This amount is your estimate of the external financing needed by The Body Shop by year-end 2002. Estimate the plug by subtracting the amounts for current liabilities and common equity from total assets.

Iterate: Initially, you entered an interest expense of zero on the income statement, but this cannot be correct if debt is outstanding or if excess cash is invested in interest-earning instruments. This is a classic finance problem arising from the income statement and balance sheet’s dependence on each other. Interest expense is necessary to estimate retained earnings, which is necessary to esti- mate debt. Let’s call this the problem of circularity. The way to deal with this problem is to insert your best estimate of interest expense in the income state- ment (using 6% # debt), then to re-estimate the plug figure, then re-estimate interest expense, and so on. By iterating through the two statements five or six times, you will come to estimates of interest expense and debt that do not change very much. Stop iterating when changes become small.

A Spreadsheet Model Forecast Fortunately, the tedium of iterating can be eliminated with the aid of a computer and spreadsheet software such as Microsoft Excel. The specific commands reviewed here relate to Excel 2000. (These commands will appear in table form within the text.) The adaptation to other spreadsheet programs should be straightforward. Now, try the same forecast for The Body Shop using a computer spreadsheet.

Setup: Start with a clean spreadsheet. Set the recalculation mode to MANUAL so that the model will iterate only when you press CALC (F9). Also, set the number of iterations to 1 so that you will be able to see Excel re-estimate the plug figure and interest expense. You can set the number of iterations higher (Excel’s default is 100), but Excel will converge on a solution after five or six iterations, so a setting of 1 is best to see the iterations in action. The commands are listed in Table 1.

146 Part Two Financial Analysis and Forecasting

Choose the <Tools> menu and then the <Options> menu item. Next, choose the <Calcula- tions> tab; select the button next to <Manual>, and enter 1 in <Maximum Iterations>. Be sure the box next to <Iterations> is checked.

TABLE 1 | Excel Spreadsheet Commands

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Saving: As you develop your model, be sure to save it every five minutes or so, just in case.

Format: Use the format in Exhibit 1 as a guide to plan your worksheet. To facili- tate sensitivity analysis, it is generally best to place the Input Data at the top of the worksheet. Next, develop the income statement just as you did on pencil and paper. Use Exhibit 2 as your guide. Be sure to tie the cells to the proper percentage rate in the Input Data section. The first time through, enter 0 for the interest. (This is very important for the iteration to work properly.) We will return to it later.

Now do the balance sheet. Again, be sure to tie the balance sheet together by for- mulas. With the basic format laid out, go back and enter the formula to calculate inter- est as “Interest rate # Debt.” Press the (F9) key, and you should see the worksheet change. You should be able to press the (F9) key several more times until the numbers stop changing, which means the model has converged to a solution. You should have interest as exactly 6% of long-term liabilities and a balance sheet that balances.

Once you have seen how this works, you may want to have the model converge without having to press <CALC> several times. In order to do that, you must set the number of iterations you wish the spreadsheet to perform. Set the number of itera- tions back to 100 (Excel’s default), and allow the computer to recalculate automati- cally. See the Excel commands listed in Table 2.

Case 9 The Body Shop International PLC 2001: An Introduction to Financial Modeling 147

Choose the <Tools> menu, and then the <Options> menu item. Next, choose the <Calcula- tions> tab; click on <Automatic>, and enter 100 in <Maximum Iterations>. Be sure the box next to <Iterations> is checked.

TABLE 2 | Excel Spreadsheet Commands

Note: Changing your iterations setting, combined with the circularity of the debt plug and interest expense (later we’ll add the circularity of data tables), can lead to some confusing situations. It is easy to forget where you have your iterations set (more data tables lead to more circularity). When comparing your work to someone else’s, be sure that both of you have the same iterations setting and have hit (F9) the same number of times (be sure you either have no data tables or the same data tables). Your worksheet should now look like Exhibit 3.

Projecting Farther So far, you have managed to project The Body Shop’s financial statements through 2002. Now, extend your projection to years 2003 and 2004. See Table 3 for Excel commands. A simple way to do this is to copy your model for two additional years. Before copying the formulas from column B to columns C and D, make sure that any references to your Input Data (cells B3 through B12) are absolute references as opposed to relative references. An absolute reference means that when you copy

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cells B16 through B35 to other parts of your spreadsheet, the cells are still linked back to the originals (i.e., B5). Otherwise, the program assumes that the cells should be linked to new cells, such as C5. To make a reference absolute, put in dollar signs— $B$3, instead of B3. Now you should be ready to copy:

148 Part Two Financial Analysis and Forecasting

Select the range of your data by highlighting it in the worksheet. Choose the <Edit> menu and then the <Copy> menu item. Highlight the cells where you want the copy to go. Choose the <Edit> menu and then the <Paste> menu item.

TABLE 3 | Excel Spreadsheet Commands

Note that you will have to change the equity formula for 2003 and 2004. For 2003, make the formula equal to 2002’s equity plus 2003’s additions to retained earn- ings. In addition, you should make sales grow by compounding. To do that, take 2002’s sales # 2003’s expected sales growth rate (say 13%). As you enter those changes, you should see the effect ripple through your model.

When Debt is Negative Now modify the model to deal with the situation where the plug for debt is negative— this can happen routinely for firms with seasonal or cyclical sales patterns. Negative debt can be interpreted as excess cash. However, this is an odd way to show cash. A nonfinancial manager (like Anita Roddick) might not appreciate this type of pres- entation. The solution is to add a line for excess cash on the assets’ side of the bal- ance sheet and then to set up three new lines below the last entry in the balance sheet.

Name Formula

Trial assets Current assets " Fixed assets Trial liabilities and equity Current liabilities " equity Plug Trial assets – Trial liabilities

Now enter the formula for excess cash:

$IF(PLUG%0,!PLUG,0)

Instead of the word plug, you should use the cell address for the actual plug number. The formula for debt is the following.

$IF(PLUG&0,"PLUG,0)

See Exhibit 4 for an example of how your spreadsheet should look. To see how these modifications really work, change your COGS/SALES assumption to 0.45 and press (F9).

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With excess cash, you should generate interest income instead of interest expense. In the event of an excess cash balance, to have your model treat interest as income rather than expense, you need to modify your interest expense formula as follows.

$"(B6*B34)!(B6*B28)

An example of the finished results appears in Exhibit 5.

Explore Sensitivities After your model replicates the exhibit, you are ready to conduct a sensitivity analy- sis on the pro forma years by seeing how variations in the forecast assumptions will affect the financing requirements. A financial analyst might want to try the following variations, or more than one in combination.

• Suppose sales in 2002 will be GBP500 million.

• Suppose COGS runs at 45% of sales.

• Suppose dividends are increased to 60% of net income.

• Suppose The Body Shop must double its manufacturing capacity by adding a new GBP100-million facility in 2002.

• Assume inventories run higher than expected (model this by increasing current assets to 40% of sales).

• Assume that accounts receivable collections improve so that current assets run at 28% of sales.

• Assume that operating expenses increase faster than sales.

What happens to the plug value (i.e., debt) under these different circumstances? In general, which assumptions in the Input Data section of your spreadsheet seem to have the biggest effect on future borrowing needs?

The data table is an invaluable tool for conducting a sensitivity analysis. It automatically calculates debt, or whatever else you want it to focus on, as it varies across different values for a particular assumption—for instance, growth rates. In Excel, you can create a data table using a two-step process illustrated in the fol- lowing examples. Suppose you want to estimate The Body Shop’s debt required and excess cash generated at COGS/SALES ratios of 0.35, 0.38, 0.40, 0.42, 0.44, 0.45, and 0.48.

1. Set up the table. Move to a clean part of the spreadsheet and type the COGS/ SALES ratios (0.35, 0.38, 0.40, 0.42, 0.44, 0.45, and 0.48) in a column. At the top of the next column (one row above your first COGS/SALES ratio), enter the location of the value to be estimated, in this case, debt, or =B34. In the next column, type the cell location for excess cash, =B28. Your data table should be formatted as shown in Exhibit 6.

2. Enter the data table commands. Table 4 gives the commands for setting up the data table.

Case 9 The Body Shop International PLC 2001: An Introduction to Financial Modeling 149

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The additional circularity brought about by data tables can lead to some confus- ing results. To avoid this, be sure at this point to set the number of iterations to at least 10. The result should look like Exhibit 7.

The data table in Exhibit 7 reveals that at COGS/SALES ratios of 45%, the firm will need to borrow. This should trigger questions in your mind about what might cause that to happen, such as a price war or a surge in materials costs. Your spread- sheet format can tell you about some more sophisticated data-table formats. No finan- cial analyst can afford to ignore that valuable tool. Armed with that tool, it is easy to go back and try the variations in other input assumptions listed previously.

Note: Remember that data tables add more calculations that need to be iterated in your worksheet. When comparing your work to that of a fellow student, make cer- tain that your iterations are set the same and that you have roughly the same data tables in your files.

Roddick Wants to Know Now that you have completed a simplified forecast, prepare a forecast based on the full range of accounts as actually reported by The Body Shop in 2001. Exhibit 8 pres- ents the results for the past three years. Please forecast all of the accounts individu- ally for the next three years. You will see many familiar accounts, as well as some unusual accounts like minority interests.

For most accounts, you should extrapolate by using the same percentage of sales borne out by the preceding years’ experience. You might use an average of the three historical years. You might want to use only the most recent year, or if you notice a significant upward or downward trend in an account, try growing or shrinking the per- centage in the future years, according to your judgment. Whatever assumptions you decide upon, you should again isolate them at the top of your worksheet, so you can easily change an assumption and then have it flow through your worksheet. Addi- tionally, this is very important for calculating sensitivities later, as you want to be able to point to one cell as the Column Input Cell in a data table.

Make overdrafts the plug figure and base interest expense (at 6%) on the over- drafts, current portion of long-term debt, and long-term liabilities. If you skipped to this section without doing the exercise above, you may differ from your fellow stu- dents in your treatment of the case where debt is negative.

150 Part Two Financial Analysis and Forecasting

Highlight the cells that contain your COGS/SALES ratios and your cell references to Debt and Excess Cash. The cells to the right of your COGS/SALES ratios and below your cell ref- erences to Debt and Excess Cash are the cells to be filled in and should also be highlighted. Choose the <Data> menu and then the <Table> menu item. In the <Column Input Cell> box, enter the cell where your COGS/SALES assumption is B4. The computer will fill in the table.

TABLE 4 | Excel Spreadsheet Commands

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Make your own assumptions regarding sales growth. Make other assumptions as needed. Be prepared to report to Roddick your answers to these questions.

1. How did you derive your forecast? Why did you choose the base case assumptions that you did?

2. Based on your pro forma projections, how much additional financing will The Body Shop need during this period?

3. What are the three or four most important assumptions or key drivers in this fore- cast? What is the effect on the financing need of varying each of these assump- tions up or down from the base case? Intuitively, why are these assumptions so important?

4. Why are your findings relevant to a general manager like Roddick? What are the implications of these findings for her? What action should she take based on your analysis?

In discussing your analysis with Roddick, do not permit yourself to get mired in forecast technicalities or financial jargon. Focus your comments on your results. State them as simply and intuitively as you can. Do not be satisfied with simply present- ing results. Link your findings to recommendations, such as key factors to manage, opportunities to enhance results, and issues warranting careful analysis. Remember that Roddick plainly admits she finds finance boring. Whenever possible, try to express your analysis in terms that she finds interesting, including people, customers, quality of natural products, and the health and dynamism of her business. Good luck!

Case 9 The Body Shop International PLC 2001: An Introduction to Financial Modeling 151

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152 Part Two Financial Analysis and Forecasting

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35

1 2 3 4 5 6 7 8

A B

Input Data

SALES

SALES

INCOME STATEMENT

COGS/SALES

COGS

BALANCE SHEET

CURRENT ASSETS FIXED ASSETS TOTAL ASSETS

CURRENT LIABILITIES DEBT EQUITY TOTAL LIAB. & NET WORTH

422,733

110,600 121,600

2002

0.38 0.50 0.06 0.30

0.32 0.28

10,900

OPERATING EXPENSES/SALES

OPERATING EXPENSES

INTEREST RATE

INTEREST EXPENSE (INCOME) PROFIT BEFORE TAX

PROFIT AFTER TAX DIVIDENDS EARNINGS RETAINED

TAX

TAX RATE DIVIDENDS (Thousand pounds) CURR. ASSETS/SALES CURR. LIABS./SALES FIXED ASSETS STARTING EQUITY

2002

EXHIBIT 1 | Format for Developing a Spreadsheet Model

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Case 9 The Body Shop International PLC 2001: An Introduction to Financial Modeling 153

EXHIBIT 2 | Spreadsheet Formulas to Forecast 2002 Financials

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35

A B

Input Data

SALES

SALES

INCOME STATEMENT

COGS/SALES

COGS

BALANCE SHEET

CURRENT ASSETS FIXED ASSETS TOTAL ASSETS

CURRENT LIABILITIES DEBT EQUITY TOTAL LIAB. & NET WORTH

422,733

110,600 121,600

2002

0.38 0.50 0.06 0.30

0.32 0.28

10,900

OPERATING EXPENSES/SALES

OPERATING EXPENSES

INTEREST RATE

INTEREST EXPENSE (INCOME) PROFIT BEFORE TAX

PROFIT AFTER TAX DIVIDENDS EARNINGS RETAINED

TAX

TAX RATE DIVIDENDS (Thousand pounds) CURR. ASSETS/SALES CURR. LIABS./SALES FIXED ASSETS STARTING EQUITY

2002

"B3 "B4*B16 "B5*B16 "B6*B33

"B7*B20

"B10*B16

"B9*B16 "B11

"B20-B21

"B28"B29

"B12"B24

"B22-B23 "B8

"B16-B17-B18-B19

"B30-B32-B34

"B32"B33"B34

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154 Part Two Financial Analysis and Forecasting

EXHIBIT 3 | Basic Forecasting Results for 2002

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35

A B

Input Data

SALES

SALES

INCOME STATEMENT

COGS/SALES

COGS

BALANCE SHEET

CURRENT ASSETS FIXED ASSETS TOTAL ASSETS

CURRENT LIABILITIES DEBT EQUITY TOTAL LIAB. & NET WORTH

422,733

110,600 121,600

422,733 160,639

135,275 110,600 245,875

118,365

147,029 245,875

(19,520)

211,367

51,899 15,570 36,329 10,900 25,429

(1,171)

2002

0.38 0.50 0.06 0.30

0.32 0.28

10,900

OPERATING EXPENSES/SALES

OPERATING EXPENSES

INTEREST RATE

INTEREST EXPENSE (INCOME) PROFIT BEFORE TAX

PROFIT AFTER TAX DIVIDENDS EARNINGS RETAINED

TAX

TAX RATE DIVIDENDS (Thousand pounds) CURR. ASSETS/SALES CURR. LIABS./SALES FIXED ASSETS STARTING EQUITY

2002

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Case 9 The Body Shop International PLC 2001: An Introduction to Financial Modeling 155

EXHIBIT 4 | Adjusting to Reflect Excess Cash

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40

A B

Input Data

SALES

SALES

INCOME STATEMENT

COGS/SALES

COGS

BALANCE SHEET

EXCESS CASH CURRENT ASSETS FIXED ASSETS TOTAL ASSETS

CURRENT LIABILITIES DEBT EQUITY

TRIAL ASSETS TRIAL LIABILITIES AND EQUITY

$IF(B40%0,-B40,0)

$IF(B40&0,"B40,0)

PLUG: DEBT (EXCESS CASH)

TOTAL LIAB. & NET WORTH

422,733

110,600 121,600

2002

0.38 0.50 0.06 0.30

0.32 0.28

10,900

OPERATING EXPENSES/SALES

OPERATING EXPENSES

INTEREST RATE

INTEREST EXPENSE (INCOME) PROFIT BEFORE TAX

PROFIT AFTER TAX DIVIDENDS EARNINGS RETAINED

TAX

TAX RATE DIVIDENDS (Thousand pounds) CURR. ASSETS/SALES CURR. LIABS./SALES FIXED ASSETS STARTING EQUITY

2002

422,733 160,639 211,367

40,706 14,247 26,459 10,900 15,559

135,275

137,159

118,365

110,600

"(B6*B34)-(B6*B28)

"B29"B30"B28

"B33"B34"B35

"B29"B30 "B33"B35 "B38!B39

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156 Part Two Financial Analysis and Forecasting

EXHIBIT 5 | Finished Results for 2002 Reflecting Excess Cash

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40

A B

Input Data

SALES

SALES

INCOME STATEMENT

COGS/SALES

COGS

BALANCE SHEET

EXCESS CASH CURRENT ASSETS FIXED ASSETS TOTAL ASSETS

CURRENT LIABILITIES DEBT EQUITY

TRIAL ASSETS TRIAL LIABILITIES AND EQUITY PLUG: DEBT (EXCESS CASH)

TOTAL LIAB. & NET WORTH

422,733

110,600 121,600

2002

0.38 0.50 0.06 0.30

0.32 0.28

10,900

OPERATING EXPENSES/SALES

OPERATING EXPENSES

INTEREST RATE

INTEREST EXPENSE (INCOME) PROFIT BEFORE TAX

PROFIT AFTER TAX DIVIDENDS EARNINGS RETAINED

TAX

TAX RATE DIVIDENDS (Thousand pounds) CURR. ASSETS/SALES CURR. LIABS./SALES FIXED ASSETS STARTING EQUITY

2002

422,733 160,639 211,367

51,899 15,570 36,329

10,900 25,429

19,520

(1,171)

135,275 110,600 265,395

118,365

245,875 265,395 (19,520)

147,029 265,395

0

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EXHIBIT 6 | Setup for a Forecast with Data Table

1 2 3 4 5 6 7 8 9

10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40

A B DC E F

Input Data

SALES

SALES

INCOME STATEMENT

COGS/SALES

COGS

BALANCE SHEET

EXCESS CASH CURRENT ASSETS FIXED ASSETS TOTAL ASSETS

CURRENT LIABILITIES DEBT EQUITY

TRIAL ASSETS TRIAL LIABILITIES AND EQUITY PLUG: DEBT (EXCESS CASH)

TOTAL LIAB. & NET WORTH

422,733

110,600 121,600

2002

0.38 0.50 0.06 0.30

0.32 0.28

10,900

OPERATING EXPENSES/SALES

OPERATING EXPENSES

INTEREST RATE

INTEREST EXPENSE (INCOME) PROFIT BEFORE TAX

PROFIT AFTER TAX DIVIDENDS EARNINGS RETAINED

TAX

TAX RATE DIVIDENDS (Thousand pounds) CURR. ASSETS/SALES CURR. LIABS./SALES FIXED ASSETS STARTING EQUITY

2002

422,733 160,639 211,367

51,899 15,570 36,329 10,900 25,429

19,520

(1,171)

135,275 110,600 265,395

118,365

245,875 265,395 (19,520)

147,029 265,395

-

Sensitivity Analysis Of Debt and Excess Cash To COGS/SALES Ratio

COGS/SALES

0.35 0.38 0.40 0.42 0.44 0.45 0.48

DEBT $B34

Ex. CASH $B28

Case 9 The Body Shop International PLC 2001: An Introduction to Financial Modeling 157

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158 Part Two Financial Analysis and Forecasting

1 2 3 4 5 6 7 8 9

10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40

A B DC E F

Input Data

SALES

SALES

INCOME STATEMENT

COGS/SALES

COGS

BALANCE SHEET

EXCESS CASH CURRENT ASSETS FIXED ASSETS TOTAL ASSETS

CURRENT LIABILITIES DEBT EQUITY

TRIAL ASSETS TRIAL LIABILITIES AND EQUITY PLUG: DEBT (EXCESS CASH)

TOTAL LIAB. & NET WORTH

422,733

110,600 121,600

2002

0.38 0.50 0.06 0.30

0.32 0.28

10,900.00

OPERATING EXPENSES/SALES

OPERATING EXPENSES

INTEREST RATE

INTEREST EXPENSE (INCOME) PROFIT BEFORE TAX

PROFIT AFTER TAX DIVIDENDS EARNINGS RETAINED

TAX

TAX RATE DIVIDENDS (Thousand pounds) CURR. ASSETS/SALES CURR. LIABS./SALES FIXED ASSETS STARTING EQUITY

2002

422,733 160,639 211,367

51,899 15,570 36,329 10,900 25,429

19,520

(1,171)

135,275 110,600 265,395

118,365

245,875 265,395 (19,520)

147,029 265,395

0

Sensitivity Analysis Debt and Excess Cash By COGS/SALES

COGS/SALES

0.35 0.38 0.40 0.42 0.44 0.45 0.48

DEBT "B34

2,102 11,369

Ex. CASH "B28

28,787 19,520 13,342 7,165

987 0 0

0 0 0 0 0

EXHIBIT 7 | Finished Forecast with Data Table

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EXHIBIT 8 | Historical Financial Statements (GBP in millions)

Fiscal Year Ended February 28

1999 1999 2000 2000 2001 2001 (GBP) (% sales) (GBP) (% sales) (GBP) (% sales)

Income Statement

Turnover 303.7 100.0 330.1 100.0 374.1 100.0 Cost of sales 127.7 42.0 130.9 39.7 149.0 39.8 Gross profit 176.0 58.0 199.2 60.3 225.1 60.2

Operating expenses: – excluding exceptional

costs 151.4 49.9 166.2 50.3 195.7 52.3 – exceptional costs1 4.5 1.5 0.0 0.0 11.2 3.0

Restructuring costs2 16.6 5.5 2.7 0.8 1.0 0.3 Net interest expense 0.1 0.0 1.5 0.5 4.4 1.2 Profit before tax 3.4 1.1 28.8 8.7 12.8 3.4 Tax expense 8.0 2.6 10.4 3.2 3.5 0.9 Profit (loss) after tax (4.6) (1.5) 18.4 5.6 9.3 2.5

Ordinary dividends 10.9 3.6 10.9 3.3 10.9 2.9 Profit (loss) retained (15.5) (5.1) 7.5 2.3 (1.6) (0.4)

Case 9 The Body Shop International PLC 2001: An Introduction to Financial Modeling 159

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EXHIBIT 8 | Historical Financial Statements (GBP in millions) (continued)

Fiscal Year Ended February 28

1999 1999 2000 2000 2001 2001 (GBP) (% sales) (GBP) (% sales) (GBP) (% sales)

Balance Sheet Assets Cash 34.0 11.2 19.2 5.8 13.7 3.7 Accounts receivable 27.8 9.2 30.3 9.2 30.3 8.1 Inventories 38.6 12.7 44.7 13.5 51.3 13.7 Other current assets 12.5 4.1 15.6 4.7 17.5 4.7 Net fixed assets 87.8 28.9 104.7 31.7 110.6 29.6 Other assets3 0.0 0.0 6.0 1.8 6.7 1.8 Total assets 200.7 66.1 220.5 66.8 230.1 61.5

Liabilities and equity Accounts payable 13.0 4.3 20.5 6.2 10.7 2.9 Taxes payable 11.3 3.7 11.7 3.5 7.1 1.9 Accruals 10.8 3.6 15.6 4.7 11.5 3.1 Overdrafts 0.0 0.0 0.3 0.1 0.7 0.2 Other current liabilities 21.6 7.1 13.3 4.0 16.9 4.5 Long-term liabilities 28.0 9.2 36.7 11.1 61.2 16.4 Other liabilities4 1.7 0.6 1.0 0.3 0.4 0.1 Shareholders’ equity 114.3 37.6 121.4 36.8 121.6 32.5 Total liabilities and equity 200.7 66.1 220.5 66.8 230.1 61.5

1Exceptional costs in 2001 included redundancy costs ($4.6 million), costs of supply chain development ($2.4 million) and impairment of fixed assets and goodwill ($4.2 million). The exceptional costs of $4.5 million in 1999 were associated with closing unprofitable shops and an impairment review of the remaining shops in the United States. 2Restructuring costs in 2001 and 2000 relate to the sale of manufacturing plants in Littlehampton, England, and to associated reorganiza- tion costs. Restructuring costs in 1999 arose from the realignment of the management structure of the business in the United States and the United Kingdom. 3Other assets in 2001 and 2000 represented receivables related to the sale of the company’s Littlehampton manufacturing plant. 4Other liabilities included mostly deferred taxes.

160 Part Two Financial Analysis and Forecasting

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Value Line Publishing, October 2002

Competition between the two major players in the industry, Home Depot and Lowe’s, has been heating up, especially now that they are operating in more of the same markets. Both companies are seeking new, but similar, ways to boost both their top and bottom lines, including initiatives aimed at bettering customer service, attracting professional customers, and creating a more favorable merchandise mix. Still, despite the growing competition between them, over the long term, we believe both companies are poised to benefit from additional market share freed up in this consolidating industry.

—Carrie Galeotafiore Value Line analyst, July 2002

Slow but positive economic growth, low interest rates, a strong housing market, rising unemployment, uncertain consumer confidence, and concern over corporate misdeeds— such was the economic environment in early October 2002. Carrie Galeotafiore had followed the retail building-supply industry for nearly three years as an analyst for the investment-survey firm Value Line Publishing. Next week, Value Line would pub- lish her quarterly report on the industry, including her five-year financial forecast for industry leaders Home Depot and Lowe’s.

The Retail Building-Supply Industry The Economist Intelligence Unit (EIU) estimated the size of the 2001 U.S. retail building- supply industry at $175 billion. The industry was traditionally divided among three retail formats: hardware stores, with 15% of sales; lumberyards, with 34% of sales; and the larger-format home centers, with 51% of sales. Annual growth

161

10CASE

This case was prepared by Professor Michael J. Schill, with research assistance from Aimee Connolly and the cooperation of Carrie Galeotafiore of Value Line Publishing. It was written as a basis for class discussion rather than to illustrate effective or ineffective handling of an administrative situation. Copyright © 2003 by the University of Virginia Darden School Foundation, Charlottesville, VA. All rights reserved. To order copies, send an e-mail to [email protected] No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means—electronic, mechanical, photocopying, recording, or otherwise—without the permission of the Darden School Foundation. Rev. 11/07.

bru6171X_case10_161-174.qxd 11/24/12 2:32 PM Page 161

had declined from 7.7% in 1998 to 4.2% in 2001, yet was arguably still high con- sidering the recessionary nature of the economic environment in 2001. Low interest rates and a robust housing-construction market provided ongoing strength to the industry. The EIU expected the industry to reach $194 billion by 2006. Exhibit 1 pro- vides the details of the EIU’s forecast.

The industry was dominated by two companies: Home Depot and Lowe’s. Together, the two players captured more than a third of the total industry sales. Both companies were viewed as fierce competitors whose rapid-expansion strategies had more than doubled own-store capacity in the past five years with the opening of 1,136 new stores. The penetration by the large Lowe’s/Home Depot warehouse-format stores had had a profound impact on the industry. Independent hardware retailers were strug- gling to remain competitive. Some hardware stores had shifted their locations to high- rent shopping centers to attract more people or remained open for longer hours. Some of the smaller players were protected by segmentations in the market between the pro- fessional market that remained loyal to the lumberyards and do-it-yourself customers who were attracted to the discount chains. Exhibit 2 provides selected company data and presents recent stock-market performances for the two companies.

Future Growth Opportunities for Home Depot and Lowe’s Galeotafiore expected that future growth for Home Depot and Lowe’s would come from a variety of sources.

Acquisition/Consolidation The industry had already experienced a substantial amount of consolidation. In 1999, Lowe’s had acquired the 38-store, warehouse-format chain Eagle Hardware in a $1.3- billion transaction. In the past few years, Home Depot had acquired the plumbing wholesale distributor Apex Supply, the specialty-lighting company Georgia Lighting, the building-repair-and-replacement-products business N-E Thing Supply Company, and the specialty-plumbing-fixtures company Your “Other” Warehouse. Just last week, Home Depot had announced the purchase of three flooring companies that “when completed would instantly make Home Depot the largest turnkey supplier of flooring to the residential construction market.”1

Professional Market Both Home Depot and Lowe’s had recently implemented important initiatives to attract professional customers more effectively, including stocking merchandise in larger quantities, training employees to deal with professionals, and carrying profes- sional brands. Home Depot had developed Home Depot Supply and the “Pro Stores” to reach out to the small-professional market. The company was also on track to install professional-specific desks at 950 stores by the end of 2002.

162 Part Two Financial Analysis and Forecasting

1Press Release, Home Depot, 24 September 2002.

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International Expansion Home Depot had already developed some international presence with its acquisition of the Canadian home-improvement retailer Aikenhead in 1994, and it continued to expand its reach in that market with 11 new-store openings in 2001. More recently, the company had targeted the $12.5-billion home-improvement market in Mexico by acquir- ing the Mexican chains TotalHOME and Del Norte. By the end of 2001, 10% of Home Depot’s stores were located outside the United States. In 2002, Lowe’s did not yet have an international presence.

Alternative Retail Formats Home Depot and Lowe’s both maintained online stores. Lowe’s specifically targeted the professional customer with a section of its Web site: “Accent & Style” offered decorating and design tips on such subjects as kitchens and baths. Home Depot was developing new retail formats for urban centers, showcased by its recently opened Brooklyn store, which offered convenient shopping to densely populated markets. These “urban” stores provided Home Depot products and services in a compact for- mat. The acquisition of EXPO Design Centers provided an additional format for Home Depot and expansion beyond the traditional hardware and building-supply retailer. EXPO Design Centers were a one-stop design and decorating source, with eight show- rooms in one location, highlighting kitchens, baths, carpets and rugs, lighting, patio and grills, tile and wood, window treatments, and appliances. Lowe’s published Cre- ative Ideas, Garden Club, and Woodworker’s Club magazines to target customers with certain hobbies.

Alternative Products Both Home Depot and Lowe’s were expanding into installation services. The “at-home” business for Home Depot was currently at $3 billion. Home Depot expected its at-home business to grow at an annual rate of 30% in the near term.

Head-to-Head Competition Home Depot had traditionally focused on large metropolitan areas, while Lowe’s had concentrated on rural areas. To maintain its growth trajectory, Lowe’s had begun sys- tematic expansion into metropolitan markets. The investment community was becom- ing increasingly concerned about the eventuality of increased price competition. Aram Rubinson, of Bank of America Securities, had reported in August, “Since Lowe’s comps [comparable store sales] have been outpacing Home Depot’s, we have been growing increasingly concerned that Home Depot would fight back with increased promotions and more aggressive everyday pricing.”

Financial Forecast for Home Depot and Lowe’s Home Depot’s new CEO, Bob Nardelli, had expressed his intention to focus on enhancing store efficiency and inventory turnover through ongoing system invest- ments. He expected to generate margin improvement through cost declines from

Case 10 Value Line Publishing, October 2002 163

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product reviews, purchasing improvements, and an increase in the number of tool- rental centers. Recently, operating costs had increased owing to higher occupancy costs for new stores and increased energy costs. Home Depot had come under criti- cism for its declining customer service. Nardelli hoped to counter this trend with an initiative to help employees focus on customers during store hours and restocking shelves only after hours. Home Depot management expected revenue growth to be 15% to 18% through 2004. Some of the growth would be by acquisition, which neces- sitated the company’s maintaining higher cash levels. Home Depot stock was trading at around $25 a share, implying a total equity capitalization of $59 billion.

Galeotafiore had been cautiously optimistic about the changes at Home Depot in her July report:

Though the program [Service Performance Improvement] is still in the early stages, the do-it-yourself giant has already enjoyed labor productivity benefits, and received positive feedback from customers. . . . The Pro-Initiative program, which is currently in place at roughly 55% of Home Depot’s stores, is aimed at providing services that accommo- date the pro customer. Stores that provide these added services have generally outper- formed strictly do-it-yourself units in productivity, operating margins, and inventory turnover. Home Depot shares offer compelling price-appreciation potential over the coming 3-to-5-year pull.

Other analysts did not seem to share her enthusiasm for Home Depot. Dan Wewer and Lisa Estabrooks observed,

Home Depot’s comp sales fell short of plan despite a step-up in promotional activity. In our view, this legitimizes our concerns that Home Depot is seeing diminishing returns from promotional efforts. . . . Our view that Lowe’s is the most attractive investment opportunity in hard-line retailing is supported by key mileposts achieved during 2Q’02. Highlights include superior relative EPS momentum, robust comp sales, expanding operating margin, improving capital efficiency, and impressive new-store productivity. Importantly, Lowe’s outstanding performance raises the hurdle Home Depot must reach if it is to return to favor with the investment community.2

Lowe’s management had told analysts that it expected to maintain sales growth of 18% to 19% over the next two years. Lowe’s planned to open 123 stores in 2002, 130 stores in 2003, and 140 stores in 2004, and to continue its emphasis on cities with populations greater than 500,000, such as New York, Boston, and Los Angeles. To date, the company’s entry into metropolitan markets appeared to be successful. Lowe’s planned to continue improving sales and margins through new merchan- dising, pricing strategies, and market-share gains, especially in the Northeast and West.3 Lowe’s stock was trading at around $37 a share, implying a total equity cap- italization of $29 billion.

Donald Trott, an analyst at Jefferies, had recently downgraded Lowe’s based on a forecast of a deflating housing-market bubble and a view that the company’s stock

164 Part Two Financial Analysis and Forecasting

2Dan Wewer and Lisa Estabrooks, CIBC World Markets, 20 August 2002. 3Bear Stearns, 20 August 2002.

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price was richly priced relative to Home Depot’s. Galeotafiore countered that Lowe’s had now shown that it could compete effectively with Home Depot. She justified the Lowe’s valuation with an expectation of ongoing improvement in sales and gross margins.

Lowe’s is gaining market share in the appliance category, and its transition into major met- ropolitan areas (which will likely comprise the bulk of the company’s expansion in the next years) is yielding solid results. Alongside the positive sales trends, the homebuilding sup- plier’s bottom line is also being boosted by margin expansion, bolstered, in part, by lower inventory costs and product-mix improvements.

Galeotafiore’s financial forecast for Home Depot and Lowe’s would go to print next week. She based her forecasts on a review of historical performance, an analysis of trends and ongoing changes in the industry and the macroeconomy, and a detailed understanding of corporate strategy. She had completed a first-pass finan- cial forecast for Home Depot, and was in the process of developing her forecast for Lowe’s. She estimated the cost of capital for Home Depot and Lowe’s to be 12.3% and 11.6%, respectively (see Exhibit 3). Exhibits 4 and 5 provide historical financial statements for Home Depot and Lowe’s. Exhibit 6 details the historical and forecast values for Value Line’s macroeconomic-indicator series. Exhibits 7 and 8 feature Galeotafiore’s first-pass historical ratio analysis and financial forecast for Home Depot.

Case 10 Value Line Publishing, October 2002 165

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EXHIBIT 1 | Sales Figures for Retail-Building-Supply Industry

Sales ($billions) 1997 1998 1999 2000 2001 2002E 2006E

Hardware 22.8 26.2 26.2 26.0 Home centers 64.5 89.0 91.9 102.0 Lumber 51.5 59.0 60.1 66.0 Total market 138.8 149.5 159.7 168.0 174.2 178.2 194.0

Share of Market 2001 Home Depot, Inc. 22.9% Lowe’s Companies 10.8% TruServe Corp. 2.9% Menard, Inc. 1.5%

Source: Economist Intelligence Unit.

166 Part Two Financial Analysis and Forecasting

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EXHIBIT 2 | Historical Company Performance

Fiscal Year

1997 1998 1999 2000 2001

Home Depot Number of stores* 624 761 930 1,134 1,333 Sq. footage (millions) 66 81 100 123 146 Number of transactions (millions) 550 665 797 937 1,091 Number of employees 124,400 156,700 201,400 227,300 256,300

Lowe’s Number of stores 477 520 576 650 744 Sq. footage (millions) 40 48 57 68 81 Number of transactions (millions) 231 268 299 342 395 Number of employees 64,070 72,715 86,160 94,601 108,317

*Excludes Apex Supply, Georgia Lighting, Maintenance Warehouse, Your “Other” Warehouse, and National Blinds.

Case 10 Value Line Publishing, October 2002 167

$7

6

5

4

3

2

1

0

Ja n-

97

Cumulative Stock Returns ($1 Invested in Dec 1996)

M ay

-9 7

Se p-

97 Ja

n- 98

M ay

-9 8

Se p-

98 Ja

n- 99

M ay

-9 9

Se p-

99 Ja

n- 00

M ay

-0 0

Se p-

00 Ja

n- 01

M ay

-0 1

Se p-

01 Ja

n- 02

M ay

-0 2

Se p-

02

The Home Depot

Lowe’s

S&P 500

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168 Part Two Financial Analysis and Forecasting

EXHIBIT 3 | Cost-of-Capital Calculation

Current yield on long-term U.S. Treasuries 4.8% Historical market-risk premium 5.5%

Home Depot Proportion of debt capital (market value) 2% Cost of debt (current yields of Aaa-rated debt) 6.8% Marginal tax rate 38.6% Cost of equity (beta ! 1.4) 12.5% Weighted average cost of capital 12.3%

Lowe’s Proportion of debt capital (market value) 12% Cost of debt (current yields of Aa-rated debt) 7.3% Marginal tax rate 37.0% Cost of equity (beta ! 1.4) 12.5% Weighted average cost of capital 11.6%

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EXHIBIT 4 | Financial Statements for Home Depot ($ millions)

Fiscal Year

1997 1998 1999 2000 2001

INCOME STATEMENT Sales 24,156 30,219 38,434 45,738 53,553 Cost of sales 17,092 21,241 26,560 31,456 36,642

Gross profit 7,064 8,978 11,874 14,282 16,911 Cash operating expenses* 4,885 5,935 7,603 9,490 11,215 Depreciation & amortization 283 373 463 601 764

EBIT 1,896 2,670 3,808 4,191 4,932 Nonrecurring expenses 0 0 0 0 0 Net interest expense (2) 16 4 (26) (25)

EBT 1,898 2,654 3,804 4,217 4,957 Income taxes 738 1,040 1,484 1,636 1,913

Net earnings 1,160 1,614 2,320 2,581 3,044

BALANCE SHEET Cash and ST investments 174 62 170 177 2,546 Accounts receivable 556 469 587 835 920 Merchandise inventory 3,602 4,293 5,489 6,556 6,725 Other current assets 128 109 144 209 170

Total current assets 4,460 4,933 6,390 7,777 10,361 Net property and equipment 6,509 8,160 10,227 13,068 15,375 Other assets 260 372 464 540 658

Total assets 11,229 13,465 17,081 21,385 26,394

Accounts payable 1,358 1,586 1,993 1,976 3,436 Accrued salaries and wages 312 395 541 627 717 Short-term borrowings 0 0 0 0 0 Current maturities of long-term debt 8 14 29 4 5 Other current liabilities 778 862 1,093 1,778 2,343

Current liabilities 2,456 2,857 3,656 4,385 6,501 Long-term debt 1,303 1,566 750 1,545 1,250 Deferred income taxes 78 85 87 195 189 Other long-term liabilities 178 208 237 245 372 Minority interest 116 9 10 11 0 Shareholders’ equity 7,098 8,740 12,341 15,004 18,082

Total liab. and owner’s equity 11,229 13,465 17,081 21,385 26,394

*Includes operating-lease payments of $262 million in 1997, $321 million in 1998, $389 million in 1999, $479 million in 2000, and $522 million in 2001.

Case 10 Value Line Publishing, October 2002 169

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170 Part Two Financial Analysis and Forecasting

EXHIBIT 5 | Financial Statements for Lowe’s ($ millions)

Fiscal Year

1997 1998 1999 2000 2001

INCOME STATEMENT Sales 10,137 12,245 15,906 18,779 22,111 Cost of sales 7,447 8,950 11,525 13,488 15,743

Gross profit 2,690 3,295 4,381 5,291 6,368 Cash operating expenses* 1,825 2,189 2,870 3,479 4,036 Depreciation & amortization 241 272 338 410 534

EBIT 624 833 1,172 1,402 1,798 Nonrecurring expenses 0 0 24 0 0 Net interest expense 66 75 85 121 173

EBT 559 758 1,063 1,281 1,625 Income taxes 201 276 390 472 601

Net earnings 357 482 673 810 1,024

BALANCE SHEET Cash and ST investments 211 243 569 469 853 Accounts receivable 118 144 148 161 166 Merchandise inventory 1,715 2,105 2,812 3,285 3,611 Other current assets 65 94 164 243 291

Total current assets 2,110 2,586 3,693 4,157 4,920 Net property and equipment 3,005 3,637 5,177 7,035 8,653 Other assets 104 122 142 166 162

Total assets 5,219 6,345 9,012 11,358 13,736

Accounts payable 969 1,133 1,567 1,714 1,715 Accrued salaries and wages 83 113 164 166 221 Short-term borrowings 98 92 92 250 100 Current maturities of long-term debt 12 99 60 42 59 Other current liabilities 286 328 503 738 922

Current liabilities 1,449 1,765 2,386 2,911 3,017 Long-term debt 1,046 1,283 1,727 2,698 3,734 Deferred income taxes 124 160 200 251 305 Other long-term liabilities 0 0 4 3 6 Minority interest 0 0 0 0 0 Shareholders’ equity 2,601 3,136 4,695 5,495 6,674

Total liab. and owner’s equity 5,219 6,345 9,012 11,358 13,736

*Includes operating-lease payments of $59 million in 1997, $89 million in 1998, $144 million in 1999, $162 million in 2000, and $188 million in 2001.

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Case 10 Value Line Publishing, October 2002 171

EXHIBIT 6 | Value Line Economic Series

Annual Statistics 1997 1998 1999 2000 2001 2002* 2003* 2005–2007*

Gross domestic product ($ bill.) 8,318 8,782 9,274 9,825 10,082 10,440 10,984 13,255 Real GDP (1996 chained $ bill.) 8,159 8,509 8,859 9,191 9,215 9,428 9,728 10,827 Total consumption ($ bill.) 5,424 5,684 5,965 6,224 6,377 6,577 6,772 7,457 Nonresidential fixed investment ($ bill.) 1,009 1,136 1,228 1,324 1,255 1,190 1,266 1,625

Industrial prod. (% change, annualized) 6.9 5.1 3.7 4.5 –3.7 3.8 5.3 4.0 Housing starts (mill. units) 1.47 1.62 1.65 1.57 1.60 1.66 1.59 1.63 Unit car sales (mill. units) 8.3 8.1 8.7 8.9 8.4 8.2 8.3 8.0 Personal savings rate (%) 4.2 4.7 2.7 2.8 2.3 3.5 3.4 1.5 National unemployment rate (%) 4.9 4.5 4.2 4.0 4.8 5.9 5.9 5.0

AAA corp. bond rate (%) 7.3 6.5 7.0 7.6 7.1 6.4 6.4 7.3 10-Year Treasury note rate (%) 6.4 5.3 5.6 6.0 5.0 4.8 5.1 6.2 3-Month Treasury bill rate (%) 5.1 4.8 4.6 5.8 3.4 1.7 2.4 4.5

Annual Rates of Change Real GDP 4.4 4.3 4.1 3.8 0.3 2.3 3.2 3.8 GDP price index 1.9 1.2 1.4 2.1 2.4 1.7 2.5 2.6 Consumer price index 2.3 1.5 2.2 3.4 2.8 2.3 2.5 2.8

Quarterly Annualized Rates 2002 2003

1st 2nd* 3rd* 4th* 1st* 2nd* 3rd* 4th*

Gross domestic product ($ bill.) 10,313 10,307 10,475 10,600 10,756 10,901 11,060 11,270 Real GDP (1996 chained $ bill.) 9,363 9,388 9,446 9,516 9,598 9,681 9,770 9,861 Total consumption ($ bill.) 6,514 6,544 6,608 6,641 6,691 6,748 6,798 6,849 Nonresidential fixed investment ($ bill.) 1,188 1,184 1,190 1,199 1,222 1,249 1,279 1,315

Industrial production (% change, annualized) 2.6 4.6 3.0 5.0 5.5 5.5 5.0 5.0 Housing starts (mill. units) 1.73 1.66 1.65 1.60 1.57 1.58 1.60 1.60 Unit car sales (mill. units) 7.9 8.1 8.4 8.2 8.2 8.2 8.3 8.4

*Estimated.

Source: Value Line Publishing.

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172 Part Two Financial Analysis and Forecasting

EXHIBIT 7 | Ratio Analysis for Home Depot

Fiscal Year

1997 1998 1999 2000 2001

Working capital (CA-NIBCL*) 2,012 2,090 2,763 3,396 3,865 Fixed assets 6,769 8,532 10,691 13,608 16,033

Total capital 8,781 10,622 13,454 17,004 19,898 Tax rate 38.9% 39.2% 39.0% 38.8% 38.6%

NOPAT (EBIT " (1– t)) 1,158 1,623 2,323 2,565 3,028

PROFITABILITY Return on capital (NOPAT/total capital) 13.2% 15.3% 17.3% 15.1% 15.2% Return on equity (net earnings/s. equity) 16.3% 18.5% 18.8% 17.2% 16.8%

MARGINS Gross margin (gross profit/sales) 29.2% 29.7% 30.9% 31.2% 31.6% Cash operating expenses/sales 20.2% 19.6% 19.8% 20.7% 20.9% Depreciation/sales 1.2% 1.2% 1.2% 1.3% 1.4% Depreciation/P&E 4.3% 4.6% 4.5% 4.6% 5.0% Operating margin (EBIT/sales) 7.8% 8.8% 9.9% 9.2% 9.2% NOPAT margin (NOPAT/sales) 4.8% 5.4% 6.0% 5.6% 5.7%

TURNOVER Total capital turnover (sales/total capital) 2.8 2.8 2.9 2.7 2.7 P&E turnover (sales/P&E) 3.7 3.7 3.8 3.5 3.5 Working-capital turnover (sales/WC) 12.0 14.5 13.9 13.5 13.9 Receivable turnover (sales/AR) 43.4 64.4 65.5 54.8 58.2 Inventory turnover (COGS/m. inventory) 4.7 4.9 4.8 4.8 5.4 Sales per store ($ millions) 38.7 39.7 41.3 40.3 40.2 Sales per sq. foot ($) 366.0 373.1 384.3 371.9 366.8 Sales per transaction ($) 43.9 45.4 48.2 48.8 49.1

GROWTH Total sales growth 25.1% 27.2% 19.0% 17.1% Sales growth for existing stores 2.6% 4.1% –2.4% –0.4% Growth in new stores 22.0% 22.2% 21.9% 17.5% Growth in sq. footage per store 0.6% 1.0% 0.9% 1.0%

LEVERAGE Total capital/equity 1.24 1.22 1.09 1.13 1.10

*Non-interest-bearing current liabilities.

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Case 10 Value Line Publishing, October 2002 173

EXHIBIT 8 | Financial Forecast for Home Depot

Fiscal Year

ASSUMPTIONS 2001 2002E 2003E 2004E 2005E 2006E

Growth in new stores 17.5% 15.0% 13.2% 9.0% 7.0% 5.5% Sales growth for existing stores –0.4% 3.0% 4.0% 8.3% 8.3% 8.3% Total sales growth 17.1% 18.0% 17.2% 17.3% 15.3% 13.8%

Gross margin 31.6% 32.0% 32.3% 32.4% 32.5% 32.5% Cash operating expenses/sales 20.9% 21.0% 20.7% 20.8% 20.5% 20.5% Depreciation/sales 1.4% 1.4% 1.4% 1.4% 1.4% 1.4% Income-tax rate 38.6% 37.6% 37.5% 37.5% 37.5% 37.5%

Cash & ST inv./sales 4.8% 5.0% 5.0% 5.1% 5.3% 5.3% Receivable turnover 58.2 55.0 53.0 52.0 50.0 50.0 Inventory turnover 5.4 5.3 5.1 5.0 4.7 4.7 P&E turnover 3.5 3.3 3.3 3.3 3.3 3.3 Payables/COGS 9.4% 9.4% 9.4% 9.4% 9.4% 9.4% Other curr. liab./sales 4.4% 4.4% 4.4% 4.4% 4.4% 4.4%

FORECAST Number of stores 1,333 1,533 1,735 1,891 2,024 2,135 Net sales 53,553 63,195 74,049 86,860 100,149 114,000 Cost of sales 36,642 42,972 50,131 58,717 67,601 76,950

Gross profit 16,911 20,222 23,918 28,143 32,549 37,050 Cash operating expenses 11,215 13,271 15,328 18,067 20,531 23,370 Depreciation & amortization 764 902 1,056 1,239 1,429 1,626

EBIT 4,932 6,050 7,533 8,837 10,589 12,054 NOPAT 3,028 3,775 4,708 5,523 6,618 7,534

Cash and ST investments 2,546 3,160 3,702 4,430 5,308 6,042 Accounts receivable 920 1,149 1,397 1,670 2,003 2,280 Merchandise inventory 6,725 8,170 9,868 11,743 14,383 16,372 Other current assets 170 170 170 170 170 170

Total current assets 10,361 12,648 15,138 18,014 21,864 24,864 Accounts payable 3,436 4,030 4,701 5,506 6,339 7,216 Accrued salaries and wages 717 717 717 717 717 717 Other current liabilities 2,348 2,765 3,240 3,800 4,382 4,988

Non-int.-bearing current liab. 6,501 7,511 8,658 10,023 11,438 12,920 Working capital 3,860 5,137 6,480 7,990 10,426 11,944

Net property and equipment 15,375 19,150 22,439 26,321 30,348 34,545 Other assets 658 658 658 658 658 658

Total capital 19,893 24,945 29,578 34,970 41,433 47,147 Return on capital 15.2% 15.1% 15.9% 15.8% 16.0% 16.0%

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Horniman Horticulture Bob Brown hummed along to a seasonal carol on the van radio as he made his way over the dark and icy roads of Amherst County, Virginia. He and his crew had just finished securing their nursery against some unexpected chilly weather. It was Christ- mas Eve 2005, and Bob, the father of four boys ranging in age from 5 to 10, was anxious to be home. Despite the late hour, he fully anticipated the hoopla that would greet him on his return and knew that it would be some time before even the youngest would be asleep. He regretted that the boys’ holiday gifts would not be substantial; money was again tight this year. Nonetheless, Bob was delighted with what his com- pany had accomplished. Business was booming. Revenue for 2005 was 15% ahead of 2004, and operating profits were up even more.

Bob had been brought up to value a strong work ethic. His father had worked his way up through the ranks to become foreman of a lumber mill in Southwest Virginia. At a young age, Bob began working for his father at the mill. After earning a degree in agricultural economics at Virginia Tech, he married Maggie Horniman in 1993. Upon his return to the mill, Bob was made a supervisor. He excelled at his job and was highly respected by everyone at the mill. In 2000, facing the financial needs of an expanding family, he and Maggie began exploring employment alternatives. In late 2002, Maggie’s father offered to sell the couple his wholesale nursery business, Horniman Horticulture, near Lynchburg, Virginia. The business and the opportunity to be near Maggie’s family appealed to both Maggie and Bob. Pooling their savings, the proceeds from the sale of their house, a minority-business-development grant, and a sizable personal loan from Maggie’s father, the Browns purchased the business for $999,000. It was agreed that Bob would run the nursery’s operations and Maggie would oversee its finances.

Bob thoroughly enjoyed running his own business and was proud of its growth over the previous three years. The nursery’s operations filled 52 greenhouses and 40 acres of productive fields and employed 12 full-time and 15 seasonal employees. Sales were primarily to retail nurseries throughout the mid-Atlantic region. The company

175

11CASE

This case was prepared by Michael J. Schill, Robert F. Vandell Research Associate Professor of Business Administration, as a basis for class discussion rather than to illustrate effective or ineffective handling of an administrative situation. Horniman Horticulture is a fictional company reflecting the issues facing actual firms. Copyright © 2006 by the University of Virginia Darden School Foundation, Charlottesville, VA. All rights reserved. To order copies, send an e-mail to [email protected] No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means––electronic, mechanical, photocopying, recording, or otherwise––without the permission of the Darden School Foundation. Rev. 04/11.

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specialized in such woody shrubs as azaleas, camellias, hydrangeas, and rhododen- drons, but also grew and sold a wide variety of annuals, perennials, and trees.1 Over the previous two years, Bob had increased the number of plant species grown at the nursery by more than 40%.

Bob was a “people person.” His warm personality had endeared him to customers and employees alike. With Maggie’s help, he had kept a tight rein on costs. The effect on the business’s profits was obvious, as its profit margin had increased from 3.1% in 2003 to an expected 5.8% in 2005. Bob was confident that the nursery’s overall prospects were robust.

With Bob running the business full time, Maggie primarily focused on attending to the needs of her active family. With the help of two clerks, she oversaw the com- pany’s books. Bob knew that Maggie was concerned about the recent decline in the firm’s cash balance to below $10,000. Such a cash level was well under her operat- ing target of 8% of annual revenue. But Maggie had shown determination to main- tain financial responsibility by avoiding bank borrowing and by paying suppliers early enough to obtain any trade discounts.2 Her aversion to debt financing stemmed from her concern about inventory risk. She believed that interest payments might be impos- sible to meet if adverse weather wiped out their inventory.

Maggie was happy with the steady margin improvements the business had expe- rienced. Some of the gains were due to Bob’s response to a growing demand for more- mature plants. Nurseries were willing to pay premium prices for plants that delivered “instant landscape,” and Bob was increasingly shifting the product mix to that line. Maggie had recently prepared what she expected to be the end-of-year financial sum- mary (Exhibit 1).3 To benchmark the company’s performance, Maggie used available data for the few publicly traded horticultural producers (Exhibit 2).

Across almost any dimension of profitability and growth, Bob and Maggie agreed that the business appeared to be strong. They also knew that expectations could change quickly. Increases in interest rates, for example, could substantially slow market demand. The company’s margins relied heavily on the hourly wage rate of $8.51, cur- rently required for H2A-certified nonimmigrant foreign agricultural workers. There was some debate within the U.S. Congress about the merits of raising this rate.

Bob was optimistic about the coming year. Given the ongoing strength of the local economy, he expected to have plenty of demand to continue to grow the busi- ness. Because much of the inventory took two to five years to mature sufficiently to sell, his top-line expansion efforts had been in the works for some time. Bob was sure

176 Part Two Financial Analysis and Forecasting

1Over the past year, Horniman Horticulture had experienced a noticeable increase in business from small nurseries. Because the cost of carrying inventory was particularly burdensome for those customers, slight improvements in the credit terms had been accompanied by substantial increases in sales. 2Most of Horniman’s suppliers provided 30-day payment terms, with a 2% discount for payments received within 10 days. 3As compensation for the Browns’ services to the business, they had drawn an annual salary of $50,000 (itemized as an SG&A expense) for each of the past three years. This amount was effectively the family’s entire income.

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that 2006 would be a banner year, with expected revenue hitting a record 30% growth rate. In addition, he looked forward to ensuring long-term-growth opportunities with the expected closing next month on a neighboring 12-acre parcel of farmland.4 But for now, it was Christmas Eve, and Bob was looking forward to taking off work for the entire week. He would enjoy spending time with Maggie and the boys. They had much to celebrate for 2005 and much to look forward to in 2006.

Case 11 Horniman Horticulture 177

4With the acquisition of the additional property, Maggie expected 2006 capital expenditures to be $75,000. Although she was not planning to finance the purchase, prevailing mortgage rates were running at 6.5%. The expected depreciation expense for 2006 was $46,000.

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178 Part Two Financial Analysis and Forecasting

EXHIBIT 1 | Projected Financial Summary for Horniman Horticulture (in thousands of dollars)

2002 2003 2004 2005

Profit and loss statement Revenue 788.5 807.6 908.2 1048.8 Cost of goods sold 402.9 428.8 437.7 503.4 Gross profit 385.6 378.8 470.5 545.4 SG&A expense 301.2 302.0 356.0 404.5 Depreciation 34.2 38.4 36.3 40.9 Operating profit 50.2 38.4 78.2 100.0

Taxes 17.6 13.1 26.2 39.2 Net profit 32.6 25.3 52.0 60.8

Balance sheet Cash 120.1 105.2 66.8 9.4 Accounts receivable 90.6 99.5 119.5 146.4 Inventory1 468.3 507.6 523.4 656.9 Other current assets2 20.9 19.3 22.6 20.9 Current assets 699.9 731.6 732.3 833.6

Net fixed assets3 332.1 332.5 384.3 347.9 Total assets 1,032.0 1,064.1 1,116.6 1,181.5

Accounts payable 6.0 5.3 4.5 5.0 Wages payable 19.7 22.0 22.1 24.4 Other payables 10.2 15.4 16.6 17.9 Current liabilities 35.9 42.7 43.2 47.3 Net worth 996.1 1,021.4 1,073.4 1,134.2

Capital expenditure 22.0 38.8 88.1 4.5 Purchases4 140.8 145.2 161.2 185.1

1Inventory investment was valued at the lower of cost or market. The cost of inventory was determined by accumulating the costs asso- ciated with preparing the plants for sale. Costs that were typically capitalized as inventory included direct labor, materials (soil, water, containers, stakes, labels, chemicals), scrap, and overhead. 2Other current assets included consigned inventory, prepaid expenses, and assets held for sale. 3Net fixed assets included land, buildings and improvements, equipment, and software. 4Purchases represented the annual amount paid to suppliers.

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Case 11 Horniman Horticulture 179

EXHIBIT 2 | Financial Ratio Analysis and Benchmarking

2002 2003 2004 2005 Benchmark1

Revenue growth 2.9% 2.4% 12.5% 15.5% (1.8)% Gross margin (gross profit/revenue) 48.9% 46.9% 51.8% 52.0% 48.9% Operating margin (op. profit/revenue) 6.4% 4.8% 8.6% 9.5% 7.6% Net profit margin (net profit/revenue) 4.1% 3.1% 5.7% 5.8% 2.8%

Return on assets (net profit/total assets) 3.2% 2.4% 4.7% 5.1% 2.9% Return on capital (net profit/total capital) 3.3% 2.5% 4.8% 5.4% 4.0%

Receivable days (AR/revenue ! 365) 41.9 45.0 48.0 50.9 21.8 Inventory days (inventory/COGS ! 365) 424.2 432.1 436.5 476.3 386.3 Payable days (AP/purchases ! 365) 15.6 13.3 10.2 9.9 26.9 NFA turnover (revenue/NFA) 2.4 2.4 2.4 3.0 2.7

1Benchmark figures were based on 2004 financial ratios of publicly traded horticultural producers.

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Guna Fibres, Ltd. Ms. Surabhi Kumar, the managing director and principal owner of Guna Fibres, Ltd., discovered the problem when she arrived at the parking lot of the company’s plant one morning in early January 2012. Trucks filled with rolls of fiber yarns were being unloaded, but they had been loaded just the night before and had been ready to depart that morning. The fiber was intended for customers who had been badgering Kumar to fill their orders in a timely manner. The government tax inspector, who was stationed at the company’s warehouse, would not clear the trucks for departure because the excise tax had not been paid. The tax inspector required a cash payment, but in seeking to draw funds for the excise tax that morning, Mr. Malik, the bookkeeper, discovered that the company had overdrawn its bank account again—the third time in as many weeks. The truck drivers were independent contractors who refused to wait while the company and government settled their accounts. They cursed loudly as they unloaded the trucks.

This shipment would not leave for at least another two days, and angry customers would no doubt require an explanation. Before granting a loan with which to pay the excise tax, the branch manager of the All-India Bank & Trust Company had requested a meeting with Kumar for the next day to discuss Guna’s financial condition and its plans for restoring the firm’s liquidity.

Kumar told Malik, “This cash problem is most vexing. I don’t understand it. We’re a very profitable enterprise, yet we seem to have to depend increasingly on the bank. Why do we need more loans just as our heavy selling season begins? We can’t repeat this blunder.”

Company Background Guna Fibres, Ltd., was founded in 1972 to produce nylon fiber at its only plant in Guna, India, about 500 kilometers (km) south of New Delhi. By using new technol- ogy and domestic raw materials, the firm had developed a steady franchise among dozens of small, local textile weavers. It supplied synthetic fiber yarns used to weave colorful cloths for making saris, the traditional women’s dress of India. On average,

181

12CASE

This case was written by Thien T. Pham and professors Robert F. Bruner and Michael J. Schill as a basis for class discussion. The names and institutions in this case are fictitious. The financial support of the Batten Institute is gratefully acknowledged. Copyright © 2012 by the University of Virginia Darden School Foundation, Charlottesville, VA. All rights reserved. To order copies, send an e-mail to [email protected] No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means––electronic, mechanical, photo- copying, recording, or otherwise––without the permission of the Darden School Foundation.

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each sari required eight yards of cloth. An Indian woman typically would buy three saris a year. With India’s female population at around 500 million, the demand for saris accounted for more than 12 billion yards of fabric. This demand was currently being supplied entirely from domestic textile mills that, in turn, filled their yarn requirements from suppliers such as Guna Fibres.

Synthetic-Textile Market The demand for synthetic textiles was stable with year-to-year growth and pre- dictable seasonal fluctuations. Unit demand increased with both population and national income. In addition, India’s population celebrated hundreds of festivals each year, in deference to a host of deities, at which saris were traditionally worn. The most important festival, the Diwali celebration in mid-autumn, caused a sea- sonal peak in the demand for new saris, which in turn caused a seasonal peak in demand for nylon textiles in late summer and early fall. Thus, the seasonal demand for nylon yarn would peak in mid-summer. Unit growth in the industry was expected to be 15% per year.

Consumers purchased saris and textiles from cloth merchants located in the vil- lages around the country. A cloth merchant was an important local figure usually well known to area residents; the merchant generally granted credit to support consumer purchases. Merchants maintained relatively low levels of inventory and built stocks of goods only shortly in advance of and during the peak selling season.

Competition among suppliers (the many small textile-weaving mills) to those merchants was keen and was affected by price, service, and the credit that the mills could grant to the merchants. The mills essentially produced to order, building their inventories of woven cloth shortly in advance of the peak selling season and keeping only maintenance stocks at other times of the year.

The yarn manufacturers competed for the business of the mills through responsive service and credit. The suppliers to the yarn manufacturers provided little or no trade credit. Being near the origin of the textile chain in India, the yarn manufacturers essentially banked the downstream activities of the industry.

Production and Distribution System Thin profit margins had prompted Kumar to adopt policies against overproduction and overstocking, which would require Guna to carry inventories through the slack selling season. She had adopted a plan of seasonal production, which meant that the yarn plant would operate at peak capacity for two months of the year and at mod- est levels the rest of the year. That policy imposed an annual ritual of hirings and layoffs.

To help ensure prompt service, Guna Fibres maintained two distribution ware- houses, but getting the finished yarn quickly from the factory in Guna to the cus- tomers was a challenge. The roads were narrow and mostly in poor repair. A truck was often delayed negotiating the trip between Calcutta and Guna, a distance of about 730 km. Journeys were slow and dangerous, and accidents were frequent.

182 Part Two Financial Analysis and Forecasting

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Company Performance Guna Fibres had experienced consistent growth and profitability (see Exhibit 1 for recent financial statements for the firm). In 2011, sales had grown at an impressive rate of 18%. Recent profits were (Indian rupees) INR2.6 million, down from INR3.6 million in 2010. Kumar expected Guna’s growth to continue with gross sales reaching INR90.9 million in 2012 (see Exhibit 2).1

Reassessment After the episode in the parking lot, Kumar and her bookkeeper went to her office to analyze the situation. She pushed aside the several items on her desk to which she had intended to devote her morning: a message from the transportation manager regarding a possible change in the inventory policy (Exhibit 3), and a proposal from the operations manager for a scheme of level annual production (Exhibit 4).

To prepare a forecast on a business-as-usual basis, Kumar and Malik agreed on various parameters. Cost of goods sold would run at 73.7% of gross sales—a fig- ure that was up from recent years because of increasing price competition. Annual operating expenses would be about 6% of gross annual sales—also up from recent years to include the addition of a quality-control department, two new sales agents, and three young nephews with whom she hoped to build an allegiance to the Kumar family business. The company’s income tax rate was 30% and, although accrued monthly, positive balances were paid quarterly in March, June, September, and December. The excise tax (at 15% of sales) was different from the income tax and was collected at the factory gate as trucks left to make deliveries to cus- tomers and the regional warehouses. Kumar proposed to pay dividends of INR500,000 per quarter to the 11 members of her extended family who held the entire equity of the firm. For years Guna had paid high dividends. The Kumar fam- ily believed that excess funds left in the firm were at greater risk than if the funds were returned to shareholders.

Malik observed that accounts receivable collections in any given month had been running steadily at the rate of 48 days, comprised of 40% of the last month’s gross sales plus 60% of the gross sales from the month before last. The cost of the raw materials for Guna’s yarn production ran about 55% of the gross sale price. To ensure sufficient raw material on hand, it was Guna’s practice to purchase each month the amount of raw materials expected to be sold in two months. The suppliers Guna used had little ability to provide credit such that accounts payable were generally paid within two weeks. Monthly direct labour and other direct costs associated with yarn manufacturing were equivalent to about 34% of purchases in the previous month.2

Accounts payable ran at about half of the month’s purchases. As a matter of policy, Kumar wanted to see a cash balance of at least INR750,000.

Case 12 Guna Fibres, Ltd. 183

1 At the time, the rupee exchange rate for U.S. dollars was roughly at the rate of INR50 per dollar. 2 The 73.7% COGS rate assumption was determined based on these purchases and direct cost figures: 73.7% ! 55% " 55% # 34%.

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Guna Fibres had a line of credit at the All-India Bank & Trust Company, where it also maintained its cash balances. All-India’s short-term interest rate was currently 14.5%, but Malik was worried that inflation and interest rates might rise in the coming year. By terms of the bank, the seasonal line of credit had to be reduced to a zero bal- ance for at least 30 days each year. The usual cleanup month had been October,3 but Guna Fibres had failed to make a full repayment at that time. Only after strong assur- ances by Kumar that she would clean up the loan in November or December had the bank lending officer reluctantly agreed to waive the cleanup requirement in October. Unfortunately, the credit needs of Guna Fibres did not abate as rapidly as expected in November and December, and although his protests increased each month, the lending officer agreed to meet Guna’s cash requirements with loans. Now he was refusing to extend any more seasonal credit until Kumar presented a reasonable financial plan for the company that demonstrated its ability to clean up the loan by the end of 2012.

Financial Forecast With some experience in financial modeling, Malik used the agreed upon assumptions to build out a monthly forecast of Guna’s financial statements (see Exhibit 5). To summarize the seasonal pattern of the model, Malik handed Kumar a graph showing the projected monthly sales and key balance sheet accounts (Exhibit 6). After study- ing the forecasts for a few moments, Kumar expostulated:

This is worse than I expected. The numbers show that we aren’t even close to paying back All-India’s loan by the end of December. The loan officer will never accept this forecast as a basis for more credit. We need a new plan, and fast. Maintaining this loan is critical for us to scale up for the most important part of our business season. Let’s go over these assump- tions in detail and look for any opportunities to improve our debt position.

Then, casting her gaze toward the two proposals she had pushed aside earlier, she muttered, “Perhaps these proposals will help.”

184 Part Two Financial Analysis and Forecasting

3 The selection of October as the loan-cleanup month was imposed by the bank on the grounds of tradition. Seasonal loans of any type made by the bank were to be cleaned up in October. Kumar had seen no reason previously to challenge the bank’s tradition.

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Case 12 Guna Fibres, Ltd. 185

EXHIBIT 1 | Guna Fibres Annual Income Statements (in 000s of Rupees)

2010 2011

Gross Sales 64,487 75,867 Excise Tax 9,673 11,380

Net Sales 54,814 64,487 Cost of Goods 44,496 53,866

Gross Profits 10,318 10,621 Operating Expenses 3,497 4,829 Depreciation 769 909 Interest Expense 910 1,240

Profit Before Tax 5,142 3,644 Income Tax 1,545 1,093

Net Profit 3,597 2,551

Cash 895 762 Accounts Receivable 2,390 2,673 Inventory 2,974 3,450

Total Current Assets 6,259 6,885 Gross Plant, Property, and Equipment 8,868 10,096

Accumulated Depreciation 1,170 1,484 Net Plant, Property, and Equipment 7,698 8,612

Total Assets 13,957 15,497

Accounts Payable 603 822 Notes to Bank 0 798 Accrued Taxes $62 $90

Total Current Liabilities 541 1,530 Owners’ Equity 13,416 13,967

Total Liabilities and Equity 13,957 15,497

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186 Part Two Financial Analysis and Forecasting

EXHIBIT 3 | Message from Transportation Manager

To: G. Kumar From: R. Sikh

January 2, 2012

As you asked me to, I have been tracking our supply shipments over the past year. I have observed a substantial improvement in the reliability of the shipments. As a result, I would propose that we reduce our raw-material inventory requirement from 60 days to 30 days. This would reduce the amount of inventory we are carrying by one month, and should free up a lot of space in the warehouse. I am not sure if that will affect any other department since we will be buying the same amount of material, but it would make inventory tracking a lot easier for me. Please let me know so we can implement this in January such that I don’t purchase any additional raw material this month.

EXHIBIT 2 | Guna Fibres Actual and Forecast of Monthly Sales (in 000s of Rupees)

2011 2012 (Actual) (Forecast)

January 2,012 2,616 February 2,314 2,892 March 3,421 4,447 April 7,043 8,804 May 12,074 13,885 June 15,294 17,588 July 14,187 16,315 August 7,144 8,576 September 4,025 5,031 October 3,421 4,447 November 2,717 3,531 December 2,214 2,767 Year 75,867 90,899

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Case 12 Guna Fibres, Ltd. 187

EXHIBIT 4 | Message from Operations Manager

To: G. Kumar From: L. Gupta

January 7, 2012

You asked me to estimate the production efficiencies arising from a scheme of level annual production. In order to provide for the estimated production needs in 2012 and 2013, I would recommend that purchases under level production be altered to INR5 million per month.

There are significant operating advantages to be gained under this operating scenario:

• Seasonal hirings and layoffs would no longer be necessary, permitting us to cultivate a stronger work force and, perhaps, to suppress labour unrest.You will recall that the unions have indicated that reducing seasonal layoffs will be one of their major negotiating objectives this year.

• Level production entails lower manufacturing risk. With the load spread throughout the year, we would suffer less from equipment breakdowns and could better match the rou- tine maintenance with the demand on the plant and equipment.

With level production my team believes that direct labour and other direct manufacturing costs could be reduced from a forecasted 34% of purchases down to 29% of purchases.

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190 Part Two Financial Analysis and Forecasting

EXHIBIT 6 | Forecast of Accounts by Month

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PART 3

Estimating the Cost of Capital

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193

Best Practices in Estimating the Cost of Capital: Survey and Synthesis

This paper presents the results of a cost-of-capital survey of 27 highly regarded corporations, ten leading financial advisers, and seven best selling textbooks and trade books. The results show close alignment among all these groups on the use of common theoretical frameworks and on many aspects of estimation. We find large variation, however, for the joint choices of the risk-free rate, beta, and the equity market risk premium, as well as for the adjustment of capital costs for specific investment risk. On these issues, we summarize arguments for different approaches and review responses in detail to glean tradeoffs faced by practitioners.

—Robert F. Bruner, Kenneth M. Eades, Robert S. Harris, and Robert C. Higgins [JEL: G12, G20, G31]

In recent decades, theoretical breakthroughs in such areas as portfolio diversification, market efficiency, and asset pricing have converged into compelling recommendations about the cost of capital to a corporation. By the early 1990s, a consensus had emerged prompting such descriptions as “traditional . . . textbook . . . appropriate,” “theoreti- cally correct,” and “a useful rule of thumb and a good vehicle.”1 Beneath this general agreement about cost-of-capital theory lies considerable ambiguity and confusion over how the theory can best be applied. The issues at stake are sufficiently important that differing choices on a few key elements can lead to wide disparities in estimated capital cost. The cost of capital is central to modern finance touching on investment and divestment decisions, measures of economic profit, performance appraisal, and

13CASE

1The three sets of quotes come in order from Ehrhardt (1994), Copeland, Koller, and Murrin (1990), and Brealey and Myers (1993).

Robert F. Bruner, Kenneth M. Eades, and Robert S. Harris are Professors at the Darden Graduate School of Business Administration, University of Virginia, Charlottesville, VA 22906. Robert C. Higgins is a Professor at the University of Washington, Seattle, WA 98195.

The authors thank Todd Brotherson for excellent research assistance, and gratefully acknowledge the financial support of Coopers & Lybrand and the University of Virginia Darden School Foundation. The research would not have been possible without the cooperation of the 37 companies surveyed. These contributions notwithstanding, any errors remain the authors’.

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incentive systems. Each year in the US, corporations undertake more than $500 billion in capital spending. Since a difference of a few percent in capital costs can mean a swing in billions of expenditures, how firms estimate the cost is no trivial matter.

The purpose of this paper is to present evidence on how some of the most finan- cially sophisticated companies and financial advisers estimate capital costs. This evi- dence is valuable in several respects. First, it identifies the most important ambiguities in the application of cost-of-capital theory, setting the stage for productive debate and research on their resolution. Second, it helps interested companies benchmark their cost-of-capital estimation practices against best-practice peers. Third, the evidence sheds light on the accuracy with which capital costs can be reasonably estimated, enabling executives to use the estimates more wisely in their decision-making. Fourth, it enables teachers to answer the inevitable question, “How do companies really esti- mate their cost of capital?”

The paper is part of a lengthy tradition of surveys of industry practice. Among the more relevant predecessors, Gitman and Forrester (1977) explored “the level of sophistication in capital budgeting techniques” among 103 large, rapidly growing busi- nesses, finding that the internal rate of return and the payback period were in com- mon use. Although the authors inquired about the level of the firm’s discount rate, they did not ask how the rate was determined. Gitman and Mercurio (1982) surveyed 177 Fortune 1000 firms about “current practice in cost of capital measurement and utilization,” concluding that “the respondents’ actions do not reflect the application of current financial theory.” Moore and Reichert (1983) surveyed 298 Fortune 500 firms on the use of a broad array of financial techniques, concluding among other things, that 86% of firms surveyed use time-adjusted capital budgeting techniques. Bierman (1993) surveyed 74 Fortune 100 companies reporting that all use some form of dis- counting in their capital budgeting, and 93% use a weighted-average cost of capital. In a broad-ranging survey of 84 Fortune 500 large firms and Forbes 200 best small companies, Trahan and Gitman (1995) report that 30% of respondents use the capital- asset pricing model (CAPM).

This paper differs from its predecessors in several important respects. Existing published evidence is based on written, closed-end surveys sent to a large sample of firms, often covering a wide array of topics, and commonly using multiple-choice or fill-in-the-blank questions. Such an approach often yields response rates as low as 20% and provides no opportunity to explore subtleties of the topic. Instead, we report the result of a telephone survey of a carefully chosen group of leading corporations and financial advisers. Another important difference is that the intent of existing papers is most often to learn how well accepted modern financial techniques are among practitioners, while we are interested in those areas of cost-of-capital estima- tion where finance theory is silent or ambiguous, and practitioners are left to their own devices.

The following section gives a brief overview of the weighted-average cost of cap- ital. The research approach and sample selection are discussed in Section II. Section III reports the general survey results. Key points of disparity are reviewed in Section IV. Section V discusses further survey results on risk adjustment to a baseline cost of capital, and Section VI offers conclusions and implications for the financial practitioner.

194 Part Three Estimating the Cost of Capital

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I. The Weighted-Average Cost of Capital A key insight from finance theory is that any use of capital imposes an opportunity cost on investors; namely, funds are diverted from earning a return on the next best equal-risk investment. Since investors have access to a host of financial market oppor- tunities, corporate uses of capital must be benchmarked against these capital market alternatives. The cost of capital provides this benchmark. Unless a firm can earn in excess of its cost of capital, it will not create economic profit or value for investors.

A standard means of expressing a company’s cost of capital is the weighted- average of the cost of individual sources of capital employed. In symbols, a company’s weighted-average cost of capital (or WACC) is

(1)

where

For simplicity, this formula includes only three sources of capital; it can be easily expanded to include other sources as well.

Finance theory offers several important observations when estimating a com- pany’s WACC. First, the capital costs appearing in the equation should be current costs reflecting current financial market conditions, not historical, sunk costs. In essence, the costs should equal the investors’ anticipated internal rate of return on future cash flows associated with each form of capital. Second, the weights appearing in the equa- tion should be market weights, not historical weights based on often arbitrary, out-of- date book values. Third, the cost of debt should be after corporate tax, reflecting the benefits of the tax deductibility of interest.

Despite the guidance provided by finance theory, use of the weighted-average expres- sion to estimate a company’s cost of capital still confronts the practitioner with a number of difficult choices.2 As our survey results demonstrate, the most nettlesome component of WACC estimation is the cost of equity capital; for unlike readily available yields in bond markets, no observable counterpart exists for equities. This forces practitioners to rely on more abstract and indirect methods to estimate the cost of equity capital.

II. Sample Selection This paper describes the results of a telephone survey of leading practitioners. Believ- ing that the complexity of the subject does not lend itself to a written questionnaire, we wanted to solicit an explanation of each firm’s approach told in the practitioner’s

t ! marginal corporate tax rate

W ! weight of each component as percent of total capital

K ! component cost of capital

WACC ! 1Wdebt1l " t2Kdebt2 # 1WpreferredKpreferred2 # 1WequityKequity2

Case 13 Best Practices in Estimating the Cost of Capital: Survey and Synthesis 195

2Even at the theoretical level, Dixit and Pindyck (1994) point out that the use of standard net-present- value (NPV) decision rules (with, for instance, WACC as a discount rate) does not capture the option value of being able to delay an irreversible investment expenditure. As a result, a firm may find it better to delay an investment even if the current NPV is positive. Our survey does not explore the ways firms deal with this issue, rather, we focus on measuring capital costs.

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own words. Though our interviews were guided by a series of questions, these were sufficiently open-ended to reveal many subtle differences in practice.

Since our focus is on the gaps between theory and application rather than on aver- age or typical practice, we aimed to sample practitioners who were leaders in the field. We began by searching for a sample of corporations (rather than investors or finan- cial advisers) in the belief that they had ample motivation to compute WACC care- fully and to resolve many of the estimation issues themselves. Several publications offer lists of firms that are well-regarded in finance;3 of these, we chose a research report, Creating World-Class Financial Management: Strategies of 50 Leading Com- panies (1992), which identified firms

selected by their peers as being among those with the best financial management. Firms were chosen for excellence in strategic financial risk management, tax and accounting, performance evaluation and other areas of financial management . . . The companies included were those that were mentioned the greatest number of times by their peers.4

From the 50 companies identified in this report, we eliminated 18 headquartered outside North America.5 Of those remaining, five declined to be interviewed, leaving a sample of 27 firms. The companies included in the sample are contained in Exhibit 1. We approached the most senior financial officer first with a letter explaining our research, and then with a telephone call. Our request was to interview the individual in charge of estimating the firm’s WACC. We promised our interviewees that, in preparing a report on our findings, we would not identify the practices of any partic- ular company by name—we have respected this promise in our presentation.

In the interest of assessing the practices of the broader community of finance practitioners, we surveyed two other samples:

• Financial Advisers. Using a “league table” of merger and acquisition advisers presented in Institutional Investor issues of April 1995, 1994, and 1993, we drew a sample of 10 of the most active6 advisers. We applied approximately7 the same set of questions to representatives of these firms’ mergers and acquisitions depart- ments. We wondered whether the financial advisers’ interest in promoting deals

196 Part Three Estimating the Cost of Capital

3For instance, Institutional Investor and Euromoney publish lists of firms with the best CFOs or with special competencies in certain areas. We elected not to use these lists because special competencies might not indi- cate a generally excellent finance department, nor might a stellar CFO. 4This survey was based upon a written questionnaire sent to CEOs, CFOs, controllers, and treasurers and was followed up by a telephone survey (Business International Corporation, 1992). 5Our reasons for excluding these firms were the increased difficulty of obtaining interviews, and possible difficulties in obtaining capital market information (such as betas and equity market premiums) that might preclude using American practices. The enlargement of this survey to firms from other countries is a subject worthy of future study. 6Activity in this case was defined as four-year aggregate deal volume in mergers and acquisitions. The sample was drawn from the top 12 advisers, using their average deal volume over the 1993-95 period. Of these 12, two firms chose not to participate in the survey. 7Specific questions differ, reflecting the facts that financial advisers infrequently deal with capital budgeting matters and that corporate financial officers infrequently value companies.

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Case 13 Best Practices in Estimating the Cost of Capital: Survey and Synthesis 197

might lead them to lower WACC estimates than those estimated by operating companies. This proved not to be the case. If anything, the estimating techniques most often used by financial advisers yield higher, not lower, capital cost estimates.

• Textbooks and Tradebooks. From a leading textbook publisher, we obtained a list of the graduate-level textbooks in corporate finance having the greatest unit sales in 1994. From these, we selected the top four. In addition, we drew on three tradebooks that discuss the estimation of WACC in detail.

Names of advisers and books included in these two samples are shown in Exhibit 1.

III. Survey Findings The detailed survey results appear in Exhibit 2. The estimation approaches are broadly similar across the three samples in several dimensions.

• Discounted Cash Flow (DCF) is the dominant investment-evaluation technique.

• WACC is the dominant discount rate used in DCF analyses.

• Weights are based on market not book value mixes of debt and equity.8

• The after-tax cost of debt is predominantly based on marginal pretax costs, and marginal or statutory tax rates.

• The CAPM is the dominant model for estimating the cost of equity. Some firms mentioned other multi-factor asset-pricing models (e.g., Arbitrage Pricing Theory) but these were in the small minority. No firms cited specific modifications of the CAPM to adjust for any empirical shortcomings of the model in explaining past returns.9

These practices differ sharply from those reported in earlier surveys.10 First, the best-practice firms show much more alignment on most elements of practice. Second, they base their practice on financial economic models rather than on rules of thumb or arbitrary decision rules.

On the other hand, disagreements exist within and among groups on how to apply the CAPM to estimate cost of equity. The CAPM states that the required return (K) on any asset can be expressed as

(2)K ! Rf " #1Rm $ Rf2 8The choice between target and actual proportions is not a simple one. Because debt and equity costs clearly depend on the proportions of each employed, it might appear that the actual proportions must be used. How- ever, if the firm’s target weights are publicly known, and if investors expect the firm soon to move to these weights, then observed costs of debt and equity may anticipate the target capital structure. 9For instance, even research supporting the CAPM has found that empirical data are better explained by an intercept higher than a risk-free rate and a price of beta risk less than the market risk premium. Ibbotson Associates (1994) offers such a modified CAPM in addition to the standard CAPM and other models, in its cost of capital service. Jagannathan and McGrattan (1995) provide a useful review of empirical evidence on the CAPM. 10See Gitman and Forrester (1977) and Gitman and Mercurio (1982).

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where:

According to CAPM then, the cost of equity, Kequity, for a company depends on three components: returns on risk-free bonds (Rf), the stock’s equity beta which meas- ures risk of the company’s stock relative to other risky assets ($ ! 1.0 is average risk), and the market risk premium (Rm – Rf) necessary to entice investors to hold risky assets generally versus risk-free bonds. In theory, each of these components must be a forward looking estimate. Our survey results show substantial disagreements on all three components.

A. The Risk-Free Rate of Return As originally derived, the CAPM is a single-period model, so the question of which interest rate best represents the risk-free rate never arises. But in a many-period world typically characterized by upward-sloping yield curves, the practitioner must choose. Our results show the choice is typically between the 90-day Treasury bill yield and a long-term Treasury bond yield (see Exhibit 3). (Because the yield curve is ordinarily relatively flat beyond ten years, the choice of which particular long-term yield to use is not a critical one.)11 The difference between realized returns on the 90-day T-bill and the ten-year T-bond has averaged 150 basis points over the long run; so choice of a risk-free rate can have a material effect on the cost of equity and WACC.12

The 90-day T-bill yields are more consistent with the CAPM as originally derived and reflect truly risk-free returns in the sense that T-bill investors avoid material loss in value from interest rate movements. However, long-term bond yields more closely reflect the default-free holding period returns available on long lived investments and thus more closely mirror the types of investments made by companies.

Our survey results reveal a strong preference on the part of practitioners for long- term bond yields. Of both corporations and financial advisers, 70% use Treasury bond yields maturities of ten years or greater. None of the financial advisers and only 4%

$ ! the relative risk of the particular asset.

market portfolio of risky assests. Rm ! return required to attract investors to hold the broad

Rf ! interest rate available on a risk-free bond.

198 Part Three Estimating the Cost of Capital

11In early January 1996, the differences between yields on the 10- and 30-year T-bonds were about 35 basis points. Some aficionados will argue that there is a difference between the ten- and 30-year yields. Ordinarily the yield curve declines just slightly as it reaches the 30-year maturity—this has been explained to us as the result of life insurance companies and other long-term buy-and-hold investors who are said to purchase the long bond in significant volume. It is said that these investors command a lower liquidity premium than the broader market, thus driving down yields. If this is true, then the yields at this point of the curve may be due not to some ordinary process of rational expectations, but rather to an anomalous supply-demand imbalance, which would render these yields less trustworthy. The counterargument is that life insurance companies could be presumed to be rational investors too. As buy-and-hold investors, they will surely suffer the consequences of any irrationality, and therefore have good motive to invest for yields “at the market.” 12This was estimated as the difference in arithmetic mean returns on long-term government bonds and US Treasury bills over the years 1926 to 1994, given by Ibbotson Associates (1995).

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Case 13 Best Practices in Estimating the Cost of Capital: Survey and Synthesis 199

of the corporations used the Treasury bill yield. Many corporations said they matched the term of the risk-free rate to the tenor of the investment. In contrast, 43% of the books advocated the T-bill yield, while only 29% used long-term Treasury yields.

B. Beta Estimates Finance theory calls for a forward-looking beta, one reflecting investors’ uncertainty about the future cash flows to equity. Because forward-looking betas are unobserv- able, practitioners are forced to rely on proxies of various kinds. Most often this involves using beta estimates derived from historical data and published by such sources as Bloomberg, Value Line, and Standard & Poor’s.

The usual methodology is to estimate beta as the slope coefficient of the market model of returns.

(3)

where

In addition to relying on historical data, use of this equation to estimate beta requires a number of practical compromises, each of which can materially affect the results. For instance, increasing the number of time periods used in the estimation may improve the statistical reliability of the estimate but risks the inclusion of stale, irrelevant information. Similarly, shortening the observation period from monthly to weekly, or even daily, increases the size of the sample but may yield observations that are not normally distributed and may introduce unwanted random noise. A third compromise involves choice of the market index. Theory dictates that Rm is the return on the market portfolio, an unobservable portfolio consisting of all risky assets, including human capital and other nontraded assets, in proportion to their importance in world wealth. Beta providers use a variety of stock market indices as proxies for the market portfolio on the argument that stock markets trade claims on a sufficiently wide array of assets to be adequate surrogates for the unobservable market portfolio.

Exhibit 4 shows the compromises underlying the beta estimates of three promi- nent providers and their combined effect on the beta estimates of our sample compa- nies. Note for example that the mean beta of our sample companies according to Bloomberg is 1.03, while the same number according to Value Line is 1.24. Exhibit 5 provides a complete list of sample betas by publisher.

Over half of the corporations in our sample (item ten, Exhibit 2) rely on pub- lished sources for their beta estimates, although 30% calculate their own. Among finan- cial advisers, 40% rely on published sources, 20% calculate their own, and another 40% use what might be called “fundamental” beta estimates. These are estimates which use multi-factor statistical models drawing on fundamental indices of firm and industry risk

!i " beta for stock i.

#i " regression constant for stock i, and

Rmt " return on the market portfolio in period t,

Rit " return on stock i in time period 1e.g., day, week, month2 t, Rit " #i $ !i1Rmt2

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to estimate company betas. The best known provider of fundamental beta estimates is the consulting firm BARRA.

Within these broad categories, a number of survey participants indicated use of more pragmatic approaches, which combine published beta estimates or adjust published estimates in various heuristic ways. (See Exhibit 6.)

C. Equity Market Risk Premium This topic prompted the greatest variety of responses among survey participants. Finance theory says the equity market risk premium should equal the excess return expected by investors on the market portfolio relative to riskless assets. How one measures expected future returns on the market portfolio and on riskless assets are problems left to prac- titioners. Because expected future returns are unobservable, all survey respondents extrapolated historical returns into the future on the presumption that past experience heavily conditions future expectations. Where respondents chiefly differed was in their use of arithmetic versus geometric average historical equity returns and in their choice of realized returns on T-bills versus T-bonds to proxy for the return on riskless assets.

The arithmetic mean return is the simple average of past returns. Assuming the distribution of returns is stable over time and that periodic returns are independent of one another, the arithmetic return is the best estimator of expected return.13 The geo- metric mean return is the internal rate of return between a single outlay and one or more future receipts. It measures the compound rate of return investors earned over past periods. It accurately portrays historical investment experience. Unless returns are the same each time period, the geometric average will always be less than the arithmetic average, and the gap widens as returns become more volatile.14

Based on Ibbotson Associates’ data (1995) from 1926 to 1995, Exhibit 7 illus- trates the possible range of equity market risk premiums depending on use of the geo- metric as opposed to the arithmetic mean equity return and on use of realized returns on T-bills as opposed to T-bonds.15 Even wider variations in market risk premiums can arise when one changes the historical period for averaging. Extending US stock expe- rience back to 1802, Siegel (1992) shows that historical market premia have changed over time and were typically lower in the pre-1926 period. Carleton and Lakonishok (1985) illustrate considerable variation in historical premia using different time peri- ods and methods of calculation even with data since 1926.

200 Part Three Estimating the Cost of Capital

13Several studies have documented significant negative autocorrelation in returns—this violates one of the essential tenets of the arithmetic calculation since, if returns are not serially independent, the simple arithmetic mean of a distribution will not be its expected value. The autocorrelation findings are reported by Fama and French (1986), Lo and MacKinlay (1988), and Poterba and Summers (1988). 14For large samples of returns, the geometric average can be approximated as the arithmetic average minus one half the variance of realized returns. Ignoring smaple size adjustments, the variance of returns in the current example is 0.09 yielding an estimate of 0.10 % 1/2(0.09) " 0.055 " 5.5% versus the actual 5.8% figure. Kritzman (1994) provides an interesting comparison of the two types of averages. 15These figures are drawn from Table 2–1, Ibbotson Associates (1995), where the Rm was drawn from the “Large Company Stocks” series, and Rf drawn from the “Long-Term Government Bonds” and “US Treasury Bills” series.

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Of the texts and tradebooks in our survey, 71% support use of the arithmetic mean return over T-bills as the best surrogate for the equity market risk premium. For long-term projects, Ehrhardt (1994) advocates forecasting the T-bill rate and using a different cost of equity for each future time period. Kaplan and Ruback (1995) studied the equity risk premium implied by the valuations in highly leveraged transactions and estimated a mean premium of 7.97%, which is most consistent with the arithmetic mean and T-bills. A minority view is that of Copeland, Koller, and Murrin (1990), “We believe that the geometric average represents a better estimate of investors’ expected over long periods of time.” Ehrhardt (1994) recommends use of the geometric mean return if one believes stockholders are buy-and-hold investors.

Half of the financial advisers queried use a premium consistent with the arith- metic mean and T-bill returns, and many specifically mentioned use of the arithmetic mean. Corporate respondents, on the other hand, evidenced more diversity of opinion and tend to favor a lower market premium: 37% use a premium of 5–6%, and another 11% use an even lower figure.

Comments in our interviews (see Exhibit 8) suggest the diversity among survey par- ticipants. While most of our 27 sample companies appear to use a 60$-year historical period to estimate returns, one cited a window of less than ten years, two cited windows of about ten years, one began averaging with 1960, and another with 1952 data.

This variety of practice should not come as a surprise since theory calls for a forward-looking risk premium, one that reflects current market sentiment and may change with market conditions. What is clear is that there is substantial variation as practitioners try to operationalize the theoretical call for a market risk premium. A glaring result is that few respondents specifically cited use of any forward-looking method to supplement or replace reading the tea leaves of past returns.16

IV. The Impact of Various Assumptions for Using CAPM To illustrate the effect of these various practices, we estimated the hypothetical cost of equity and WACC for Black & Decker, which we identified as having a wide range in estimated betas, and for McDonald’s, which has a relatively narrow range. Our esti- mates are “hypothetical” in that we do not adopt any information supplied to us by the companies but rather apply a range of approaches based on publicly available information as of late 1995. Exhibit 9 gives Black & Decker’s estimated costs of equity and WACCs under various combinations of risk-free rate, beta, and market risk premia. Three clusters of practice are illustrated, each in turn using three betas as pro- vided by S & P, Value Line, and Bloomberg (unadjusted). The first approach, as sug- gested by some texts, marries a short-term risk-free rate (90-day T-bill yield) with

Case 13 Best Practices in Estimating the Cost of Capital: Survey and Synthesis 201

16Only two respondents (one adviser and one company) specifically cited forward-looking estimates although others cited use of data from outside sources (e.g., a company using an estimate from an investment bank) where we cannot identify whether forward-looking estimates were used. Some studies using financial analyst forecasts in dividend growth models suggest market risk premia average in the 6% to 6.5% range and change over time with higher premia when interest rates decline. See for instance, Harris and Marston (1992). Ibbotson Asso- ciates (1994) provides industry-specific cost-of-equity estimates using analysts’ forecasts in a growth model.

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202 Part Three Estimating the Cost of Capital

Ibbotson’s arithmetic mean (using T-bills) risk premium. The second, adopted by a number of financial advisers, uses a long-term risk-free rate (30-year T-bond yield) and a risk premium of 7.2% (the modal premium mentioned by financial advisers). The third approach also uses a long-term risk-free rate but adopts the modal premium mentioned by corporate respondents of 5.5%. We repeated these general procedures for McDonald’s.

The resulting ranges of estimated WACCs for the two firms are

Maximum WACC Minimum WACC Difference in Basis Points

Black & Decker 12.80% 8.50% 430 McDonald’s 11.60% 9.30% 230

The range from minimum to maximum is large for both firms, and the economic impact is potentially stunning. To illustrate this, the present value of a level perpetual annual stream of $10 million would range between $78 million and $118 million for Black and Decker, and between $86 million and $108 million for McDonald’s.

Given the positive but relatively flat slope of the yield curve in late 1995, most of the variation in our illustration is explained by beta and the equity market premium assumption. Variations can be even more dramatic, especially when the yield curve is inverted.

V. Risk Adjustments to WACC Finance theory is clear that a single WACC is appropriate only for investments of broadly comparable risk: a firm’s overall WACC is a suitable benchmark for a firm’s average risk investments. Finance theory goes on to say that such a company-specific figure should be adjusted for departures from such an average risk profile. Attracting capital requires payment of a premium that depends on risk.

We probed whether firms use a discount rate appropriate to the risks of the flows being valued in questions on types of investment (strategic vs. operational), terminal values, synergies, and multidivisional companies. Responses to these ques- tions displayed in Exhibit 2 do not display much apparent alignment of practice. When financial advisers were asked how they value parts of multidivision firms, all ten firms surveyed reported that they use different discount rates for component parts (item 17). However, only 26% of companies always adjust the cost of capital to reflect the risk of individual investment opportunities (item 12). Earlier studies (sum- marized in Gitman and Mercurio, 1982) reported that between one-third and one- half of the firms surveyed did not adjust for risk differences among capital projects. These practices stand in stark contrast to the recommendations of textbooks and tradebooks: the books did not explicitly address all subjects, but when they did, they were uniform in their advocacy of risk-adjusted discount rates.

A closer look at specific responses reveals the tensions as theory based on traded financial assets is adapted to decisions on investments in real assets. Inevitably, a fine line is drawn between use of financial market data versus managerial judgments.

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Responses from financial advisers illustrate this. As shown in Exhibit 2, all advisers use different capital costs for valuing parts (e.g., divisions) of a firm (item 17); only half ever select different rates for synergies or strategic opportunities (item 18); only one in ten state any inclination to use different discount rates for terminal values and interim cash flows (item 16). Two simplistic interpretations are that 1) advisers ignore important risk differences, or 2) material risk differences are rare in assessing factors such as terminal values. Neither of these fit; our conversations with advisers reveal that they recognize important risk differences but deal with them in a multitude of ways. Consider comments from two prominent investment banks who use different capital costs for valuing parts of multidivision firms. When asked about risk adjust- ments for prospective merger synergies, these same firms responded:

• “We make these adjustments in cash flows and multiples rather than in discount rates.”

• “Risk factors may be different for realizations of synergies, but we make adjustments to cash flows rather than the discount rate.”

While financial advisers typically value existing companies, corporations face fur- ther challenges. They routinely must evaluate investments in new products and tech- nologies. Moreover, they deal in an administrative setting that melds centralized (e.g., calculating a WACC) and decentralized (e.g., specific project appraisal) processes. As Exhibit 10 illustrates, these complexities lead to a blend of approaches for dealing with risk. A number of respondents mentioned specific rate adjustments to distinguish between divisional capital costs, international versus domestic investments and leas- ing versus nonleasing situations. In other instances, however, these same respondents favored cash flow adjustments to deal with risks.

Why do practitioners risk adjust discount rates in one case and work with cash flow adjustments in another? Our interpretation is that risk-adjusted discount rates are more likely used when the analyst can establish relatively objective financial market benchmarks for what rate adjustments should be. At the business (division) level, data on comparable companies provide cost-of-capital estimates. Debt markets provide sur- rogates for the risks in leasing cash flows. International financial markets shed insights on cross-country differences. When no such market benchmarks are available, practi- tioners look to other methods for dealing with risks. Lacking a good market analog from which to glean investor opinion (in the form of differing capital costs), the ana- lyst is forced to rely more on internal focus. Practical implementation of risk-adjusted discount rates thus appears to depend on the ability to find traded financial assets that are comparable in risk to the cash flows being valued and then to have financial data on these traded assets.

The pragmatic bent of application also comes to the fore when companies are asked how often they reestimate capital costs (item 13, Exhibit 2). Even for those firms who reestimate relatively frequently, Exhibit 11 shows that they draw an impor- tant distinction between estimating capital costs and policy changes about the capital cost figure used in the firm’s decision making. Firms consider administrative costs in structuring their policies on capital costs. For a very large venture (e.g. an acquisition), capital costs may be revisited each time. On the other hand, only large material changes

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in costs may be fed into more formal project evaluation systems. Firms also recognize a certain ambiguity in any cost number and are willing to live with approximations. While the bond market reacts to minute basis point changes in investor return require- ments, investments in real assets, where the decision process itself is time consuming and often decentralized, involve much less precision. To paraphrase one of our sam- ple companies, we use capital costs as a rough yardstick rather than the last word in project evaluation.

Our interpretation is that the mixed responses to questions about risk adjusting and reestimating discount rates reflect an often sophisticated set of practical tradeoffs; these involve the size of risk differences, the quality of information from financial markets, and the realities of administrative costs and processes. In cases where there are material differences in perceived risk, a sufficient scale of investment to justify the effort, no large scale administrative complexities, and readily identifiable infor- mation from financial markets, practitioners employ risk adjustments to rates quite routinely. Acquisitions, valuing divisions of companies, analysis of foreign versus domestic investments, and leasing versus nonleasing decisions were frequently cited examples. In contrast, when one or more of these factors is not present, practitioners are more likely to employ other means to deal with risks.

VI. Conclusions Our research sought to identify the “best practice” in cost-of-capital estimation through interviews of leading corporations and financial advisers. Given the huge annual expenditure on capital projects and corporate acquisitions each year, the wise selection of discount rates is of material importance to senior corporate managers.

The survey revealed broad acceptance of the WACC as the basis for setting dis- count rates. In addition, the survey revealed general alignment in many aspects of the estimation of WACC. The main area of notable disagreement was in the details of implementing CAPM to estimate the cost of equity. This paper outlined the varieties of practice in CAPM use, the arguments in favor of different approaches, and the prac- tical implications.

In summary, we believe that the following elements represent best current prac- tice in the estimation of WACC:

• Weights should be based on market-value mixes of debt and equity.

• The after-tax cost of debt should be estimated from marginal pretax costs, com- bined with marginal or statutory tax rates.

• CAPM is currently the preferred model for estimating the cost of equity.

• Betas are drawn substantially from published sources, preferring those betas using a long interval of equity returns. Where a number of statistical publishers disagree, best practice often involves judgment to estimate a beta.

• Risk-free rate should match the tenor of the cash flows being valued. For most capital projects and corporate acquisitions, the yield on the US government Treasury bond of ten or more years in maturity would be appropriate.

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• Choice of an equity market risk premium is the subject of considerable controversy both as to its value and method of estimation. Most of our best-practice companies use a premium of 6% or lower while many texts and financial advisers use higher figures.

• Monitoring for changes in WACC should be keyed to major changes in financial market conditions, but should be done at least annually. Actually flowing a change through a corporate system of project valuation and compensation targets must be done gingerly and only when there are material changes.

• WACC should be risk adjusted to reflect substantive differences among different businesses in a corporation. For instance, financial advisers generally find the corporate WACC to be inappropriate for valuing different parts of a corporation. Given publicly traded companies in different businesses, such risk adjustment in- volves only modest revision in the WACC and CAPM approaches already used. Corporations also cite the need to adjust capital costs across national boundaries. In situations where market proxies for a particular type of risk class are not avail- able, best practice involves finding other means to account for risk differences.

Best practice is largely consistent with finance theory. Despite broad agreement at the theoretical level, however, several problems in application remain that can lead to wide divergence in estimated capital costs. Based on these remaining problems, we believe that further applied research on two principal topics is warranted. First, prac- titioners need additional tools for sharpening their assessment of relative risk. The variation in company-specific beta estimates from different published sources can cre- ate large differences in capital-cost estimates. Moreover, use of risk-adjusted discount rates appears limited by lack of good market proxies for different risk profiles. We believe that appropriate use of averages across industry or other risk categories is an avenue worth exploration. Second, practitioners could benefit from further research on estimating equity market risk premia. Current practice displays large variations and focuses primarily on averaging past data. Use of expectational data appears to be a fruitful approach. As the next generation of theories gradually sharpen our insights, we feel that research attention to implementation of existing theory can make for real improvements in practice.

Finally our research is a reminder of the old saying that too often in business we measure with a micrometer, mark with a pencil, and cut with an ax. Despite the many advances in finance theory, the particular “ax” available for estimating company cap- ital costs remains a blunt one. Best-practice companies can expect to estimate their weighted average cost of capital with an accuracy of no more than plus or minus 100 to 150 basis points. This has important implications for how managers use the cost of capital in decision making. First, do not mistake capital budgeting for bond pric- ing. Despite the tools available, effective capital appraisal continues to require thor- ough knowledge of the business and wise business judgment. Second, be careful not to throw out the baby with the bath water. Do not reject the cost of capital and atten- dant advances in financial management because your finance people are not able to give you a precise number. When in need, even a blunt ax is better than nothing.

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Jagannathan, Ravi and Ellen R. McGrattan, 1995, “The CAPM Debate,” The Federal Reserve Bank of Minneapolis Quarterly Review 19 (No. 4, Fall), 2–17.

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EXHIBIT 1 | Three Survey Samples

Company Sample Adviser Sample Textbook/Tradebook Sample

Advanced Micro CS First Boston Textbooks Allergan Dillon, Read Brealey and Myers Black & Decker Donaldson, Lufkin, Jenrette Brigham and Gapenski Cellular One J. P. Morgan Gitman Chevron Lehman Brothers Ross, Westerfield & Jaffe Colgate-Palmolive Merrill Lynch Tradebooks Comdisco Morgan Stanley Copeland, Koller & Murrin Compaq Salomon Brothers Ehrhardt Eastman Kodak Smith Barney Ibbotson Associates Gillette Wasserstein Perella Guardian Industries Henkel Hewlett-Packard Kanthal Lawson Mardon McDonald’s Merck Monsanto PepsiCo Quaker Oats Schering-Plough Tandem Union Carbide US West Walt Disney Weyerhauser Whirlpool

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EXHIBIT 2 | General Survey Results

Corporations Financial Advisers Textbooks/Tradebooks

1. Do you use DCF 89%—Yes, as a primary tool. 100%—Rely on DCF, 100%—Yes techniques to evaluate 7%—Yes, only as secondary comparable companies investment opportunities? tool. multiples, comparable

4%—No transactions multiples. Of these, 10%—DCF is a primary tool.

10%—DCF is used mainly as a check.

80%—Weight the three approaches depending on purpose and type of analysis.

2. Do you use any form of a 89%—Yes 100%—Yes 100%—Yes cost of capital as your 7%—Sometimes discount rate in your 4%—N/A DCF analysis?

3. For your cost of capital, do 85%—Yes 100%—Yes 100%—Yes you form any combination 4%—Sometimes of capital cost to determine 4%—No a WACC? 7%—N/A

4. What weighting factors do Target/Current Market/Book Target/Current Market/Book Target/Current Market/Book you use? 52%—Target 59%—Market 90%—Target 90%—Market 86%—Target 100%—Market target vs. current debt/equity 15%—Current 15%—Book 10%—Current 10%—Book 14%—Current/Target market vs. book weights 26%—Uncertain 19%—Uncertain

7%—N/A 7%—N/A

5. How do you estimate your 52%—Marginal cost 60%—Marginal cost 71%—Marginal cost before tax cost of debt? 37%—Current average 40%—Current average 29%—No explicit

4%—Uncertain recommendation 7%—N/A

6. What tax rate do you use? 52%—Marginal or statutory 60%—Marginal or statutory 71%—Marginal or statutory 37%—Historical average 30%—Historical average 29%—No explicit 4%—Uncertain 10%—Uncertain recommendation 7%—N/A

7. How do you estimate your 81%—CAPM 80%—CAPM 100%—Primarily cost of equity? (If you do 4%—Modified CAPM 20%—Other (including CAPM not use CAPM, skip to 15%—N/A modified CAPM) Other methods question 12.) mentioned: Dividend-

Growth Model, Arbitrage- Pricing Model.

8. As usually written, the 85%—Yes 90%—Yes 100%—Yes CAPM version of the cost 0%—No 10%—N/A of equity has three terms: 15%—N/A a risk-free rate, a volatility or beta factor, and a market-risk premium. Is this consistent with your company’s approach?

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210 Part Three Estimating the Cost of Capital

EXHIBIT 2 | (continued)

Corporations Financial Advisers Textbooks/Tradebooks

9. What do you use for the 4%—90-day T-Bill 10%—90-day T-Bill 43%—T-Bills risk-free rate? 7%—three- to seven-year 10%—five- to ten-year 29%—LT Treasuries

Treasuries Treasuries 14%—Match tenor of 33%—ten-year Treasuries 30%—ten- to 30-year Treasuries investment 4%—20-year Treasuries 40%—30-year Treasuries 14%—Don’t say 33%—ten- to 30-year Treasuries 10%—N/A 4%—ten-years or 90-Day;

Depends 15%—N/A (Many said they match the

term of the risk-free rate to the tenor of the investment.)

10. What do you use as your 52%—Published source 30%—Fundamental beta 100%—Mention availability volatility or beta factor? 3%—Financial adviser’s (e.g., BARRA) of published sources

estimate 40%—Published source 30%—Self calculated 20%—Self calculated 15%—N/A 10%—N/A

11. What do you use as your 11%—Use fixed rate of 4.0–4.5% 10%—Use fixed rate of 5.0% 71%—Arithmetic historical market-risk premium? 37%—Use fixed rate of 5.0–6% 50%—Use 7.0–7.4% mean

4%—Use geometric mean (Similar to arithmetic) 15%—Geometric historical 4%—Use arithmetic mean 10%—LT arithmetic mean mean 4%—Use average of historical 10%—Both LT arithmetic 14%—Don’t say

and implied and geometric mean 15%—Use financial adviser’s 10%—Spread above

estimate treasuries 7%—Use premium over 10%—N/A

treasuries 3%—Use Value Line estimate 15%—N/A

12. Having estimated your 26%—Yes Not asked. 86%—Adjust beta for company’s cost of 33%—Sometimes investment risk capital, do you make any 41%—No 14%—Don’t say further adjustments to reflect the risk of individual investment opportunities?

13. How frequently do you 4%—Monthly Not asked. 100%—No explicit re-estimate your 19%—Quarterly recommendation company’s cost of 11%—Semi-Annually capital? 37%—Annually

7%—Continually/Every Investment

19%—Infrequently 4%—N/A (Generally, many said that

in addition to scheduled reviews, they re-estimate as needed for significant events such as acquisitions and high-impact economic events.)

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Case 13 Best Practices in Estimating the Cost of Capital: Survey and Synthesis 211

EXHIBIT 2 | (concluded)

Corporations Financial Advisers Textbooks/Tradebooks

14. Is the cost of capital 51%—Yes Not asked. 100%—No explicit used for purposes other 44%—No discussion than project analysis in 4%—N/A your company? (For example, to evaluate divisional performance?)

15. Do you distinguish 48%—Yes Not asked. 29%—Yes between strategic and 48%—No 71%—No explicit operational investments? 4%—N/A discussion Is cost of capital used differently in these two categories?

16. What methods do you Not asked. 30%—Exit multiples only 71%—Perpetuity DCF use to estimate terminal 70%—Both multiples and model value? Do you use the perpetuity DCF model 29%—No explicit same discount rate for 70%—Use same WACC discussion the terminal value as for TV 100%—No explicit for the interim cash 20%—No response discussion of separate flows? 10%—Rarely change WACC for terminal

value

17. In valuing a multidivisional Not asked. 100%—Value the parts 100%—Use distinct WACC company, do you 100%—Use different WACCs for each division aggregate the values of for separate valuations the individual divisions, or just value the firm as a whole? If you value each division separately, do you use a different cost of capital for each one?

18. In your valuations do Not asked. 30%—Yes 29%—Use distinct WACC you use any different 50%—No for synergies methods to value 20%—Rarely 71%—No explicit synergies or strategic discussion opportunities (e.g., higher or lower discount rates, options valuation)?

19. Do you make any Not asked. 20%—Yes 14%—Yes adjustments to the risk 70%—No 86%—No explicit premium for changes in 10%—N/A discussion market conditions?

20. How long have you 10 years—Mean 7.3 years—Mean N/A been with the company? All senior, except one 4—MDs, 2 VPs, What is your job title? 4—Associates

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Some of our best-practice companies noted that their choice of a bond market proxy for a risk-free rate depended specifically on how they were proposing to spend funds. We asked, “What do you use for a risk-free rate?” and heard the following:

• “Ten-year Treasury bond or other duration Treasury bond if needed to better match project horizon.”

• “We use a three- to five-year Treasury note yield, which is the typical length of our company’s investment. We match our average investment horizon with maturity of debt.”

EXHIBIT 3 | Choice of Bond Market Proxy

EXHIBIT 4 | Compromises Underlying Beta Estimates and Their Effect on Estimated Betas of Sample Companies

Bloomberga Value Line Standard & Poor’s

Number 102 260 60 Time Interval wkly (2 yrs.) wkly (5 yrs.) mthly (5 yrs.) Market Index Proxy S&P 500 NYSE composite S&P 500 Mean Beta 1.03 1.24 1.18 Median Beta 1.00 1.20 1.21

aWith the Bloomberg service, it is possible to estimate a beta over many differing time periods, market indices, and as smoothed or unadjusted. The figures presented here represent the base-line or default-estimation approach used if other approaches are not specified.

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EXHIBIT 5 | Betas for Corporate Survey Respondents

In this exhibit, Bloomberg’s adjusted beta is !adj " (0.66)!raw $ (0.33)1.00 and Value Line reported only Total Debt/Total Cap for these firms, except in the case of US West, in which LT Debt/Total Cap was reported.

Bloomberg Betas Range

Raw Adjusted Value Line Betas S&P Betas Max.–Min.

Advanced Micro 1.20 1.13 1.70 1.47 0.57 Allergan 0.94 0.96 1.30 1.36 0.42 Black & Decker 1.06 1.04 1.65 1.78 0.74 Cellular One Not Listed Chevron 0.70 0.80 0.70 0.68 0.12 Colgate-Palmolive 1.11 1.07 1.20 0.87 0.33 Comdisco 1.50 1.34 1.35 1.20 0.30 Compaq 1.26 1.18 1.50 1.55 0.37 Eastman Kodak 0.54 0.69 NMF 0.37 0.32 Gillette 0.93 0.95 1.25 1.30 0.37 Guardian Industries Not Listed Henkel Not Listed Hewlett-Packard 1.34 1.22 1.40 1.96 0.74 Kanthal Not Listed Lawson Mardon Not Listed McDonald’s 0.93 0.96 1.05 1.09 0.16 Merck 0.73 0.82 1.10 1.15 0.42 Monsanto 0.89 0.93 1.10 1.36 0.47 PepsiCo 1.12 1.08 1.10 1.19 0.11 Quaker Oats 1.38 1.26 0.90 0.67 0.71 Schering-Plough 0.51 0.67 1.00 0.82 0.49 Tandem 1.35 1.23 1.75 1.59 0.52 Union Carbide 1.51 1.34 1.30 0.94 0.57 US West 0.61 0.74 0.75 0.53 0.22 Walt Disney 1.42 1.28 1.15 1.22 0.27 Weyerhauser 0.78 0.85 1.20 1.21 0.43 Whirlpool 0.90 0.93 1.55 1.58 0.68 Mean 1.03 1.02 1.24 1.18 0.42 Median 1.00 1.00 1.20 1.21 0.42 Standard Deviation 0.31 0.21 0.29 0.41 0.19

Case 13 Best Practices in Estimating the Cost of Capital: Survey and Synthesis 213

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214 Part Three Estimating the Cost of Capital

We asked our sample companies, “What do you use as your volatility or beta factor?” A sam- pling of responses shows the choice is not always a simple one.

• “We use adjusted betas reported by Bloomberg. At times, our stock has been extremely volatile. If at a particular time the factor is considered unreasonably high, we are apt to use a lower (more consistent) one.”

• “We begin with the observed 60-month covariance between our stock and the market. We also consider, Value Line, Barra, S&P betas for comparison and may adjust the observed beta to match assessment of future risk.”

• “We average Merrill Lynch and Value Line figures and use Bloomberg as a check.” • “We do not use betas estimated on our stock directly. Our company beta is built up as a

weighted average of our business segment betas—the segment betas are estimated using pure-play firm betas of comparable companies.”

EXHIBIT 6 | Beta Factor

EXHIBIT 7 | The Equity Market Risk Premium

T-Bill Returns T-Bond Returns

Arithmetic Mean Return 8.5% 7.0% Geometric Mean Return 6.5% 5.4%

1Rm % Rf2

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EXHIBIT 8 | Market Risk Premium

“What do you use as your market risk premium?” A sampling of responses from our best- practice companies shows the choice can be a complicated one.

• “Our 400 basis point market premium is based on the historical relationship of returns on an actualized basis and/or investment bankers’ estimated cost of equity based on analysts’ earnings projections.”

• “We use an Ibbotson arithmetic average starting in 1960. We have talked to investment banks and consulting firms with advice from 3–7%.”

• “A 60-year average of about 5.7%. This number has been used for a long time in the com- pany and is currently the subject of some debate and is under review. We may consider us- ing a time horizon of less than 60 years to estimate this premium.”

• “We are currently using 6%. In 1993, we polled various investment banks and academic studies on the issue as to the appropriate rate and got anywhere between 2% and 8%, but most were between 6% and 7.4%.”

Comments from financial advisers also were revealing. While some simply responded that they use a published historical average, others presented a more complex picture.

• “We employ a self-estimated 5% (arithmetic average). A variety of techniques are used in estimation. We look at Ibbotson data and focus on more recent periods, around 30 years (but it is not a straight 30-year average). We use smoothing techniques, Monte Carlo simu- lation and a dividend discount model on the S&P 400 to estimate what the premium should be, given our risk-free rate of return.”

• “We use a 7.4% arithmetic mean, after Ibbotson, Sinquefeld. We used to use the geometric mean following the then scholarly advice, but we changed to the arithmetic mean when we found later that our competitors were using the arithmetic mean and scholars’ views were shifting.”

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216 Part Three Estimating the Cost of Capital

EXHIBIT 9 | Variations in Cost of Capital (WACC) Estimates for Black and Decker Using Different Methods of Implementing the Capital-Asset Pricing Model

In this Exhibit, in all cases the CAPM is used to estimate the cost of equity, the cost of debt is assumed to be 7.81% based on a Beta rating, the tax rate is assumed to be 38%, and debt is assumed to represent 49% of capital.

Panel A. Short-Term Rate Plus Arithmetic Average Historical Risk Premium

(recommended by some texts) 90-day T-bills

Ibbotson arithmetic average since 1926Rm % Rf " 8.50%, Rf " 5.36%,

Panel B. Long-Term Rate Plus Risk Premium of 7.20%

(modal practice of financial advisers surveyed) 30-year T-bonds

modal response of financial advisersRm % Rf " 7.20%, Rf " 6.26%,

Panel C. Long-Term Rate Plus Risk Premium of 5.50%

(modal practice of corporations surveyed) 30-year T-bonds

modal response of corporationsRm % Rf " 5.50%, Rf " 6.26%,

Cost of Equity Cost of Capital

Beta Service Ke WACC Bloomberg, 14.40% 9.70% Value Line, 19.40% 12.20% S&P, 20.25% 12.80%! " 1.78

! " 1.65 ! " 1.06

Cost of Equity Cost of Capital

Beta Service Ke WACC Bloomberg, 13.90% 9.40% Value Line, 18.10% 11.60% S&P, 19.10% 12.10%! " 1.78

! " 1.65 ! " 1.06

Cost of Equity Cost of Capital

Beta Service Ke WACC Bloomberg, 12.10% 8.50% Value Line, 15.30% 10.20% S&P, 16.10% 10.50%! " 1.78

! " 1.65 ! " 1.06

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EXHIBIT 10 | Adjustments for Project Risk

When asked whether they adjusted discount rates for project risk, companies provided a wide range of responses.

• “No, it’s difficult to draw lines between the various businesses we invest in and we also try as best we can to make adjustments for risk in cash flow projections rather than in cost of capital factors . . . We advocate minimizing adjustments to cost of capital calculations and maximizing understanding of all relevant issues, e.g., commodity costs and international/ political risks.” At another point the same firm noted that “for lease analysis only the cost of debt is used.”

• “No (we don’t risk adjust cost of capital). We believe there are two basic components: 1) projected cash flows, which should incorporate investment risk, and 2) discount rate.” The same firm noted, however: “For international investments, the discount rate is adjusted for country risk.” and “For large acquisitions, the company takes significantly greater care to estimate an accurate cost of capital.”

• “No, but use divisional costs of capital to calculate a weighted average company cost of capital . . . for comparison and possible adjustment.”

• “Yes, we have calculated a cost of capital for divisions based on pure play betas and also suggest subjective adjustments based on each project. Our feeling is that use of divisional costs is the most frequent distinction in the company.”

• “Rarely, but at least on one occasion we have for a whole new line of business.” • “We do sensitivity analysis on every project.” • “For the most part we make risk adjustments qualitatively, i.e., we use the corporate WACC

to evaluate a project, but then interpret the result according to the risk of the proposal being studied. This could mean that a risky project will be rejected even though it meets the cor- porate hurdle rate objectives.”

• “No domestically; yes internationally—we assess a risk premium per country and adjust the cost of capital accordingly.”

EXHIBIT 11 | Cost-of-Capital Estimates

How frequently do you re-estimate your company’s cost of capital? Here are responses from best-practice companies.

• “We usually review it quarterly but would review more frequently if market rates changed enough to warrant the review. We would only announce a change in the rate if the recom- puted number was materially different than the one currently being used.”

• “We reestimate it once or twice a year, but we rarely change the number that the business units use for decision and planning purposes. We expect the actual rate to vary over time, but we also expect that average to be fairly constant over the business cycle. Thus, we tend to maintain a steady discount rate within the company over time.”

• “Usually every six months, except in cases of very large investments, in which it is reestimated for each analysis.”

• “Whenever we need to, such as for an acquisition or big investment proposal.” • “Re-evaluate as needed e.g., for major tax changes, but unless the cost of capital change

is significant (a jump to 21%, for instance), our cutoff rate is not changed; it is used as a yardstick rather than the last word in project evaluation.”

• “Probably need 100 basis point change to publish a change. We report only to the nearest percent.”

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Roche Holding Ag: Funding The Genentech Acquisition

We are confident that we will have the financing available when the money is needed . . . The plan is to use as financing partly our own funds and then obviously bonds and then commercial paper and traditional bank financing. We will start by going to the bond market first.1

—Roche Chairman Franz Hume

In July 2008, Swiss pharmaceutical company Roche Holding AG (Roche) made an offer to acquire all remaining outstanding shares of U.S. biotechnology leader Genen- tech for (U.S. dollars) USD89.00 per share in cash. Six months later, with equity mar- kets down 35%, Roche announced its recommitment to the deal with a discounted offer of USD86.50 in cash per share of Genentech stock.

To pay for the deal, Roche needed USD42 billion in cash. To meet that massive cash need, which was not fully available through bank debt, management planned to sell USD32 billion in bonds at various maturities from 1 year to 30 years and in three different currencies (U.S. dollar, euro, and British pound). The sale would begin with the dollar-denominated offering and followed up soon after with rounds of offerings in the other currencies.

In mid-February 2009, Roche was ready to move forward with what was antici- pated to be the largest bond offering in history. With considerable ongoing turmoil in world financial markets and substantial uncertainty surrounding the willingness of

219

14CASE

1Sam Cage, “Roche Goes Hostile, Cuts Genentech Bid to $42 Billion,” Reuters, January 30, 2009.

This case, based on publicly available data, was prepared by Brett Durick (MBA’11), Drew Chambers (MBA’11), and Michael J. Schill, Robert F. Vandell Research Associate Professor of Business Administra- tion. This case is dedicated to Courtney Turner Chambers, in recognition of the sacrifice and contribution of Darden partners. It was written as a basis for class discussion rather than to illustrate effective or ineffective handling of an administrative situation. Copyright © 2011 by the University of Virginia Darden School Foundation, Charlottesville, VA. All rights reserved. To order copies, send an e-mail to [email protected] No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means––electronic, mechanical, photocopying, recording, or otherwise––without the permission of the Darden School Foundation.

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Genentech minority shareholders to actually sell their shares for the reduced offer of USD86.50, Roche’s financing strategy was certainly bold.

Roche In 1894, Swiss banker Fritz Hoffmann-La Roche, 26, joined Max Carl Traub to take over a small factory on Basel’s Grenzacherstrasse from druggists Bohny, Hollinger & Co. Following a difficult first two years, Hoffmann-La Roche bought out his partner and entered F. Hoffmann-La Roche & Co. in the commercial register.

In the early years, the company’s primary products included sleeping agents, antiseptics, and vitamins; by the late 1930s, the company had already expanded to 35 countries, an expansion that continued in the decades following the Second World War. In 1990, the company, by then known as Roche, acquired a majority stake in Genentech, a South San Francisco biotechnology company, for USD2.1 billion. Genentech’s research focused primarily on developing products based on gene splic- ing or recombinant DNA to treat diseases such as cancer and AIDS. The acquisition gave Roche a strong foothold in the emerging biologics market as well as stronger presence in the U.S. market.

Since the 1990s, Roche had maintained focus on its two primary business units, pharmaceuticals and medical diagnostics; in 2004, Roche sold its over-the-counter consumer health business to Bayer AG for nearly USD3 billion. In 2008, Roche expanded its diagnostics business with the acquisition of Ventana Medical Systems for USD3.4 billion.

By the end of 2008, Roche’s total revenue was just shy of (Swiss francs) CHF50 billion. The pharmaceutical division contributed 70% of the total Roche revenue and over 90% of the operating profit. Roche was clearly one of the leading pharmaceuti- cals in the world. Exhibit 1 provides a revenue breakdown of Roche’s 2008 revenue by geography and therapeutic area, as well as a detailed overview of Roche’s top sell- ing pharmaceutical products. Roche and Genentech’s financial statements are detailed in Exhibit 2 and 3, respectively, and the stock performance of the two companies is shown in Exhibit 4.

Market Conditions The past 18 months had been historic for global financial markets, which had under- gone a sharp correction after dramatic declines in real estate prices and an overheated credit market. Since October 2007, world equity market prices had declined over 45%. Large numbers of commercial and investment banks had failed. The global labor mar- ket was shedding jobs, resulting in sharp increases in unemployment rates. Broad eco- nomic activity was also affected, with large declines in overall economic activity.

In response to what some feared would become the next Great Depression, world governments made massive investments in financial and industrial institutions. In an effort to stimulate liquidity, central banks had lowered interest rates. The market uncer- tainty was accompanied with a massive “flight to quality” as global investors moved capital to U.S. Treasury securities (particularly short-term T-bills), thereby driving down U.S. benchmark yields to historic lows. Exhibit 5 shows the prevailing yield

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Case 14 Roche Holding Ag: Funding The Genentech Acquisition 221

curve in U.S. dollars, euros, and British pounds. Exhibit 6 contains the prevailing credit spreads over benchmark yields for U.S. industrial corporate bonds based on bond rat- ings from bond-rating agency Standard and Poor’s. Exhibit 7 plots historical trends in yields of bonds by various credit ratings over the past two years. Exhibit 8 provides a definitional overview of Standard and Poor’s credit ratings. Roche’s current credit rating with Standard and Poor’s was AA—and with Moody’s was Aa1. Exhibit 9 details median values for various financial ratios for companies rated within a partic- ular category for 2007 and 2008. Despite the uncertainty in the credit markets, corpo- rate transactions were reawakening in the pharmaceutical industry. Pfizer had recently agreed to acquire Wyeth for USD68 billion. In the deal, five banks had agreed to lend Pfizer USD22.5 billion to pay for the deal, and Pfizer was funding the remaining USD45.5 billion through issuance of a combination of cash and stock.

The Bond Offering Process The issuance of publicly traded bonds, in addition to the pricing and marketing of the deal, required the satisfaction of certain legal requirements. Because of the complex- ity and importance of these two processes, corporations typically hired investment bankers to provide assistance. Given the size of the deal, Roche hired three banks as joint lead managers for the U.S. dollar deal (Banc of America Securities, Citigroup Global Markets, and JPMorgan) and four bankers for the euro and pound sterling deals (Barclays Capital, BNP Paribas, Deutsche Bank, and Banco Santander).

Because Roche’s bonds would be publicly traded, it had to file with the appro- priate regulatory agencies in the countries where the bonds would be issued. Simul- taneous with the drafting of the documentation by legal teams, the underwriting banks’ debt capital markets and syndication desks began the marketing process. The initial phase of this process was the “road show.” During the road show, management teams for Roche and the banks held initial meetings with investors from all over the world. The Roche management team expected to meet with investors in many of the major investment centers in the United States and Europe.

Given the global nature of Roche’s business, the banks determined that a mix of bonds at different maturities and in different currencies was the best option. By match- ing differing maturities and currencies to the company’s operating cash flows in those currencies, Roche was able to reduce exchange rate risk. Exhibit 10 provides an overview of the different currency and maturity tranches planned in the offering. The final amounts raised from each offering, along with the coupon rate, were not yet determined because pricing was expected to be highly influenced by investor demand. To ensure that the bond offering raised the targeted proceeds, the coupon rate was set to approximate the anticipated yield, such that the bond traded at par. Following mar- ket conventions, the U.S. dollar bonds would pay interest semiannually, and the euro and sterling issues would pay interest annually.

The coupon payments of the shorter durations were to be floating, and the inter- est to be paid was equivalent to the short-term interbank interest rate (LIBOR) plus a credit spread. The longer durations were to have fixed coupon payments for the dura- tion of the bond. Investors typically referenced the “price” of bonds as the spread over

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the applicable risk-free rate. The risk-free rate was commonly established as the respec- tive government borrowing rate and was referred to as the benchmark, sovereign, or Treasury rate. The spread was referred to as the credit spread, the logic being that the issuer had to offer a price over the risk-free rate to entice investors to buy the bonds.

During the road show, banks received feedback from investors on the demand for each tranche. Determining the final size and pricing of each issue was an iterative process between the investors, banks, and issuer. In the case of Roche, if investors showed strong demand for the four-year euro tranche, Roche could decide to either issue more at that price (thus reducing the amount of another tranche) or lower the coupon and pay a lower interest rate on the four-year euro issue. The banks’ process of deter- mining demand and receiving orders for each issue was known as book-building. Bond prices were set based on prevailing yields of bond issues by similar companies. Exhibits 11 and 12 provide a sample of prevailing prices and terms of company bonds traded in the market, in addition to various equity market and accounting data.

The Genentech Deal On July 21, 2008, Roche publicly announced an offer to acquire the 44.1% of Genen- tech’s outstanding shares that it did not already own. The offer price of USD89.00 represented a 19% premium over the previous one-month share prices for Genentech. Roche management believed that economies justified the premium with an estimate that, following the transaction, the combined entity could realize USD750 million to USD850 million in operational efficiencies. Following the offer, Genentech’s stock price shot up beyond the USD89.00 offer price with the anticipation that Roche would increase its offer.

On August 13, 2008, a special committee of Genentech’s board of directors (those without direct ties to Roche) responded to Roche’s offer. The committee stated that the offer “substantially undervalues the company.” Without the support of Genentech’s board of directors, Roche needed either to negotiate with the board or take the offer directly to shareholders with what was known as a tender offer. In that case, share- holders would receive a take-it-or-leave-it offer. If sufficient shareholders “tendered” their shares, the deal would go through regardless of the support of the board.

Over the next six months, the capital markets fell into disarray. As credit mar- kets deteriorated, Genentech shareholders realized that Roche might not be able to finance an increased bid for the company, and the share price continued to decline through the end of the year. Contemporaneously with the deal, Genentech was await- ing the announcement of the clinical trial results for several of its next generation of potential drugs, including its promising cancer drug Avastin.

On January 30, 2009, Roche announced its intention to launch a tender offer for the remaining shares at a reduced price of USD86.50. The revised offer was contin- gent on Roche’s ability to obtain sufficient financing to purchase the shares. The announcement was accompanied by a 4% price drop of Genentech’s share price to USD80.82. Bill Tanner, analyst at Leerink Swann, warned Genentech shareholders that the stock was overvalued and that if upcoming Genentech drug trials showed mediocre results then the stock would fall into the USD60 range. He encouraged

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shareholders to take the sure USD86.50 offer claiming that “DNA’s [the stock ticker symbol for Genentech] best days may be over.”2

Jason Napadano, analyst at Zach’s Investment Research, claimed that Roche was trying “to pull the wool over the eyes of Genentech shareholders.” He continued, “Roche is trying to get this deal done before the adjuvant colon cancer data comes out and Genentech shareholders are well aware of that. I don’t know why they would tender their shares for [USD]86.50, which is only 10% above today’s price, when they can get closer to $95 to $100 a share if they wait.”3

The Financing Proposal Unlike Pfizer in its acquisition of Wyeth, Roche could not issue equity to Genentech shareholders. Roche was controlled by the remnants of its founder in the Oeri, Hoff- man, and Sacher families. The company maintained two classes of shares, bearer and Genussscheine (profit-participation) shares. Both share classes had equal economic rights (i.e., same dividends, etc.) and traded on the Swiss Stock Exchange, but the bearer shares were the only shares with voting rights, and the founding family con- trolled just over 50% of the bearer shares. This dual-share structure existed before modern shareholder rights legislation in Switzerland and was grandfathered in. In the event Roche were to issue equity to Genentech shareholders, this dual-class share structure would have to be revisited, and the family might lose control. Given this ownership structure, Roche was forced to finance the deal entirely of debt and cur- rent cash on hand.

When Roche originally announced the transaction, the company had intended to finance the acquisition with a combination of bonds and loans from a variety of com- mercial banks. The collapse of the financial markets caused many of the commercial banks to demand a much higher interest rate on the loans than originally anticipated by Roche. As a result of the change in market conditions, Roche was limited to the bond market for the majority of its financing. Despite the magnitude of the debt- financing need, the investment banks assisting in the deal expected that Roche’s cash flow was stable enough to manage the additional level of debt.

To ensure that Roche raised the necessary capital, it was important to correctly anticipate the required yield on each bond and set the coupon rate at the rate that would price the bond at par. This was done by simply setting the coupon rate equal to the anticipated yield. With such a substantial amount of money riding on the deal, it was critical that Roche correctly set the price, despite the immense uncertainty in capital markets.

2Bob O’Brien, “Analysts Debate Strategy Behind Sourer Offer,” Barron’s, January 30, 2009. 3O’Brien.

Case 14 Roche Holding Ag: Funding The Genentech Acquisition 223

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224

EXHIBIT 1 | 2008 Revenue Breakdown (sales in millions of Swiss francs)

By Geography Share Product (Indication) Sales

North America 41% MabThera/Rituxin (lymphoma, leukemia, rheumatoid 5,923 arthritis)

Western Europe 29% Avastin (colorectal, breast, lung, and kidney cancer) 5,207 CEMAI1 9% Herceptin (breast cancer) 5,092 Japan 9% CellCept (transplantation) 2,099 Latin America 6% NeoRecormon/Epogin (anemia) 1,774 Asia-Pacific 5% Peasys (hepatitis) 1,635 Others 1% Tarceva (lung cancer, pancreatic cancer) 1,215

Lucentis (macular degeneration) 960 By Therapeutic Category Share Tamiflu (influenza) 609 Oncology 55% Xolair (asthma) 560 Inflammation and autoimmune

diseases, transplantation 9% Valcyte/Cymevene (herpes) 553 Xenical (weight loss and control) 502

Central nervous system 3% Pulmozyme (cystic fibrosis) 496 Respiratory 3% Nutropin (growth hormone deficiency) 413 Metabolic diseases, bone diseases 8% Neutrogin (neutropenia associated with chemotherapy) 404 Infectious diseases 1% Rocephin (bacterial infections) 344 Cardiovascular diseases 3% Activase, TNKase (heart attack) 342 Virology 9% Madopar (Parkinson’s disease) 311 Renal anemia 4% Ophthalmology 3% Others 2%

Data Source: Roche 2008 annual report. 1CEMAI: Central and Eastern Europe, the Middle East, Africa, Central Asia, and the Indian Subcontinent. This acronym appears to be unique to Roche.

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EXHIBIT 2 | Roche Financial Statements, Financial Years Ended December 31 (in millions of Swiss francs)

Income statement 2004 2005 2006 2007 2008

Revenue 31,092 36,958 43,432 48,376 47,904 COGS 7,718 9,270 13,096 13,738 13,605 Gross margin 23,374 27,688 30,336 34,638 34,299

Operating expense Sales and marketing 10,423 11,816 11,588 11,576 11,317 Research and development 5,154 5,672 7,286 8,327 8,720 Other operating 1,572 1,011 0 0 0 Operating income 6,225 9,189 11,462 14,735 14,262 Net interest expense (income) 311 (742) (443) (791) (488) Other non-operating expenses (income) (677) 769 (682) 222 589 Income tax 1,865 2,284 3,436 3,867 3,317 Minority interest !457 !943 !1,291 !1,676 !1,875 Net income 6,606 5,923 7,880 9,761 8,969

Balance sheet Total cash and ST investments 12,999 20,885 24,996 24,802 21,438 Total other current assets 16,680 14,741 15,899 18,032 17,166 Net PP&E 12,408 15,097 16,417 17,832 18,190 Other noncurrent assets 16,359 18,472 17,102 17,699 19,295 Total assets 58,446 69,195 74,414 78,365 76,089

Total current liabilities 10,134 9,492 12,692 14,454 12,104 Long-term debt 7,077 9,322 6,191 3,831 2,971 Unearned revenue 0 183 163 243 174 Other noncurrent liabilities 13,237 16,864 15,924 14,354 16,361 Total liabilities 30,448 35,861 34,970 32,882 31,610

Common stock 160 160 160 160 160 Retained earnings 35,960 38,624 44,251 50,922 52,081 Treasury stock !4,326 !3,485 !2,102 !1,017 ! Comprehensive inc. and other !3,796 !1,965 !2,865 !4,582 !7,762 Total shareholder equity 27,998 33,334 39,444 45,483 44,479

Total liabilities and SE 58,446 69,195 74,414 78,365 76,089

Data Source: Capital IQ.

Case 14 Roche Holding Ag: Funding The Genentech Acquisition 225

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226 Part Three Estimating the Cost of Capital

EXHIBIT 3 | Genentech Financial Statements (in millions of U.S. dollars)

Income statement 2004 2005 2006 2007 2008

Revenue 4,621 6,633 9,284 11,724 13,418 COGS 805 1,155 1,366 1,767 1,971 Gross margin 3,816 5,478 7,918 9,957 11,447

Operating expense Sales and marketing 1,088 1,435 2,014 2,256 2,405 Research and development 816 1,118 1,588 2,250 2,573 Other operating 739 946 1,110 1,212 1,400 Operating income 1,173 1,979 3,206 4,239 5,069 Net interest expense (income) (83) (93) (156) (224) (75) Other non-operating expenses (income) 36 59 (35) 38 (286) Income tax 435 734 1,290 1,657 2,004 Minority interest 0 0 0 0 0 Net income 785 1,279 2,107 2,768 3,426

Balance sheet Total cash and ST investments 1,665 2,365 2,493 3,975 6,198 Total other current assets 1,760 2,021 3,211 4,778 3,875 Net PP&E 2,091 3,349 4,173 4,986 5,404 Other noncurrent assets 3,887 4,412 4,965 5,201 6,310 Total assets 9,403 12,147 14,842 18,940 21,787 Total current liabilities 1,238 1,660 2,010 3,918 3,095 Long-term debt 412 2,083 2,204 2,402 2,329 Unearned revenue 268 220 199 418 444 Other noncurrent liabilities 703 714 951 297 248 Total liabilities 2,621 4,677 5,364 7,035 6,116

Common stock 21 21 21 21 21 Additional paid in capital 8,003 9,263 10,091 10,695 12,044 Retained earnings (1,533) (2,067) (838) 992 3,482 Comprehensive inc. and other 291 253 204 197 124 Total shareholder equity 6,782 7,470 9,478 11,905 15,671

Total liabilities and SE 9,403 12,147 14,842 18,940 21,787

Data Source: Capital IQ.

bru6171X_case14_219-234.qxd 11/26/12 11:01 AM Page 226

Case 14 Roche Holding Ag: Funding The Genentech Acquisition 227

EXHIBIT 4 | Stock Price Performance of Roche and Genentech, February 2007 to February 2009 (in Swiss francs and U.S. dollars, respectively)1

Data Source: Capital IQ. 1Correspondence of values between axes is approximate, based on exchange rates on February 28, 2007. The average rate for the period was USD1.13/CHF1.00.

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Roche Holding AG (SWX:ROG) Genentech, Inc. (NYSE:DNA)

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228 Part Three Estimating the Cost of Capital

EXHIBIT 5 | Annual Yield Rate to Maturity (U.S. Dollar, Euro, British Pound), February 2009 (in percent)

U.S.Treasuries Euro Benchmark1 UK Sovereign

6-mo 0.34 n/a 0.48 1 0.48 2.09 0.56 2 0.93 2.26 0.88 3 1.35 2.55 1.39 4 1.50 2.81 1.85 5 1.87 3.01 2.29 6 n/a 3.19 2.79 7 2.18 3.35 3.06 8 2.67 3.48 3.25 9 2.80 3.60 3.50

10 2.85 3.70 3.66 12 n/a 3.87 n/a 15 3.45 3.99 4.13 20 3.91 3.99 4.29 25 3.90 3.83 4.34 30 3.59 3.69 4.35

Data Source: Bloomberg. 1The euro benchmark is obtained from the midrate of the euro versus the EURIBOR mid-interest rate swap.

EXHIBIT 6 | U.S. Yield Spreads of U.S. Industrial Corporate Bonds over Comparable Maturity of U.S. Treasuries for S&P’s Bond-Rating Categories, February 2009 (in basis points)

Years to maturity

Rating 1 2 3 5 7 10 30

AAA 90 82 77 90 136 114 170 AA 210 201 198 202 224 204 242 A" 211 201 217 226 243 226 242 A 279 261 278 277 290 275 263 A! 289 271 287 286 303 284 273 BBB" 406 387 409 406 412 406 394 BBB 417 398 422 424 435 418 411 BBB! 493 497 510 520 527 509 506

Data Source: Bloomberg.

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Case 14 Roche Holding Ag: Funding The Genentech Acquisition 229

EXHIBIT 7 | History of U.S. Bond Yields for 30-Year Maturities, February 2006 to February 2009 (in percent)

Data Source: Datastream, Mergent Bond Record.

10.00

Yi eld

(% )

9.00

8.00

7.00

6.00

5.00

4.00

3.00

2.00 Feb-06 Aug-06 Aug-07 Aug-08Feb-07 Feb-08 Feb-09

Mergent Corporate Bond Yield Average - Baa Rating Mergent Corporate Bond Yield Average - Aa Rating U.S. Treasuries 30-Year Yield

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230 Part Three Estimating the Cost of Capital

EXHIBIT 8 | S&P Credit Ratings Overview

S&P’s global bond-rating scale provides a benchmark for evaluating the relative credit risk of issuers and issues worldwide.

Investment grade

AAA Extremely strong capacity to meet financial commitments. Highest rating AA Very strong capacity to meet financial commitments A Strong capacity to meet financial commitments, but somewhat susceptible to adverse economic condi-

tions and changes in circumstances BBB Adequate capacity to meet financial commitments, but more subject to adverse economic conditions

Speculative grade

BB Less vulnerable in the near-term but faces major ongoing uncertainties to adverse business, financial, and economic conditions

B More vulnerable to adverse business, financial, and economic conditions but currently has the capac- ity to meet financial commitments

CCC Currently vulnerable and dependent on favorable business, financial, and economic conditions to meet financial commitments

CC Currently highly vulnerable C A bankruptcy petition has been filed or similar action taken, but payments of financial commitments

are continued D Payment default on financial commitments

Ratings from “AA” to “CCC” may be modified by the addition of a plus (") or minus (!) sign to show relative standing within the major rating categories. The Moody’s bond-rating service had a similar rating scale but denoted an S&P “BBB” rating, for example, as “Baa.”

Data Source: Guide to Credit Rating Essentials, Standard and Poor’s, http://www2.standardandpoors.com/spf/pdf/ fixedincome/SP_CreditRatingsGuide.pdf (accessed February 16, 2011).

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Case 14 Roche Holding Ag: Funding The Genentech Acquisition 231

EXHIBIT 9 | Median Financial Ratio Values for all U.S. Rated Industrial Companies, 2007 and 2008

Number of Debt/ EBITDA/ EBIT/ Debt/ companies (Debt + BookEq) Int. Expense Int. Expense EBITDA

2007

AAA 26 0.51 95.47 74.06 2.26 AA 189 0.30 35.92 31.05 0.85 A 539 0.41 12.45 9.86 1.63 BBB 924 0.50 8.20 6.11 2.66 BB 470 0.52 6.59 4.63 2.82 B 335 0.71 3.71 2.30 4.66

2008

AAA 18 0.51 113.97 81.62 3.25 AA 182 0.26 43.97 31.21 0.81 A 559 0.43 12.78 9.89 1.81 BBB 924 0.50 8.23 6.42 2.47 BB 417 0.52 6.40 4.51 2.82 B 321 0.75 3.41 2.10 4.92

Data Source: Case writer analysis of Compustat data.

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232 Part Three Estimating the Cost of Capital

EXHIBIT 10 | Plan for Currency and Maturity of Roche Bond Offering Tranches1

U.S. dollar-denominated

Maturity Amount (in billions of U.S. dollars) Coupon

1 year 3.00 Floating rate 2 years 1.25 Floating rate 3 years 2.50 Fixed rate 5 years 2.75 Fixed rate 10 years 4.50 Fixed rate 30 years 2.50 Fixed rate

Euro-denominated

Maturity Amount (in billions of euros) Coupon

1 year 1.50 Floating rate 4 years 5.25 Fixed rate 7 years 2.75 Fixed rate 12 years 1.75 Fixed rate

Sterling-denominated

Maturity Amount (in billions of British pounds) Coupon

6 years 1.25 Fixed rate

Data Source: Company documents. 1Prevailing exchange rates at the time were CHF1.67/GBP1.00, CHF1.18/USD1.00, and CHF1.48/EUR1.00.

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Case 14 Roche Holding Ag: Funding The Genentech Acquisition 233

EXHIBIT 11 | Prevailing Prices of Sample of Recently Rated Corporate Bonds (Mid-February 2009)

Years Amount remaining S&P issued

Company Issue date Maturity to maturity rating (millions) Coupon Price

U.S. dollar-denominated Altria 2/3/2009 2/6/2014 5 BBB 525 7.75 105.835 Altria 2/3/2009 2/6/2019 10 BBB 2,200 9.25 104.612 Altria 2/3/2009 2/6/2039 30 BBB 1,500 10.2 105.079 AT&T 1/29/2009 2/15/2014 5 A 1,000 4.85 99.790 AT&T 1/29/2009 2/15/2019 10 A 2,250 5.8 98.877 AT&T 1/29/2009 2/15/2039 30 A 2,250 6.55 96.626 Johnson & Johnson 6/23/2008 7/15/2038 29 AAA 700 5.85 111.000 McKesson 2/9/2009 2/15/2014 5 BBB" 350 6.5 103.372 McKesson 2/9/2009 2/15/2019 10 BBB" 350 7.5 106.156 Novartis 2/10/2009 2/10/2014 5 AA! 2,000 4.125 101.778 Novartis 2/10/2009 2/10/2019 10 AA! 3,000 5.125 100.746 Pfizer 2/3/2004 2/15/2014 5 AA 750 4.5 105.660 Schering-Plough 11/26/2003 12/1/2013 5 AA! 1,250 5.3 103.820 Schering-Plough 9/17/2007 9/15/2037 29 AA! 1,000 6.55 101.332 Verizon 11/4/2008 11/1/2018 10 A 2,000 8.75 118.582 Verizon 11/4/2008 3/31/2039 30 A 1,250 8.95 124.467 Warner Chilcott 2/1/2006 2/1/2015 6 BB- 600 8.75 95.000

Euro-denominated Anheuser-Busch InBev 2/9/2009 2/27/2014 5 BBB" 750 6.57 100.558 Imperial Tobacco 2/10/2009 2/17/2016 7 BBB 1,500 8.375 101.048 John Deere 1/19/2009 1/24/2014 5 A 600 7.5 105.801 Schering-Plough 10/1/2007 10/1/2014 6 AA! 1,500 5.375 99.710 Volkswagen 1/30/2009 2/9/2012 3 A! 2,500 5.625 100.332 Volkswagen 1/30/2009 2/9/2016 7 A! 1,000 7 100.238

Pound sterling-denominated Bayer AG 5/23/2006 5/23/2018 9 A! 350 5.625 100.817 Imperial Tobacco 2/10/2009 2/17/2022 13 BBB 1,000 9 107.062 Tesco 2/17/2009 2/24/2014 5 A! 600 5 100.284

Data Source: Case writer analysis using Bloomberg data.

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234 Part Three Estimating the Cost of Capital

EXHIBIT 12 | Selected Comparable Companies’ Data for 2008 (in millions of U.S. dollars)1

Shareholder Total Cash and Interest Current equity debt equivalents EBITDA expense rating

Bayer AG 21,381 21,779 2,740 8,183 1,626 A! Schering-Plough 10,529 8,176 3,373 2,917 536 AA! Johnson & Johnson 46,100 11,852 10,768 19,001 435 AAA Pfizer 57,556 17,290 2,122 20,929 516 AA Wyeth 19,174 11,739 10,016 7,954 492 A" GlaxoSmithKline 15,900 25,211 8,758 15,388 1,291 A" Merck & Co 21,080 6,240 4,368 7,854 251 AA! AstraZeneca 15,912 11,848 4,286 12,553 714 AA Warner Chilcott 1,350 963 36 508 94 BB! Roche Holding 41,569 4,051 4,870 16,751 213 AA!

Roche + Genentech (pro forma) 41,569 46,051 4,870 16,751 2,303

Data Source: Capital IQ and case writer analysis. 1Because the Genentech financial figures are already consolidated in the Roche financial statements, only the debt and interest expense is expected to vary. The pro-forma interest expense is based on an arbitrary 5% interest rate.

bru6171X_case14_219-234.qxd 11/26/12 11:01 AM Page 234

Nike, Inc.: Cost of Capital On July 5, 2001, Kimi Ford, a portfolio manager at NorthPoint Group, a mutual-fund management firm, pored over analysts’ write-ups of Nike, Inc., the athletic-shoe man- ufacturer. Nike’s share price had declined significantly from the beginning of the year. Ford was considering buying some shares for the fund she managed, the NorthPoint Large-Cap Fund, which invested mostly in Fortune 500 companies, with an emphasis on value investing. Its top holdings included ExxonMobil, General Motors, McDonald’s, 3M, and other large-cap, generally old-economy stocks. While the stock market had declined over the last 18 months, the NorthPoint Large-Cap Fund had performed extremely well. In 2000, the fund earned a return of 20.7%, even as the S&P 500 fell 10.1%. At the end of June 2001, the fund’s year-to-date returns stood at 6.4% versus –7.3% for the S&P 500.

Only a week earlier, on June 28, 2001, Nike had held an analysts’ meeting to dis- close its fiscal-year 2001 results.1 The meeting, however, had another purpose: Nike management wanted to communicate a strategy for revitalizing the company. Since 1997, its revenues had plateaued at around $9 billion, while net income had fallen from almost $800 million to $580 million (see Exhibit 1). Nike’s market share in U.S. athletic shoes had fallen from 48%, in 1997, to 42% in 2000.2 In addition, recent supply-chain issues and the adverse effect of a strong dollar had negatively affected revenue.

At the meeting, management revealed plans to address both top-line growth and operating performance. To boost revenue, the company would develop more athletic- shoe products in the midpriced segment3—a segment that Nike had overlooked in recent years. Nike also planned to push its apparel line, which, under the recent leadership of

235

15CASE

1Nike’s fiscal year ended in May. 2Douglas Robson, “Just Do . . . Something: Nike’s insularity and Foot-Dragging Have It Running in Place,” BusinessWeek, (2 July 2001). 3Sneakers in this segment sold for $70–$90 a pair.

This case was prepared from publicly available information by Jessica Chan, under the supervision of Robert F. Bruner and with the assistance of Sean D. Carr. The financial support of the Batten Institute is gratefully acknowledged. It was written as a basis for class discussion rather than to illustrate effective or ineffective handling of an administrative situation. Copyright © 2001 by the University of Virginia Darden School Foundation, Charlottesville, VA. All rights reserved. To order copies, send an e-mail to [email protected] dardenbusinesspublishing.com. No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means—electronic, mechanical, photocopying, recording, or otherwise—without the permission of the Darden School Foundation. Rev. 10/05.

bru6171X_case15_235-242.qxd 12/14/12 2:51 PM Page 235

industry veteran Mindy Grossman,4 had performed extremely well. On the cost side, Nike would exert more effort on expense control. Finally, company executives reiter- ated their long-term revenue-growth targets of 8% to 10% and earnings-growth targets of above 15%.

Analysts’ reactions were mixed. Some thought the financial targets were too aggressive; others saw significant growth opportunities in apparel and in Nike’s inter- national businesses.

Kimi Ford read all the analysts’ reports that she could find about the June 28 meeting, but the reports gave her no clear guidance: a Lehman Brothers report rec- ommended a strong buy, while UBS Warburg and CSFB analysts expressed misgiv- ings about the company and recommended a hold. Ford decided instead to develop her own discounted cash flow forecast to come to a clearer conclusion.

Her forecast showed that, at a discount rate of 12%, Nike was overvalued at its current share price of $42.09 (Exhibit 2). However, she had done a quick sensitivity analysis that revealed Nike was undervalued at discount rates below 11.17%. Because she was about to go into a meeting, she asked her new assistant, Joanna Cohen, to estimate Nike’s cost of capital.

Cohen immediately gathered all the data she thought she might need (Exhibits 1 through 4) and began to work on her analysis. At the end of the day, Cohen submit- ted her cost-of-capital estimate and a memo (Exhibit 5) explaining her assumptions to Ford.

236 Part Three Estimating the Cost of Capital

4Mindy Grossman joined Nike in September 2000. She was the former president and chief executive of Jones Apparel Group’s Polo Jeans division.

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Case 15 Nike, Inc.: Cost of Capital 237

EXHIBIT 1 | Consolidated Income Statements

Year Ended May 31 (in millions of dollars except per-share data) 1995 1996 1997 1998 1999 2000 2001

Revenues $4,760.8 $6,470.6 $9,186.5 $9,553.1 $8,776.9 $8,995.1 $9,488.8 Cost of goods sold 2,865.3 3,906.7 5,503.0 6,065.5 5,493.5 5,403.8 5,784.9

Gross profit 1,895.6 2,563.9 3,683.5 3,487.6 3,283.4 3,591.3 3,703.9 Selling and administrative 1,209.8 1,588.6 2,303.7 2,623.8 2,426.6 2,606.4 2,689.7

Operating income 685.8 975.3 1,379.8 863.8 856.8 984.9 1,014.2 Interest expense 24.2 39.5 52.3 60.0 44.1 45.0 58.7 Other expense, net 11.7 36.7 32.3 20.9 21.5 23.2 34.1 Restructuring charge, net — — — 129.9 45.1 (2.5) —

Income before income taxes 649.9 899.1 1,295.2 653.0 746.1 919.2 921.4 Income taxes 250.2 345.9 499.4 253.4 294.7 340.1 331.7

Net income $ 399.7 $ 553.2 $ 795.8 $ 399.6 $ 451.4 $ 579.1 $ 589.7

Diluted earnings per common share $1.36 $1.88 $2.68 $1.35 $1.57 $2.07 $2.16

Average shares outstanding (diluted) 294.0 293.6 297.0 296.0 287.5 279.8 273.3

Growth (%) Revenue 35.9 42.0 4.0 (8.1) 2.5 5.5 Operating income 42.2 41.5 (37.4) (0.8) 15.0 3.0 Net income 38.4 43.9 (49.8) 13.0 28.3 1.8

Margins (%) Gross margin 39.6 40.1 36.5 37.4 39.9 39.0 Operating margin 15.1 15.0 9.0 9.8 10.9 10.7 Net margin 8.5 8.7 4.2 5.1 6.4 6.2

Effective tax rate (%)* 38.5 38.6 38.8 39.5 37.0 36.0

*The U.S. statutory tax rate was 35%. The state tax varied yearly from 2.5% to 3.5%.

Sources of data: Company filing with the Securities and Exchange Commission (SEC), UBS Warburg.

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238 Part Three Estimating the Cost of Capital

EXHIBIT 2 | Discounted Cash Flow Analysis

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Assumptions: Revenue growth (%) 7.0 6.5 6.5 6.5 6.0 6.0 6.0 6.0 6.0 6.0 COGS/sales (%) 60.0 60.0 59.5 59.5 59.0 59.0 58.5 58.5 58.0 58.0 SG&A/sales (%) 28.0 27.5 27.0 26.5 26.0 25.5 25.0 25.0 25.0 25.0 Tax rate (%) 38.0 38.0 38.0 38.0 38.0 38.0 38.0 38.0 38.0 38.0 Current assets/sales (%) 38.0 38.0 38.0 38.0 38.0 38.0 38.0 38.0 38.0 38.0 Current liabilities/sales (%) 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5 11.5 Yearly depreciation and

capex equal each other. Cost of capital (%) 12.00 Terminal value growth

rate (%) 3.00

Discounted Cash Flow (in millions of dollars except per-share data) Operating income $ 1,218.4 $1,351.6 $1,554.6 $1,717.0 $1,950.0 $2,135.9 $2,410.2 $2,554.8 $2,790.1 $2,957.5 Taxes 463.0 513.6 590.8 652.5 741.0 811.7 915.9 970.8 1,060.2 1,123.9

NOPAT 755.4 838.0 963.9 1,064.5 1,209.0 1,324.3 1,494.3 1,584.0 1,729.9 1,833.7 Capex, net of depreciation — — — — — — — — — — Change in NWC 8.8 (174.9) (186.3) (198.4) (195.0) (206.7) (219.1) (232.3) (246.2) (261.0)

Free cash flow 764.1 663.1 777.6 866.2 1,014.0 1,117.6 1,275.2 1,351.7 1,483.7 1,572.7 Terminal value 17,998.3

Total flows 764.1 663.1 777.6 866.2 1,014.0 1,117.6 1,275.2 1,351.7 1,483.7 19,571.0 Present value of flows $ 682.3 $ 528.6 $ 553.5 $ 550.5 $ 575.4 $ 566.2 $ 576.8 $ 545.9 $ 535.0 $6,301.2

Enterprise value $11,415.4 Less: current outstanding

debt $ 1,296.6

Equity value $10,118.8 Current shares

outstanding 271.5

Equity value per share $ 37.27 Current share price: $ 42.09

Sensitivity of equity value to discount rate:

Discount rate Equity value

8.00% $ 75.80

8.50% 67.85

9.00% 61.25

9.50% 55.68

10.00% 50.92

10.50% 46.81

11.00% 43.22

11.17% 42.09

11.50% 40.07

12.00% 37.27

Source: Case writer’s analysis.

bru6171X_case15_235-242.qxd 12/14/12 2:51 PM Page 238

Case 15 Nike, Inc.: Cost of Capital 239

EXHIBIT 3 | Consolidated Balance Sheets

As of May 31,

(in millions of dollars) 2000 2001

Assets Current assets:

Cash and equivalents $ 254.3 $ 304.0 Accounts receivable 1,569.4 1,621.4 Inventories 1,446.0 1,424.1 Deferred income taxes 111.5 113.3 Prepaid expenses 215.2 162.5

Total current assets 3,596.4 3,625.3

Property, plant and equipment, net 1,583.4 1,618.8 Identifiable intangible assets and goodwill, net 410.9 397.3 Deferred income taxes and other assets 266.2 178.2

Total assets $ 5,856.9 $ 5,819.6

Liabilities and shareholders’ equity Current liabilities:

Current portion of long-term debt $ 50.1 $ 5.4 Notes payable 924.2 855.3 Accounts payable 543.8 432.0 Accrued liabilities 621.9 472.1 Income taxes payable — 21.9

Total current liabilities 2,140.0 1,786.7

Long-term debt 470.3 435.9 Deferred income taxes and other liabilities 110.3 102.2 Redeemable preferred stock 0.3 0.3

Shareholders’ equity: Common stock, par 2.8 2.8 Capital in excess of stated value 369.0 459.4 Unearned stock compensation (11.7) (9.9) Accumulated other comprehensive income (111.1) (152.1) Retained earnings 2,887.0 3,194.3

Total shareholders’ equity 3,136.0 3,494.5

Total liabilities and shareholders’ equity $ 5,856.9 $ 5,819.6

Source of data: Company filing with the Securities and Exchange Commission (SEC).

bru6171X_case15_235-242.qxd 12/14/12 2:51 PM Page 239

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Case 15 Nike, Inc.: Cost of Capital 241

EXHIBIT 5 | Joanna Cohen’s Analysis

TO: Kimi Ford

FROM: Joanna Cohen

DATE: July 6, 2001

SUBJECT: Nike’s cost of capital

Based on the following assumptions, my estimate of Nike’s cost of capital is 8.4%:

I. Single or Multiple Costs of Capital? The first question that I considered was whether to use single or multiple costs of capital, given that Nike has multiple business segments. Aside from footwear, which makes up 62% of its revenue, Nike also sells apparel (30% of revenue) that complements its footwear products. In addition, Nike sells sport balls, timepieces, eye- wear, skates, bats, and other equipment designed for sports activities. Equipment products account for 3.6% of its revenue. Finally, Nike also sells some non-Nike-branded products such as Cole Haan dress and casual footwear, and ice skates, skate blades, hockey sticks, hockey jerseys, and other products under the Bauer trademark. Non-Nike brands accounted for 4.5% of revenue.

I asked myself whether Nike’s business segments had different enough risks from each other to warrant different costs of capital. Were their profiles really different? I concluded that it was only the Cole Haan line that was somewhat different; the rest were all sports-related businesses. Since Cole Haan makes up only a tiny fraction of revenues, however, I did not think that it was necessary to compute a separate cost of capital. As for the apparel and footwear lines, they are sold through the same marketing and distribution channels and are often marketed in other collections of similar designs. Since I believe they face the same risk factors, I decided to compute only one cost of capital for the whole company.

II. Methodology for Calculating the Cost of Capital: WACC Since Nike is funded with both debt and equity, I used the WACC method (weighted-average cost of capital). Based on the latest available balance sheet, debt as a proportion of total capital makes up 27.0% and equity accounts for 73.0%: Capital Sources Book Values (in millions) Debt

Current portion of long-term debt $ 5.4 Notes payable 855.3 Long-term debt 435.9

$1,296.6 ➔ 27.0% of total capital Equity $3,494.5 ➔ 73.0% of total capital

III. Cost of Debt My estimate of Nike’s cost of debt is 4.3%. I arrived at this estimate by taking total interest expense for the year 2001 and dividing it by the company’s average debt balance.1 The rate is lower than Treasury yields, but that is because Nike raised a portion of its funding needs through Japanese yen notes, which carry rates between 2.0% and 4.3%.

After adjusting for tax, the cost of debt comes out to 2.7%. I used a tax rate of 38%, which I obtained by adding state taxes of 3% to the U.S. statutory tax rate. Historically, Nike’s state taxes have ranged from 2.5% to 3.5%.

1Debt balances as of May 31, 2000 and 2001, were $1,444.6 million and $1,296.6 million, respectively.

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242 Part Three Estimating the Cost of Capital

EXHIBIT 5 | (continued)

IV. Cost of Equity I estimated the cost of equity using the capital-asset-pricing model (CAPM). Other methods, such as the dividend-discount model (DDM) and the earnings-capitalization ratio, can be used to estimate the cost of equity. In my opinion, however, the CAPM is the superior method.

My estimate of Nike’s cost of equity is 10.5%. I used the current yield on 20-year Treasury bonds as my risk-free rate, and the compound average premium of the market over Treasury bonds (5.9%) as my risk pre- mium. For beta, I took the average of Nike’s betas from 1996 to the present.

Putting it All Together Inputting all my assumptions into the WACC formula, my estimate of Nike’s cost of capital is 8.4%.

WACC ! Kd(l " t) # D/(D $ E) $ Ke # E/(D $ E)

! 2.7% # 27.0% $ 10.5% # 73.0% ! 8.4%

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Teletech Corporation, 2005 Margaret Weston, Teletech Corpora- tion’s CFO, learned of Victor Yossarian’s letter late one evening in early Octo- ber 2005. Quickly, she organized a team of lawyers and finance staff to assess the threat. Maxwell Harper, the firm’s CEO, scheduled a teleconfer- ence meeting of the firm’s board of directors for the following afternoon. Harper and Weston agreed that before the meeting they needed to fashion a response to Yossarian’s assertions about the firm’s returns.

Ironically, returns had been the subject of debate within the firm’s cir- cle of senior managers in recent months. A number of issues had been raised about the hurdle rate used by the company when evaluating perform- ance and setting the firm’s annual cap-

ital budget. As the company was expected to invest nearly $2 billion in capital proj- ects in the coming year, gaining closure and consensus on those issues had become an important priority for Weston. Now, Yossarian’s letter lent urgency to the discussion.

In the short run, Weston needed to respond to Yossarian. In the long run, she needed to assess the competing viewpoints on Teletech’s returns, and she had to

243

CASE 16

Raider Dials Teletech “Wake-Up Call Needed,” Says Investor

New York—The reclusive billionaire Victor Yos- sarian has acquired a 10 percent stake in Teletech Corporation, a large regional telecommunications firm, and has demanded two seats on the firm’s board of directors. The purchase was revealed yesterday in a filing with the Securities and Exchange Commission, and separately in a letter to Teletech’s CEO, Maxwell Harper. “The firm is misusing its resources and not earning an ade- quate return,” the letter said. “The company should abandon its misguided entry into comput- ers, and sell its Products and Systems segment. Management must focus on creating value for shareholders.” Teletech issued a brief statement emphasizing the virtues of a link between com- puter technology and telecommunications.

Wall Street Daily News, October 15 2005

This case was written by Robert F. Bruner, with the assistance of Sean D. Carr. It is dedicated to the memory of Professor Robert F. Vandell, a scholar in corporate finance and investment analysis and the author of an antecedent case upon which the present case draws. Teletech Corporation is a fictional company, reflecting the issues facing actual firms, and is used as a basis for class discussion rather than to illustrate effective or ineffective handling of an administrative situation. The financial support of the Batten Institute is gratefully acknowledged. Copyright © 2005 by the University of Virginia Darden School Foundation, Charlottesville, VA. All rights reserved. To order copies, send an e-mail to [email protected] No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means—electronic, mechanical, photocopying, recording, or otherwise—without the permission of the Darden School Foundation. Rev. 10/10.

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recommend new policies as necessary. What should the hurdle rates be for Teletech’s two business segments, telecommunications services and its newer products and sys- tems unit? Was the products and systems segment really paying its way?

The Company The Teletech Corporation, headquartered in Dallas, Texas, defined itself as a “provider of integrated information movement and management.” The firm had two main busi- ness segments: telecommunications services, which provided long-distance, local, and cellular telephone service to business and residential customers, and the products and systems segment, which engaged in the manufacture of computing and telecommuni- cations equipment.

In 2004, telecommunications services had earned a return on capital (ROC)1 of 9.10%; products and systems had earned 11%. The firm’s current book value of net assets was $16 billion, consisting of $11.4 billion allocated to telecommunications serv- ices, and $4.6 billion allocated to products and systems. An internal analysis suggested that telecommunications services accounted for 75% of the market value (MV) of Teletech, while products and systems accounted for 25%. Overall, it appeared that the firm’s prospective ROC would be 9.58%. Top management applied a hurdle rate of 9.30% to all capital projects and in the evaluation of the performance of business units.

Over the past 12 months, Teletech’s shares had not kept pace with the overall stock market or with industry indexes for telephone, equipment, or computer stocks. Securities analysts had remarked on the firm’s lackluster earnings growth, pointing especially to increasing competition in telecommunications, as well as disappointing performance in the Products and Systems segment. A prominent commentator on TV opined, “There’s no precedent for a hostile takeover in this sector, but, in the case of Teletech, there is every reason to try.”

244 Part Three Estimating the Cost of Capital

95

In de

x ( 10

0 = 11

/1/ 04

)

Nov. 2004

Teletech Share Prices vs. Market and Industry Indexes

Dec. Jan. Feb. Mar. Apr. May June July Aug. Sep.

Teletech

TelephoneS&P 100

Computers

Telecom Eq

Oct. 2005

100

105

110

115

1Return on capital was calculated as the ratio of net operating profits after tax (NOPAT) to capital.

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Telecommunications Services The telecommunications services segment provided long-distance, local, and cellular telephone service to more than 7 million customer lines throughout the Southwest and Midwest. Revenues in this segment grew at an average rate of 3% during 2000–04. In 2004, segment revenues, net operating profit after tax (NOPAT), and net assets were $11 billion, $1.18 billion, and $11.4 billion, respectively.

Since the court-ordered breakup of the Bell System telephone monopoly in 1983, Teletech had coped with the gradual deregulation of its industry through aggressive expansion into new services and geographical regions. Most recently, the firm had been a leading bidder for cellular telephone operations and for licenses to offer per- sonal communications services (PCS). In addition, the firm had purchased a number of telephone-operating companies through privatization auctions in Latin America. Finally, the firm had invested aggressively in new technology—primarily, digital switches and optical-fiber cables—in an effort to enhance its service quality. All of those strategic moves had been costly: the capital budget in this segment had varied between $1.5 billion and $2 billion in each of the previous 10 years.

Unfortunately, profit margins in the telecommunications segment had been under pressure for several years. Government regulators had been slow to provide rate relief to Teletech for its capital investments. Other leading telecommunications providers had expanded into Teletech’s geographical markets and invested in new technology and quality-enhancing assets. Teletech’s management noted that large cable-TV com- panies had aggressively entered the telecommunications market and continued the pressure on profit margins.

Nevertheless, Teletech was the dominant service provider in its geographical mar- kets and product segments. Customer surveys revealed that the company was the leader in product quality and customer satisfaction. Its management was confident that the company could command premium prices no matter how the industry might evolve.

Products and Systems Before 2000, telecommunications had been the company’s core business, supple- mented by an equipment-manufacturing division that produced telecommunications components. In 2000, the company acquired a leading computer-workstation manu- facturer with the goal of applying state-of-the-art computing technology to the design of telecommunications equipment. The explosive growth in the microcomputer mar- ket and the increased usage of telephone lines to connect home- and office-based com- puters with mainframes convinced Teletech’s management of the potential value of marrying telecommunications equipment with computing technology. Using Teletech’s capital base, borrowing ability, and distribution network to catapult growth, the prod- ucts and systems segment increased its sales by nearly 40% in 2004. This segment’s 2004 NOPAT and net assets were $480 million and $4.6 billion, respectively.

The products and systems segment was acknowledged as a technology leader in the industry. While this accounted for its rapid growth and pricing power, maintenance

Case 16 Teletech Corporation, 2005 245

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of that leadership position required sizable investments in research and development (R&D) and fixed assets. The rate of technological change was increasing, as witnessed by sudden major write-offs by Teletech on products that, until recently, management had thought were still competitive. Major computer manufacturers were entering the telecommunications-equipment industry. Foreign manufacturers were proving to be stiff competition for bidding on major supply contracts.

Focus on Value at Teletech We will create value by pursuing business activities that earn premium rates of return.

—Teletech Corporation mission statement (excerpt)

Translating Teletech’s mission statement into practice had been a challenge for Margaret Weston. First, it had been necessary to help managers of the segments and business units understand what creating value meant. Because the segments and smaller business units did not issue securities in the capital markets, the only objective measure of value was the securities prices of the whole corporation—but the activi- ties of any particular manager might not be significant enough to drive Teletech’s secu- rities prices. Therefore, the company had adopted a measure of value creation for use at the segment and business-unit level that would provide a proxy for the way investors would view each unit’s performance. This measure, called economic profit, multiplied the excess rate of return of the business unit by the capital it used:

Economic profit ! (ROC " Hurdle rate) # Capital employed

Where:

NOPAT ! Net operating profit after taxes

Each year, the segment and business-unit executives were evaluated based on eco- nomic profit. This measure was an important consideration in strategic decisions about capital allocation, manager promotion, and incentive compensation.

The second way in which the value-creation perspective influenced managers was in the assessment of capital-investment proposals. For each investment, projected cash flows were discounted to the present using the firm’s hurdle rate to give a measure of the net present value (NPV) of each project. A positive (or negative) NPV indicated the amount by which the value of the firm would increase (or decrease) if the project were undertaken. The following shows how the hurdle rate was used in the familiar NPV equation:

Net present value !a n

t!1 c Free cash flowt11 $ Hurdle rate2t d " Initial investment

ROC ! Return on capital ! NOPAT Capital

246 Part Three Estimating the Cost of Capital

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Hurdle Rates The hurdle rate used in the assessments of economic profit and NPV had been the focus of considerable debate in recent months. This rate was based on an estimate of Teletech’s weighted average cost of capital (WACC). Management was completely satisfied with the intellectual relevance of a hurdle rate as an expression of the oppor- tunity cost of money. The notion that the WACC represented this opportunity cost had been hotly debated within the company, and while its measurement had never been considered wholly scientific, it was generally accepted.

Teletech was “split-rated” between A" and BBB$. An investment banker recently suggested that, at those ratings, new debt funds might cost Teletech 5.88% (about 3.53% after a 40% tax rate). With a beta of 1.15, the cost of equity might be about 10.95%. At market-value weights of 22% for debt and 78% for equity, the resulting WACC would be 9.30%. Exhibit 1 summarizes the calculation. The hurdle rate of 9.30% was applied to all investment and performance-measurement analyses at the firm.

Arguments for Risk-Adjusted Hurdle Rates How the rate should be used within the company in evaluating projects was another point of debate. Given the differing natures of the two businesses and the risks each one faced, differences of opinion arose at the segment level over the appropriateness of measuring all projects against the corporate hurdle rate of 9.30%. The chief advo- cate for multiple rates was Rick Phillips, executive vice president of telecommunica- tions services, who presented his views as follows:

Each phase of our business is different. They must compete differently and must draw on capital differently. Given the historically stable nature of this industry, many telecommuni- cations companies can raise large quantities of capital from the debt markets. In operations comparable to telecommunications services, 50% of the necessary capital is raised in the debt markets at interest rates reflecting solid A quality, on average. This is better than Teletech’s corporate bond rating of A"/BBB$.

I also have to believe that the cost of equity for telecommunications services is lower than it is for products and systems. Although the products and systems segment’s sales growth and profitability have been strong, its risks are high. Independent equipment manu- facturers are financed with higher-yielding BB-rated debt and a greater proportion of equity.

In my book, the hurdle rate for products and systems should reflect those higher costs of funds. Without the risk-adjusted system of hurdle rates, telecommunications services will gradually starve for capital, while products and systems will be force-fed—that’s be- cause our returns are less than the corporate hurdle rate, and theirs are greater. Telecommu- nications services lowers the risk of the whole corporation, and should not be penalized. Here’s a rough graph of what I think is going on (Figure 1):

Telecommunications services, which can earn 9.10% on capital, is actually profitable on a risk-adjusted basis, even though it is not profitable compared to the corporate hurdle rate. The triangle shape on the drawing shows about where telecommunications services is located. My hunch is that the reverse is true for products and systems [P&S], which prom- ises to earn 11.0% on capital. P&S is located on the graph near the little circle. In deciding

Case 16 Teletech Corporation, 2005 247

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how much to loan us, lenders will consider the composition of risks. If money flows into safer investments, over time the cost of their loans to us will decrease.

Our stockholders are equally as concerned with risk. If they perceive our business as being more risky than other companies are, they will not pay as high a price for our earn- ings. Perhaps this is why our price-to-earnings ratio is below the industry average most of the time. It is not a question of whether we adjust for risk—we already do, informally. The only question in my mind is whether we make those adjustments systematically or not.

While multiple hurdle rates may not reflect capital-structure changes on a day-to-day basis, over time they will reflect prospects more realistically. At the moment, as I under- stand it, our real problem is an inadequate and very costly supply of equity funds. If we are really rationing equity capital, then we should be striving for the best returns on equity for the risk. Multiple hurdle rates achieve that objective.

Implicit in Phillips’s argument, as Weston understood it, was the notion that if each segment in the company had a different hurdle rate, the costs of the various forms of capital would remain the same. The mix of capital used, however, would change in the calculation. Low-risk operations would use leverage more extensively, while the high-risk divisions would have little to no debt funds. This lower-risk segment would have a lower hurdle rate.

248 Part Three Estimating the Cost of Capital

FIGURE 1 | Rick Phillips’s assessment of constant versus risk-adjusted hurdle rates.

0.00% 2.00% 4.00% 6.00% 8.00%

10.00% 12.00% 14.00% 16.00% 18.00%

Risk Free Low Risk Teletech Corp. Higher Risk Risk Level

% R

at e o

f R et

ur n

Risk-adjusted Hurdle Teletech Corp. Hurdle Telecomm. Services Products and Systems

Products and Systems

Telecommunications Services

bru6171X_case16_243-256.qxd 11/24/12 2:33 PM Page 248

Opposition to Risk-Adjusted Hurdle Rates While several others within Teletech supported Phillips’s views, opposition was strong within the products and systems segment. Helen Buono, executive vice president of products and systems, expressed her opinion as follows:

All money is green. Investors can’t know as much about our operations as we do. To them the firm is a black box; they hire us to take care of what is inside the box, and judge us by the dividends coming out of the box. We can’t say that one part of the box has a different hurdle rate than another part of the box if our investors don’t think that way. Like I say, all money is green: all investments at Teletech should be judged against one hurdle rate.

Multiple hurdle rates are illogical. Suppose that the hurdle rate for telecommunica- tions services was much lower than the corporate-wide hurdle rate. If we undertook invest- ments that met the segment hurdle rate, we would be destroying shareholder value because we weren’t meeting the corporate hurdle rate.

Our job as managers should be to put our money where the returns are best. A single hurdle rate may deprive an under profitable division of investments in order to channel more funds into a more profitable division, but isn’t that the aim of the process? Our chal- lenge today is simple: we must earn the highest absolute rates of return that we can get.

In reality, we don’t finance each division separately. The corporation raises capital based on its overall prospects and record. The diversification of the company probably helps keep our capital costs down and enables us to borrow more in total than the sum of the capabilities of the divisions separately. As a result, developing separate hurdle rates is both unrealistic and misleading. All our stockholders want is for us to invest our funds wisely in order to increase the value of their stock. This happens when we pick the most promising projects, irrespective of the source.

Margaret Weston’s Concerns As Weston listened to these arguments, presented over the course of several months, she became increasingly concerned about several related considerations. First, Teletech’s corporate strategy had directed the company toward integrating the two segments. One effect of using multiple hurdle rates would be to make justifying high-technology research and application proposals more difficult, as the required rate of return would be increased. On the one hand, she thought, perhaps multiple hurdle rates were the right idea, but the notion that they should be based on capital costs rather than strategic con- siderations might be wrong. On the other hand, perhaps multiple rates based on capital costs should be used, but, in allocating funds, some qualitative adjustment should be made for unquantifiable strategic considerations. In Weston’s mind, the theory was cer- tainly not clear on how to achieve strategic objectives when allocating capital.

Second, using a single measure of the cost of money (the hurdle rate or discount factor) made the NPV results consistent, at least in economic terms. If Teletech adopted multiple rates for discounting cash flows, Weston was afraid that the NPV and eco- nomic-profit calculations would lose their meaning and comparability across business segments. To her, a performance criterion had to be consistent and understandable, or it would not be useful.

Case 16 Teletech Corporation, 2005 249

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In addition, Weston was concerned about the problem of attributing capital struc- tures to divisions. In the telecommunications services segment, a major new switch- ing station might be financed by mortgage bonds. In products and systems, however, it was impossible for the division to borrow directly; indeed, any financing was only feasible because the corporation guaranteed the debt. Such projects were considered highly risky—at best, perhaps, warranting only a minimal debt structure. Also, Weston considered the debt-capacity decision difficult enough for the corporation as a whole, let alone for each division. Judgments could only be very crude.

In further discussions with others in the organization about the use of multiple hurdle rates, Weston discovered two predominant themes. One argument held that investment decisions should never be mixed with financing decisions. A firm should first decide what its investments should be and then determine how to finance them most efficiently. Adding leverage to a present-value calculation would distort the results. The use of multiple hurdle rates was simply a way of mixing financing with investment analysis. This argument also held that a single rate made the risk decision clear-cut. Management could simply adjust its standard (NPV or economic profit) as the risks increased.

The contrasting line of reasoning noted that the WACC tended to represent an aver- age market reaction to a mixture of risks. Lower-than-average-risk projects should probably be accepted even when they did not meet the weighted-average criterion. Higher-than-normal-risk projects should provide a return premium. While the multiple- hurdle-rate system was a crude way to achieve this end, at least it was a step in the right direction. Moreover, some argued that Teletech’s objective should be to maximize return on equity funds, and because equity funds were and would remain a compara- tively scarce resource, a multiple-rate system would tend to maximize returns to stock- holders better than a single-rate system would.

To help resolve these issues, Weston asked her assistant, Bernard Ingles, to sum- marize the scholarly thought regarding multiple hurdle rates. His memorandum is given in Exhibit 2. She also requested that Ingles obtain samples of firms comparable with the telecommunications services segment and the products and systems unit that might be used in deriving segment WACCs. A summary of the data is given in Exhibit 3. Information on capital-market conditions in October 2005 is given in Exhibit 4.

Conclusion Weston could not realistically hope that all the issues before her would be resolved in time to influence Victor Yossarian’s attack on management. But the attack did dic- tate the need for an objective assessment of the performance of Teletech’s two segments—the choice of hurdle rates would be very important in the analysis. She did want to institute a pragmatic system of appropriate hurdle rates (or one rate), how- ever, that would facilitate judgments in the changing circumstances faced by Teletech. What were the appropriate hurdle rates for the two segments? Was the products and systems segment underperforming, as suggested by Yossarian? How should Teletech respond to the raider?

250 Part Three Estimating the Cost of Capital

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Case 16 Teletech Corporation, 2005 251

EXHIBIT 1 | Summary of the WACC Calculation for Teletech Corporation and Segment Worksheet

Telecommunications Products Corporate Services and Systems

MV asset weights 100% 75% 25% Bond rating A"/BBB$ A BB Pretax cost of debt 5.88% 5.74% 7.47% Tax rate 40% 40% 40% After-tax cost of debt 3.53% 3.44% 4.48%

Equity beta 1.15 Rf 4.62% RM 10.12% RM–Rf 5.50% Cost of equity 10.95%

Weight of debt 22.2% Weight of equity 77.8% WACC 9.30%

Data Source: Bloomberg LP, S&P Research Insight, and case writer analysis.

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252 Part Three Estimating the Cost of Capital

EXHIBIT 2 | Theoretical Overview of Multiple Hurdle Rates To: Margaret Weston From: Bernard Ingles Subject: Segment cost-of-capital theory Date: October 2005

You requested an overview of the theories on multiple hurdle rates. Without getting into the minutiae, the theo- ries boil down to the following points:

1. The central idea is that required returns should be driven by risk. This is the dominant view in the field of investment management, and is based on a mountain of theory and empirical research stretching over several decades. The extension of this idea from investment management to corporate decision making is, at least in theory, straightforward.

2. An underlying assumption is that the firm is transparent (i.e., that investors can see through the corporate veil and evaluate the activities going on inside). No one believes firms are completely transparent, or that in- vestors are perfectly informed. But financial accounting standards have evolved toward making the firm more transparent. And the investment community has grown tougher and sharper in its analysis. Teletech now has 36 analysts publishing both reports and forecasts on the firm. The reality is that for big publicly held firms, transparency is not a bad assumption.

3. Another underlying assumption is that the value of the whole enterprise is simply the sum of its parts—this is the concept of value additivity. We can define “parts” as either the business segments (on the left-hand side of the balance sheet) or the layers of the capital structure (on the right-hand side of the balance sheet). Market values have to balance.

MVTeletech ! (MVTelecommunication Services $ MVProducts$Systems) ! (MVdebt $ MVequity) If those equalities did not hold, then a raider could come along and exploit the inequality by buying or selling the whole and the parts. This is arbitrage. By buying and selling, the actions of the raider would drive the MVs back into balance.

4. Investment theory tells us that the only risk that matters is nondiversifiable risk, which is measured by beta. Beta indicates the risk that an asset will add to a portfolio. Since we assume that an investor is diversified, we also assume she seeks a return for only the risk that she cannot shed, which is the nondiversifiable risk. The important point here is that the beta of a portfolio is equal to a weighted average of the betas of the portfolio components. Extending this to the corporate environment, the asset beta for the firm will equal a weighted average of the components of the firm—again, the components of the firm can be defined in terms of either the right-hand side or the left-hand side of the balance sheet.

!Teletech Assets ! (wTel.Serv. !Tel.Serv. $ wP$S !P$S ) ! (wdebt !debt $ wequity !equity) Where:

w ! percentage weights based on market values. !Tel. Serv., !P$S ! Asset betas for business segments.

!debt ! ! for the firm’s debt securities. !equity ! ! of firm’s common stock (given by Bloomberg, etc.)

This is a very handy way to model the risk of the firm, for it means that we can use the capital asset pricing model to estimate the cost of capital for a segment (i.e., using segment asset betas).

5. Given the foregoing, it follows that the weighted average of the various costs of capital (K) for the firm (WACC), which is the theoretically correct hurdle rate, is simply a weighted average of segment WACCs:

WACCTeletech ! (WTel.Serv.WACCTel.Serv.)$ (WP$SWACCP$S)

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Case 16 Teletech Corporation, 2005 253

EXHIBIT 2 | Theoretical Overview of Multiple Hurdle Rates (Continued) Where:

w ! percentage weights based on market values. WACCTel. Serv. ! (wdebt, Tel. Serv. Kdebt, Tel. Serv. ) $ (wequity, Tel. Serv. Kequity, Tel. Serv.)

WACCP$S ! (wdebt, P$S Kdebt, P$S) $ (wequity, P$S Kequity, P$S)

6. The notion in point number 5 may not hold exactly in practice. First, most of the components in the WACC for- mula are estimated with some error. Second, because of taxes, information asymmetries, or other market im- perfections, assets may not be priced strictly in line with the model—for a company like Teletech, it is reason- able to assume that any mispricings are just temporary. Third, the simple two-segment characterization ignores a hidden third segment: the corporate treasury department that hedges and aims to finance the whole corporation optimally—this acts as a shock absorber for the financial policies of the segments. Modeling the WACC of the corporate treasury department is quite difficult. Most companies assume that the impact of cor- porate treasury is not very large, and simply assume it away. As a first cut, we could do this too, although it is an issue we should revisit.

Conclusions • In theory, the corporate WACC for Teletech is appropriate only for evaluating an asset having the same risk as

the whole company. It is not appropriate for assets having different risks than the whole company. • Segment WACCs are computed similarly to corporate WACCs. • In concept, the corporate WACC is a weighted average of the segment WACCs. In practice, the weighted aver-

age concept may not hold, due to imperfections in the market and/or estimation errors. • If we start computing segment WACCs, we must use the cost of debt, cost of equity, and the weights appropri-

ate to that segment. We need a lot of information to do this correctly, or else we really need to stretch to make assumptions.

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254 Part Three Estimating the Cost of Capital

EXHIBIT 3 | Samples of Comparable Firms Book Val. Mkt. Val. Mkt. Val.

2004 Equity Bond Debt/Total Price to Debt/ Debt/ Price/ Company Name Revenues Beta Rating Capital Book Capital Equity Earnings Teletech Corporation 16,000 1.15 A!/BBB" 46% 3.0 22% 29% 12.9

Telecommunications Services Industry Alltel Corp. 8,246 1.00 A 42.3% 2.4 23.2% 30.1% 15.4 AT&T Corp. 30,537 1.10 BB$ 53.9% 2.0 36.6% 57.7% (2.4) BellSouth Corp. 20,350 1.00 A 38.1% 2.1 22.9% 29.7% 16.7 Centurytel Corp. 2,411 1.05 BBB$ 42.5% 1.3 37.0% 58.8% 13.3 Citizens Communications Co. 2,193 1.00 BB$ 76.1% 3.5 47.7% 91.1% 65.0 IDT Corp. 2,217 1.05 NA 2.5% 1.2 2.1% 2.1% (19.3) SBC Communications Inc. 40,787 1.05 A 32.3% 1.9 20.0% 25.0% 19.6 Sprint Corp. 27,428 1.15 A" 50.8% 2.4 30.3% 43.4% (43.1) Verizon Communications Inc. 71,283 1.00 A$ 45.0% 2.6 24.1% 31.8% 12.5

Average 1.04 42.6% 2.15 27.1% 41.1% 8.65

Telecommunications Equipment Industry Avaya Inc. 4,057 1.35 BB 14.0% 3.5 4.4% 4.6% 18.3 Belden CDT Inc. 966 1.45 NA 19.9% 1.2 17.5% 21.3% 38.7 Commscope Inc. 1,153 1.10 BB 36.9% 2.0 22.4% 28.9% 10.3 Corning Inc. 3,854 1.45 BBB" 41.9% 5.4 11.8% 13.4% (11.1) Harris Corp. 2,519 1.05 BBB" 24.5% 2.7 10.7% 11.9% 21.9 Lucent Technologies Inc. 9,045 1.75 B 109.8% (26.0) 30.1% 43.0% 6.0 Nortel Networks Corp. 9,828 1.75 NA 43.9% 3.0 20.7% 26.0% (51.8) Plantronics Inc. 560 1.20 NA 0.7% 4.2 0.2% 0.2% 17.0 Scientific-Atlanta Inc. 1,708 1.45 NA 0.4% 2.6 0.1% 0.1% 20.7

Average 1.39 32.5% (0.15) 13.1% 16.6% 7.77

Computer and Network Equipment Industry EMC Corp. 8,229 1.55 BBB 1.0% 2.9 0.4% 0.4% 34.3 Gateway Inc. 3,650 1.35 NA 42.3% 5.5 11.8% 13.4% (4.2) Hewlett-Packard Corp. 79,905 1.45 A" 12.7% 1.7 7.8% 8.5% 18.5 Int’l. Business Machines Corp. 96,293 1.10 A$ 27.1% 4.1 8.4% 9.1% 15.2 Lexmark Int’l. Inc. 5,314 1.15 NA 5.5% 4.2 1.4% 1.4% 15.5 NCR Corp. 5,984 1.20 NA 13.7% 3.3 4.5% 4.8% 21.1 Seagate Technology 6,224 1.20 NA 33.0% 4.4 10.0% 11.1% 25.0 Storage Technology Corp. 2,224 1.15 NA 0.8% 2.4 0.3% 0.3% 18.2 Western Digital Corp. 3,047 1.80 NA 12.5% 4.8 2.9% 3.0% 16.7

Average 1.33 16.5% 3.70 5.3% 5.8% 17.81

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Case 16 Teletech Corporation, 2005 255

EXHIBIT 4 | Debt-Capital-Market Conditions, October 2005 Corporate Bond Yields U. S.Treasury Securities Industrials AAA 5.44% 3-month 3.56% AA 5.51% 6-month 3.99% A 5.74% 2-year 4.23%

3-year 4.23% BBB 6.23% 5-year 4.25% BB 7.47% 10-year 4.39% B 8.00% 30-year 4.62%

Phones A 6.17% BBB 6.28%

Utilities A 5.69% BBB 6.09%

Data Source: Bloomberg LP.

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The Boeing 7E7 We still have a lot to get done as we move toward authority to offer the 7E7 to our customers. The team is making great progress—understanding what our customer wants, developing an airplane that meets their needs, and defining a case that will demonstrate the value of the program.

—Michael Bair, Boeing Senior Vice President1

In early 2003, Boeing announced plans to design and sell a new, “super-efficient” jet dubbed the 7E7, subsequently called the “Dreamliner.” However, news over the next six months depressed the market for aircrafts, which were already in sharp con- traction. The United States went to war against Iraq, spasms of global terrorism offered shocking headlines, and a deadly illness called SARS resulted in global travel warnings. For those and other reasons, airline profits were the worst seen in a generation. This seemed like an incredible environment in which to launch a major new airframe project. Nevertheless, on June 16, 2003, at the prestigious Paris Air Show, Michael Bair, the leader of the 7E7 project, announced that Boeing was mak- ing “excellent progress on the development of the 7E7 and continues to be on track to seek authority to offer the airplane.”2 In order to proceed with the project, Bair sought a firm commitment from Boeing’s board of directors in early 2004. If the board approved the plan, he could start collecting orders from airlines and expect passengers to start flying on the new jets in 2008. Between now and his recom- mendation to the board, he would need to complete a valuation of the 7E7 project and gain the support of Boeing’s CEO, Philip Condit, and the other senior man- agers. Would the financial analysis show that this project would be profitable for Boeing’s shareholders?

257

CASE 17

1“Bair Provides Update on Boeing 7E7 Dreamliner,” Le Bourget, 16 June 2003. 2“Bair Provides Update.”

This case was prepared by Professors James Tompkins and Robert F. Bruner using public information. It was written as a basis for class discussion rather than to illustrate effective or ineffective handling of an adminis- trative situation. Copyright © 2004 by the University of Virginia Darden School Foundation, Charlottesville, VA. All rights reserved. To order copies, send an e-mail to [email protected] No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means—electronic, mechanical, photocopying, recording, or otherwise—without the permis- sion of the Darden School Foundation.

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Origins of the 7E7 Project Boeing had not introduced a new commercial aircraft since it rolled out the highly successful 777 in 1994. Later in the 1990s, however, Boeing announced and then can- celled two new commercial-aircraft programs. The most prominent of those was the “Sonic Cruiser,” which promised to fly 15% to 20% faster than any commercial air- craft and bragged of a sleek and futuristic design. Unfortunately, after two years of developing the Sonic Cruiser, Boeing’s potential customers were sending the message that passengers were not willing to pay a premium price for a faster ride. Boeing was now long overdue to develop a product that would pull it out of its financial slump, as well as help it regain the commercial-aircraft sales that the company had lost over the years to Airbus, its chief rival.

With the 7E7, an Airbus executive argued that Boeing seemed to be promising a “salesperson’s dream and engineer’s nightmare.”3 The 7E7, while carrying between 200 and 250 passengers, would be capable of both short, domestic flights as well as long, international hauls. It would use 20% less fuel than existing planes of its pro- jected size and be 10% cheaper to operate than Airbus’s A330-200. At a time when major airlines were struggling to turn a profit, less fuel, cheaper operating costs, and long or short distance flexibility would be a very attractive package at the right price.

Skeptics of the 7E7 were not in short supply and suggested that the name “Dreamliner” was appropriate. To make the plane more fuel efficient, the 7E7 would be the first commercial aircraft built primarily with carbon-reinforced material, which was both stronger and lighter than the traditional aluminum. In addition, Boeing promised greater fuel efficiency by using a more efficient engine. Boeing claimed that the use of composites would also reduce its manufacturing costs. The goal would be to design a plane with fewer components that could be assembled in 3 days as opposed to the cur- rent 20 days that it took to rivet together the Boeing 767. The use of composite mate- rials, however, had its risks. Composite materials were suspected as a contributory cause to a 2001 plane crash in New York and, therefore, would have to overcome regulatory scrutiny. Boeing would also have to change its production methods radically. The last time Boeing made a major production change was in 1997 in an effort to cut costs. However, because the process was not smooth, it resulted in two production lines being shut down for 30 days and hundreds of missed airline deliveries.

The ability to produce a short and long distance aircraft would also have to over- come engineering obstructions. Analysts argued that building a plane that would do short hops in Asia and long trans-Atlantic flights would require two versions of the plane with different wingspans.4 Boeing engineers considered the possibility of snap-on wing extensions. The question was whether this would be too costly, as well as being technically feasible.

Finally, there was the matter of Boeing’s board. Two of the most powerful mem- bers of the 11-person board, Harry Stonecipher and John McDonnell, were rumored

258 Part Three Estimating the Cost of Capital

3“Will Boeing’s New Idea Really Fly?” BusinessWeek, 23 June 2003. 4Noted by Richard Aboulafia, a senior analyst at Teal Group consultant, in “Will Boeing’s New Idea Really Fly?”

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to have raised serious concerns regarding the cost of the 7E7. While the cost of devel- oping the 7E7 project could be as high as $10 billion, there was an imminent veto threat if that number did not shrink by billions. More specifically the board wanted to keep 7E7 development costs down to only 40% of what it took to develop the 777. An additional pressure from the board was to keep the 7E7 per-copy costs to only 60% of the 777 costs. In response, Philip Condit, Boeing’s CEO and chair, was quoted as saying that “Boeing has a responsibility to develop jetliners for less.”5 He knew, however, that if Boeing did not take bold risks in the commercial-aircraft industry that their days as a serious competitor to Airbus were numbered.

Commercial-Aircraft Industry In 2002, two companies, Boeing and Airbus, dominated the large plane (100! seats) commercial-aircraft industry. While Boeing historically held the lead in this market, through a number of measures Airbus became number one. In 2002, Airbus received 233 commercial orders compared to Boeing’s 176 orders, representing a 57% unit market share and an estimated 53.5% dollar value market share.6

Airbus Industry Airbus was understandably proud of its growth. Established in 1970, by a consortium of European companies, it took Airbus 23 years to deliver its first 1000 aircrafts, another six years to deliver the next 1000, and only another three years (by 2002) to pass the 3000 aircraft milestone.7 In 1999, for the first time in its history, Airbus recorded more plane orders than its rival, Boeing.

Airbus’s large plane commercial-aircraft products included the A300/310, A320, A330/340, and A380 families. Airbus touted the A300/310 family as having the flexibility to serve short-, medium-, and extended-range routes. The widebody, twin-engine aircraft was considered mid-size, with a typical passenger configuration of about 250 passengers. This family first flew passengers in 1983, and it was this aging fleet that provided a replacement opportunity for Boeing’s 7E7. However, while Boeing was betting on the future demand for mid-size aircraft, Airbus announced its A380, superjumbo four-engine jet in 2000. The A380 was due to fly in 2006 with a 550-passenger configuration and long distance range of up to 8000 miles. It would be the largest passenger aircraft ever built.

The Boeing Company Boeing was split into two primary segments: commercial airplanes and integrated defense systems. In 2002, it was awarded $16.6 billion in defense contracts, second

Case 17 The Boeing 7E7 259

5“Losing Ground to Airbus, Boeing Faces a Key Choice,” Wall Street Journal, 21 April 2003. 6“2002 Commercial Results,” www.airbus.com. 7In 2001, Airbus formally became a single integrated entity through the transfer of Airbus related assets to the newly incorporated company. European Aeronautic Defense and Space Company (EADS) owned 80% of the new company, and BAE systems owned the remaining 20%.

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only to Lockheed Martin with $17.0 billion. Exhibit 1 shows that in 2002, each seg- ment earned Boeing’s revenues almost equally. In addition, while commercial-aircraft revenues had been falling, defense revenues had been rising. Analysts believed that Boeing was able to transfer significant amounts of technology from the defense R&D to the commercial-aircraft segment.

The commercial-aircraft segment produced and sold six main airframes designed to meet the needs of the short- to long-range markets: the 717, 737, and 757 standard- body models and the 747, 767, and 777 wide-body models. As of December 31, 2002, Boeing undelivered units under firm order of 1083 commercial aircraft and had a declining backlog of about $68 billion. For 2003, it projected 280 commercial-aircraft deliveries and expected between 275 and 300 in 2004. Boeing estimated that in 2003, the revenues for its commercial-airplane segment would be approximately $22 billion, down from $28 billion in 2002. Recognizing the negative impact of the September 11th attacks on commercial-aircraft demand, Boeing cut the production rates for 2002 in half in order to maintain profitability in that segment.

Exhibits 2 and 3 show Boeing’s balance sheet and income statement respectively. While Boeing’s earnings were down significantly from 2001 to 2002, most of this was the result of an accounting change (SFAS No. 142). However, a drop in commercial- airplane deliveries from 527 in 2001 to 381 in 2002 also contributed to the decline.

Demand for Commercial Aircraft The long-term outlook for aircraft demand seemed positive.8 Boeing’s Market Out- look said the following:

In the short term, air travel is influenced by business cycles, consumer confidence, and exogenous events. Over the long-term, cycles smooth out, and GDP, international trade, lower fares, and network service improvements become paramount. During the next 20 years, economies will grow annually by 3.2%, and air travel will continue its historic relationship with GDP by growing at an average annual rate of 5.1%.

As shown in Exhibit 4, Boeing’s 20-year forecast from 2003 to 2022, was for 24,276 new commercial aircraft in 2002, valued at $1.9 trillion. The company predicted a composition of 4,303 smaller regional jets (fewer than 90 seats); 13,647 single-aisle airplanes; 5,437 intermediate twin-aisle airplanes; and 889 747-size or larger airplanes. This prediction reflected a world fleet that would more than double, with one-fourth of the market coming from aircraft replacement and three-fourths from projected pas- senger and cargo growth.

Exhibit 5 illustrates Airbus’s 20-year predictions for the years 2000–2020. Although the report was dated 2002, because of the September 11 attacks, numbers included the year 2000, to serve as a benchmark year. For that period, Airbus predicted

260 Part Three Estimating the Cost of Capital

8The primary sources for commercial-aircraft demand estimates include Boeing’s 2003 Current Market Outlook and Airbus’s 2002 Global Market Forecast 2001–2020. While both reports recognized the negative effects of “exogenous events” such as September 11, 2001, they both agreed on a healthy long-term outlook.

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the delivery of 15,887 new commercial aircraft in 2002, with a value of (U.S. dollars) $1.5 trillion. This included 10,201 single-aisle aircraft; 3,842 twin-aisle aircraft; 1,138 very large aircraft, and 706 freighters. The 15,887-unit forecast did not include planes with less than 90 seats.

Although Boeing and Airbus’s numbers are not directly comparable due to the slightly different time periods and aircraft classifications, it appeared that Airbus was more optimistic about the market for large aircraft than Boeing was. While Airbus predicted it to be a $270 billion market, including 1138 passenger units, Boeing pro- jected only $214 billion with 653 passenger units. Boeing, however, estimated that the share of intermediate-size planes would increase from 18% to 22%. In its fore- cast, Boeing acknowledged that intermediate-size airplanes would economically allow airlines to fly the increased frequencies, city pairs, and nonstop flights requested by passengers. According to a recent study by Frost & Sullivan, they believed that the Airbus market projection for the A380 was “over-optimistic.”9

Aircraft Development and Lifecycle The development of a new airframe was characterized by huge initial cash outflows that might require between one and two decades to recoup. For example, the devel- opment costs for the Boeing 777 were rumored to be $7 billion. Any pricing would not only have to recoup the upfront development costs but also the production costs. In addition, pricing would be subject to rigorous, competitive pressures. In short, because of the financial strains a new product line might create, each new aircraft was a “bet the ranch” proposition. Over time, survival in the industry depended on intro- ducing successful products and having the deep financial pockets with which to sur- vive the initially gushing cash flow.

While aircraft sales were subject to short-term, cyclical deviations, there was some degree of predictability in sales. Sales would typically peak shortly after the introduction of the new aircraft, and then fall. Thereafter, sales would rise and fall as derivatives of the aircraft were offered. Exhibit 6 shows the cycles for the first 20 years of the 757 and 767 sales.

The 7E7 The concept of the Boeing 7E7 was driven by customer requirements. Boeing originally announced in March 2001, its plans to build the Sonic Cruiser, a plane that would fly just below the speed of sound. The success of the Cruiser depended on whether pas- sengers would pay a premium for a faster flight. However, potential airplane customers who had been interested in the Cruiser during a robust, commercial-air travel market were now focusing on survival. The events of September 11 and the bursting of the technology bubble led to a significant decline in airplane orders. As a result, Boeing solicited updated feedback from a number of potential customers who would soon need

Case 17 The Boeing 7E7 261

9“An Ongoing Rivalry,” Avionics Today, August 2003.

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to replace their aging fleet of mid-range planes, such as the 757s, 767s, A300s, A310s, A321s, and A330s. Overwhelmingly, the revised message from customers was for a plane with lower operating costs.

Based on discussions with over 40 airlines throughout the world, Bair identified a fresh market to replace mid-size planes, based not only on lower operating costs, but also on the creation of a mid-size plane that could travel long distances, a feat previously viable by only large planes, such as the 747. Such flexibility would allow airlines to offer nonstop service on routes that required long-range planes but did not justify the subsequent larger size. Bair estimated there to be more than 400 city pairs (e.g., Atlanta–Athens) that could be served efficiently on a nonstop basis by the 7E7.

Boeing was considering two new members for the 7E7 family, a basic and a stretch version. Exhibit 7 gives Boeing’s description of the two configurations. Other improvements for passengers included wider aisles, lower cabin altitude, and increased cabin humidity. In addition, the planes would include systems that provided in-flight entertainment, Internet access, real-time airplane systems and structure health moni- toring, and crew connectivity. Furthermore, Boeing claimed the 7E7 would have the smallest sound “footprint” with the quietest takeoff and landing in its class.

Boeing projected a demand for between 2000 and 3000 planes of the 7E7 type within 20 years of each one entering service. A study by Frost & Sullivan predicted the sale of “at least 2000 B7E7s.”10 However, the demand was highly dependent on whether Boeing could deliver the promised 20% cheaper fuel costs and the range flex- ibility in a mid-size aircraft. Furthermore, if the range flexibility did require snap-on wings, such a design may significantly increase the building costs of the aircraft. Not only did Boeing face the engineering uncertainty of being able to deliver such an air- craft, but also the risk of its duplication by Airbus. Airbus had already stated that if the fuel efficiency was primarily generated by new engine designs, then it would sim- ply order the more efficient engines for its planes. Any uncertainty in the 7E7 plane specifications and risk of competition clearly put downward pressure on both the price Boeing could demand, as well as the number of units it would be able to sell.

Financial Forecast and Analysis Exhibit 8 contains a 20-year forecast of free cash flows from the Boeing 7E7 project consistent with public information released by Boeing, Airbus, analysts, and other experts in the field. See the Appendix for detailed forecast assumptions. The primary implication of the forecast is that the 7E7 project would provide an internal rate of return (IRR) close to 16%. This assumes that Boeing would not only deliver the promised plane specifications, but that Airbus would be unable to replicate the 7E7 efficiencies.

Based on both analysts’ and Boeing’s expectations, the base case assumes that Boeing could sell 2500 units in the first 20 years of delivery. Pricing was estimated using 2002 prices for Boeing’s 777 and 767. The 7E7 would be a hybrid of the two planes in terms of the number of passengers and range. By interpolating between the

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10“An Ongoing Rivalry”

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777 and 767 prices, it was possible to estimate the value placed on the range and number of passengers. Using this methodology, without any premium for the prom- ised lower operating costs, the minimum price for the 7E7 and 7E7 Stretch was esti- mated to be $114.5 million and $144.5 million, respectively, in 2002. The forecast assumed that customers would be willing to pay a 5% price premium for the lower operating costs.

The IRR, which is consistent with “base case” assumptions, was 15.7%. But, the estimate of IRR was sensitive to variations in different assumptions. In particular, some obvious uncertainties would be the number of units that Boeing would be able to sell and at what price. For example, if Boeing only sold 1,500 units in the first 20 years, then, as shown in Exhibit 9, the IRR would drop to 11%. This might occur if air travel demand worsened, or if Airbus entered this segment with a new compet- ing product.

Additional unknown variables were the development costs and the per-copy costs to build the 7E7. Boeing’s board was anxious to minimize those costs. The forecast assumes $8 billion for development costs; however, analyst estimates were in the $6 billion to $10 billion range. The cost to manufacture the 7E7 was also subject to great uncertainty. On the one hand, engineers were challenged to build a mid-size air- craft with long-range capabilities. The engineering design to achieve this could push building costs up significantly. Conversely, if Boeing succeeded in using composite materials, which required a fraction of the normal assembly time, then construction costs would be lower. Consistent with Boeing’s history, the base case assumes 80% as the percentage of cost of goods sold to sales. As shown in Exhibit 9, however, the IRR of the 7E7 was very sensitive to keeping production costs low.

Cost of Capital Boeing’s weighted-average cost of capital (WACC) could be estimated using the following well-known formula:

where:

Exhibit 10 gives information about betas and debt/equity ratios for Boeing and comparable companies. Exhibit 11 provides data about Boeing’s outstanding debt issues. While Boeing’s marginal effective tax rate had been smaller in the past, it currently was expected to be 35%. In June 2003, the yield on the three-month U.S. Treasury bill was 0.85%, and the yield on the 30-year Treasury bond was 4.56%. On June 16, 2003, Boeing’s stock price closed at $36.41.

percent Equity " Proportion of equity in a market # value capital structure

re " Cost of equity capital

percent Debt " Proportion of debt in a market # value capital structure

tc " Marginal effective corporate tax rate

rd " Pretax cost of debt capital

WACC " 1percent Debt2 1rd2 11 # tc2 ! 1percent Equity2 1re2

Case 17 The Boeing 7E7 263

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Analysts pointed out that Boeing actually consisted of two separate businesses: the relatively more stable defense business and the conversely more volatile com- mercial business. Defense corporations were the beneficiaries when the world became unstable due to the terrorist attacks on September 11, 2001. Furthermore, the United States, along with some of its allies, went to war against Iraq on March 20, 2003. While Bush declared an end to major Iraqi combat operations on May 1, 2003, as of June 16, the death toll in Iraq continued to rise on a daily basis. A different type of risk emanated with the outbreak of SARS. On February 1, 2003, China announced the discovery of the deadly and contagious illness that subsequently spread to Canada and Australia. As of June 16, travel warnings were still outstanding. Thus, the question arose of whether one should estimate Boeing’s cost of capital to serve as a benchmark- required rate of return. Would a required return on a portfolio of those two businesses be appropriate for evaluating the 7E7 project? If necessary, how might it be possible to isolate a required return for commercial aircraft?

Conclusion Within the aircraft-manufacturing industry, the magnitude of risk posed by the launch- ing of a major new aircraft was accepted as a matter of course. With huge, upfront, capital costs in an environment of intense technology and price competition, there was no guarantee of success or major significant losses if the gamble did not pay off. At a time of great political and economic uncertainty, Michael Bair said:

Clearly, we have to make a compelling business proposition. It could be [that] we’ll still be in a terrible business climate in 2004. But you can’t let what’s happening today cause you to make bad decisions for this very long business cycle. This plane is very important to our future.11

Central to any recommendation that Bair would make to Boeing’s board of direc- tors was an assessment of the economic profitability of the 7E7 project. Would the project compensate the shareholders of Boeing for the risks and use of their capital? Were there other considerations that might mitigate the economic analysis? For instance, to what extent might organizational and strategic considerations influence the board? If Boeing did not undertake the 7E7, would it be conceding leadership of the commercial-aircraft business to Airbus?

264 Part Three Estimating the Cost of Capital

11“New Team, Name for Boeing ‘Super-Efficient’ Jet,” Seattle Times, 30 January 2003.

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Case 17 The Boeing 7E7 265

EXHIBIT 1 | Revenues, Operating Profits, and Identifiable Assets by Segment for the Boeing Company

2002 2001 2000

Revenues Commercial airplanes $28,387 $35,056 $31,171 Integrated defense systems 24,957 22,815 19,963 Accounting eliminations and other 725 1,047 187

Total $54,069 $58,918 $51,321 Operating Profit Commercial airplanes $2,847 $2,632 $2,736 Integrated defense systems 2,009 2,965 1,002 Accounting eliminations and other (988) (1,701) (680)

Total $3,868 $3,896 $3,058 Identifiable Assets Commercial airplanes $9,726 $10,851 $10,367 Integrated defense systems 12,753 12,461 12,579 Unallocated and other 29,863 25,666 20,588

Total $52,342 $48,978 $43,534

Source: Boeing Company, 2002 Annual Report.

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266 Part Three Estimating the Cost of Capital

EXHIBIT 2 | Boeing Balance Sheets ($ in millions)

2002 2001

Assets Cash and cash equivalents $2,333 $633 Accounts receivable 5,007 5,156 Inventories, net of advances, progress billings, and reserves 6,184 7,559 Other current assets 3,331 3,497

Total current assets 16,855 16,845 Customer and commercial financing–net 10,922 9,345 Property, plant, and equipment–net 8,765 8,459 Goodwill and other acquired intangibles–net 3,888 6,447 Prepaid pension expense 6,671 5,838 Deferred income taxes and other assets 5,241 2,044

Total assets $52,342 $48,978

Liabilities and Shareholders’ Equity Accounts payable and other liabilities $13,739 $14,237 Short-term debt and current portion of long-term debt 1,814 1,399 Other current liabilities 4,257 4,930

Total current liabilities 19,810 20,566 Accrued retiree health-care and pension-plan liability 11,705 5,922 Long-term debt 12,589 10,866 Other liabilities 542 799 Shareholders’ equity:

Common shares 1,831 4,994 Retained earnings 14,262 14,340 Treasury shares (8,397) (8,509)

Total shareholders’ equity 7,696 10,825 Total liabilities and shareholders’ equity $52,342 $48,978

Source: Boeing Company, 2002 Annual Report.

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Case 17 The Boeing 7E7 267

EXHIBIT 3 | Boeing Income Statements ($ in millions; except per-share data)

2002 2001

Sales and other operating revenues $54,069 $58,198 Cost of products and services 45,499 48,778 General and administrative expense 2,534 2,389 Research and development expense 1,639 1,936 Impact of September 11, 2001 charges/(recoveries) (2) 935 Other operating expenses 531 264

Earnings from operations 3,868 3,896 Other income/(expense) 42 318 Interest and debt expense (730) (650)

Earnings before income taxes 3,180 3,564 Income taxes1 861 738 Net earnings before cumulative effect of accounting change 2,319 2,826 Cumulative effect of accounting change, net of tax (1,827) 1

Net earnings $492 $2,827

Earnings per share $0.62 $3.46

Source: Boeing Company, 2002 Annual Report. 1Boeing’s average tax rate consistent with reported financial performance for 2002 was 27%. Yet Boeing’s marginal effective tax rate was 35%.

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268 Part Three Estimating the Cost of Capital

EXHIBIT 4 | Boeing Delivery Distribution Forecast 2003–2022

Passenger Units 2002 Dollars Freighter Units

Seat Category Models (billions) Total Units

Single-aisle Small and intermediate Fewer than 90 seats 96.5 4,303 regional jets Regional jets 0

4,303 90–170 717-200 575.5 11,249

737-600/-700/-800 58

A318/A319/A320 11,307 Larger regional jets

171–240 737-900 170.0 2,307 757 33

A321 2,340

Twin-aisle 230–310 767 370.7 2,521 (181–249) A300 272

A310 2,793 A330-200

311–399 777 488.3 2,482 (250–368) A330-300 162

A340 2,644

Large 747 and larger 747-400 214.0 653

A380 236

889

Total 1,915.0 23,515 761

24,276

Source: Boeing Company.

174002

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Case 17 The Boeing 7E7 269

EXHIBIT 5 | Airbus Delivery Distribution Forecast, 2000–2020

2002 Seat Category Dollars (number of seats) Examples of Models (billions) Units

Single-aisle (passenger) A318, A319, A320, A321 609 10,201 (100–210) Twin-aisle (passenger) A330, A340 524 3,842 (250–400) Very large (passenger) A380 270 1,138 ($400) Freighters 106 706 Total 1,509 15,887

Source: Boeing Company.

EXHIBIT 6 | Lifecycle of Unit Sales (Averaged across the Boeing 757 and 767)

Source: Boeing Company Web site, www.boeing.com.

1 2 3 Year since introduction

P er

ce nt

o f t

ot al

u ni

t s al

es

4 5 6 7 8 9 10

10%

9%

8%

7%

6%

5%

4%

3%

2%

1%

0% 11 12 13 14 15 16 17 18 19 20

Airframe Lifecycle Annual Units Sold/Total Units Sold

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270 Part Three Estimating the Cost of Capital

EXHIBIT 7 | Description of Product Configurations for the Baseline and Stretch Models of the 7E7

Boeing 7E7 Baseline Model

Brief Description: The Boeing 7E7 Baseline is a super-efficient air- plane with new passenger-pleasing features. It will bring the economics of large jet transports to the middle of the market, using 20% less fuel than any other airplane its size. Seating:

200 passengers in three-class configuration 300! in single-class configuration

Range: 6,600 nautical miles

Configuration: Twin-aisle

Cross Section: 226 inches

Wing Span: 186 feet

Length: 182 feet

Cruise Speed: Mach 0.85

Cargo Capacity after Passenger Bags: containers

Program Milestones: Authority to offer:

Late 2003/Early 2004 Assembly start: 2005 First flight: 2007 Certification/entry into service: 2008

5 pallets ! 5 LD3

Boeing 7E7 Stretch

Brief Description: The Boeing 7E7 Stretch is a slightly bigger version of the 7E7 Baseline. Both are super-efficient air- planes with new passenger-pleasing features. The Stretch will bring the economics of large jet trans- ports to the middle of the market, using 20% less fuel than any other airplane its size. Seating:

250 passengers in three-class configuration 350! in single-class configuration

Range: 8,000 nautical miles

Configuration: Twin-aisle

Cross Section: 226 inches

Wing Span: 186 feet

Length: 202 feet

Cruise Speed: Mach 0.85

Cargo Capacity after Passenger Bags: containers

Program Milestones: Entry into service 2010 likely,

but depends on marketplace

6 pallets ! 8 LD3

Source: Boeing Company.

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EXHIBIT 8 | Forecast of Boeing 7E7 Free Cash Flows ($ in millions)

Assumptions

Initial price of 7E7 $136.95 Initial price of 7E7 Stretch $170.87 Cost of goods sold (% of sales) 80% Working capital requirement (WCR) as a % of sales 6.7% General, selling, and administrative (GS&A) as a % of sales 8% R&D expense (% of sales) 2.3% (excluding 2004–2007) Capital expenditure (% of sales) 0.16% (excluding 2004–2007) Development costs (2004–2009) $8,000 Total number of planes: yrs 1–20 2,500 Total number of planes: yrs 20–30 Same as year 20 Inflation 2% Marginal effective tax rate 35%

Case 17 The Boeing 7E7 271

2004 2005 2006 2007 2008

Revenues Planes delivered 30

7E7 planes 30 7E7 Stretch planes 0

7E7 price $136.95 7E7 Stretch price Total product revenues 4,108.64 Cost of goods sold 3,286.91 Gross profit 821.73 Depreciation 7.50 29.44 102.23 117.06 123.78 GS&A expense 308.15 Operating profit (before R&D) (7.50) (29.44) (102.23) (117.06) 389.80 R&D expense 300.00 900.00 3,000.00 900.00 694.50 Pretax profit (307.50) (929.44) (3,102.23) (1,017.06) (304.69) Taxes (or tax credit) (107.63) (325.30) (1,085.78) (355.97) (106.64) After-tax profit (199.88) (604.13) (2,016.45) (661.09) (198.05) Capital expenditure 100.00 300.00 1,000.00 300.00 206.57 Depreciation add-back 7.50 29.44 102.23 117.06 123.78 Change in WCR 275.28 Annual free cash flow $(292.38) $(874.70) $(2,914.22) $(844.03) $(556.13)

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EXHIBIT 8 | (continued)

2009 2010 2011 2012 2013

Revenues Planes delivered 108 64 82 84 104

7E7 planes 108 51 41 42 52 7E7 Stretch planes 0 13 41 42 52

7E7 price $139.69 $142.49 $145.34 $148.24 $151.21 7E7 Stretch price 170.87 174.28 177.77 181.33 Total product revenues 15,086.93 9,488.14 13,104.49 13,692.60 17,291.79 Cost of goods sold 12,069.55 7,590.51 10,483.59 10,954.08 13,833.44 Gross profit 3,017.39 1,897.63 2,620.90 2,738.52 3,458.36 Depreciation 123.80 115.66 108.67 102.83 99.64 GS&A expense 1,131.52 711.61 982.84 1,026.94 1,296.88 Operating profit (before R&D) 1,762.06 1,070.36 1,529.40 1,608.75 2,061.83 R&D expense 647.00 218.23 301.40 314.93 397.71 Pretax profit 1,115.06 852.13 1,227.99 1,293.82 1,664.12 Taxes (or tax credit) 390.27 298.25 429.80 452.84 582.44 After-tax profit 724.79 553.89 798.19 840.98 1,081.68 Capital expenditure 124.14 15.18 20.97 21.91 27.67 Depreciation add-back 123.80 115.66 108.67 102.83 99.64 Change in WCR 735.55 (375.12) 242.30 39.40 241.15 Annual free cash flow $(11.09) $1,029.48 $643.60 $882.50 $912.51

2014 2015 2016 2017 2018

Revenues Planes delivered 136 119 185 192 219

7E7 planes 68 60 93 96 110 7E7 Stretch planes 68 59 92 96 109

7E7 price $154.23 $157.32 $160.46 $163.67 $166.95 7E7 Stretch price 184.95 188.65 192.42 196.27 200.20 Total product revenues 23,064.59 20,569.48 32,626.19 34,554.82 40,185.75 Cost of goods sold 18,451.67 16,455.59 26,100.95 27,643.86 32,148.60 Gross profit 4,612.92 4,113.90 6,525.24 6,910.96 8,037.15 Depreciation 99.95 100.84 103.70 106.87 110.54 GS&A expense 1,729.84 1,542.71 2,446.96 2,591.61 3,013.93 Operating profit (before R&D) 2,783.12 2,470.35 3,974.57 4,212.48 4,912.68 R&D expense 530.49 473.10 750.40 794.76 924.27 Pretax profit 2,252.64 1,997.25 3,224.17 3,417.72 3,988.40 Taxes (or tax credit) 788.42 699.04 1,128.46 1,196.20 1,395.94 After-tax profit 1,464.21 1,298.21 2,095.71 2,221.52 2,592.46 Capital expenditure 36.90 32.91 52.20 55.29 64.30 Depreciation add-back 99.95 100.84 103.70 106.87 110.54 Change in WCR 386.78 (167.17) 807.80 129.22 377.27 Annual free cash flow $1,140.48 $1,533.31 $1,339.41 $2,143.88 $2,261.44

272 Part Three Estimating the Cost of Capital

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EXHIBIT 8 | (continued)

2019 2020 2021 2022 2023

Revenues Planes delivered 165 149 108 115 119

7E7 planes 83 75 54 58 60 7E7 Stretch planes 82 74 54 57 59

7E7 price $170.29 $173.69 $177.17 $180.71 $184.32 7E7 Stretch price 204.20 208.29 212.45 216.70 221.03 Total product revenues 30,878.29 28,440.04 21,039.33 22,833.05 24,100.43 Cost of goods sold 24,702.63 22,752.03 16,831.46 18,266.44 19,280.34 Gross profit 6,175.66 5,688.01 4,207.87 4,566.61 4,820.09 Depreciation 112.89 114.85 115.88 117.16 118.63 GS&A expense 2,315.87 2,133.00 1,577.95 1,712.48 1,807.53 Operating profit (before R&D) 3,746.89 3,440.15 2,514.04 2,736.97 2,893.92 R&D expense 710.20 654.12 483.90 525.16 554.31 Pretax profit 3,036.69 2,786.03 2,030.13 2,211.81 2,339.61 Taxes (or tax credit) 1,062.84 975.11 710.55 774.13 818.86 After-tax profit 1,973.85 1,810.92 1,319.59 1,437.68 1,520.75 Capital expenditure 49.41 45.50 33.66 36.53 38.56 Depreciation add-back 112.89 114.85 115.88 117.16 118.63 Change in WCR (623.60) (163.36) (495.85) 120.18 84.91 Annual free cash flow $2,660.94 $2,043.63 $1,897.65 $1,398.13 $1,515.90

2024 2025 2026 2027 2028

Revenues Planes delivered 136 150 120 115 115

7E7 planes 68 75 60 58 58 7E7 Stretch planes 68 75 60 57 57

7E7 price $188.01 $191.77 $195.61 $199.52 $203.51 7E7 Stretch price 225.46 229.96 234.56 239.26 244.04 Total product revenues 28,115.61 31,630.06 25,810.13 25,209.53 25,713.72 Cost of goods sold 22,492.49 25,304.05 20,648.10 20,167.63 20,570.98 Gross profit 5,623.12 6,326.01 5,162.03 5,041.91 5,142.74 Depreciation 116.20 105.31 62.54 50.92 43.54 GS&A expense 2,108.67 2,372.25 1,935.76 1,890.72 1,928.53 Operating profit (before R&D) 3,398.25 3,848.45 3,163.73 3,100.27 3,170.68 R&D expense 646.66 727.49 593.63 579.82 591.42 Pretax profit 2,751.60 3,120.96 2,570.09 2,520.45 2,579.26 Taxes (or tax credit) 963.06 1,092.33 899.53 882.16 902.74 After-tax profit 1,788.54 2,028.62 1,670.56 1,638.29 1,676.52 Capital expenditure 44.98 50.61 41.30 40.34 41.14 Depreciation add-back 116.20 105.31 62.54 50.92 43.54 Change in WCR 269.02 235.47 (389.94) (40.24) 33.78 Annual free cash flow $1,590.73 $1,847.86 $2,081.74 $1,689.12 $1,645.13

Case 17 The Boeing 7E7 273

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EXHIBIT 8 | (continued)

2029 2030 2031 2032 2033

Revenues Planes delivered 115 115 115 115 115

7E7 planes 58 58 58 58 58 7E7 Stretch planes 57 57 57 57 57

7E7 price $207.58 $211.73 $215.96 $220.28 $224.69 7E7 Stretch price 248.92 253.90 258.98 264.16 269.44 Total product revenues 26,228.00 26,752.56 27,287.61 27,833.36 28,390.03 Cost of goods sold 20,982.40 21,402.05 21,830.09 22,266.69 22,712.02 Gross profit 5,245.60 5,350.51 5,457.52 5,566.67 5,678.01 Depreciation 39.86 41.10 42.13 43.19 44.07 GS&A expense 1,967.10 2,006.44 2,046.57 2,087.50 2,129.25 Operating profit (before R&D) 3,238.64 3,302.97 3,368.82 3,435.98 3,504.68 R&D expense 603.24 615.31 627.62 640.17 652.97 Pretax profit 2,635.39 2,687.66 2,741.21 2,795.81 2,851.71 Taxes (or tax credit) 922.39 940.68 959.42 978.53 998.10 After-tax profit 1,713.00 1,746.98 1,781.78 1,817.28 1,853.61 Capital expenditure 41.96 42.80 43.66 44.53 45.42 Depreciation add-back 39.86 41.10 42.13 43.19 44.07 Change in WCR 34.46 35.15 35.85 36.57 37.30 Annual free cash flow $1,676.45 $1,710.13 $1,744.41 $1,779.37 $1,814.96

2034 2035 2036 2037

Revenues Planes delivered 115 115 115 115

7E7 planes 58 58 58 58 7E7 Stretch planes 57 57 57 57

7E7 price $229.18 $233.77 $238.44 $243.21 7E7 Stretch price 274.83 280.33 285.93 291.65 Total product revenues 28,957.83 29,536.99 30,127.73 30,730.28 Cost of goods sold 23,166.26 23,629.59 24,102.18 24,584.22 Gross profit 5,791.57 5,907.40 6,025.55 6,146.06 Depreciation 44.59 45.33 45.25 45.08 GS&A expense 2,171.84 2,215.27 2,259.58 2,304.77 Operating profit (before R&D) 3,575.14 3,646.80 3,720.72 3,796.21 R&D expense 666.03 679.35 692.94 706.80 Pretax profit 2,909.11 2,967.45 3,027.78 3,089.41 Taxes (or tax credit) 1,018.19 1,038.61 1,059.72 1,081.29 After-tax profit 1,890.92 1,928.84 1,968.06 2,008.12 Capital expenditure 46.33 47.26 48.20 49.17 Depreciation add-back 44.59 45.33 45.25 45.08 Change in WCR 38.04 38.80 39.58 40.37 Annual free cash flow $1,851.14 $1,888.10 $1,925.52 $1,963.65

274 Part Three Estimating the Cost of Capital

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EXHIBIT 9 | Sensitivity Analysis of Project IRRs by Price, Volume, Development, and Production Costs

Unit Volume Price Premium Above Expected Minimum Price

(First 20 Years) 0% 5% 10% 15%

1,500 10.5% 10.9% 11.3% 11.7% 1,750 11.9% 12.3% 12.7% 13.1% 2,000 13.0% 13.5% 13.9% 14.4% 2,250 14.1% 14.6% 15.1% 15.5% 2,500 15.2% 15.7% 16.1% 16.6% 2,750 16.1% 16.6% 17.1% 17.6% 3,000 17.1% 17.6% 18.1% 18.6%

Development Cost of Goods Sold as a Percentage of Sales

Costs 78% 80% 82% 84%

$6,000,000,000 21.3% 18.7% 15.9% 12.6% $7,000,000,000 19.4% 17.0% 14.4% 11.3% $8,000,000,000 17.9% 15.7% 13.2% 10.3% $9,000,000,000 16.6% 14.5% 12.1% 9.4%

$10,000,000,000 15.5% 13.5% 11.2% 8.6%

Note: The IRR consistent with “base case” assumptions is 15.7% and is indicated in italics in the table.

Source: Case writer’s analysis.

Case 17 The Boeing 7E7 275

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276 Part Three Estimating the Cost of Capital

EXHIBIT 10 | Information on Comparable Companies (Specially calculated betas estimated from daily stock and market returns over the periods indicated)

Lockheed Northrop Boeing Martin Grumman Raytheon

Percentage of revenues derived from government (defense and space) 46% 93% 91% 73% Estimated betas 1. Value Line1 1.05 0.60 0.70 0.80 2. Calculated against the S&P 500

index:2

60 months 0.80 0.36 0.34 0.43 21 months 1.03 0.38 0.31 0.46 60 trading days 1.45 0.34 0.27 0.66

3. Calculated against the NYSE composite index:2

60 months 1.00 0.49 0.44 0.59 21 months 1.17 0.44 0.36 0.53 60 trading days 1.62 0.37 0.30 0.73

Effective marginal tax rate 0.35 0.35 0.35 0.35

Market-value debt/equity ratios 0.525 0.410 0.640 0.624

Sources: Case writer’s analysis and Value Line Investment Survey. 1Value Line betas are calculated from a regression analysis between the weekly percentage change in price of a stock and the weekly percentage changes of the New York Stock Exchange Composite Index. The beta is calculated using the last five years of data. 2Regression periods for the 60-day, 21-month, and 60-month begin on March 20, 2003, September 17, 2001, and June 16, 1998, respectively. Regression periods end on June 16, 2003.

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Case 17 The Boeing 7E7 277

EXHIBIT 11 | Outstanding Bonds of the Boeing Company as of June 2003 ($ values in millions)

Debt Debt Amount Rating Coupon Maturity Price Yield To Maturity

$202 A- 7.625% 2/15/2005 106.175 3.911% $298 A- 6.625% 6/1/2005 105.593 3.393% $249 A- 6.875% 11/1/2006 110.614 3.475% $175 A- 8.100% 11/15/2006 112.650 4.049% $349 A- 9.750% 4/1/2012 129.424 5.470% $597 A- 6.125% 2/15/2013 103.590 4.657% $398 A- 8.750% 8/15/2021 127.000 6.239% $300 A- 7.950% 8/15/2024 126.951 5.732% $247 A- 7.250% 6/15/2025 114.506 6.047% $249 A- 8.750% 9/15/2031 131.000 6.337% $173 A- 8.625% 11/15/2031 138.974 5.805% $393 A- 6.125% 2/15/2033 103.826 5.850% $300 A- 6.625% 2/15/2038 106.715 6.153% $100 A- 7.500% 8/15/2042 119.486 6.173% $173 A- 7.825% 4/15/2043 132.520 5.777% $125 A- 6.875% 10/15/2043 110.084 6.191%

Note: This table does not include the outstanding debt of Boeing’s financing subsidiary, Boeing Capital Corporation.

Sources: Boeing Company 10-Q, Bloomberg Financial Services, and Mergent Online.

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278 Part Three Estimating the Cost of Capital

APPENDIX | Assumptions Underlying the Forecast of Cash Flows

Revenue Estimation In order to project revenues for the project, several assumptions were made about the expected demand and timing for the units, their price, and price increases.

Demand: Boeing estimated that in the first 20 years they would sell 2,000–3,000 units.1 Frost & Sullivan, aviation industry analysts, predicted at least 2,000 units.2 Analysis assumes 2,500 units in years 1 through 20. Years 20–30 assume unit sales equal to year 20. First delivery of 7E7 expected in 2008 and 7E7 Stretch in 2010.

Timing of demand: Units sold per year is the percentage of the total units in the first 20 years as shown in Exhibit 6. Exhibit 6 uses an historical average of the 757 and 767 unit sales during their first 20 years. The Boeing 7E7 is expected to be a replacement aircraft for the 757 and 767. Analysis assumes the 7E7 Stretch accounts for only 20% of unit sales in its first year of delivery and 50% thereafter. If the total number of unit sales per year is an odd number, the 7E7 units are rounded up and the 7E7 Stretch are rounded down.

Price: The expected price of the 7E7 and Stretch version is a function of the 767 and 777 prices in 2002. Using range and capacity as the primary variables, the 7E7 and 7E7 Stretch would be expected to have a mini- mum price of $114.5 million and $144.5 million respectively in 2002 dollars. This does not include a premium for the expected lower operating costs and flexibility of the 7E7. The analysis assumes a 5% price premium as a benchmark, resulting in expected prices of $120.2 million and $151.7 million in 2002.

Rate of price increases: Aircraft prices are assumed to increase at the rate of inflation. Inflation is assumed to be 2% per year until 2037. Expense Estimation

Cost of goods sold: The average cost of goods sold for Boeing’s commercial-aircraft division was 80% over the three-year period 2000–2002. The range was 77.9% to 81.1%. The analysis assumes 80% as the COGS.

General, selling, and administrative expense: The average general, selling, and administrative expense for Boeing was 7.5% over the three-year period 2000–2002. The range was 7.4% to 7.7%. The analysis assumes 7.5% as the general, selling, and administrative expense.

Depreciation: Boeing depreciated its assets on an accelerated basis. The forecast uses 150% declining balance depreciation with a 20-year asset life and zero salvage value as the base.

Research and development as a percentage of sales: The average research and development expense for Boeing’s commercial-aircraft division as a percentage of commercial-aircraft sales was 2.3% over the three-year period 2000–2002. The range was 1.8% to 2.7%. During that period, Boeing did not have any extraordinary new commercial-aircraft development expenses. The analysis, therefore, assumes 2.3% as the estimated research and development expense. That does not include the initial research and development costs required to design and develop the 7E7.

Tax expense: Boeing’s expected marginal effective tax rate was 35%. Other Adjustments to Cash Flow

Capital expenditures: The 1998–2002 average for capital expenditures as a percentage of sales was 0.93%. During this period, Boeing did not have any extraordinary new commercial-aircraft development expenses. At the time, Boeing had six families of aircraft: the 717, 737, 747, 757, 767, and 777. The average capital expendi- tures per family line, as a percentage of sales, was therefore 0.16%. This does not include the initial capital ex- penditure costs required to develop and build the 7E7.

Change in working capital requirements (WCR): For the years 2000–2002, Boeing had negative working capital due to factors such as advance customer payments. The analysis assumes that the commercial segment of Boeing would require positive working capital. The years prior to 2000, Boeing had positive working capital. The 1997–1999, three-year average of working capital as a percentage of sales is 6.7% with a range from 3.5% to 11.2%. The analysis assumes this percentage.

1“New Team, Name for Boeing ‘Super-Efficient’ Jet,” Seattle Times, 30 January 2003, 1. 2“An Ongoing Rivalry,” Aviation Today, August 2003.

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Case 17 The Boeing 7E7 279

APPENDIX | (continued)

Initial development costs: Development costs include the research and capital requirements needed to design and build the 7E7. Analysts estimated between $6 billion and $10 billion.3 The analysis assumes $8 billion. Assuming a launch in 2004, analysts expected spending to peak in 2006. Timing of the development costs are assumed to be 2004: 5%, 2005: 15%, 2006: 50%, 2007: 15%, 2008: 10%, and 2009: 5%. It is estimated that 75% of the initial development costs are research and development expenses, while the remaining 25% are capital expenditures.

3“Boeing Plays Defense,” Business Week, 3 June 2003.

Source: Case writer’s analysis.

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PART

Capital Budgeting and Resource Allocation

4

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The Investment Detective The essence of capital budgeting and resource allocation is a search for good invest- ments to place the firm’s capital. The process can be simple when viewed in purely mechanical terms, but a number of subtle issues can obscure the best investment choices. The capital-budgeting analyst, therefore, is necessarily a detective who must winnow bad evidence from good. Much of the challenge is in knowing what quanti- tative analysis to generate in the first place.

Suppose you are a new capital-budgeting analyst for a company considering investments in the eight projects listed in Exhibit 1. The chief financial officer of your company has asked you to rank the projects and recommend the “four best” that the company should accept.

In this assignment, only the quantitative considerations are relevant. No other project characteristics are deciding factors in the selection, except that management has determined that projects 7 and 8 are mutually exclusive.

All the projects require the same initial investment: $2 million. Moreover, all are believed to be of the same risk class. The firm’s weighted average cost of capital has never been estimated. In the past, analysts have simply assumed that 10% was an appropriate discount rate (although certain officers of the company have recently asserted that the discount rate should be much higher).

To stimulate your analysis, consider the following questions:

1. Can you rank the projects simply by inspecting the cash flows?

2. What criteria might you use to rank the projects? Which quantitative ranking methods are better? Why?

3. What is the ranking you found by using quantitative methods? Does this ranking differ from the ranking obtained by simple inspection of the cash flows?

4. What kinds of real investment projects have cash flows similar to those in Exhibit 1?

283

18CASE

This case was prepared by Robert F. Bruner, with the permission of Professor Gordon Donaldson, the author of an antecedent case. It was written as a basis for class discussion rather than to illustrate effective or ineffective handling of an administrative situation. Copyright © 1988 by the University of Virginia Darden School Foundation, Charlottesville, VA. All rights reserved. To order copies, send an e-mail to [email protected] No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means—electronic, mechanical, photocopying, recording, or otherwise—without the permission of the Darden School Foundation. Rev. 06/12.

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284 Part Four Capital Budgeting and Resource Allocation

EXHIBIT 1 | Projects’ Free Cash Flows (dollars in thousands)

Project number: 1 2 3 4 5 6 7 8 Initial investment $(2,000) $(2,000) $(2,000) $(2,000) $(2,000) $(2,000) $(2,000) $(2,000)

Year 1 $ 330 $1,666 $ 160 $ 280 $ 2,200* $1,200 $ (350) 2 330 334* 200 280 900* (60) 3 330 165 350 280 300 60 4 330 395 280 90 350 5 330 432 280 70 700 6 330 440* 280 1,200 7 330* 442 280 $ 2,250* 8 $1,000 444 280* 9 446 280

10 448 280 11 450 280 12 451 280 13 451 280 14 452 280 15 $10,000* $(2,000) $ 280

Sum of cash flow benefits $3,310 $2,165 $10,000 $ 3,561 $4,200 $ 2,200 $2,560 $ 4,150

Excess of cash flow over initial investment $1,310 $ 165 $ 8,000 $ 1,561 $2,200 $ 200 $ 560 $ 2,150

*Indicates year in which payback was accomplished.

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Worldwide Paper Company In December 2006, Bob Prescott, the controller for the Blue Ridge Mill, was consid- ering the addition of a new on-site longwood woodyard. The addition would have two primary benefits: to eliminate the need to purchase shortwood from an outside sup- plier and create the opportunity to sell shortwood on the open market as a new mar- ket for Worldwide Paper Company (WPC). The new woodyard would allow the Blue Ridge Mill not only to reduce its operating costs but also to increase its revenues. The proposed woodyard utilized new technology that allowed tree-length logs, called long- wood, to be processed directly, whereas the current process required shortwood, which had to be purchased from the Shenandoah Mill. This nearby mill, owned by a com- petitor, had excess capacity that allowed it to produce more shortwood than it needed for its own pulp production. The excess was sold to several different mills, including the Blue Ridge Mill. Thus adding the new longwood equipment would mean that Prescott would no longer need to use the Shenandoah Mill as a shortwood supplier and that the Blue Ridge Mill would instead compete with the Shenandoah Mill by selling on the shortwood market. The question for Prescott was whether these expected benefits were enough to justify the $18 million capital outlay plus the incremental investment in working capital over the six-year life of the investment.

Construction would start within a few months, and the investment outlay would be spent over two calendar years: $16 million in 2007 and the remaining $2 million in 2008. When the new woodyard began operating in 2008, it would significantly reduce the operating costs of the mill. These operating savings would come mostly from the difference in the cost of producing shortwood on-site versus buying it on the open mar- ket and were estimated to be $2.0 million for 2008 and $3.5 million per year thereafter.

Prescott also planned on taking advantage of the excess production capacity afforded by the new facility by selling shortwood on the open market as soon as pos- sible. For 2008, he expected to show revenues of approximately $4 million, as the facility came on-line and began to break into the new market. He expected shortwood sales to reach $10 million in 2009 and continue at the $10 million level through 2013.

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This case was prepared by Professor Kenneth M. Eades and is intended for illustrative purposes only. Copyright © 2002 by the University of Virginia Darden School Foundation, Charlottesville, VA. All rights reserved. To order copies, send an e-mail to [email protected] No part of this publica- tion may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means—electronic, mechanical, photocopying, recording, or otherwise—without the permission of the Darden School Foundation. Rev. 9/10.

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Prescott estimated that the cost of goods sold (before including depreciation expenses) would be 75% of revenues, and SG&A would be 5% of revenues.

In addition to the capital outlay of $18 million, the increased revenues would necessitate higher levels of inventories and accounts receivable. The total working cap- ital would average 10% of annual revenues. Therefore the amount of working capital investment each year would equal 10% of incremental sales for the year. At the end of the life of the equipment, in 2013, all the net working capital on the books would be recoverable at cost, whereas only 10% or $1.8 million (before taxes) of the capi- tal investment would be recoverable.

Taxes would be paid at a 40% rate, and depreciation was calculated on a straight- line basis over the six-year life, with zero salvage. WPC accountants had told Prescott that depreciation charges could not begin until 2008, when all the $18 million had been spent, and the machinery was in service.

Prescott was conflicted about how to treat inflation in his analysis. He was rea- sonably confident that his estimates of revenues and costs for 2008 and 2009 reflected the dollar amounts that WPC would most likely experience during those years. The capital outlays were mostly contracted costs and therefore were highly reliable esti- mates. The expected shortwood revenue figure of $4.0 million had been based on a careful analysis of the shortwood market that included a conservative estimate of the Blue Ridge Mill’s share of the market plus the expected market price of shortwood, taking into account the impact of Blue Ridge Mill as a new competitor in the market. Because he was unsure of how the operating costs and the price of shortwood would be impacted by inflation after 2009, Prescott decided not to include it in his analysis. Therefore the dollar estimates for 2010 and beyond were based on the same costs and prices per ton used in 2009. Prescott did not consider the omission critical to the final decision because he expected the increase in operating costs caused by inflation would be mostly offset by the increase in revenues associated with the rise in the price of shortwood.

WPC had a company policy to use 15% as the hurdle rate for such investment opportunities. The hurdle rate was based on a study of the company’s cost of capital conducted 10 years ago. Prescott was uneasy using an outdated figure for a discount rate, particularly because it was computed when 30-year Treasury bonds were yield- ing 10%, whereas currently they were yielding less than 5% (Exhibit 1).

286 Part Four Capital Budgeting and Resource Allocation

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Case 19 Worldwide Paper Company 287

EXHIBIT 1 | Cost-of-Capital Information

Interest Rates: December 2006

Bank loan rates (LIBOR) Market risk premium 1-year 5.38% Historical average 6.0%

Government bonds Corporate bonds (10-year maturities): 1-year 4.96% Aaa 5.37% 5-year 4.57% Aa 5.53% 10-year 4.60% A 5.78% 30-year 4.73% Baa 6.25%

Worldwide Paper Financial Data

Balance-sheet accounts ($ millions) Bank loan payable (LIBOR ! 1%) 500 Long-term debt 2,500 Common equity 500 Retained earnings 2,000

Per-share data Shares outstanding (millions) 500 Book value per share $ 5.00 Recent market value per share $24.00

Other Bond rating A Beta 1.10

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Target Corporation On November 14, 2006, Doug Scovanner, CFO of Target Corporation, was preparing for the November meeting of the Capital Expenditure Committee (CEC). Scovanner was one of five executive officers who were members of the CEC (Exhibit 1). On tap for the 8:00 a.m. meeting the next morning were 10 projects representing nearly $300 million in capital-expenditure requests. With the fiscal year’s end approaching in January, there was a need to determine which projects best fit Target’s future store growth and capital-expenditure plans, with the knowledge that those plans would be shared early in 2007, with both the board and investment community. In reviewing the 10 projects coming before the committee, it was clear to Scovanner that five of the projects, representing about $200 million in requested capital, would demand the greater part of the committee’s attention and discussion time during the meeting.

The CEC was keenly aware that Target had been a strong performing company in part because of its successful investment decisions and continued growth. More- over, Target management was committed to continuing the company’s growth strat- egy of opening approximately 100 new stores a year. Each investment decision would have long-term implications for Target: an underperforming store would be a drag on earnings and difficult to turn around without significant investments of time and money, whereas a top-performing store would add value both financially and strate- gically for years to come.

Retail Industry The retail industry included a myriad of different companies offering similar product lines (Exhibit 2). For example, Sears and JCPenney had extensive networks of stores that offered a broad line of products, many of which were similar to Target’s product lines. Because each retailer had a different strategy and a different customer base, truly comparable stores were difficult to identify. Many investment analysts, however, focused on Wal-Mart and Costco as important competitors for Target, although for

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20CASE

This case was prepared by David Ding (MBA ’08) and Saul Yeaton (MBA ’08) under the supervision of Kenneth Eades, Professor of Business Administration. It was written as a basis for class discussion rather than to illustrate effective or ineffective handling of an administrative situation. Copyright © 2008 by the University of Virginia Darden School Foundation, Charlottesville, VA. All rights reserved. To order copies, send an e-mail [email protected] No part of this publication may be reproduced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means—electronic, mechanical, photo- copying, recording, or otherwise—without the permission of the Darden School Foundation. Rev. 07/12.

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different reasons. Wal-Mart operated store formats similar to Target, and most Target stores operated in trade areas where one or more Wal-Mart stores were located. Wal- Mart and Target also carried merchandising assortments, which overlapped on many of the same items in such areas as food, commodities, electronics, toys, and sporting goods.

Costco, on the other hand, attracted a customer base that overlapped closely with Target’s core customers, but there was less often overlap between Costco and Target with respect to trade area and merchandising assortment. Costco also differed from Target in that it used a membership-fee format.1 Most of the sales of these compa- nies were in the broad categories of general merchandise and food. General merchandise included electronics, entertainment, sporting goods, toys, apparel, acces- sories, home furnishing, and décor, and food items included consumables ranging from apples to zucchini.

Wal-Mart had become the dominant player in the industry, with operations located in the United States, Argentina, Brazil, Canada, Puerto Rico, United Kingdom, Central America, Japan, and Mexico. Much of Wal-Mart’s success was attributed to its “every- day low price” pricing strategy that was greeted with delight by consumers but created severe challenges for local independent retailers who needed to remain competitive. Wal-Mart sales had reached $309 billion for 2005 for 6,141 stores and a market cap- italization of $200 billion, compared with sales of $178 billion and 4,189 stores in 2000. In addition to growing its top line, Wal-Mart had been successful in creating efficiency within the company and branching into product lines that offered higher margins than many of its commodity type of products.

Costco provided discount pricing for its members in exchange for membership fees. For fiscal 2005, these fees comprised 2.0% of total revenue and 72.8% of oper- ating income. Membership fees were such an important factor to Costco that an equity analyst had coined a new price-to-membership-fee-income ratio metric for valuing the company.2 By 2005, Costco’s sales had grown to $52.9 billion across its 433 ware- houses, and its market capitalization had reached $21.8 billion. Over the previous five years, sales excluding membership fees had experienced compound growth of 10.4%, while membership fees had grown 14.6% making the fees a significant growth source and highly significant to operating income in a low-profit-margin business.

In order to attract shoppers, retailers tailored their product offerings, pricing, and branding to specific customer segments. Segmentation of the customer population had led to a variety of different strategies, ranging from price competition in Wal-Mart stores to Target’s strategy of appealing to style-conscious consumers by offering unique assortments of home and apparel items, while also pricing competitively with Wal-Mart on items common to both stores. The intensity of competition among retail- ers had resulted in razor-thin margins making every line item on the income state- ment an important consideration for all retailers.

The effects of tight margins were felt throughout the supply chain as retailers constantly pressured their suppliers to accept lower prices. In addition, retailers used

290 Part Four Capital Budgeting and Resource Allocation

1 Sam’s Club, which was owned by Wal-Mart, also employed a membership-fee format and represented 13% of Wal-Mart revenues. 2 “Costco Wholesale Corp. Initiation Report” by Wachovia Capital Markets, September 18, 2006.

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off-shore sources as low-cost substitutes for their products and implemented methods such as just-in-time inventory management, low-cost distribution networks, and high sales per square foot to achieve operational efficiency. Retailers had found that profit margins could also be enhanced by selling their own brands, or products with exclu- sive labels that could be marketed to attract the more affluent customers in search of a unique shopping experience.

Sales growth for retail companies stemmed from two main sources: creation of new stores and organic growth through existing stores. New stores were expensive to build, but were needed to access new markets and tap into a new pool of consumers that could potentially represent high profit potential depending upon the competitive landscape. Increasing the sales of existing stores was also an important source of growth and value. If an existing store was operating profitably, it could be considered for renovation or upgrading in order to increase sales volume. Or, if a store was not profitable, management would consider it a candidate for closure.

Target Corporation The Dayton Company opened the doors of the first Target store in 1962, in Roseville, Minnesota. The Target name had intentionally been chosen to differentiate the new discount retailer from the Dayton Company’s more upscale stores. The Target con- cept flourished. In 1995, the first SuperTarget store opened in Omaha, Nebraska, and in 1999, the Target.com Web site was launched. By 2000, the parent company, Day- ton Hudson, officially changed its name to Target Corporation.3

By 2005, Target had become a major retailing powerhouse with $52.6 billion in revenues from 1,397 stores in 47 states (Exhibits 3 and 4). With sales of $30 billion in 2000, the company had realized a 12.1% sales growth over the past five years and had announced plans to continue its growth by opening approximately 100 stores per year in the United States in the foreseeable future. While Target Corporation had never committed to expanding internationally, analysts had been speculating that domestic growth alone would not be enough to sustain its historic success. If Target continued its domestic growth strategy, most analysts expected capital expenditures would continue at a level of 6–7% of revenues, which equated to about $3.5 billion for fiscal 2006.

In contrast with Wal-Mart’s focus on low prices, Target’s strategy was to consider the customer’s shopping experience as a whole. Target referred to its customers as guests and consistently strived to support the slogan, “Expect more. Pay less.” Target focused on creating a shopping experience that appealed to the profile of its “core guest”: a college-educated woman with children at home who was more affluent than the typical Wal-Mart customer. This shopping experience was created by emphasiz- ing a store décor that gave just the right shopping ambience. The company had been

Case 20 Target Corporation 291

3 The Dayton Company merged with J. L. Hudson Company in 1969. After changing its name to Target, the company renamed the Dayton-Hudson stores as Marshall Field’s. In 2004, Marshall Field’s was sold to May Department Stores, which was acquired by Federated Department Stores in 2006; all May stores were given the Macy’s name that same year.

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highly successful at promoting its brand awareness with large advertising campaigns; its advertising expenses for fiscal 2005 were $1.0 billion or about 2.0% of sales and 26.6% of operating profit. In comparison, Wal-Mart’s advertising dollars amounted to 0.5% of sales and 9.2% of operating income. Consistent advertising spending resulted in the Target bull’s-eye logo’s (Exhibit 5) being ranked among the most recognized corporate logos in the United States, ahead of the Nike “swoosh.”

As an additional enhancement to the customer shopping experience, Target offered credit to qualified customers through its REDcards: Target Visa Credit Card and Target Credit Card. The credit-card business accounted for 14.9% of Target’s oper- ating earnings and was designed to be integrated with the company’s overall strategy by focusing only on customers who visited Target stores.

Capital-Expenditure Approval Process The Capital Expenditure Committee was composed of a team of top executives that met monthly to review all capital project requests (CPRs) in excess of $100,000. CPRs were either approved by the CEC, or in the case of projects larger than $50 million, required approval from the board of directors. Project proposals varied widely and included remodeling, relocating, rebuilding, and closing an existing store to building a new store.4 A typical CEC meeting involved the review of 10 to 15 CPRs. All of the proposals were considered economically attractive, as any CPRs with question- able economics were normally rejected at the lower levels of review. In the rare instance when a project with a negative net present value (NPV) reached the CEC, the committee was asked to consider the project in light of its strategic importance to the company.

CEC meetings lasted several hours as each of the projects received careful scrutiny by the committee members. The process purposefully was designed to be rig- orous because the CEC recognized that capital investment could have significant impact on the short-term and long-term profitability of the company. In addition to the large amount of capital at stake, approvals and denials also had the potential to set precedents that would affect future decisions. For example, the committee might choose to reject a remodeling proposal for a store with a positive NPV, if the invest- ment amount requested was much higher than normal and therefore might create a troublesome precedent for all subsequent remodel requests for similar stores. Despite how much the projects differed, the committee was normally able to reach a consen- sus decision for the vast majority of them. Occasionally however, a project led to such a high degree of disagreement within the committee that the CEO made the final call.

Projects typically required 12 to 24 months of development prior to being for- warded to the CEC for consideration. In the case of new store proposals, which rep- resented the majority of the CPRs, a real-estate manager assigned to that geographic region was responsible for the proposal from inception to completion and also for

292 Part Four Capital Budgeting and Resource Allocation

4 Target expected to allocate 65% of capital expenditures to new stores, 12% to remodels and expansions, and 23% to information technology, distribution, etc.

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reviewing and presenting the proposal details. The pre-CPR work required a certain amount of expenditures that were not recoverable if the project were ultimately rejected by CEC. More important than these expenditures, however, were the “emo- tional sunk costs” for the real-estate managers who believed strongly in the merits of their proposals and felt significant disappointment if any project was not approved.

The committee considered several factors in determining whether to accept or reject a project. An overarching objective was to meet the corporate goal of adding about 100 stores a year while maintaining a positive brand image. Projects also needed to meet a variety of financial objectives, starting with providing a suitable financial return as measured by discounted cash-flow metrics: NPV and IRR (internal rate of return). Other financial considerations included projected profit and earnings per share impacts, total investment size, impact on sales of other nearby Target stores, and sen- sitivity of NPV and IRR to sales variations. Projected sales were determined based on economic trends and demographic shifts but also considered the risks involved with the entrance of new competitors and competition from online retailers. And lastly, the committee attempted to keep the project approvals within the capital budget for the year. If projects were approved in excess of the budgeted amount, Target would likely need to borrow money to fund the shortfall. Adding debt unexpectedly to the balance sheet could raise questions from equity analysts as to the increased risk to the share- holders as well as to the ability of management to accurately project the company’s funding needs.

Other considerations included tax and real-estate incentives provided by local communities as well as area demographics. Target typically purchased the properties where it built stores, although leasing was considered on occasion. Population growth and affluent communities were attractive to Target, but these factors also invited com- petition from other retailers. In some cases, new Target stores were strategically located to block other retailers despite marginal short-term returns.

When deciding whether to open a new store, the CEC was often asked to con- sider alternative store formats. For example, the most widely used format was the 2004 version of a Target store prototype called P04, which occupied 125,000 square feet, whereas a SuperTarget format occupied an additional 50,000 square feet to accommodate a full grocery assortment. The desirability of one format over another often centered on whether a store was expected to eventually be upgraded. Smaller stores often offered a higher NPV; but the NPV estimate did not consider the effect of future upgrades or expansions that would be required if the surrounding commu- nities grew, nor the advantage of opening a larger store in an area where it could serve the purpose of blocking competitors from opening stores nearby.

The committee members were provided with a capital-project request “dash- board” for each project that summarized the critical inputs and assumptions used for the NPV and IRR calculations. The template represented the summary sheet for an elaborate discounted cash flow model. For example, the analysis of a new store included incremental cash flow projections for 60 years over which time the model included a remodeling of the store every 10 years. Exhibit 6 provides an example of a dashboard with a detailed explanation of the “Store Sensitivities” section. The exam- ple dashboard shows that incremental sales estimates, which were computed as the

Case 20 Target Corporation 293

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total sales expected for the new store less the sales cannibalized from Target stores already located in the general vicinity. Sales estimates were made by the Research and Planning group. The R&P group used demographic and other data to make site- specific forecasts. Incremental sales were computed as total sales less those canni- balized from other Target stores. The resulting NPV and IRR metrics were divided between value created by store sales and credit-card activity. NPV calculations used a 9.0% discount rate for cash flows related to the store cash flows and a 4.0% discount rate for credit-card cash flows. The different discount rates were chosen to represent the different costs of capital for funding store operations versus funding credit-card receivables.

The dashboards also presented a variety of demographic information, investment- cost details and sensitivity analyses. An important sensitivity feature was the com- parison of the project’s NPV and IRR to the prototype. For example, the P04 store had an NPV of about $10 million and an IRR of 13%.5 The sensitivity calculations answered the question of how much a certain cost or revenue item needed to change in order for the project to achieve the same NPV or IRR that would be experienced for the typical P04 or SuperTarget store.

The November Meeting Of the 10 projects under consideration for the November CEC meeting, Doug Scov- anner recognized that five would be easily accepted, but that the remaining five CPRs were likely to be difficult choices for the committee. These projects included four new store openings (Gopher Place, Whalen Court, The Barn, and Goldie’s Square) and one remodeling of an existing store into a SuperTarget format (Stadium Remodel). Exhibit 7 contains a summary of the five projects, and Exhibit 8 contains the CPR dashboards for the individual projects.

As was normally the case, all five of the CPRs had positive NPVs, but Scovan- ner wondered if the projected NPVs were high enough to justify the required invest- ment. Further, with stiff competition from other large retailers looking to get footholds in major growth areas, how much consideration should be given to short-term versus long-term sales opportunities? For example, Whalen Court represented a massive investment with relatively uncertain sales returns. Should Scovanner take the stance that the CEC should worry less about Whalen Court’s uncertain sales and focus more on the project as a means to increase Target’s brand awareness in an area with dense foot traffic and high-fashion appeal? Goldie’s Square represented a more typical investment level of $24 million for a SuperTarget. The NPV, however, was small at $317,000, well below the expected NPV of a SuperTarget prototype, and would be negative without the value contribution of credit-card sales.

As CFO, Scovanner was also aware that Target shareholders had experienced a lackluster year in 2006, given that Target’s stock price had remained essentially flat (Exhibit 9). Stock analysts were generally pleased with Target’s stated growth policy

294 Part Four Capital Budgeting and Resource Allocation

5 These NPV and IRR figures exclude the impact of the credit card.

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Case 20 Target Corporation 295

and were looking for decisions from management regarding investments that were con- sistent with the company maintaining its growth trajectory. In that regard, Scovanner recognized that each of the projects represented a growth opportunity for Target. The question, however, was whether capital was better spent on one project or another to create the most value and the most growth for Target shareholders. Thus, Scovanner felt that he needed to rank the five projects in order to be able to recommend which ones to keep and which ones to reject during the CEC meeting the next day.

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296 Part Four Capital Budgeting and Resource Allocation

EXHIBIT 1 | Executive Officers and Capital Expenditure Committee Members

Timothy R. Baer Executive Vice President, General Counsel, and Corporate Secretary

Michael R. Francis Executive Vice President, Marketing John D. Griffith Executive Vice President, Property Development CEC Jodeen A. Kozlak Executive Vice President, Human Resources Troy H. Risch Executive Vice President, Stores CEC Janet M. Schalk Executive Vice President, Technology Services and

Chief Information Officer Douglas A. Scovanner Executive Vice President and Chief Financial Officer CEC Terrence J. Scully President, Target Financial Services Gregg W. Steinhafel President CEC Robert J. Ulrich Chairman and Chief Executive Officer CEC

Chairman and CEO Bob Ulrich, 62. Ulrich began his career at Dayton-Hudson as a merchandising trainee in 1967. He advanced to the position of CEO of Target Stores in 1987 and to the position of Dayton-Hudson’s CEO in 1994. EVP and CFO Doug Scovanner, 49. Scovanner was named Target CFO in February 2000 after previously serving as CFO of Dayton-Hudson. President of Target Stores Gregg Steinhafel, 50. Steinhafel began his career at Target as a merchandising trainee in 1979. He was named president in 1999. EVP of Stores Troy Risch, 37. Risch was promoted to EVP in September 2006. EVP of Property Development John Griffith, 44. Griffith was promoted to EVP in February 2005 from the position of senior vice president of Property Development he had held since February 2000.

Source: Target Corp.

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Case 20 Target Corporation 297

EXHIBIT 3 | Target Income Statements ($ millions)

Fiscal Year Ending 28 Jan 2006 29 Jan 2005

Net revenues 52,620 46,839 Cost of goods sold 34,927 31,445 Depreciation, depletion, and amortization 1,409 1,259

Gross income 16,284 14,135 Selling, general, and, admin expenses 11,961 10,534

Earnings before interest and taxes (EBIT) 4,323 3,601 Net interest expense 463 570

Pretax income 3,860 3,031 Income taxes 1,452 1,146

Net income before extra items 2,408 1,885 Gain (loss) sale of assets 1,313

Net income after extra items 2,408 3,198

Capital expenditures (net of disposals) 3,330 3,012 Capital expenditures/sales 6.3% 6.4%

Source: Target Corp. annual reports.

EXHIBIT 2 | Retail Company Financial Information

Market Debt Fiscal Capitalization

Revenue Basic Debt Rating Year as of Oct 31, 2006 ($ billions) EPS ($ billions) (S&P) Beta Ended ($ billions)

Bed Bath & Beyond Inc. $5.8 $1.95 $0.0 BBB 1.05 Feb-06 $11.4 Best Buy Co., Inc. $30.8 $2.33 $0.6 BBB 1.25 Feb-06 $26.2 Costco Wholesale Corp. $52.9 $2.24 $0.8 A 0.85 Aug-05 $24.1 Dick’s Sporting Goods, Inc. $2.6 $1.47 $0.2 Not Rated 1.15 Jan-06 $1.3 JCPenney Company, Inc. $18.8 $4.30 $3.5 BB! 1.05 Jan-06 $16.6 Kohl’s Corporation $13.4 $2.45 $1.2 BBB 0.90 Jan-06 $23.1 Sears Holdings Corporation $49.1 $5.63 $4.0 BB! NMF Jan-06 $26.9 Wal-Mart Stores, Inc. $315.7 $2.68 $38.8 AA 0.80 Jan-06 $199.9

Target Corporation $52.6 $2.73 $9.9 A! 1.05 Jan-06 $50.1

Data Source: Yahoo! Finance (www.finance.yahoo.com [accessed October 24, 2008]) and Value Line Investment Survey.

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298 Part Four Capital Budgeting and Resource Allocation

EXHIBIT 4 | Balance Sheet Statements ($ millions)

Fiscal Year Ending 28 Jan 2006 29 Jan 2005 31 Jan 2004

Assets Cash and cash equivalents 1,648 2,245 708 Accounts receivable (net) 5,666 5,069 4,621 Inventory 5,838 5,384 4,531 Other current assets 1,253 1,224 3,092

Total current assets 14,405 13,922 12,952 Property plant and equipment, net 19,038 16,860 15,153 Other assets 1,552 1,511 3,311

Total assets 34,995 32,293 31,416

Liabilities Accounts payable 6,268 5,779 4,956 Current portion of LT debt and notes payable 753 504 863 Income taxes payable 374 304 382 Other current liabilities 2,193 1,633 2,113

Total current liabilities 9,588 8,220 8,314 Long-term debt 9,119 9,034 10,155 Other liabilities 2,083 2,010 1,815

Total liabilities 20,790 19,264 20,284

Shareholders’ equity Common equity 2,192 1,881 1,609 Retained earnings 12,013 11,148 9,523

Total liabilities and shareholders’ equity 34,995 32,293 31,416

Source: Target Corp. annual reports.

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Case 20 Target Corporation 299

EXHIBIT 5 | Target Logo

Source: Target Corp.

TARGET

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EXHIBIT 6 | Example of a Capital Project Request Dashboard

300

Project: Sensitivities Key - Dashboard Example Market: St. Louis Open:

Prototype: P04 Size: 126,842 October, 2008

Developer: NA Own/Lease: Own

Capital Expenditure Committee: October 2007 Address: NA

Anchors: NA

FINANCIAL SUMMARY INVESTMENT DETAIL TOTAL R&P SALES Project B/(P) Proto Land

Acres: 11.00 B/(P) ProtoProject

N/A

1st year 2006 Equivalent $27,000 $2,588 PSF: $7.93

RE Tax CAM

Sitework

($8)

5th year 2006 Equivalent $34,155 $3,279 Closing: 10/2007

$0 $222 $71

Sales maturity 1.27 0.00 Options None BUILDING COST VS. PROTOTYPE

INCREMENTAL R&P SALES Project B/(P) Proto Subgeographic $0 1st year 2006 Equivalent $23,000 ($1,412) Proto Update 0 5th year 2006 Equivalent $34,155 $3,279 Market Conditions 0 Sales maturity 1.49 0.22 Government Fees 0

Architectural 0 INVESTMENT Project B/(P) Proto Technical 0 Land $3,802 ($202) Procurement 0 Sitework 3,804 (812) A/E Fees 0 Subtotal $7,606 ($1,014) Signs 0 Building 12,786 (2,736) Contingency 0 Other 1,295 (53) Total Variance $0 Total Net Investment $21,687 ($3,804) INCENTIVE SUMMARY

None Available Vendor Fee $0 VALUE IRR NPV B/(P) Proto Legal Fee $0 Store 12.8% $12,860 $1,860 Credit 10.2% $3,767 $322 DEMOGRAPHICS TOTAL 12.6% $16,626 $2,182 Characteristics MSA Trade Area 3-Mile Radius

STORE SENSITIVITIES 2005 Population (000’s) 0 0 0 HURDLE ADJUSTMENT NPV IRR 2000-2005 Growth 0.0% 0.0% 0.0% Sales (3.0%) 1.0% Median HH Income $0 $0 $0 Gross Margin (0.55) 0.19 # HH +$50,000 (000’s) 0 0 0 Construction (Building & Sitework) $2,398 ($498) % Adults 4+ Yrs. College, 2005 0% 0% 0% Full Transfer Impact 4.0% 7.5% COMMENTS

RISK/OPPORTUNITY 10% sales decline ($6,259) (1.8) 1 pp GM decline ($3,388) (1.0) 10% Const. cost increase ($1,287) (0.6) Market margin, wage rate, etc. ($603) (0.2) 10% sales increase $6,269 1.8

VARIANCE TO PROTOTYPE Land ($219) (0.1) Non-Land Investment ($2,660) (1.5) Sales $4,818 1.4 Real Estate Tax ($79) (0.0)

P&L SUMMARY EBIT IMPACT Project B/(P) Proto Thru Open Yr ($1,060) ($117) 5th Yr $4,066 $455

Capital Project Request

“B/(P) Proto” => Better or Poorer relative to the prototype

TARGET. NPV & Investment

0.0 5.0

10.0 15.0 20.0 25.0

Project Prototype Investment NPV

–10% Sales +10% Sales

15.0 20.0 25.0 30.0 35.0

1 2 3 4 5

Total Incremental Prototype

Sales40.0

2009

33%

45%

22%

Target Wal-Mart WMSC WMSC =Wal-Mart Super Center

2007

33%

67%

Target

Wal-Mart

Competition

2.2 SF/Cap

3.3 SF/Cap

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EXHIBIT 6 | Example of a Capital Project Request Dashboard (continued)

Source: Target Corp.

Dashboard Sensitivities Key (use with “Sensitivities Key-Dashboard Example”) Dashboard Example: P04; Store NPV: $12,860; Store IRR: 12.8%

HURDLE ADJUSTMENT (CPR Dashboard) Sales NPV (3.0%) Sales could decrease (3.0%) and still achieve Prototype Store NPV IRR 1.0% Sales would have to increase 1.0% to achieve Prototype Store IRR

Gross Margin NPV (0.55) Gross Margin could decrease (0.55) pp and still achieve Prototype Store NPV IRR 0.19 Gross Margin would have to increase 0.19 pp to achieve Prototype Store IRR

Construction (Building & Sitework) NPV $2,398 Construction costs could increase $2,398 and still achieve Prototype Store NPV IRR ($498) Construction costs would have to decrease ($498) to achieve Prototype Store IRR

Full Transfer Impact Prototype Assumption: A nearby store transferring sales to a new store, fully recovers these sales by the 5th yr. Sensitivity Assumption: If transfer sales are NOT fully recovered by the transferring store in year 5:

NPV 4.0% Sales would have to increase 4.0% to achieve Prototype Store NPV IRR 7.5% Sales would have to increase 7.5% to achieve Prototype Store IRR

RISK/OPPORTUNITY 10% Sales Decline NPV ($6,259) If sales decline by 10%, Store NPV would decline by ($6,259) IRR (1.8) If sales decline by 10%, Store IRR would decline by (1.8) pp

1 pp GM Decline Cost NPV % NPV ($3,388) If margin decreased by 1 pp, Store NPV would decline by ($3,388) Land: $100K ($110K) 110% IRR (1.0) If margin decreased by 1 pp, Store IRR would decline by (1.0) pp Sitework: $100K ($70K) 70%

10% Construction Cost Increase Building: $100K ($85K) 85% NPV ($1,287) If construction costs increased by 10%, Store NPV would decline by ($1,287) On-going Exp: $100K ($1M) x10 IRR (0.6) If construction costs increased by 10%, Store IRR would decline by (0.6) pp On-going Expense: eg. Real Estate Taxes, Operating Expense

Market Margin, Wage Rate, etc. NPV ($603) If we applied market specific assumptions, Store NPV would decrease by ($603) IRR (0.2) If we applied market specific assumptions, Store IRR would decrease by (0.2) pp

10% Sales Increase NPV $6,269 If sales increased by 10%, Store NPV would increase by $6,269 IRR 1.8 If sales increased by 10%, Store IRR would increase by 1.8 pp

VARIANCE TO PROTOTYPE The example dashboard with a Store NPV of $12,860 is $1,860K above Prototypical Store NPV. The following items contributed to the variance:

Land NPV ($219) Land cost contributed a negative ($219) to the variance from Prototype IRR (0.1) Land cost contributed a negative (0.1) pp to the variance from Prototype

Non-Land Investment NPV ($2,660) Building/Sitework costs contributed a negative ($2,660) to the variance from Prototype IRR (1.5) Building/Sitework costs contributed a negative (1.5) pp to the variance from Prototype

Sales NPV $4,818 Sales contributed a positive $4,818 to the variance from Prototype IRR 1.4 Sales contributed a positive 1.4 pp to the variance from Prototype

Real Estate Taxes NPV ($79) Real Estate Taxes contributed a negative ($79) to the variance from Prototype IRR (0.0) Real Estate Taxes contributed a negative (0.0) pp to the variance from Prototype

Assumes Store Opening occurs 1 year after closing.

APPROX $ IMPACT ON STORE NPV

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EXHIBIT 7 | Economic Analysis Summary of Project Proposals

Net Present Value* Trade Area**

Base Case 10% Sales Population % Adults Investment NPV Decline Increase Median 4! yrs.

($000) ($000) ($000) IRR Population 2000–2005 Income college

Gopher Place $23,000 $16,800 ($4,722) 12.3% 70,000 27% $56,400 12% Whalen Court $119,300 $25,900 ($16,611) 9.8% 632,000 3% $48,500 45% The Barn $13,000 $20,500 ($4,066) 16.4% 151,000 3% $38,200 17% Goldie’s Square $23,900 $300 ($4,073) 8.1% 222,000 16% $56,000 24% Stadium Remodel $17,000 $15,700 ($7,854) 10.8% N. Ap. N. Ap. $65,931 42%

*NPV is computed using 9.0% as discount rate for store cash flows and 4.0% for credit-card cash flows.

**Trade area is the geographical area from which 70% of store sales will be realized.

Gopher Place was a request for $23.0 million to build a P04 store scheduled to open in October 2007. The prototype NPV would be achieved with sales of 5.3% below the R&P forecast level. This market was considered an important one, with five existing stores already in the area. Wal-Mart was expected to add two new supercenters in response to favorable population growth in the trade area, which was considered to have a very favorable median household income and growth rate. Because of the high density of Target stores, nearly 19% of sales included in the forecasts were expected to come from existing Target stores.

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EXHIBIT 7 | Economic Analysis Summary of Project Proposals (continued)

Whalen Court was a request for $119.3 million to build a unique single-level store scheduled to open in October 2008. The prototype NPV could be achieved with sales of 1.9% above the R&P forecast level. Although Target currently operated 45 stores in this market, the Whalen Court mar- ket represented a rare opportunity for Target to enter the urban center of a major metropolitan area. Unlike other areas, this opportunity provided Target with major brand visibility and essentially free advertising for all passersby. Considering Target’s larger advertising budget, the request for more than $100 million of capital investment could be balanced against the brand awareness benefits it would bring. Further, this opportunity was only available for a limited time. Unlike the majority of Target stores, this store would have to be leased. Thus, if it was not approved at the November meeting, the property would surely be leased by another retailer. The Barn was a request for $13.0 million to build a P04 store scheduled to open in March 2007. The prototype NPV was achievable with sales of 18.1% below the R&P forecast level. This project was being resubmitted after initial development efforts failed because of a disagreement with the developer. This small rural area was an extreme contrast to Whalen Court. The small initial investment allowed for a large return on invest- ment even if sales growth turned out to be less than expected. This investment represented a new market for Target as the two nearest Target stores were 80 and 90 miles away. Goldie’s Square was a request for $23.9 million to build a SuperTarget store scheduled to open in October 2007. The prototype NPV required sales 45.1% above the R&P forecast level. This area was considered a key strategic anchor for many retailers. The Goldie’s Square center in- cluded Bed Bath & Beyond, JCPenney, Circuit City, and Borders. Target currently operated 12 stores in the area and was expected to have 24 eventually. Despite the relatively weak NPV figures, this was a hotly contested area with an affluent and fast-growing population, which could afford good brand awareness should the growth materialize. Stadium Remodel was a request for $17.0 million to remodel a SuperTarget store opening March 2007. As a remodel, there was no prototype NPV for comparison. The recent sales decline and deteriorating facilities at this location could lead to tarnishing the brand image. This trade area had supported Target stores since 1972 and had already been remodeled twice previously. The $17 million investment would certainly give a lift to the lagging sales.

Source: Target Corp.

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304 EXHIBIT 8 | Individual Capital Project Request Dashboards

Project: “Gopher Place” Market: Gopherville Open: October, 2007

Prototype: P04.383-MSP Size: 127,000 Developer: Henderson Associates Own/Lease: Own

Address: SWC of Hudson and Elk

Anchors: Freestanding

FINANCIAL SUMMARY INVESTMENT DETAIL TOTAL R&P SALES Project B/(P) Proto Land Acres: 9.78 Sitework Pro Rata, Maximum 1st year 2005 Equivalent $26,000 $2,745 PSF: $7.52 RE Tax-Per Corp Tax $136 5th year 2005 Equivalent $35,100 $5,688 Closing: 11/2006 B/(P) Proto $62 Sales maturity 1.35 0.09 Options Garden Center, Seismic

BUILDING COST VS. PROTOTYPE INCREMENTAL R&P SALES Project B/(P) Proto Subgeographic ($1,238) 1st year 2005 Equivalent $22,800 ($455) Proto Update (117) 5th year 2005 Equivalent $35,100 $5,688 Market Conditions (1,158) Sales maturity 1.54 0.27 Government Fees (1,049)

Architectural (485) INVESTMENT Project B/(P) Proto Technical (615) Land $3,205 $264 Procurement (239) Sitework 3,164 (580) A/E Fees (81) Subtotal $6,369 ($315) Signs 6 Building 15,420 (5,052) Contingency (75) Other 1,227 (96) Total Variance ($5,052) Total Net Investment $23,016 ($5,463) INCENTIVE SUMMARY

None Available Vendor Fee $0 VALUE IRR NPV B/(P) Proto Legal Fee $0 Store 12.7% $13,201 $2,493 Credit 8.1% $3,554 $544 DEMOGRAPHICS TOTAL 12.3% $16,755 $3,038 Characteristics MSA Trade Area 3-Mile Radius

STORE SENSITIVITIES 2005 Population (000’s) 650 70 16 HURDLE ADJUSTMENT NPV IRR 2000-2005 Growth 15.0% 27.0% 20.0% Sales (5.3%) 2.2% Median HH Income $46,700 $56,400 $59,400 Gross Margin (0.72) 0.29 # HH +$50,000 (000's) 97 11 3 Construction (Building & Sitework) $3,102 ($751) % Adults 4+ Yrs. College, 2005 15% 12% 11% Full Transfer Impact 2.3% 9.3% COMMENTS

- Target currently operates 5 stores in the market. RISK/OPPORTUNITY - Transfer Sales: T-1526: 8% (7 miles E) derives 19% of sales from the proposed 10% sales decline ($4,722) (1.3) trade area. 1 pp GM decline ($3,481) (0.9) - R&P Sales assume Wal-Mart relocates a store to a Supercenter in 2007; 10% Const. cost increase ($1,494) (0.6) Wal-Mart adds an additional Supercenter in Badgerville in 2008. Market margin, wage rate, etc. ($5,434) (1.5) 10% sales increase $4,621 1.2

VARIANCE TO PROTOTYPE Land $287 0.1 Non-Land Investment ($4,741) (2.6) Sales $6,331 1.9 Real Estate Tax $615 0.2

P&L SUMMARY EBIT IMPACT Project B/(P) Proto Thru Open Yr ($567) ($97) 5th Yr $4,452 $886

Capital Expenditure Committee: November 2006

Capital Project Request TARGET.

NPV & Investment

0.0 5.0

10.0 15.0 20.0 25.0

Project Prototype Investment NPV

–10% Sales +10% Sales

15 20 25 30 35

1 2 3 4 5

Total Incremental Prototype

Sales40

2008

24%

76%

Target

WMSC

2006 Competition

0.0 SF/Cap

6.5 SF/Cap

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EXHIBIT 8 | Individual Capital Project Request Dashboards (continued)

Project: “Whalen Court” Market: Buildback Open: October, 2008

Prototype: Unique Single Level Size: 173,585 Developer: Sawicky and Co. Own/Lease: Lease

Address: NWQ of Gopher and High Investment Blvd.

Anchors: Home Depot, Best Buy

FINANCIAL SUMMARY INVESTMENT DETAIL TOTAL R&P SALES Project B/(P) Proto Lease Type: Building Lease Sitework N/A 1st year 2005 Equivalent $86,000 $52,185 Rent: Prepay+$3.3K RE Tax (net of abatement) $358 5th year 2005 Equivalent $111,800 $69,031 Closing: 10/2006 B/(P) Proto ($60) Sales maturity 1.30 0.04 Options L4: Unique Risk Security, District Office, 13k sf Exp. Stock, 2nd Lvl Stock

BUILDING COST VS. PROTOTYPE INCREMENTAL R&P SALES Project B/(P) Proto Subgeographic ($1,200) 1st year 2005 Equivalent $79,600 $45,785 Proto Update (124) 5th year 2005 Equivalent $111,800 $69,031 Market Conditions 0 Sales maturity 1.40 0.14 Government Fees 0

Architectural 0 INVESTMENT Project B/(P) Proto Technical (7,927) Lease $87,309 ($78,855) Procurement (2,429) Sitework 0 3,796 A/E Fees (428) Subtotal $87,309 ($75,059) Signs (18) Building 29,434 (15,128) Contingency (3,000) Other 2,520 93 Total Variance ($15,128) Total Net Investment $119,263 ($90,094) INCENTIVE SUMMARY

Vendor Fee $92 VALUE IRR NPV B/(P) Proto Legal Fee $0 Store 9.9% $14,225 ($3,174) Credit 8.2% $11,650 $7,164 DEMOGRAPHICS TOTAL 9.8% $25,875 $3,989 Characteristics MSA Trade Area 3-Mile Radius

STORE SENSITIVITIES 2005 Population (000's) 18,768 632 1,248 HURDLE ADJUSTMENT NPV IRR 2000-2005 Growth 2.0% 3.0% 2.0% Sales 1.9% 31.1% Median HH Income $57,200 $48,500 $43,800 Gross Margin 0.28 4.58 # HH +$50,000 (000’s) 3,750 143 238 Construction (Building & Sitework) ($4,289) ($41,070) % Adults 4+ Yrs. College, 2005 30% 45% 37% Full Transfer Impact 7.7% 36.3% COMMENTS

See attached for additional information. RISK/OPPORTUNITY 10% sales decline ($16,611) (1.0) 1 pp GM decline ($11,494) (0.7) 10% Const. cost increase ($2,178) (0.1) Market margin, wage rate, etc. ($16,877) (1.1) 10% sales increase $16,647 1.0

VARIANCE TO PROTOTYPE Lease ($78,912) (15.1) Non-Land Investment ($10,168) (7.9) Sales $99,963 22.9 Real Estate Tax ($637) (0.2)

P&L SUMMARY EBIT IMPACT Project B/(P) Proto Thru Open Yr ($1,599) ($1,136) 5th Yr $14,034 $8,509

0.0 SF/Cap

0.5 SF/Cap

Capital Expenditure Committee: November 2006

Capital Project Request TARGET.

NPV & Investment

0.0 20.0 40.0 60.0 80.0

100.0 120.0 140.0

Project Prototype Investment NPV

–10% Sales +10% Sales

Total Incremental Prototype

15 35 55 75

115 95

1 2 3 4 5

Sales135

Competition

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306 EXHIBIT 8 | Individual Capital Project Request Dashboards (continued)

Project: “The Barn” Market: Moose Land Open: March, 2007

Prototype: P04.383-MSP Size: 126,842 Developer: Hulbert Ventures Own/Lease: Own

Address: NWQ of Badger and Wolverine

Anchors: Lowe’s

FINANCIAL SUMMARY INVESTMENT DETAIL TOTAL R&P SALES Project B/(P) Proto Land Acres: 11.48 Sitework Fixed Cost 1st year 2005 Equivalent $24,000 $2,043 PSF: $0.02 RE Tax-Per Corp. Tax $136 5th year 2005 Equivalent $30,500 $2,729 Closing: 4/2006 B/(P) Proto $62 Sales maturity 1.27 0.01 Options L3: Enhanced Risk Security

BUILDING COST VS. PROTOTYPE Subgeographic $523 Proto Update (22) Market Conditions (410) Government Fees 0 Architectural (95)

INVESTMENT Project B/(P) Proto Technical (122) Land $10 $3,390 Procurement (91) Sitework 2,303 290 A/E Fees (76) Subtotal $2,313 $3,680 Signs (9) Building 9,705 (378) Contingency (75) Other 998 121 Total Variance ($378) Total Net Investment $13,017 $3,423 INCENTIVE SUMMARY

None Available Vendor Fee $0 VALUE IRR NPV B/(P) Proto Legal Fee $0 Store 17.5% $17,406 $7,326 Credit 8.2% $3,121 $279 DEMOGRAPHICS TOTAL 16.4% $20,527 $7,605 Characteristics MSA Trade Area 3-Mile Radius

STORE SENSITIVITIES 2005 Population (000’s) 135 151 19 HURDLE ADJUSTMENT NPV IRR 2000–2005 Growth 3.0% 3.0% 7.0% Sales (18.1%) (23.2%) Median HH Income $36,600 $38,200 $47,300 Gross Margin (2.35) (3.04) # HH +$50,000 (000’s) 20 22 4 Construction (Building & Sitework) $8,908 $6,973 % Adults 4+ Yrs. College, 2005 16% 17% 34%

COMMENTS - Target is entering a new small market. The nearest Target stores are 80 miles NE, 80 miles S, 90 miles NW. - R&P Sales assume Target is part of a major retail development of 600K sf. - See attached Resubmission Summary.

RISK/OPPORTUNITY 10% sales decline ($4,066) (1.9) 1 pp GM decline ($3,111) (1.5) 10% Const. cost increase ($988) (1.0) Market margin, wage rate, etc. ($2,999) (1.4) 10% sales increase $4,096 1.9

VARIANCE TO PROTOTYPE Land $3,675 3.2 Non-Land Investment ($570) (0.3) Sales $3,603 1.4 Real Estate Tax $617 0.2

NPV & Investment

0.0 5.0

10.0 15.0 20.0 25.0 30.0

Project Prototype Investment NPV

–10% Sales +10% Sales

15 17 19 21 23 25 27 29 31

1 2 3 4 5

Total Incremental Prototype

Sales33

2008 13%

58%

20%

9%

Target WMSC Sam’s Club Kmart

2006

67% 10%

23%

Competition

5.7 SF/Cap

6.4 SF/Cap

WMSC

Sam’s Club Kmart

Capital Expenditure Committee: November 2006

Capital Project Request TARGET.

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Case 20 Target Corporation 309

EXHIBIT 9 | Stock Price Performance 2002–06

Data Source: Yahoo! Finance, http://finance.yahoo.com/.

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Aurora Textile Company In January 2003, Michael Pogonowski, the chief financial officer of Aurora Textile Company, was questioning whether the company should install a new ring-spinning machine, the Zinser1 351, in the Hunter production facility. A primary advantage of the new ring spinner was its ability to produce a finer-quality yarn that would be used for higher-quality and higher-margin products. The finer-quality yarn would be sold in a niche market that would command a 10% increase in the selling price of yarn, which was currently $1.0235 a pound. In addition, the Zinser would provide increased efficiency as well as greater reliability, which Aurora’s operations management had been requesting for many years. The Zinser’s efficiency would reduce operating costs, with lower power consumption and maintenance expenses. Sales volume, however, would be 5% lower than the current market, and the cost of customer returns would be higher, which, when combined with the $8.25 million installed cost, made the Zinser decision a difficult one.

Pogonowski believed that the decision to invest in the new technology was complicated by Aurora’s lackluster financial performance as well as the difficult circumstances facing the U.S. textile industry. Aurora, however, was competing in a few select markets that were likely to continue to survive foreign competition, albeit at lower margins over the long run. He also recognized that there was unlikely to be a better time to upgrade to the Zinser as its price had been increas- ing 5% annually. Not every member of the management team, however, agreed with Pogonowski’s logic. Some managers were arguing that it would be cheaper to continue with the current maintenance schedule, which should keep the current spinning machine running reliably and allow Aurora to postpone replacement indefinitely.

311

21CASE

1The Zinser compact spinning technology was marketed under the trademark CompACT3.

Based on “Aurora Spinning Mills,” an unpublished case by Robert Barnhardt (Dean Emeritus of the College of Textiles, North Carolina State University), this case was written by Lucas Doe (MBA/ME ’04), under the supervision of Professor Kenneth Eades, as a basis for class discussion rather than to illustrate effective or ineffective handling of an administrative situation. Although the case is based on an actual company, many of the names and much of the data have been disguised for pedagogical purposes. Copyright © 2007 by the University of Virginia Darden School Foundation, Charlottesville, VA. All rights reserved. To order copies, send an e-mail to [email protected] No part of this publication may be repro- duced, stored in a retrieval system, used in a spreadsheet, or transmitted in any form or by any means— electronic, mechanical, photocopying, recording, or otherwise—without the permission of the Darden School Foundation. Rev. 2/08.

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The Company Aurora Textile Company was a yarn manufacturer established in the early 1900s to service both the domestic and the international textile industry. Aurora’s finished prod- ucts were cotton and synthetic/cotton blend yarns that were sold to a variety of apparel and industrial-goods manufacturers that sold their products mainly in U.S. retail mar- kets. Aurora serviced four major customer segments: hosiery, knitted outerwear, wovens, and industrial and specialty products. Although each of these markets had both domestic and international components, 90% of the company’s revenue came from the domestic textile market.

Yarn sales for the hosiery market accounted for 43% of Aurora’s revenue. The primary consumer products were athletic and dress socks, with white athletic socks accounting for the majority of sales. In fact, Aurora was the largest volume pro- ducer of all cotton yarns for white athletic socks in the United States, with nearly half the U.S. population owning socks made with Aurora yarns. Aurora had long enjoyed supplying the hosiery market for several reasons. First, as a leader in the market, Aurora was able to command attractive margins and maintain relationships with some of the largest and most profitable hosiery companies in the world. Second, hosiery was produced using bulky, heavy yarns. Aurora’s plants were designed for this type of manufacturing operation, which allowed the company to process large quantities of yarn efficiently. Third, unlike other segments of the textile industry, the hosiery market had successfully defended itself against global competition. The heavy yarns and bulky products were costly to transport, making them less attrac- tive for foreign producers. Moreover, this type of production was highly automated in the United States such that labor costs had been reduced to the point that Asian manufacturers did not have sufficient opportunity to provide significant cost savings over U.S. manufacturers.

The knitted-outerwear market was the second-largest revenue source for Aurora, accounting for 35% of sales. Aurora’s customers within this market mainly produced knitted cotton and polyester/cotton dress shirts for a variety of major retailers. The yarns produced were medium- to fine-count yarns (14/1 to 22/1 ring and rotor).2 This quality yarn, however, was easily produced by other market participants, leaving very little opportunity for suppliers to differentiate their products and creating an environ- ment where there was constant price pressure on outerwear yarns.

Accounting for 13% of Aurora’s business revenue, the wovens market was a rel- atively small but important segment for the company. Most of these yarns were used to produce denim for jeans. Although much of the production had shifted offshore to lower-cost producers, most weavers continued to purchase U.S. yarns in order to avoid the supply risks associated with sourcing yarns from other countries. In addition, the yarns produced for the wovens market were coarse (5/1 to 14/1 ring and rotor) and

312 Part Four Capital Budgeting and Resource Allocation

2The coarseness of a yarn was measured by the amount of yarn it took to equal one pound: the more yarns per pound, the finer the yarn. One “hank” held 840 yards of yarn. A count of 22/1 specified that 22 hanks were needed to equal one pound. A count of 14/1 indicated a coarser yarn than a count of 22/1 in that one pound of 14/1 yarn required only 14 ! 840 yards.

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were cost efficient to produce in Aurora’s manufacturing facilities. Aurora manage- ment believed that the company had an excellent opportunity for growth in this market.

Industrial and specialty products constituted the remaining 9% of Aurora’s revenue. These yarns were used to produce medical supplies, industrial adhesives, rubber- and vinyl-coated fabrics, and protective clothing. Because the yarn component of many of these products was very small, it was not a high-volume business. Nevertheless, this segment provided the highest margins for Aurora, which made it an attractive opportu- nity for growth.

Aurora used rotor- and ring-spinning production processes, although rotor spin- ning, which was also called “open-end” spinning, had constituted the majority of the company’s total revenue for many years. (Exhibits 1 and 2 present Aurora’s financial statements for 1999 through 2002.) The steady decline in sales had led to manage- ment’s decision to close four manufacturing facilities in 2000 in an effort to rightsize Aurora’s capacity to the shrinking textile market and reduce manufacturing costs. In January 2003, the company had four plants operating: Hunter, Rome, Barton, and Butler (see Exhibit 3 for product mix, capacity, and process technology by plant).

The Textile-Mill Industry The U.S. textile-mill industry had experienced dramatic changes over the years because of globalization, U.S. government trade policies, cheaper production costs overseas, and customer preferences and fads. The industry, which had started in New England, moved to the southern United States to take advantage of cheaper produc- tion costs. In more recent years, the search for cheaper production costs had begun to move the textile-mill industry to Asia. As more apparel makers moved their pro- duction abroad, the yarn makers followed suit. Thus, U.S. yarn manufacturers were declining in number while facing tougher and tougher competition from the influx of imported yarns. At the same time, the strong U.S. dollar had made it more appealing for some foreign textile manufacturers to export aggressively, flooding the U.S. mar- ket. Companies like Aurora, which had kept their manufacturing base exclusively in the United States, were frequently forced to cut costs and modernize their operations to remain competitive.

Consumer preferences and fads also shaped the market. The emphasis in the industry had shifted from mass production to flexible manufacturing as textile mills aimed to supply customized markets. Firms were concentrating on manufacturing sys- tems that allowed small quantities of customized goods to be produced with minimal lead time. This change enabled apparel producers to bring goods to retailers and con- sumers in a significantly shorter time frame. Information technology allowed retailers to assess their merchandise needs rapidly and to communicate those needs through apparel manufacturers to textile firms. In general, consumer preferences had moved toward finer-quality yarn with minimum defects, and those preferences were even stronger in the high-end market.

Information technology also had a downside for yarn producers like Aurora because of the liability associated with customer returns. For example, a dress shirt that was sold at JCPenney for $25 might include $5 of Aurora yarn. If the yarn was

Case 21 Aurora Textile Company 313

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defective and the defect could be traced back to Aurora, the company would be required to reimburse JCPenney for the full retail price of $25, five times the amount of revenue received by Aurora for the garment. In 2002, 1.5% of the Hunter plant’s sales volume had been returned by its retailers. The percentage of volume returned had risen over the past few years owing to advancements in technology and infor- mation flow through the supply chain that made it easier to identify the yarn manu- facturer associated with a particular garment. If Aurora began selling yarns for use in the high-end market, the company’s dollar liability per garment would increase. For example, if Aurora supplied the yarn for a shirt that sold for $75 at Nordstrom, a cus- tomer return would make Aurora liable for paying $75 to Nordstrom despite the fact that Aurora would have received only $10 for the yarn used to make the shirt. Aurora’s production engineers were confident that the Zinser would yield such high-quality yarn that the volume returned would drop to 1.0%.

The U.S. government’s free-trade policies were implemented through the North American Free Trade Agreement (NAFTA) and the Caribbean Basin Initiative (CBI). These trade agreements had created a burden on the U.S. textile industry by encourag- ing trade with Canada, Mexico, and Caribbean countries, which lowered the prices of consumer goods in the U.S. market. This enriched trade also forced U.S. textile com- panies to compete against cheaper labor, lower environmental standards, and government- subsidized operations. The net effect was substantially lower-priced goods for U.S. consumers but a very difficult competitive environment for U.S.-based manufacturers.

For other parts of the world, the U.S. State Department had used textile quotas and tariffs as a political bargaining tool to obtain cooperation from foreign govern- ments. The United States and other countries also used quotas and tariffs as a mech- anism to prevent the dumping of foreign goods into local markets and to protect the domestic industry. Recently, however, the World Trade Organization (WTO)3 had announced that, as the governing body for international trade, it would ban its mem- bers from using quotas, effective January 1, 2005. This move would further open the U.S. market to competition from countries beyond its immediate borders. Notwith- standing this outlook, most research analysts believed that the U.S. textile industry would grow around 2% in real terms, with prices and costs increasing at a 1% infla- tion rate for the foreseeable future.

Production Technology The production of yarn involved the processes of cleaning and blending, carding, combining the slivers, spinning, and winding (Exhibit 4). Aurora used only rotor spinning and ring spinning in its yarn production. Ring spinning was a process of inserting twists by means of a rotating spindle. In ring spinning, twisting the yarn and winding it on a bobbin occurred simultaneously and continuously. Although ring spinning was more

314 Part Four Capital Budgeting and Resource Allocation

3Established through agreements and negotiations signed by the bulk of the members of the General Agree- ment on Tariffs and Trade (GATT), the WTO replaced GATT in January 1995. The WTO was an interna- tional, multilateral organization that laid down rules for global trading systems and resolved disputes between member states. Of its 148 members, 76 were founding members, including the United States.

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