Strategic Management Accounting in a Network Economy (Management for Professionals) 9819952522, 9789819952526

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Management for Professionals

Wingsun Li

Strategic Management Accounting in a Network Economy

Management for Professionals

The Springer series “Management for Professionals” comprises high-level business and management books for executives, MBA students, and practice-oriented business researchers. The topics cover all themes relevant to businesses and the business ecosystem. The authors are experienced business professionals and renowned professors who combine scientific backgrounds, best practices, and entrepreneurial vision to provide powerful insights into achieving business excellence. The Series is SCOPUS-indexed.

Wingsun Li

Strategic Management Accounting in a Network Economy

Wingsun Li Faculty of Business Management Beijing Normal University & Hong Kong Baptist University—United International College Zhuhai, China

ISSN 2192-8096 ISSN 2192-810X (electronic) Management for Professionals ISBN 978-981-99-5252-6 ISBN 978-981-99-5253-3 (eBook) https://doi.org/10.1007/978-981-99-5253-3 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

About This Book

This book continues from my first SMA publication in 2018 (also by Springer) and discusses the new roles of SMA in the new network economy. Emerging digital technologies have revolutionized the business world with groundbreaking rules and innovative business models. New knowledge and information technologies have inspired new business ideas and created more information platforms at a lower cost, yet highly efficient in the market. The new business transformation also encourages more inter-organizational cooperation to cope with rapid changes. All these novelties add challenges to corporate individuals in managing businesses beyond their organizations, in particular financial professionals (e.g., CFO) who are experts in the team. Therefore, SMA is assigned a new role in the new network economy. Similarly, SMA calls for major updates and revisions. This urges me to write this book to meet the new demand. I have selected important topics that are particularly pertinent to the new Internet economy. These topics include how to make decisions under business uncertainty, how to value businesses in general, Internet stocks and intangible assets in particular. Business collaboration and integration are usual means to acquire synergy value. How does SMA help deliver the best results? How are business models and information platforms built as sense-making revenue models, even though these platforms never charge for services? How is market power and brand value measured? How does trust supplement control in new network organizations? Finally, how is value created, captured, and allocated in a fair manner? The book will go through detailed examinations of each topic with cases, examples, and illustrations as required.

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Entering the Network Economy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 SMA Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 SMA Dimensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Value as the Central Theme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4 Beyond the Boundary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5 Business Integration in the Network Economy . . . . . . . . . . . . . . . 1.6 SMA in the Transforming Network Economy . . . . . . . . . . . . . . . 1.7 Objectives of the Book . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.8 Organization of the Book . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.9 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1 1 4 5 7 8 9 13 14 16 17

2

Decision Making Under Uncertainty—Basic Concepts and Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Decision Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Frame of References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.1 Decision Making . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.2 Decision Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Decision Tree . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Example: Build or Buy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.1 Illustration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 Probability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5.1 Subjective Probability . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6 Expected Value . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.7 Evaluation Unit & Evaluation Date . . . . . . . . . . . . . . . . . . . . . . . . 2.8 Making Choices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.8.1 Direct Choice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.8.2 Outcome Dominance . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.8.3 Probabilistic Dominance . . . . . . . . . . . . . . . . . . . . . . . . . 2.9 Certainty Equivalents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

19 19 20 21 21 22 24 24 26 27 27 28 32 32 32 34 36

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2.10 Further Remarks on Expected Value . . . . . . . . . . . . . . . . . . . . . . . 2.11 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

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Decision Making Under Uncertainty—Preference Curve, Sequential Analysis, and Multiple Criteria Assessment . . . . . . . . . . . 3.1 Preference Curve . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Plotting a Preference Curve . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.1 Risk Behaviors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Example 1—Preference Curve . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3.1 Implications and Limitations . . . . . . . . . . . . . . . . . . . . . 3.4 Mixed Method with Risk Focus . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 Sequential Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5.1 Example II - Rollback Technique . . . . . . . . . . . . . . . . . 3.5.2 Complete Strategy Using Mixed Method . . . . . . . . . . . 3.5.3 Further Example with Strict Sequential Constraints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6 Multiple Criteria Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6.1 Satisficing Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6.2 Tradeoff Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Reference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Valuing Business—Concepts and Techniques . . . . . . . . . . . . . . . . . . . . 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 General Valuation Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Discounted Cash Flow (DCF) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.1 Discount Rate (R) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Free Cash Flow (FCF) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4.1 Transformation Process . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 Terminal Value . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.6 Abnormal Income-Based Approach . . . . . . . . . . . . . . . . . . . . . . . . 4.7 Cost Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.7.1 Asset Overstatement . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.7.2 Asset Understatement . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.8 Multiple Comparable . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.8.1 Candidates for Comparison . . . . . . . . . . . . . . . . . . . . . . 4.8.2 Equity Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.8.3 Entity Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.9 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

37 40 41 43 43 45 45 47 49 49 51 51 54 55 61 61 62 64 65 67 67 68 71 71 73 75 78 81 85 85 85 87 88 91 95 98 99

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Competitive Position—Strategic Cost and Value . . . . . . . . . . . . . . . . . . 5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 A Search for Competitive Position . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Competitive Drivers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.1 Value Attributes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.2 Cost Attributes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.3 Configuration Attributes . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.4 Example—BBK Electronics and Xiaomi . . . . . . . . . . . 5.4 Value Curve and Value Chains Analysis . . . . . . . . . . . . . . . . . . . . 5.4.1 Value Curve . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4.2 Profit Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4.3 Value Chain Analysis (VCA) . . . . . . . . . . . . . . . . . . . . . 5.4.4 Value-Added Versus Non Value-added Activities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4.5 Case Discussion—Faro Furniture Pty . . . . . . . . . . . . . . 5.4.6 New Value Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 Scale Driver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5.1 Manage the Scale Driver . . . . . . . . . . . . . . . . . . . . . . . . . 5.6 Industry Value Chain Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7 Competitive Position and Financial Metrics . . . . . . . . . . . . . . . . . 5.8 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

101 101 102 103 103 103 104 105 108 108 110 112

Competitive Position: Network Integration . . . . . . . . . . . . . . . . . . . . . . 6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Network as the Fourth Contributor . . . . . . . . . . . . . . . . . . . . . . . . . 6.3 Theoretical Explanations on Network Effect . . . . . . . . . . . . . . . . 6.4 Forms of Network Integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.5 Assessment of Network Integration . . . . . . . . . . . . . . . . . . . . . . . . 6.5.1 Financial Assessment in Outsourcing Decision . . . . . . 6.5.2 Financial Assessment in Supply Chain Management (SCM) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.5.3 Financial Assessment in Strategic Alliance . . . . . . . . . 6.6 Determinants of Network Influence . . . . . . . . . . . . . . . . . . . . . . . . 6.6.1 Social Network Analysis . . . . . . . . . . . . . . . . . . . . . . . . 6.6.2 Resource Dependence and Symmetry of Interest . . . . 6.7 Implications for the Network Influence . . . . . . . . . . . . . . . . . . . . . 6.8 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

131 131 132 133 136 141 141

Market Power and Market Value Creation . . . . . . . . . . . . . . . . . . . . . . 7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 Market Power Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.1 Price Elasticity from Strategic Perspective . . . . . . . . . . 7.3 Price Elasticity, Sales Revenue and Price . . . . . . . . . . . . . . . . . . . 7.4 Brands and Strategic Synchronization . . . . . . . . . . . . . . . . . . . . . .

159 159 159 161 163 167

113 115 117 122 124 126 127 128 130

143 148 152 152 154 156 157 157

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7.4.1 Brand and Market Consequences . . . . . . . . . . . . . . . . . 7.4.2 Strategic Synchronization . . . . . . . . . . . . . . . . . . . . . . . . 7.5 From Brand Strength to Brand Value . . . . . . . . . . . . . . . . . . . . . . . 7.5.1 Brand Value . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.6 Customer Value Creation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.6.1 “True” Profits (please also refer to Chapters 4 and 5 of my book in [2018]) . . . . . . . . . . . . . . . . . . . . . . 7.6.2 Customer Lifetime Value (CLV) (please also refer to Kumar and Rajan [2009]; Kumar and Shah [2009]) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.7 Market Value Accumulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.8 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

167 168 170 171 174

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Pricing Strategies in a Dynamic Market . . . . . . . . . . . . . . . . . . . . . . . . . 8.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2 Pricing as a Strategic Weapon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3 Price Tiers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4 Cost-Based Pricing Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4.1 Short-Term Basis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4.2 Long Term Basis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.5 Market-Based Pricing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.5.1 Game Theory in Pricing . . . . . . . . . . . . . . . . . . . . . . . . . 8.5.2 Implications for Pricing Strategies . . . . . . . . . . . . . . . . 8.6 Value-Based Pricing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.6.1 Target Costing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.7 Pricing Discretion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.8 Dynamic Pricing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.9 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

183 183 184 185 187 188 190 193 194 196 197 197 203 206 208 209

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Digital Business and Revenue Models . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.2 Rethinking the Network Economy . . . . . . . . . . . . . . . . . . . . . . . . . 9.3 Internet Business Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.4 Revenue Drivers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.4.1 Long-Tail Operation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.4.2 Network Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.5 Lock-in Effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.6 Price Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.7 Case Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.8 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

211 211 212 213 218 218 219 222 224 227 234 235

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175 179 181 181

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10 Valuing Internet Stock and Intangible Assets . . . . . . . . . . . . . . . . . . . . 10.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.2 Accounting Conservatism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.3 Valuation Methods for Internet Stock . . . . . . . . . . . . . . . . . . . . . . . 10.3.1 Adjusted P/E Multiples . . . . . . . . . . . . . . . . . . . . . . . . . . 10.3.2 Margin Adjusted Sales Multiples . . . . . . . . . . . . . . . . . 10.3.3 Customer-Based Valuation . . . . . . . . . . . . . . . . . . . . . . . 10.4 Valuation Under Uncertainty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.4.1 Discounted Valuations Under Uncertainty . . . . . . . . . . 10.5 Intangible Assets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.6 Valuing Specific Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.7 Valuing Brand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.8 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

237 237 238 240 241 244 245 248 248 253 255 257 260 262

11 Management Control System in the Business Network: Control and Trust . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2 MCS Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2.1 Strategic Control Process . . . . . . . . . . . . . . . . . . . . . . . . 11.2.2 Management Control Process . . . . . . . . . . . . . . . . . . . . . 11.2.3 Motivation Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2.4 Informal Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.3 Formal vs Informal Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.4 Management Control and Networks . . . . . . . . . . . . . . . . . . . . . . . . 11.5 Trust and Risk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.6 Control and Risk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.7 Trust as a Complementary Mechanism . . . . . . . . . . . . . . . . . . . . . 11.8 Payoff Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.9 The Impact of PCB and Reliance on Trusting Behaviour . . . . . . 11.10 The Use of Trust and Control in the Business Network . . . . . . . . 11.10.1 Outsourcing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.10.2 Virtual Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.10.3 Collaborative Alliance . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.10.4 Business Ecosystem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.11 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

263 263 264 265 266 266 267 268 269 272 274 276 278 281 284 286 286 287 287 289 290

12 Value Creation, Capture, and Allocation . . . . . . . . . . . . . . . . . . . . . . . . 12.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.2 Value Creation and Network Integration . . . . . . . . . . . . . . . . . . . . 12.2.1 Added Value Business Activities . . . . . . . . . . . . . . . . . . 12.2.2 Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.2.3 Products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.2.4 Vertical Value Chain . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.3 Value Capture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

293 293 294 295 296 296 296 298

xii

Contents

12.4 12.5

Frictions with Value Capture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Revenue Allocation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.5.1 Stand-Alone Basis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.5.2 Incremental Revenue . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.6 Shapley Value . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.7 More Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.7.1 E-marketing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.7.2 Product Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.7.3 Shared Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.8 Governance in the Network Economy . . . . . . . . . . . . . . . . . . . . . . 12.9 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

300 310 311 312 313 316 316 318 320 323 323 325

About the Author

Dr. Wingsun Li was a teaching faculty who taught undergraduate and postgraduate management accounting and strategic management courses at universities. He retired a few years ago but continued to be part-time faculty at United International College in China. He had been a CPA (Hong Kong) for forty years. Prior to academic career, he had been in senior management positions for a long time, including vice president in Ericsson China, CFOs in food factories, and management consultant at KPMG. Dr. Li holds a doctoral program in management and master degrees in accounting and economics. He had served many professional bodies including Past Chairman in North Asia Regional Board at CIMA (UK). He wrote several publications in local and international publishers.

xiii

Chapter 1

Entering the Network Economy

1.1 SMA Review Strategic management accounting (SMA) is an integrated knowledge discipline. It combines management accounting techniques with strategic management concepts to assist corporate managers in interpreting company information (both financially and non-financially), analyzing business environments, evaluating decision options, formulating and implementing strategies, as well as monitoring performance outcome from action plans. This enlarged concept scope was first introduced in 1981 by Simmonds1 in the Management Accounting (a UK professional journal). He viewed SMA as an extension of management accounting. Accounting data was employed in business and competitor analysis for the purpose of formulating and monitoring business strategies. SMA divulged from the traditional role of management accounting and opened an avenue for this practical discipline to advance its development. SMA is featured as external focus, forward looking, and strategic orientation. Furthermore, the extended new domains to customers, market, and competitors’ analysis, along with the traditional product cost and internal analysis, strengthens its diagnostic strength and instrumental use in both operational and strategic management. On the other hand, the new SMA scope leads accountants to think from multi-dimensional perspectives including internal operations, marketing, customers, and competitors…etc. The integrated approach supplements strategic management practitioners in business analysis and corporate decision formulation and suggests a common language for managers (in dollar sense) to drive the corporate growth. Simmonds’ indigenous idea has inspired endless ideas from professionals and academics. SMA started to grow in scope contents, concepts, and techniques. For

1

Simmonds K. was named by many distinguished scholars (e.g. Kaplan), who was the pioneer in elating management accounting to a strategic horizon. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 W. Li, Strategic Management Accounting in a Network Economy, Management for Professionals, https://doi.org/10.1007/978-981-99-5253-3_1

1

2

1 Entering the Network Economy

example, some scholars2 propose SMA to be focused in product markets, competitors’ costs, and cost structure. SMA information aims to monitor the firm’s strategy as against its rivals in the target markets. Shank3 emphasizes the importance of strategic cost as an input to the corporate strategic control system. Strategic cost has a primary role in serving corporate mission. SMA should enable corporate management to steer corporate goals and directions. Marketing advocates4 take a narrow marketing lens as a generic approach to accounting for strategic positioning. They propose “the marriage between marketing and accounting”. There are many other scholars and professionals contributed to the growing repertoire of SMA concepts and techniques. Doubtless to say, SMA was evolved from the strategic management discipline (SM). Its evolution has a strong association with development of SM theories. SM concepts were dominated by Michael Porter’s competitive advantage concepts in 70s and 80s, featuring competition from external market view. However, critical scholars started to question the over-dominance of external driven market competition approach. They began to find answers from inside—quality and unique characteristics of corporate resources that traced back to the corporation’s historical account in search of resource uniqueness and resource capabilities. These resourced based view (RBV) researchers5 believe that resource capabilities account for corporate success and failure in face of changing market landscape, not purely the outcome of external market competition. Dynamic resources are the key for corporate success. RBV theory supplements competitive advantage theory in the market competition game. The burgeoning RBV theories gradually divert the attention of SMA towards internal resources and capabilities. For example, Shank’s cost driver analysis (in terms of structural and execution drivers) examines firms’ internal resource capabilities. Some scholars6 call for new techniques to deal with organizational capabilities in intangible assets or intellectual capital. Gupta & Lehmann7 puts customers as asset value and promotes new method to value customer from its lifetime value. Total cost and management concept have also been raised to address corporate issues from a broader perspective. Value analysis further shifts the focal lens from a short-time profit to customer perceived value. Both total cost and management concept, as well as value analysis, directs the attention to a longer corporate value dimension. Stern Stewart’s EVA and Kaplan and Norton’s balanced scorecard8 uplifted SMA to a new height after introducing these popular practicing tool. SMA embraces a broader scope of concepts, techniques, and time horizons in dealing with external forces and 2

E.g. in Bromwich’s 1990 article. Shank has established a complete strategic cost management (SCM) approach to explain his proposed propositions. Please refer to his book published in 1989. 4 Roslender and Hart (2003) is a typical representative of this marketing school. 5 e.g. Barney, Peteraf. 6 e.g. Nixon, Burns, Taylor. 7 Gupta and Lehmann’s simplified version of customer life cycle as a proxy for customer asset value calculation will be fully discussed in Chapter 7. 8 Both EVA and Balanced scorecard are welcome by large corporations as supplementary performance monitoring tools for the traditional budget and forecast system. 3

1.1 SMA Review

3

internal drivers. In fact, corporate value is enshrined in these emerging concepts as a superimposing objective for the firm. By the turn of the twenty-first century, business world is getting more complicated, exemplified by increasing number of global companies and rapid technological development. Disruptive digital technology destroyed the old order of the traditional economy. Ingenious business models redefine new rules of the business game in competitive markets. New Era challenges conventional focuses and practices of firms. Firms in the same trade or across trades align in business ecosystem. Firms envision cooperation as important as competition. Cooperation with strategic partners (suppliers, customers, or even competitors) is a quick pathway to achieve the corporate goal (e.g. joint development for technological advancement). Cooperation with external parties accelerates developments of skills, knowledge, or idiosyncratic resources that could not have been obtained by the firm alone. Cooperation therefore increases the firm’s dynamic resource capabilities, i.e. the ability to adapt to new market demand very quickly. However, this paradigm shift has also shaken the conventional management control concept in an organization. Traditional management control becomes ineffectual as new business models do not provide consistence and stability which are per-requisite conditions of a stable organization. Organizational control is further restrained when strategic partners are not employees of the firm. Similarly, the shift challenges knowledge ownership concept. Who owns knowledge, especially tacit knowledge? Is owned by individual employees, or team of employees (especially for innovative technology) in a joint project, or partners in the joint project. Firms are given the knowledge integrator role to transform knowledge into value. When control loses its legitimacy, trust rather than control may be more effective in such environmental settings. These changes alter the manner firms manage their corporate performance. Business ecosystem is particularly emphasized in the new digital economy because business models are built on different strategic cooperative platforms. SMA requires a different approach to cope with these changes. SMA concepts and tools need to be revamped to meet this new demand. In sum, there was a rapid development of SMA concepts and techniques during 1980s and 1990s, but slowed down by the turn of the century. SMA faced a new challenge in the new century characterized by a volatile business environment, making planning and control difficult to be effectively exercised. Digital economy increases accessible information in the market. Market cost pressure and rapid changing market demand urge managers to embrace multi-disciplinary knowledge about their business. SMA is not only an important knowledge and practicing domain for practicing accountants, but also for non-accountants such as business analysts, strategic managers, and senior management. Therefore, SMA increases its significance both in the academic and business worlds.

4

1 Entering the Network Economy

1.1 Focus The Business ecosystem of Android In 2007, Google as the owner of Android system has redefined the rule of the new game in the mobile device businesses. Android announced free access of its operating systems (OS) to all apps developers. Before that, Apple developed its legacy OS for I-phone products. Symbian made OS platform for its mobile phone patronage such as Ericsson, Nokia, Psion. Microsoft just started to entrench into the mobile phone by making its own OS. In fact, Google was a new kid in the market, who was ambitious to take a lion share in face of strong market rivals. It had no better choice but seeking partners in the network. Google made a bold stride. It provided open source code for all apps developers, which developed apps and content offerings in the Android software platform. All partners share revenues with Google. As the number of apps and contents grew to a critical scale, Android platform provided an abundance of apps free of charge to users who subscribed to Android platform. The growing popularity in the platform has forced handset makers to adopt Android OS along with their own bundled apps. Google also formed Open Handset Alliance (OHA) to promote Android among partners in the trade. In only four years, Google kicked Symbian and Microsoft out of the mainstream markets. Apple’s costly legacy system was contained to the upmarket. Given its huge repertoire of apps and contents, Android system managed to dominate the mass markets. Google just spent a few years to make Android ecosystem an indispensable platform in the mobile world.

1.2 SMA Dimensions For ease of explanations, SMA can be summed up into four main dimensions. Strategic cost This dimension relates to the use of cost data to formulate strategic plan and control to serve customers and market needs. Existing SMA techniques under this category include strategic cost management, value chain analysis, quality costing, target costing, and total cost ownership analysis. Strategic market analysis These are sources of market information (both from customers and competitors) that contribute to value creation. They are customer information (financial and nonfinancial) to evaluate customer contribution to business performance (i.e. customer profitability analysis, lifetime customer profitability)… etc. It can also be the use of competitor information (both financial and non-financial) to evaluate competitor’s strength and weaknesses in the target market, competitor cost assessment, competitor position analysis, competitor performance appraisal. Finally, it can also be strategic

1.3 Value as the Central Theme

5

pricing strategy which evaluates fully the focal firm’s market position relative to customers’ perceived value and competitors’ market power. Strategic performance management This area covers integrated management control system of the entire firm. Strategic plans, forecasts, balanced scorecard, and EVM (by Stewart) are tools under this category. Strategic value analysis This category includes some critical valuation of the company, business units, specific business ventures, and also some intangible assets such as brands, customers, and technology development. SMA provides a wide portfolio of tools and techniques to suit firm’s needs. By and large, industries with high market rivalry would be more eager to nourish a high customer intimacy, understand what their rivals are doing, and evaluate their own competitive advantages relative to their rivals. They tend to apply more SMA in analyzing competitor and customer data. Firms in a stable market environment tend to build more internal resources to strengthen competitive advantages. Therefore, they are inclined to make more strategic plans, install control and performance measurement mechanism to steer corporate direction. This is particularly true for large firms whose coordination and monitoring abilities are success factors to sustain critical mass of operational economies. Also, firms pursuing employee participation policy would spend resources on management control systems to align empowerment and accountability. In addition, firms select their own apt cost structure to meet its internal capabilities, external market needs, product portfolio. SMA cost dimension provides a repertoire of SMA tools for firms to match their best fit.

1.3 Value as the Central Theme Organizations have diverse objectives for their corporate goals. Management goes through strategic formulation, implementation, and control processes to achieve these ends. However, these goals may embody conflicting objectives (e.g. stakeholder vs. shareholders). Top managers may pursue their own short-term performance objective at the expense of the long-term goal. This is what Michael Jensen9 refers to ‘agency problem’. Therefore, it is very important in SMA practices to put value discipline as the central theme, and business value growth as the pivotal link. That is to say, all other long objectives are subordinated to value objective. Its primacy is based on the following reasons. a) Value based approach is always underscored by SMA techniques and concepts. This is particularly relevant to profit making organizations where value creation of the firm is the mission and responsibility shareholders asked for the corporate management. 9

Michael Jenson is a pioneer scholar challenging the linking of budgets in a firm’s reward system.

6

1 Entering the Network Economy How a firm’s cost structure creates competitive advantages

How a firm effectively increases market power Provides conditions




Strategic cost analysis

Value creation

Increases bargaining power

How a firm sustains its value creation

Strategic value analysis How a firm measures value creation


) have been coded against the contribution value. For example, 15 M in the preference curve is equivalent to 0.95 preference value and 6 M is equivalent to 0.7 preference value. By converting the contribution into preference value. We start to use the preference value to compute the expected value for each option pertinent to market expansion and product expansion. Based on the information in the decision diagram (Fig. 3.4.As such, we have the calculations for the options as follows: Market expansion: (0.3 × 0.95) + (0.4 × 0.6) + (0.3 × 0) = 0.525(pv) Product expansion: (0.45 × 0.7) + (0.4 × 0.55) + (0.15 × 0.1) = 0.55(pv) The computed preference values (pv) are used to evaluate two individual options. The decision of choice is based on the highest preference value among all options. In this case, product expansion is apparently the preferred choice. In fact, we can translate back the preference value into certainty equivalence unit by referring to the preference value again. For the market expansion option, the certainty equivalence is $4.5 M where as the product expansion option will produce a certainty equivalence of $5 M. (see Fig. 3.4). Therefore, the certainty equivalence unit can quantify the amount of difference instead of scale difference.

48

3 Decision Making Under Uncertainty—Preference Curve, Sequential …

Fig. 3.3 Preference curve

Contr. Success 0.3 Market expansion

CE=4.5M

CE=5M Product expansion

Pv.

15M

Average 0.4

6M

Failure 0.3 Success 0.45

-5M

8M

Average 0.4

5M

Failure 0.15

-1M

Fig. 3.4 Decision diagram

For ease of reference, the following provides a general guidelines. 1. Plotting the company preference curve by the method used Sect. 3.2. 2. Replace the expected outcome value (e.g. contribution) by the preference scale by reference of the preference curve 3. The preference scales are used to calculate expected value taking into consideration of the probability level of each outcome event. The calculated results (both the expected preference values or the translated certainty equivalences) can be used for comparison

3.4 Mixed Method with Risk Focus

49

3.3.1 Implications and Limitations Preference curve and the certainty equivalence concept incorporates the behavioral consideration of decision makers. It has the ability to decompose risk and certainty portions from the calculated expected values and provides an added risk dimension in the decision making analysis. It rectifies the shortfall of expected value analysis which has taken risk neutrality as the only risk orientation and ignores the risk orientation on decision makers. However, preference curve is more relevant to individual decision. In a group decision, individual decision makers with different risk preference may nullify risk impact of the decision finally. Corporate risk preference curve may revert to risk neutrality curve. Risk neutrality assumption is valid in decision making in general situations. Furthermore, preference curve of individuals and (even group) may change over time or under special situations. It may not be a stable condition. It may be wise for decision makers to use it as a robust test or complementary test for special decision making, but not a necessary process to convert into certainty equivalent. That is to say, we can maintain the assumption of risk neutrality in calculation of expected value in the decision tree.

3.4 Mixed Method with Risk Focus As mentioned in the prior chapter, direct choice has limitations whose choice is based on absolute value or some probability analysis. While it may be desirable for decision makers to choose absolute expected performance, it may also be a necessity for managers to evaluate risk dispersion in parallel. Let’s illustrate Lago’s example again in in Table 3.2, I have prepared a summary of these two strategies in regard to contribution and risk dispersion. Now, we review these two options by using mixed method (see Table 3.2). This mixed method takes into account of both absolute dominance and probabilistic dominance, as discussed in Chapter 2. In the above summary table, I include key data and statistics in terms of standard deviation, probability distribution of contribution (selected range). These risk related data enable us to make more accurate evaluative judgment. Expected values: Market expansion: (15M X 0.3) + (6M X 0.4) + (-5M X 0.3) = 5.4 Product expansion: (8M x 0.45) + (5M x 0.4) + (-1M x 0.15) = 5.45

Means: Market expansion: (15M + 6M -5M) /3 = 5.33M Product expansion: (8M + 5M -1M) / 3 = 4M

Dispersion between highest value and the lowest value: Market expansion: 15M + 5M =20M

50

3 Decision Making Under Uncertainty—Preference Curve, Sequential …

Table 3.2 Summary of key information Market expansion

Product expansion

Expected value

5.4

5.45

Maximum contribution

15 M

8M

Minimum contribution

−5 M

−1 M

Dispersion

20 M

9M

Mean

5.33 M

4M

Standard Deviation

5.32

3.37

Probability: Contribution 0 or less

30%

15%

Probability: Contribution 5 or less

30%

55%

Probability: Contribution 10 or less

70%

100%

Probability: Contribution 10.1 or more

30%

0

Product expansion: 8M + 1M = 9M

∑ Standard deviations: [square root of (contribution i – mean)2 × probability i )]. Market expansion: [(15 – 5.33)2 × 0.3 + (6 – 5.33)2 × 0.4 + (-5 + 5.33)2 × 0.3]1/2 = 28.26 1/2 = 5.32. Product expansion: [(8 – 4)2 × 0.45 + (5 – 4)2 × 0.4 + (−1 – 4)2 × 0.15]1/2 = 11.35 1/2 = 3.37 The set of data as noted above presents a more complete information about outcome performance, providing a holistic view of risk on each project under evaluation. As a decision maker, we can base on our risk attitude to make evaluation and choice. From the above data, both feasible projects do not follow a strict dominance over the other. Market expansion has a higher contribution potential but also a higher dispersion, meaning that a higher downside risk. The probability distribution of returns and standard deviation also suggest market expansion runs a higher risk compared to the product expansion. Furthermore, product expansion seems to present a higher expected value than market expansion. With a higher expected value and a lower variance, product expansion strategy is the best choice for the firm. However, firms with a higher risk tolerance may also consider market expansion given a marginal difference in expected value and good upside benefits as suggested in the probability distribution pattern. In short, risk averse decision makers should refer to the following rules of thumb, either: a) the expected value is equal or higher than the other options, and its variance (i.e. standard deviation) is the lowest; or b) its variance is equal or lower than other options, but the expected value is not inferior than the others; or c) The probability distributions for all options are reasonably symmetrical (not complied in this example)

3.5 Sequential Analysis

51

These rules provide a very useful guideline for decision makers to make choice under specific conditions. However, there are situations which require more detailed analysis for other conditions. The most essential factor among all factors is the risk tolerance level of the company, which is the ruler for all risk factors. Mixed method with risk focus incorporating all key concepts of expected value and risk evaluation dimensions have been discussed in detail. Nevertheless, preference curve has its theoretical limitations, due to the fact that group preference curve are sensitive to grouping of decision makers. Combination of group decision makers with diverse risk orientation may undermine overall risk orientation, making preference curve unstable in operation. Prior to employing preference curve, managers need to test the stability of the curve. It also restrains its usability in real business.

3.5 Sequential Analysis I have discussed so far a decision scenario with a single stage analysis. How do we deal with more complex situations which have a multiple stages in the decision processes? Many situations have undergone a series of activities which require decision at every sequential stage. This is the focus of this section. In fact, there is no large difference in the previous decision diagram. It demands more circles uncertain events (circles) in a sequential order of steps leading to the final uncertain event. Let’s demonstrate the sequential analysis in an example below. As decision diagram approach becomes more complex for a multiple-stage analysis, we may apply a rollback procedure technique. Rollback procedure works back from the end to the start of the decision tree, making sure no future decisions to be addressed later on. While we consider decisions at every stage, we keep the good outcomes and discard the bad outcomes. With this rollback technique, we can be able to decide sequential stage and trace to the initial stage. A general guideline for the rollback procedure is highlighted below: 1. Start at the right-hand nodes and choose from one of those events at that decision node 2. Cross out those decision nodes which could be eliminated for further examination. 3. Continue to trace back to the initial decision.

3.5.1 Example II - Rollback Technique The business team of Lago furniture has come up with another set of strategies for consideration by the Board. The new strategies were rooted from Lago’s resource problem that: (a) excess capacity undermines it operating performance. (b) low end brand image affects profit potential. Therefore, business management has made a proposal to create a new brand for the middle market in parallel to the existing brand

52

3 Decision Making Under Uncertainty—Preference Curve, Sequential …

for low market. They also propose to promote new international market business or increase product portfolios for the existing market. Due to the financial constraint, Lago can proceed either one of the two strategies in the near future. For the market expansion strategy, they have explored two markets, one is the neighboring country in Asia and the other is a middle market in England. If the business team do nothing, Lago can rent out excess production capacity to its strategic partner where it can earn a fixed annual income of $1million, net of additional cost. The internal business analyst has worked out outcome probabilities of each activity for a one-year period basis. For new brand development, effective (success) rate is 0.6, and ineffective rate (failure) is 0.4. For new market expansion and product expansion, all contributions and probabilities of the possible outcomes are noted in Fig. 3.5. Please recall that the square in the decision diagram represents decision node and the circle node is event activity node. We have a few decision strategies, namely (a) go 2.14 2.55

Euro

X

D

I

pe

2.55

Asia

Good 0.4

J

Modest 0.3 Poor 0.3

me

bra

nd

Good 0.3 5.0M Modest 0.3 2.0M Poor 0.4 -1.5M

Sa

tive

rop N ew

bran

d

in e f fe c (0.4 tive )

X

1.52

X

Eu

B

2.55

Good 0.4 4.5M Modest 0.2 3.5M Poor 0.4 -2.0M

L

Good 0.2 4.0M Modest 0.2 3.5M Poor 0.6 -1.5M

E 1.52 As ia

A

H

tive effec ) (0.6

M

t duc Pro sion X an exp

N

2.1 S

ame brand

O

C

1.0

X

X

New

bra

nd

1.03 F

) ve (0.6 effecti

Ineff

Good 0.4 3.5M Modest 0.4 2.5M Poor 0.2

-2.0M

inef fec (0.4 tive )

2.1 Rent out excess capacity

K

e

2.55 t ke n ar io M ans p ex

1.26 effec 6) (0. G

P

Good 0.2 3.0M Modest 0.4 2.0M Poor 0.4 -1.5M Good 0.4 3.0M Modest 0.4 2.5M Poor 0.2 -0.5M Good 0.3 3.5M Modest 0.5 2.5M Poor 0.2 -1.0M Good 0.2

ectiv

e (0.

4)

4.5M 3.5M -1.0M

Q

3.0M

Modest 0.4 2.0M Poor 0.4

-1.0M

1.0M

Fig. 3.5 Decision diagram

3.5 Sequential Analysis

53

for a new market, increase product portfolio, or simply rent out facility; (b) consider employing new brand, or simply using the existing brand; (c) under new market expansion we need to decide Asia or Europe (i.e. England); also taking into account whether new brand strategy is effective or not, it comes out with 22 outcome events (note: the effectiveness of new brand strategy will affect the outcome of going for new market or increasing product portfolio). As noted in Fig. 3.5, the decision diagram links up all 22 outcome events in a web diagram with probability and evaluating units (i.e. contribution) for each uncertain outcome. It is a sequential analysis because we start from the final stage of outcome activities and roll back seven key strategies. Let’s start with the expected value approach initially. We will employ mixed method to address risk evaluation issue at a later stage. According to the guideline above, we begin from the right-hand nodes. For clarity of presentation, I named every node with a number and presented the working on calculations below (Table 3.3). As can be seen above, the decision node on E is Asia market which is 1.52 M in node H. We now compare node E and node D, the decision at this stage (decision node B) should be on node D as node D has a high expected value compared to node E (2.55>1.52). Therefore, we can focus on the single brand strategy where the firm goes for market expansion. The evaluation of product expansion has applied the same logic and sequences. By the rollover method, we compare same brand (activity node O) with new brand (activity node F) and find out same brand (node O) contributes more expected value (2.1 M vs 1.03 M). Therefor, we shall employ a single brand strategy should the firm go for product expansion. The final option is to rent out excess capacity which is 1 M per year. After tidying the two expansion strategies, it is very clear the Asian market expansion with same brand is better than product expansion with new brand, and renting strategy is the worst choice in terms of annual contribution (2.55 M > 2.1 M > 1 M). Asian market Table 3.3 Expected value evaluation Computation Activity node I:

5M×0.3+2 M×0.3−0.15 M×0.4=2.14

Activity node J:

4.5M×0.4+3.5 M×0.3−1 M × 0.3 = 2.55

Decision node D:

J > I, J selected (Asia)

Activity node G:

(4.5M×0.4×0.6+3.5 M×0.2×0.6—2 M×0.4×0.6)+(4 M×0.2×0.4+3.5 M× 0.2×0.4—1.5 M×0.6×0.4) = 1.26

Activity node H:

(3.5M×0.4×0.6+2.5 M×0.4×0.6—2 M×0.2×0.6)+(3 M×0.2×0.4+2 M×0.4× 0.4—1.5M×0.4×0.4) = 1.52

Decision node E:

H>G, H selected (Asia)

54

3 Decision Making Under Uncertainty—Preference Curve, Sequential …

expansion with the same brand strategy is therefore selected. For facilitating sequential analysis, I have placed the value in boldface in the decision nodes at each round which has the highest value and discard those routes not qualified for further evaluation in the next round. By this rollback method, it is very easy to identify the preferred choice (also with a highlighted path) and trace all alternatives from the end. The above rollback method demonstrated the logical approach to make choice even though under a complex situation of multiple stage. However, we should not take it for granted that the highest value outcome among all options should be the best choice. We may need to look into the risk perspective of each strategy. Therefore, we apply the mixed method again. Apart also evaluating risk perspective, we have the opportunity to consider this decision from multiple lens. This method applies to single stage problem as well as for multiple stage problem.

3.5.2 Complete Strategy Using Mixed Method This complete strategy, assisted by the rollback method, delineates all possible downstream alternatives raised by the initial strategic initiatives. It is a complete strategy approach because it outlines the decisions for all possible contingencies For example, the Lago example have come out with seven strategies from the strategic initiative with the aim to eliminate excess capacity and improve business performance. There seven strategies are the following: i. ii. iii. iv. v. vi. vii.

market expansion in Asia with the existing brand market expansion in Asia with a new brand market expansion in Europe with the existing brand market expansion in Europe with a new brand Product portfolio expansion with the existing brand Product portfolio expansion with a new brand renting out excess capacity to the affiliate company

By using a mixed method approach, I summed up the key information for each strategy in Table 3.4. We should compare the numbers for each strategy with reference to the key strategic initiative and their risk distribution. We then prioritize the strategy and see which strategies best serve the strategic initiative. The statistics as shown below give us more information about expected performance of each strategy in terms of contribution and risk bearing. Comparing all options, Asian market expansion under existing brand (i.e. strategy (i)) is still the preferred strategy among all according to expected value evaluation. It is the second lowest risk variance among all alternatives (s.d. 4.3). Also, its probability distribution is also biased upwards higher contribution (70% of probability between 5 M to 3.1 M). Therefore, it has the highest dominance in value (at least no other alternatives higher than (i)), probability dominance, as well as second lowest variance. Compared to the second best choice—(v) product expansion under existing brand, it has the lowest risk variance (s.d. 2.7), low probability in losing money (20%) and

3.5 Sequential Analysis

55

Table 3.4 Summary of key information—all strategies In $M Expected value

(i)

(ii)

2.55

1.52

(iii) 2.14

(iv) 1.26

(v) 2.10

(vi)

(viii)

1.03

1.0

Max. contribution

4.5

3.5

4.0

4.5

3.0

3.5

1.0

Min. contribution

−1.5

−2.0

−1.5

−1.5

−0.5

−1.0

1.0

Dispersion

6.0

5.5

5.5

6.0

3.5

4.5

n.a

Mean

1.6

1.25

1.83

2.0

1.67

1.5

n.a

Standard Deviation

4.3

5.3

4.6

6.6

2.7

4.5

n.a

Prob.:Contr. 0 or less

30%

28%

40%

48%

20%

28%

0

Prob.:Contr. 3 or less

30%

58%

70%

48%

100%

82%

100%

Prob.:Contr. 5 or less

100%

100%

100%

100%

100%

100%

100%

stable income (80% in 3 M or less). Expected contribution is reasonable. The only setback is maximum contribution is $3 M. However, it is particularly the appetite of the risk-averse firm. This can also be the preferred choice for those firms with a high risk-averse orientation. The third preferred choice is (iii)—Europe market expansion under existing brand. It has the third highest expected value, moderate risk variance (s.d. 4.6), and probability distribution is fairly even. By a mixed method evaluation, we can prioritize the above strategies as follows: (i) > (v) > (iii) if the firm has a higher risk tolerance. Or lese, it can be (v) > (i) > (iii) if the firm has a high risk-adverse orientation. We can do a robust test on certainty equivalence by changing the contribution in terms of preference scale from the preference curve. We can calculate the expected valued based on preference scales and convert back into certainty equivalence. In fact, there is a common characteristic among all three strategies—all pointing at the existing branding. Apparently, new brand strategy may not be desirable to bring in additional benefits over the period of evaluation.

3.5.3 Further Example with Strict Sequential Constraints There are decision scenarios which must follow a sequential order in order to proceed to the next stage. For example, the decision for commercial development or residential development for property development must go through an application for change of land use if the original land use is residential development only. The development of a new product may be subject to a new technology. Therefore, this strict sequential order is required to be complied. Let’s discuss one more example based on this consideration. I employed Lago Example again, but altered some assumptions. Example III—Sequential Constraints

56

3 Decision Making Under Uncertainty—Preference Curve, Sequential …

The Lago management wants to create a new mid-end product range but requires a new design (R&D) spending of $0.5 million to enhance the overall design. Due to a new design, they are not sure whether the overall new design will be successful or not. If the new design works, Lago will create a new market in Europe and launch a new mid-range product. Product manager forecasts the success rate is about 80%. In the failed case, Lago can also go into a new Asian market with the existing low end products. However, they cannot launch low end products in Europe given the high transportation cost and market competition. For the safe side, Lago is confident that existing low end product is welcome in a new Asian market or the existing local market, but the local market is subject to the constraining price. Price, cost, potential sale volume (base line) for the three markets are shown below (Table 3.5). In fact, Lago can boost the sale volume by appointing a special sale channel. It is forecast that this sale channel requires $0.5 million for the Asian market and $1 million for the UK market. According to the market research, the chance is 70% that can induce additional sales by 35%. Due to the familiar local brand, promotion spending is not required for the local market. Lago estimates three business scenarios for each market: best scenario and bad scenarios are 140% and 80% of the baseline scenario. Probabilities for the outcomes of scenarios are: Old market: Best, base and bad scenarios are 0.3, 0.4, 0.3 respectively New market: Best, base and bad scenarios are 0.2, 0.4, 0.4 respectively.

I want to make a few clarifications. First, I am using a relevant cost approach for this case, meaning that only relevant costs will be considered for this decision. Therefore, committed fixed costs are irrelevant to the evaluation, with exception of new fixed costs. Second, we are not free to choose new markets but conditional on the success of the new design. If successful, Lago goes for Europe expansion, otherwise Asian market. Third, new design and special sale channel are relevant cost as it is subject to the choice of strategy. Let me identify strategic options in Fig. 3.6—Strategic options (with constraint on new design). As noted above, new design (R&D) is critical for the strategic choice. The chance is 80%-20%. Lago can go for the Europe market expansion for introduction of a midrange product if the new design is successful, or else go for expansion in the local market or an Asian country. By now, we can identify five options in the following: Table 3.5 Prices, costs, & sales volumes US$

Potential quantity

Unit price

Variable cost

UCM*

Add. Fixed cost

Local market

650 K

9.0

7.5

1.5

–

Asian market

850 K

10

8.0

2.0

500 K

UK market

650 K

15

9.0

6.0

1200 K

*

contribution margin per unit

3.5 Sequential Analysis

Constraint on R&D

Failure

20% 80%

Success

57

Product

Market Local market

Low end products Mid range products

Asian markets Europe markets

Sale channel

a Existing channel b c d e

Add new channel

Fig. 3.6 Strategic option (with constraint on success in new design)

(a) (b) (c) (d)

Low-end product expansion for the existing local market; Low-end product expansion in a new Asian market with existing sale channel; Low-end product expansion in a new Asian market with special sale channel; Mid-range product development in Europe market with existing sale channel (subject to successful new design); (e) Mid-range product development in Europe market with special sale channel (subject to successful new design).

Subsequently, we have to compute the payoff for all outcomes in terms of contribution margin (Table 3.6, based on relevant income). Recall that the best and the bad scenarios are 1.4 and 0.8 of the sales in the base scenario respectively while special sale channel has a chance to increase original forecast sales by 35%.

3.5.3.1

Decision Diagram with Strict Sequential Constraint

Decision diagram (see Fig. 3.7) outlines Lago’s strategic option with strict sequential order. I highlighted the outcome path (in orange) which earns the highest expected value. Please note that the primary strategic option is whether the firm should introduce mid-range product into the Europe market (proposition 1). Therefore, the sequential order of choice is first to evaluate two key marketing strategies—introduce mid-range product vs expand existing low end products. However, it is subject to the success of new design. The first evaluation is the choice of product direction. We have to be sure that new mid range products will generate more contribution income than low end products in the existing local market. The subsequent strategic choice will be triggered when the new design fails to materialize. It is then to evaluate the potential performance of new Asian market or existing local market (proposition 2). In short, we have to address two sequential decision choices in this evaluation exercise. Two propositions have to be examined in the analysis: Proposition 1: Shall Lago introduce mid-range product for the Europe market?

58

3 Decision Making Under Uncertainty—Preference Curve, Sequential …

Table 3.6 Payoff table for all outcomes (based on contribution) Payoffs for all outcome events New Design—Failure (20%) Low end product expansion for local market Best: 650 K × 1.4 x $1.5 = 1365 K Base: 650 K × 1.0x $1.5 = 975 K Bad: 650 K × 0.8 x $1.5 = 780 K Low end product for a new Asian market with existing sale channel Best: 850 K × 1.4 x $2.5—0.5 M = 2475 K Base: 850 K × 1.0 x $2.5—0.5 M = 1625 K Bad: 850 K × 0.8 x $2.5—0.5 M = 1200 K Low end product for a new Asian market with new sale channel (Up 35%) Best: 850 K × 1.4 × 1.35 x $2.5—0.5 M – 0.5 M = 3016 K Base: 850 K x $2.5 × 1.35—0.5 M—0.5 M = 1869 K Bad: 850 K × 0.8 × 1.35 x $2.5—0.5 M—0.5 M = 1295 K Low end product for a new Asian market with new sale channel (0 effect) Best: 850 K × 1.4 x $2.5—0.5 M—0.5 M = 1975 K Base: 850 K x $2.5—0.5 M—0.5 M = 1125 K Bad: 850 K × 0.8 x $2.5—0.5 M—0.5 M = 700 K New Design—Success (80%) Mid-range product for a new Europe market with existing sale channel Best: 650 K × 1.4 x $6—1.2 M—0.5 M = 3760 K Base: 650 K × 1.0 x $6—1.2 M—0.5 M = 2200 K Bad: 650 K × 0.8 x $6—1.2 M—0.5 M = 1160 K Mid-range product for a new Europe market with new sale channel (Up 35%) Best: 650 K × 1.4 × 135% x $6—1.2 M—0.5 M – 1 M = 4671 K Base: 650 K × 1.0 × 135% x $6—1.2 M—0.5 M – 1 M = 2565 K Bad: 650 K × 0.8 × 135% x $6—1.2 M—0.5 M- 1 M = 1512 K Mid-range product for a new Europe market with new sale channel (0 effect) Best: 650 K × 1.4 x $6—1.2 M—0.5 M – 1 M = 2760 K Base: 650 K x $6—1.2 M—0.5 M – 1 M = 1200 K Bad: 650 K × 0.8 x $6—1.2 M—0.5 M- 1 M = 420 K

Proposition 2: Shall Lago expand low end products in a new Asian country or in the existing local market, if new design fails to materialize?

3.5 Sequential Analysis

59 Best (0.2) Growth effect (0.7)

Europe market

2155.5K Add new sale channel

New design successful (0.8)

Best (0.2)

Zero effect (0.3)

Existing sale channel

b

i

2096K

x

j

New design unsuccessful (0.2)

a

(From prop. 1 to prop.2)

Expand low end products

f

d

1624.4K Introduce mid-r ange products

h

2155.5K

c

2760K

Base (0.4) 1200K

420K 3760K Base (0.4) 2200K Bad (0.4) 1160K

Bad (0.4) Best (0.2)

-500K 3016K Base (0.4) 1869K Bad (0.4) 1295K Best (0.2)

Growth effect (0.7)

Add new 1645.7K Asian 1645.7K sale channel market

k

g

e

Best (0.2)

Zero effect (0.3)

Local market

4671K

Base (0.4) 2565K Bad (0.4) 1512K

Existing sale channel

l

1625K

x

m 1033.5K

x

n

1975K

Base (0.4) 1125K Bad (0.4) Best (0.2)

700K

2475K

Base (0.4) 1625K Bad (0.4) 1200K Best (0.3)

1365K 975K Bad (0.3) 780K Base (0.4)

Fig. 3.7 Decision Diagram (Sequential constraint)

3.5.3.2

Rollback Method

Let us address these questions in Table 3.7. Shall we introduce mid-range product than expand low end product in the local market. If new design fails to deliver midrange market, we will consider Asian market or local market market to be selected. In both cases, we need to evaluate using existing channel or adding new sale channel as well.

3.5.3.3

Strategy Priority

Upon the final evaluation review, we can conclude that the strategy priority should be (b) > ((e) > (n). Expansion in the existing local market should be the last resort. Nevertheless, Lago needs to reconsider the feasibility for building a product portfolio for a new mid-range market in which the firm has no experience in the past. Of course, business potential will be a major consideration which should be examined beyond one year of assessment.

60

3 Decision Making Under Uncertainty—Preference Curve, Sequential …

Table 3.7 Expected value evaluation Computation Proposition 1 Activity node f:

(4671Kx0.2+2565Kx0.4+1512Kx0.4)× 0.7+(2760Kx0.2+1200Kx0.4+420Kx0.4)×0.3 = 2155.5 K

Activity node j:

(3760Kx0.2+2200Kx0.4+1160Kx0.4)= 2096 K

Decision d:

Node f>j, Node f selected

Activity n

(1365Kx0.3+975 K×0.4+780 K×0.3) = 1033.5 K

Decision a

B>N, B is selected (1624.4 K vs 1033.5 K)

Proposition 2 Decision c

Node e>n, Node e selected (1645.7 K vs 1033.5 K)

3.2 Focus Scenario planning Scenario planning is a holistic method for corporations to deal with forecasts embodying a wide range of issues and high uncertainty in the context of study. Strategic planning has often come with usual human errors—overconfidence or tunnel vision. Big organizations such as Royal Dutch/Shell, IBM or many government bureaus employed scenario planning to explore futures under a few divergent key trends and uncertainty factors. Scenario planning allows more imaginations and considerations to be put in the planning scenes with changes in trends and key factors which have different degrees of uncertainty. For example, trade regulations, economic structure of a market, demographics, social trends are quite certain factors in a global/regional market analysis. However, how government policies, political stability or changing customer habits affecting the market are the issues of planning. Scenario planning differs from contingency plan which attempts to ask “what if” about the impact one key factor at a time on the plan. It is also not aimed to unfold everything but attempts to circumscribe some issues which are of critical to the planning. Therefore, scenario plans usually develop three cases: good scenario, base scenario, and poor scenario. Each case attempts to explore “what happen” to the plan if a few key uncertainty factors have changed. In so doing, it enables the management to set fallback plans for these situations. How to work on scenario planning, Professor Paul Schoemaker has the hints to follow: 1. 2. 3. 4. 5.

Define the scope Identify the major stakeholders Identify basic trends Identify key uncertainty factors Construct initial scenario themes

3.6 Multiple Criteria Assessment

61

6. Check for consistency and plausibility 7. Develop learning scenarios (by changing weights or attention in the trends and uncertainty factors) 8. Identify research needs (if required for a deeper understanding) 9. Develop quantitative methods 10. Evolve towards decision scenarios (after repeating of testing the impact of various learning scenarios on strategies) For those who are interested in his scenario development model, please refer to his article—Scenario planning: a tool for strategic thinking. Source Schoemaker, P. J. (1995). Scenario planning: A tool for strategic thinking. Sloan Management Review, 36(2), 25–50.

3.6 Multiple Criteria Assessment The above example has given a very clear priority in the evaluation; i.e. business performance (contribution margin). It has also pointed out that risk factor is an important assessment attribute. In the real business world, we may need to assess simultaneously a group of assessment criteria. For example, we may need to deal with business performance, risk, new market potential, new technology in this new strategic direction. It will be a headache in such a situation. No panic. There is also a way to resolve it. This is my last discussion topic in this chapter—multiple criteria assessment. The overall principle for the multiple criteria assessment is the same dominance concept that if all options are at least as preferred as the other on all attributes but one attribute of option A is more preferred than that from option B, A dominates B. There are two approaches for the multiple criteria assessment: satisficing procedure method and trade-off procedure. Let’s see how we deal with this situation.

3.6.1 Satisficing Procedure This method requires that all criteria selected for assessment has to define a threshold level or a minimum satisfactory level to be achieved. For example, Lago management establishes threshold levels for assessment attribute: Minimum expected contribution level at $1 million: more than 0.8 probability on contribution at or more than $1 million; more than 0.2 probability on contribution more than $3 million; a new market; and a new product. What would be the result under this assessment? For explanation, I have relaxed the sequential assumption for the three options and

62

3 Decision Making Under Uncertainty—Preference Curve, Sequential …

Table 3.8 Summary of multiple criteria assessment Europe market

Asian market

Local market

Exp. Contr.. Level ($1 M)

$1.62 M

$1.65 M

$1.04 M

≥0.80 prob. on contr. >$1 M

Yes

Yes

No

≥0.2 prob. on contr. >$3 M

Yes

No

No

Is market diversified?

Yes

Yes

No

Is product diversified?

Yes

No

No

consider all three options simultaneously. Summary of multiple criteria assessment (see Table 3.8) shows the evaluation result based on satisficing procedure method. Table 3.8 shows the evaluation of all three proposed options against each evaluation attribute. As noted, only option for the Europe market has all attributes met the given threshold levels. This example demonstrated how satisficing procedure is applied for evaluation of multiple attributes. The method is simple to use and easy to comprehend. However, the satisficing level for each attribute so defined is subject to the perceived priority of the decision maker.

3.6.2 Tradeoff Procedure Satisficing procedure requires all thresholds for their respective attributes to be met. However, it does not address some situation that evaluation performance of a single or a few attributes are high enough to offset the impact of attributes with low thresholds. Tradeoff procedure can be applied to bridge a gap by converting various options (or strategies) into similar set of bases for comparison. The procedure is devised to find an alternative option that can be equivalent to the original set of option but only differs in the scale level of one attribute. Let me illustrate this procedure by using Lago Furniture again. Example IV—Tradeoff The management of Lago Furniture now boils down to two strategies—(a) to go for a Europe market, or (b) maintain in the low end market. The first option would allow Lago to have more balanced market penetration, open a wider market with a higher potential profit in future, and diversify market risk. The tradeoff is to forgo immediate return. The second option allows Lago to continue a higher ROI for shareholders. Evaluation attributes for each option are set out below: (a) Mid-range products (base scenario: 0.6):

Expected contribution over the defined period: $3 million No. of new products introduced 3 No. of sale channels 3 (bad scenario (0.4) has reduced expected contribution 60%, other attributes remain unchanged)

3.6 Multiple Criteria Assessment

63

(b) Low-range product (base scenario: 0.7):

Expected contribution over the defined period: $4 million No. of new product introduced 1 No. of sale channels 1 (bad scenario (0.3) has reduced expected contribution 80%, other attributes remain unchanged) There are four steps for the tradeoff procedure: 1. Select a survival attribute, e.g. contribution evaluation unit. 2. Select a base level for the remaining attributes. 3. Devise alternatives that are equivalent to the existing set but with changes to the base level. 4. Compare the surviving attributes among alternatives. 1. Surviving Attributes: Obviously, the surviving attribute for Lago should be expected contribution because this is one of the most important attributes for the firm’s success. It means that we need to convert the other attributes to the same evaluation unit—contribution amount. 2. Base Level: To reduce all attributes to the similar base level, we need to consider how much the management would like to take the compensations if no. of products introduced and sale channels are same as the low end products. 3. Devise Alternative: In the case, Option a1 (the base scenario) will be: Expected contribution $3 million + ? + ?; no. of mid-range product market is 1; no. of sale channels is 1. Lago management needs to ask themselves how much compensation they can reduce no. of mid-range products and also reduce sale channels. For example, they can trade off by $1.5 million for the first and $1 million for the latter attribute. The alternative Option a_alt will be: Option a1(base): Contribution amount: 3 million; new products=3 ; no. of sale channels =3. Option a1_alt: Contribution amount: 5.5 million; new product =1; no. of sale channels =1

The contribution amount for the bad scenario will be: Option a2 (bad): Contribution amount: 1.8 million; new product=3 ; no. of sale channels =3. Option a2_alt Contribution amount: 4.3 million; new product =1; no. of sale channels =1

4. Compare the Surviving Attribute: Since the options of all attributes except the surviving attribute have been aligned in the same base level (1 new products, 1 sale channels). The evaluative comparison can be conducted with the decision diagram (Fig. 3.8). By aligning all attributes (except the surviving attribute) to two options, we are able to compare these two options (i.e. products and sale channels are the same).

64

3 Decision Making Under Uncertainty—Preference Curve, Sequential …

a1_alt. Base 0.6

Option A

Contr. Amt.

Base level Mkt. Tech.

5.5M

0

no

4.3M

0

no

4.0M

0

no

3.2M

0

no

0.4

a.2_alt Bad b1.

Base 0.7

Option B

0.3

b2.

Bad

Fig. 3.8 Decision diagram—allying all attributes

Option A_alt: 5.5M x 0.6 + 4.3M x 0.4 = 5.02M Option B: 4M x 0.7 + 3.2M x 0.3 = 3.76M

Option A_alt is equivalent to option A and its expected value is higher than option B, the option for the min-range product market should be selected. The above illustration has shown how a multiple criteria assessment can be compared by selecting a surviving attribute, transforming the values of other attributes to the surviving scale value, and aligning all alternatives under the same base level. Still, it requires subjective assessment in estimating equivalent value to replace the attributes (other than surviving attribute) to the scale value as the surviving attribute. As the only surviving attribute in the evaluation, it must be the most fundamental factor in the assessment.

3.7 Conclusion This chapter has gone through more complicated topics of decision making under uncertainty. In an emerging digital economy where many new business models are inventing and new business rules are yet to be finalized, firms are facing business opportunities but also bear high business uncertainty. I have discussed in the chapter 2 and 3 a few decision models which are highly regarded in the business practices without too difficult mathematical techniques. Decision making is a cognitive exercise. It employs decision model to approximate the real decision problems. However, models need parameters to operate which are based on a set of behavioral assumptions such as subjective probabilistic calculations, behavioral consistence, and perceptive continuity. However, we are quite often confined by our bounded rationality. Therefore, rational choice does not guarantee the best outcome out of the choices. Circumstantial changes emerge outside prediction, and perceptive bias prevents decision makers from making an optimal choice. Decision making requires examination from different perspectives. It often goes beyond

Reference

65

rational approach that solicits a sense making method (gut feeling) combined with a heuristic view. Decision making model is a technique and a thinking approach. More direct experiences and intuitive insights gained from business practices can help build up competence and filter bias judgment which may undermine decision quality in making complicated decision. Takeaway Tips • Expected value calculation has taken an assumption that risk is neutral, but in practice individual decision makers have a preference curve. The curve tends to reflect risk preference of the owner how much he is willing take less compensation in order to obtain certainty amount. Preference curve takes the shape of riskaverse in a concave form while risk-taking orientation in a convex curve. This behavioral orientation tends to have less impact in group decision making when peoples’ different risk orientations may nullify the behavioral consequences in the group decision making. Risk neutrality assumption remains valid in the decision making. • In a more meticulous assessment, mixed method of assessment takes into considerations of many factors including expected value, spreads, probability, risk dispersion..etc. which provides a more comprehensive assessment on event outcome for selection. • Sequential analysis deals with decision that will be considered at every stage. Rollback procedure is the technique that review starts from the end to ensure no future decisions to be addressed later. As we consider decision at every stage, only the good outcomes are kept and the bad outcomes are discarded sequentially at every stage until the initial decisions. • In the real world, it often comes up with a multiple criteria assessment in a decision making process. It is unusual that the choice is a strict dominance—meaning that the choice is preferred at all attribute assessment. As such, we may need to apply satisficing procedure or tradeoff procedure. The former method requires that all criteria selected for assessment have a threshold level or a minimum satisfactory level to be achieved. The latter adopts a practical method to converting all options (or strategies) into a similar set of bases for comparison. This requires to find out a surviving attribute as the base unit for all attributes in the conversion process.

Reference Schoemaker, P. J. (1995). Scenario planning: A tool for strategic thinking. Sloan Management Review, 36(2), 25–50.

Chapter 4

Valuing Business—Concepts and Techniques

4.1 Introduction Business valuation1 has taken an important role in the modern financial development. It is employed for internal use in strategic value analysis, Credit assessors appraise corporate lending, security analyst value stocks in capital markets, and investment analyst estimates price in M&A deals, to quote a few. It has the sole purpose to identify the true and fair value of the firm, in part (business units) or in whole (entire organization). However, it is difficult to assess the fair value of a business, partly because of cognitive bias in interpreting historical financial performance, partly due to selective bias in extrapolating future performance based on subjective experiences. It has an underlying weakness in assessing future-oriented business value given the unpredictable business worlds. Technically, business valuation needs to address two time-frames: (a) past situations of the focal firm that provides business parameters for valuation; (b) future activities that influence foreseeable business performance and growth potential. In fact, information plays a pivotal role in the overall valuation process. Past business performance can be verified by published financial statements and the ability to generate “surplus profits2 ” can be ascertained. However, future business performance must be rationally assessed from its market position and resource capabilities. This cognitive assessment is grounded on assumptions but inevitably blended with value bias. Empirical research has proved that accuracy of business valuation is particularly low in new e-businesses in which business performance is yet to be proved and verifiable information is very inadequate. In the absence of internal information, external oriented multiple comparable analysis is resorted to in the valuation exercise. This approach makes use of proxy measures to compare and assess the “value” of the focal firm based on peer group benchmarks. Due to this reason, it requires stricter 1

A lot of concepts and techniques were adopted from Koller, Goedhart, and Wessels’s classic book in Valuation: Measuring and Managing the value of Companies (2005). 2 The surplus profit concept will be fully discussed in the Abnormal earnings section. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 W. Li, Strategic Management Accounting in a Network Economy, Management for Professionals, https://doi.org/10.1007/978-981-99-5253-3_4

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4 Valuing Business—Concepts and Techniques

scrutiny and severe assessments from different dimensions in order to conclude a persuasive business value. In the forthcoming sections, I will go through all basic concepts, techniques and detailed procedures in business valuation.

4.2 General Valuation Approaches Valuation is assessed in many methods. There is no agreement on definite rules. It is contrary to the accounting discipline which has standards and rules. Business valuers must approximate “a fair value” of the subject matter. The most importance of valuation is legitimate rationale for the valuation basis and the applicability of valuation techniques to ascertain business value. It is not uncommon to find out an extreme situation where inconclusive valuation has been noted. The whole valuation exercise can be taken as a reference value. Valuation in all circumstances mandates valid numbers, assumptions and bases in the exercise which should be verifiable and comparable. To a less extent, it ought to be believable and non-refutable. Quantitative method is preferred to qualitative method. Financial numbers based on facts, basis, and assumptions are prone to be verifiable, measurable, comparable, and testable. Qualitative method is bound to be subjective biased. However, it has a stronger descriptive and interpretative ability in valuing business. Therefore, it supplements the mechanistic ruled-based methodology. In both methods, assessment results should be consistent, logical, and believable. In the operational dimension, valuation can be divided into four approaches. They are income-based approach, market-based approach, cost-based approach, optionbased approach. The following provides a brief summary. Income Approach Income approach is based on the premise that value of the assets comes from its intrinsic value generated from its surplus cash flows. Valuation begins from reviewing the current and past financial statements. Further assumptions, bases, and predictions are made based on strategic initiatives and directions the management board has planned to pursue. For the income approach, business forecast and estimates are essential documents and blueprints for assessment of business value. More technical details of the income approach are further delved into two divergent concepts, namely: Discounted cash flow (DCF): This method estimates future cash flow stream of the business and discount the nominal cash over the forecast period to the present value by an appropriate discount rate. Abnormal-earnings basis: Abnormal earnings approach argues that firm earns value from its “surplus profits” that is net income after deducting cost of capital employed to support investment activities. This approach adopts “economic profit” as a practical framework for computation. Akin to DCF, all future economic profit is discounted to the present value.

4.2 General Valuation Approaches

69

These two practicing concepts will be further explored in subsequent sections. Income approach employs current financial information as base year and extrapolates forecast income supplemented by specific strategic inputs. Though analytical as it looks, income approach unavoidably involves subjective assumptions derived from past experiences, market perceptions, and management consensus. The result may require further robust tests (including scenario and sensitivity tests) to unfold its limitations. Market Approach Market approach evaluates business based on market transactions of comparable firms which have similar market conditions and operational scale. This approach is ‘objective’ as per se because it has taken reference from the market reality and identify key market drivers as the basis for valuation assessment. It is instrumental when no adequate internal information is accessible to assist valuation. The approach is often applied for fund raising purposes (IPO or M&A). However, it has a drawback that there is a strong subjective bias in choosing “peer group” for comparable analysis, and there is often weak evidence to link views to facts. Albeit the above, it is one of the popular approaches in conducting valuation assessment. I will give more deliberations on this approach. Cost Approach Cost method is based on actual cost or net replacement cost of the assets being assessed. Asset value can be found from the balance sheet and the value of the basis links directly to cost and economic value in terms of opportunity cost forgone to deploy these asset resources; e.g. how many times of the value equivalent to the cost. Cost method is simple and straight forward. Financial numbers are gathered from balance sheet which are measurable and verifiable. However, all financial numbers are based on past performance which may not the representations of future performance. However, it can serve as a baseline value (i.e. total net assets based on replacement cost) of the business or piece(s) of asset. Option Approach Option valuation approach takes into accounts the flexibility of the investment opportunity that can be deferred until more market information is available. Simply speaking, it is derived from option theory that option holder can exercise call option (predetermined price of right to buy) when the value of the asset is higher than the pre-determined price, or he can give up the exercise of the right to buy (deferral of investment) at expiry date. The value of the asset is therefore zero. The same token is applicable for put option (fixed price to sell) but in a reverse direction. The value of the asset is equivalent to the value of the option and its lowest value is zero. The method is theoretically complicated and will rarely be employed for ordinary businesses. However, it is more applicable for valuation of financial derivative especially for financial institutions. As more advanced mathematical skills and statistical techniques and interpretations are required for option theory, the option approach will not be covered in this chapter.

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4 Valuing Business—Concepts and Techniques

In sum, the above four basic valuation approaches are employed for various valuation purposes. Cost method suits valuation purposes for individual assets or valuation requires high verifiability. Option method is more apt for firms (e.g. financial institutions) with very unpredictable investment opportunities. Income and market approaches are more compatible for ordinary courses of business operations. I will make fuller discussions on the first three approaches. The choice of valuation techniques is dependent on two business situations: (a) predictability of business outcome; (b) accessibility of information internally and/or externally. The combined effect determines the degree of verification of the valuation. Figure 4.1 presents two dimensions pertinent to predictability and external orientation which impacts the degree of verification on each approach. As noted in the diagram, cost approach is predictable (due to its rule-based principle) and internally oriented. It has high degree of verification and can be applicable for situations that require high credibility (e.g. by liquidation law). Option approach has the lowest predictability and is externally oriented because the value is largely affected by external conditions computed by statistical inference. Verification is built from a highly sophisticated and robust models. It is usually applicable for financial derivatives issued by financial houses. Income approach can be mildly predictable as information is largely from internal source estimates where bases and assumptions can be traceable. Verification can be possible based on internal documents. Market approach has lower predictability and verification compared to income approach as information is based on external market which does not necessarily have strict associations with the peer groups. However, it will be a set of good proxy measures when internal information is inadequate. From a practical viewpoint, these methods can be employed altogether to form a set of business values for final decision. Income Approach

Hi Predictability

Fig. 4.1 Predictability vs external orientation

De gre eo fv eri fic ati on

Lo Lo

External oriented

Hi

4.3 Discounted Cash Flow (DCF)

71

4.3 Discounted Cash Flow (DCF) DCF is a fundamental concept for valuing business. It is a financial technique that applies net present value concept in a cash flow stream over a longer period. We learn that money has a time value. For an instance, we will get $105 ($100 × (1 + 5%)) a year later if we place $100 into a bank deposit at an interest rate of 5% p.a. If we continue to keep the money rolling over for 2 years, we will obtain $110.25 (i.e. $100 × (1 + 5%) (1 + 5%)). Therefore, money value of $100 at year 1 and year 2 will be $105, $110.25 accordingly. This is the concept of time value of money. In the above example, we can develop an equation as follows: Money value at Year 1 : FV = PV0 (1 + r) = $100 × (1 + 5%) = $105 Money value at Year 2 : FV = PV0 (1 + r)2 = $100 × (1 + 5%)2 = $110.25 where PV = present value, FV = future value, r = discount rate We can now generalize the equation into the following: FVt = PV0 (1 + r)t equation for the future value, t = time period PV0 = equation for the present value, t = time period where t ranges from period 0 to period t Present value equation also depicts the discount cash flow technique of the future cash flow, in which future series of monies can be discounted to the present value. DCF rectifies the conventional method in computing multiple period computation that ignores the time value of money. For any cash receipts or outflow over a year, DCF provides a precise method to discount future cash to the present value. This is an appropriate method for computing a longer term investment.

4.3.1 Discount Rate (R) I mentioned in the above example that bank interest rate is the selected discount rate. What is discount rate in a real sense? How do we determine discount rate (r)? What is its role in the equation as it determines the ultimate present value of the discounted cash flow. Let’s investigate this discount rate concept. Discount rate is a rate employed to align nominal values to the same time dimension so that all cash flows at different periods have a uniform period, i.e. present time (t = 0). Discount rate is interpreted from different situations. For example, interest rate is the discount rate when calculating bank deposits. For investment evaluation, firms will employ cost of capital or required rate of return for the discount rate.

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4 Valuing Business—Concepts and Techniques

In the latter case, discount rate can be interpreted as how much surplus cash flow can the investment generate, after deducting opportunity cost (e.g. cost of capital or required rate of return) for pursuing this investment opportunity. Discount rate helps figure out the “surplus value”. Therefore, it is important to find an appropriate discount rate to reflect the opportunity cost of the firm. Furthermore, discount rate also reflects risk taking factors. The higher the risk, the higher the discount rate is to be employed to compensate for the likelihood of investment loss. In contrast, lower risk in investment can apply a lower discount rate, meaning that discounted surplus cash flow will be higher. Discount rate, being the denominator with (1 + r), embraces the following characteristics: (a) the higher the discount rate (r), the lower the present value of the cash flow at a given time t will be, and vice versa, (b) the longer the time t, the smaller the value of the discounted cash flow will be. Discount rate sums up a series of cash flow over a period into a single present value time. Let’s take another example. What is the present value (PV) of a constant cash flow of $1000 (i.e. FV) for a period of 4 years, using a discount rate of 10%.? The computation of the present value for the above series of cash flow would be: PV0 = FVt /(1 + r)t = 1000/(1 + 10%)1 + 1000/(1 + 10%)2 + 1000/(1 + 10%)3 +1000/(1 + 10%)4 = 909.1 + 826.4 + 751.3 + 683.0 = $3169.8 How is about a constant cash flow over a period of time? This specific stream of cash flow (constant stream) is the concept of annuity. In fact, we can refer the present value from a discount factor table. We observe that the present value of $1000 decreases in value as time goes. Total nominal value of $4000 becomes $3169.8 at the present value. Indeed, there are two basic interpretations in the discount rate application. (I) Cost of capital The rate should equate the cost of capital of the firm. Cost of capital can be the cost of borrowing for the firm or the weighted cost of capital3 that reflects the capital structure of the firm (proportion of the respective equity and debt in the total assets). (II) Required rate of return The rate should reflect the minimum return the firm wants the investment to be achieved. The rate may also reflect the risk level being calculated in the investment. The return rate can be the return of investment (ROI), return on equity (ROE), or CAPM, a more sophisticated capital asset pricing model CAPM exhibits more explicit assumptions on risk level of investment. Comparing these two interpretations, the first approach emphasizes capital structure and opportunity cost of the target investment. The second one focuses on the 3

WACC takes into accounts of the capital structure of the firm which is the equity and debt ratio of the firm. WACC is computed as follows: cost of equity × equity (MV)/(total equity + interestbearing debts (MV)) + Cost of debts (after tax shield) × debt (MV)/(total equity + interest-bearing debts (MV).

4.4 Free Cash Flow (FCF)

73

‘reasonable’ rate of return given the risk level of the investment project. A firm has its own risk-orientation (i.e. risk-averse or risk-taking). Project also has inherent project risk. Though both interpretations are acceptable in valuation, I opine to consider that the second approach is more appropriate for the firm to evaluate an unusual risky investment prospect (e.g. new internet business model).

4.4 Free Cash Flow (FCF) FCF approach is a popular technique for business valuation. FCF is prevalent due to the readily available information extracted from corporate financial forecast. Business analysts can collect information from various business sources. In particular, financial information has common bases and standards to enhance comparability among peer group companies when cross checking the valuation. In this FCF method, two salient points are noted. First, what are the key FCF drivers? What are the relationship of FCF drivers to FCF. In fact, a closer scrutiny of key FCF drivers helps develop forecast FCF. Second, how FCF numbers are extracted from financial statements. It is the technical detail that will be discussed in the transformation process. FCF Drivers FCF is the basis for business valuation. Forecast financial numbers have to be converted into a series of free cash flow over the forecast period and all FCFs in the respective periods are discounted to the present value. Prior to the transformation process, it is advisable at this juncture to check the basis and assumptions of the forecast. As discussed in Chapter 5, three competition drivers have been discussed, namely value drivers (e.g. value curve, markets), cost drivers (e.g. operations), and configuration drivers (e.g. capacity). These competition drivers increase market power when a firm anchors proper market position from its competitive advantages orchestrated by these drivers. The market impact will be reflected in revenue, profitability (i.e. net operating profit after tax (NOPAT), corporate growth, and return on invested capital (ROIC). In fact, growth, ROIC, and investment rate (IR) are three key FCF drivers of the firm to generate corporate value. Figure 4.2 depicts that the conceptual process of competition drivers turn into key FCF drivers which create value through proper discounting a set of FCFs into enterprise value.

Fig. 4.2 Key FCF drivers

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4 Valuing Business—Concepts and Techniques

To turn the above concept into an operational technique, let’s elucidate how growth, ROIC, and investment can translate into FCF. In fact, the inextricable relationships of the these FCF drivers can be imbedded in an equation to make a short cut method for FCF calculation. The following mathematical deduction unveils their relationships. We know that internal growth is generated from the ability to make profit. For simplicity reason, let’s assume depreciation is negligible compared to NOPAT. Therefore, FCF = NOPAT−Invested new capital (residual income reinvested) The logic of the equation is obvious that FCF is arrived from NOPAT after deducting invested new capital during the period. Of course, it is expected the invested new capital would generate return, which is ROIC. Therefore, ROIC can be explained as follows: ROIC =

NOPAT Invested new capital

(4.1)

Let’s look from the other angle. If we invert the right hand side equation, it will become the reinvestment rate. Reinvestment rate =

Invested new capital NOPAT

(4.2)

The new equation represents a portion of NOPAT that will be spent on investing new capital investment, that is the reinvestment rate (IR). Now we turn to the growth concept. Growth is represented by reinvestment rate and expected ROIC on the new investment. Therefore, growth (g) can be expressed as g = IR × ROIC;

(4.3)

or IR =

g ROIC

(4.4)

Since invested new capital = IR × NOPAT, see (Eq. 4.2), we can now convert FCF into the following equation. FCF = NOPAT − NOPAT × IR = NOPAT × (1−IR) = NOPAT × (1 −

g ) ROIC

The new FCF equation shows the relationship of growth, ROIC, and reinvestment g ). This new equation proves that in principle FCF can be rate from NOPAT (i.e. ROIC ascertained from accounting numbers directly obtained from financial statements.

4.4 Free Cash Flow (FCF)

75

The new equation has the following implications: (i) faster growth requires the firm to be either very financial efficient (higher ROIC) or higher investment rate, or both; (ii) High growth must accompany high ROIC. A high growth with low ROIC will dissipate FCF; (iii) NOPAT can approximate FCF, given the knowledge of growth rate and ROIC. These FCF drivers are imperative in delivering FCF, thereby creating enterprise value. In fact, we can use the above equation as a short-cut method in FCF calculation. Example I—FCF ABC Co. has reported a NOPAT of $14 m in year t. The company anticipates a growth rate of 6% and ROIC at 12%, what will be the free cash flow for the next year (t + 1)? We can plug the parameters into the above FCF equation, showing the result below. Answer : FCF = 14 m × (1−6%/12%) = $7M

4.4.1 Transformation Process Transformation process is the critical step to covert all strategic assumptions into forecast parameter. This strategic transformation will ultimately bring to the change in shareholder value. Transformation process can be divided into four components: • convert strategic assumptions into forecast parameters and form the basis for forecast; • determine invested capital; • discount the FCFs into the present point of value; • Terminal value I will discuss the first three steps in this section and put terminal value in the subsequent section. In regard to transformation, two approaches can be employed. For strategic formulation involving brand new corporate strategy, the firm may trigger major changes in future revenue model, growth and cost structure. Growth and ROIC may not follow a consistent operation pattern over the forecast period. Implementation of such new corporate strategies will exhibit different impact on FCFs over different time periods. Therefore, financial forecast must be estimated on a year on year basis. Basis and assumptions will fluctuate from year to year in the execution process. This approach is appealing where the forecast is underpinned by internal information. A second approach assumes consistent corporate strategies to steer business operations. FCFs will theoretically follow a consistent manner. Growth and ROIC follow a consistent pattern and cost structure should remain in a consistent relationship with sales. As such, forecast FCFs can be easier to be arrived by following the current

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4 Valuing Business—Concepts and Techniques

key financial ratios. This approach is applicable especially for external financial analysts who have no detailed information to support future business but employ this method as a short-cut approach. This is a valid approach when considering a consistent business strategy ahead. I will illustrate by an example for this simple version of forecast. In such, FCFs assume consistent corporate strategies being adopted to support a stable business operation. Example II—Consistent Forecast Parameters DB Ltd. develops a 7-year financial forecast based on the actual financial performance. It predicts a strong market to support an annual growth rate of 12% over the forecast period. In a stable corporate strategy and market expectations, there will be a stable gross margin % and operating expense structure (same opex ratios to sales), and a consistent depreciation at $150 million per year, Table 4.1 shows a period of 7-year financial forecast. Forecast Parameters: In the first place, we review the actual operating performance and capital investment (see Table 4.1), particularly key FCF drivers. As an underlining assumption, cost structure is stable for consistent business strategies. As such, income statement reflecting stable operating expense to sales pattern can apply for the forecast expenses. However, revenue growth requires clear justification. From the forecast viewpoint, the management is required to justify why 12% growth rate is expected over the period. Forecast income statement is then prepared based on the above forecast parameters. Invested Capital: Invested capital includes change in net working capital, net capital expenditure, invest in other assets and intangibles. It is assumed that the change in net working Table 4.1 NOPAT and invested capital Revenue COGS Gross Margin Selling expenses Operating expenses Depreciation NOPBT Tax (at 25%) NOPAT

Actual 4500.0 2025.0 2475.0 590.0 640.0 150.0 1095.0 273.8 821.3

FY1 5040.0 2268.0 2772.0 660.7 716.7 150.0 1244.6 311.1 933.4

Change in net WC Net capital expenditure Invest in other assets Invest in intangibles Invested capital

45.0 250.0 30.0 50.0 375.0

30.0 287.5 30.0 50.0 397.5

(In M illion)

Forecast Income Statement FY2 FY3 FY4 5644.8 6322.2 7080.8 2540.2 2845.0 3186.4 3104.6 3477.2 3894.5 740.0 828.8 928.3 802.7 899.0 1006.9 150.0 150.0 150.0 1411.9 1599.3 1809.3 353.0 399.8 452.3 1058.9 1199.5 1357.0 Invested Capital 33.6 37.6 42.1 330.6 380.2 437.3 30.0 30.0 30.0 50.0 50.0 50.0 444.2 497.9 559.4

FY5 7930.5 3568.7 4361.8 1039.7 1127.7 150.0 2044.4 511.1 1533.3

FY6 8882.2 3997.0 4885.2 1164.5 1263.0 150.0 2307.7 576.9 1730.8

FY7 9948.1 4476.6 5471.4 1304.2 1414.6 150.0 2602.6 650.7 1952.0

47.2 502.8 30.0 50.0 630.0

52.9 578.3 30.0 50.0 711.1

59.2 665.0 30.0 50.0 804.2

4.4 Free Cash Flow (FCF)

77

capital is 20 days of monthly sales. Net capital expenditure increases by 15% annually. Other items assume constant throughout the period. As a matter of fact, depreciation is a non-cash item. Therefore, it adds back to cash inflow. Free cash flow is arrived after deduction of cash outflow—invested capital. By now, forecast numbers are ready to be transformed into free cash flow. Discount the FCF: This is the process to convert all accounting numbers into Free cash flow. Table 4.2 provides a summary of financial numbers converted into FCF. The FCF forecast shows an increasing rate of positive cash flow over the 7-year forecast period. Furthermore, there is an underlining assumption that business operation is a going concern basis, meaning that it will continue after 7 years. Technically, we should divide future business value into (a), business value over the forecast period; and (b), business value after the forecast period. It pertains to the cumulative business value after the forecast period—terminal value. Let’s address the first business value of the forecast period by adopting a discount rate of 8%. In the Table 4.3, NPV computation. We see the table is in a vertical form. It has four columns. First column indicates period Y0 based year, and forecast years from Y1 to Y7. Second column (FCF) is the FCF at nominal value. Third column is the discount factor at a discount rate of 8%. Please note that discount factor reduces in value in more remote future periods. Finally, fourth column is the present value of the free cash flow at each period. The value of the business over the forecast period is $4,874.46 million—the accumulative value generated from free cash flow. Up to this Table 4.2 Free cash flow forecast (In $Million) NOPAT Add Depreciation Cash Inflow

Actual FY1 821.3 933.4 150.0 150.0 971.3 1,083.4

Invested capital Free cash flow

375.0 596.3

Table 4.3 NPV Computations

397.5 685.9

FY2 FY3 FY4 FY5 FY6 FY7 1,058.9 1,199.5 1,357.0 1,533.3 1,730.8 1,952.0 150.0 150.0 150.0 150.0 150.0 150.0 1,208.9 1,349.5 1,507.0 1,683.3 1,880.8 2,102.0 444.2 764.7

497.9 851.6

559.4 947.6

630.0 1053.3

711.1 1169.7

804.2 1297.8

Year (In $Million)

FCF

Disc.@8%

PV

Y0

0

1.0000

–

Y1

685.9

0.9259

635.09

Y2

764.7

0.8573

655.61

Y3

851.6

0.7938

676.03

Y4

947.6

0.7350

696.51

Y5

1053.3

0.6806

716.86

Y6

1169.7

0.6302

737.11

Y7

1297.8

0.5835

757.25

Total

4,874.46

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4 Valuing Business—Concepts and Techniques

point, we have arrived the business value of the firm over the forecast period. As a going concern business, we need to figure out the firm’s post forecast value. That is the terminal value we need to make further deliberations on this important topic.

4.5 Terminal Value Terminal value of a business is the value of the business for its remaining lifetime—perpetual forever. Therefore, terminal value can also be named perpetual (or continuous) value for the business after the forecast period. In fact, it is quite common that terminal value will be much greater than the forecast period. Therefore, terminal value cannot be ignored just because of its remoteness. However, it is cumbersome to forecast 50 years or longer future years as no one knows what happens after a more remote period. It is fair enough to assume that the firm will be in a stable state of condition. We can generalize two states of conditions: (I) the condition of zero growth, and (II) the condition of constant growth. Let’s discuss how terminal value is computed on these two states of condition. Condition of Zero-Growth It is assumed that the firm will generate the same FCF every year, which is equivalent to Gordan’s constant dividend model which has the following formula: Terminal valuet =

Constant FCFt+1 r

Terminal value t = Total value at time t. FCFt+1 = Cash flow at time t + 1, the period after the end of the forecast. r = Discount rate. Let’s continue Example II. It is given that the firm will generate a constant free cash flow of $70M after the forecast period at FY7. (a) What will be the terminal value and, (b) what will be the terminal value at present value, given that discount rate is 8% (a)(a)(a)(a)(a)(a) The terminal value after the forecast period: Terminal valuet=F7 = $70M/8% = $875M (b)(b)(b)(b)(b)(b) Terminal value at the present value: PV = 875M × 0.5835 = $510.6M This example has shown two steps in computing terminal value at the present value. The first step is to compute the terminal value after the forecast period time t, and the second step is to discount the terminal value to the present value time t 0 . Condition of Constant Growth

4.5 Terminal Value

79

It refers to the situation that the firm continues to increase in value at a constant rate after the forecast period. It requires strong evidence to support the assumption. The formula for this state of condition is written as follow: Terminal valuet =

FCFt(1+g) r −g

Terminal value t = Total value at time t. FCFt+1 = Cash flow at time t+1, the period after the end of the forecast r = Discount rate g = growth rate Let’s continue the above example 4.2. I assume the terminal value after the forecast period with a constant growth of 4.5%. (a)(a)(a)(a)(a)(a) The terminal value after the forecast period: Terminal valuet=F7 = $70M(1 + 4.5%)/(8% − 4.5%) = $2, 090M (b)(b)(b)(b)(b)(b) Terminal value at the present value: PV = 2090M × 0.5835 = $1219.5M Recall the prior section that free cash flow (FCF) can be replaced by NOPAT directly assuming that depreciation is relatively small. The formula is then rewritten as follows: FCF = NOPAT − NOPAT × IR = NOPAT × (1−IR) = NOPAT × (1 −

g ) ROIC

This is the short-cut method to retain the accounting profit concept (i.e. NOPAT) instead of converting into FCF when computing discounting cash flow. Accounting numbers can also be discounted to present value with some amendments. Let’s see how the equation for the present value and terminal value in terms of NOPAT. ( n ∑ NOPATt−1 1 − PV of NOPAT over forecast period = PV0 = (1 + r )t t=0 Terminal valuet (zero - growth) = Terminal valuet (constant growth) =

NOPATt+1 r

NOPATt × (1 + g) r −g

g ) ROIC

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4 Valuing Business—Concepts and Techniques

Let’s illustrate in a simple example on how to apply the above equations in DCF computation. Example III—Terminal Value with Growth MD Ltd has a stable market environment and business performance. Currently, it has a NOPAT of $12M. MD invested 60% of the NOPAT as new capital every year and expect a ROIC of 12% over the forecast period. Assuming that the above is the firm’s investment policy for the forthcoming 5 years and a discount rate of 8% is applied, (a) what will be the value of the business over the forecast period; (b) what will be the terminal value assuming zero-growth after the forecast period; (c) what will be the terminal value when a perpetual growth is assumed? The first thing to do is to compute growth rate (g). Growth rate g is equivalent to Investment rate x ROIC. Since investment rate is 0.6 and ROIC is 12%, g is equal g ), which is (1 − 7.2%/12%) = 0.4. 0.6 × 12% = 7.2%. Next, we find that (1 − ROIC Finally, we define NOPATt as (NOPAT × (1 + 0.4))t . For the forecast year FY1 to FY5, its NOPATt is given as follows: FY1:

NOPAT1 =

12M × (1 + 7.2%) = $12.86 M

FY2:

NOPAT2 =

12.86M × (1 + 7.2%) = $13.79M

FY3:

NOPAT3 =

13.79M × (1 + 7.2%) = $14.78M

FY4:

NOPAT4 =

14.78M × (1 + 7.2%) = $15.85M

FY5:

NOPAT5 =

15.85M × (1 + 7.2%) = $16.99M

Now, we can plug in all numbers in the PV equation. (a)

PV = 12.86M × 0.4/(1 + 8%) + 13.79M × 0.4/(1 + 8%)2 + 14.78M × 0.4/(1 + 8%)3

+15.85M × 0.4/(1 + 8%)4 + 16.99M × 0.4/(1 + 8%)5 = $58.68M (b) Terminal value (zero growth) = 16.99M /8% = $212.4M (c) Terminal value (constant growth) = 16.99 × (1 + 7.2%)/(8% − 7.2%) = $2276.7M As noted above, terminal value is higher than the PV of the forecast year. There will be tremendous value in the terminal value with growth potential beyond the valuation period. Practically speaking, terminal value with growth should continue for some time and slow down until zero growth as there is very rare for a perpetual growth in business reality. Therefore, a very huge terminal as noted in (c) should be reconsidered seriously. In short, there are also advantages by using accrued accounting profits concept as the basis for computing present value. First, accrued accounting profit can be used directly for computing cash flow. There is no need to establish another set of cash flow assumptions. Second, all free cash flow drivers (i.e. NOPAT, invested capital, and ROIC as discussed above) can be explicitly shown in the equation to facilitate interpretation. Third, it facilitates the interpretation of the concept of abnormal income-based approach. I am going to discuss this concept immediately.

4.6 Abnormal Income-Based Approach

81

4.6 Abnormal Income-Based Approach Abnormal income-based approach takes the view that a firm cannot create value if its net income is equal to its opportunity cost only. Value creation is hinged on excess income a firm can produce after deducting capital charge (i.e. cost of capital). This is the concept of economic profit. Putting it in other words, a firm’s value creation is judged on how much deviation of its net income from the normal rate of return. Economic value added (EVA) concept, which draws the world’s attention since 1990s, advocates the similar economic profit concept but adds technical rules that net income after tax should deduct capital charge on the base of invested capital at the beginning of the year. The charge rate is by rule determined by the weighted average of cost of capital (WACC).4 By adopting economic profit concept as the base for abnormal income approach, the equations for valuing business based on the abnormal income-based approach can be written as follows Enterprise value = Invested capital + PV of projected economic profit Invested capital = Long term assets + (current assets−current liabilities) Projected economic profit = NOPAT−(Invested capital × WACC) Please note that NOPATt in the economic profit equation is the current period while invested capital refers to the beginning of the period (t − 1). Invested capital is the long term asset combined with net current assets. Economic profit is equivalent to free cash flow that can be discounted directly to the present value. Advocates to economic profit argues that companies adopting different accounting methods (e.g. depreciation policy) differs little in the present value of projecting economic profit. It is because the difference will be reduced automatically by the components in the equation. For example, a higher depreciation charge reduces NOPAT, but it also reduces invested capital as the base for capital charges. Using economic profit as abnormal income base can elucidate the size, return on capital and cost of capital in a single equation. As more meaningful information can be found in the equation, it is therefore better than earning income approach (i.e. NOPAT). Let’s demonstrate in the Example IV how economic profit is employed in the valuation exercise. Example IV—Economic Profit ED Ltd. has a balance sheet of last year as follows:

4

See footnote 2.

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Long term asset

$450M

Equity

$400M

Current assets

$125M

Long term liabilities

$75M

Current liabilities

$100M

Equity + Liabilities

$575M

Total assets

$575M

ED expects a NOPAT of $57M in the coming year, which will grow at 6% p.a. until Year 5 and will settle down with the same amount after the forecast period. Assuming 50% of the NOPAT will be reinvested and the remaining sum will be distributed as dividends. What will be the business value of ED Ltd. assuming the firm’s WACC is 8% and working capital will remain the same throughout the forecast period. Table 4.4 presents how valuation is arrived by using economic profit as the base for abnormal income approach. Recall that NOPAT grows at 6% every year. Half of it will go to reinvestment and the remaining is distributed as dividends. Invested capital is long term assets + net working capital which is &475M ($450M + ($125M − $100M)). Net growth of invested capital of the coming year is invested capital from last year plus an incremental investment (50% of NOPAT) of the current year (i.e. Invested capital at Y2 = $475M + ($57M × 50%). Terminal value is a constant sum of economic profit after forecast period. With a discount rate of 8%, the terminal value becomes $299.88M ($23.99M/8%). Combining the initial invested capital of $475M at time 0, the value of ED Ltd. is $763.86M. Abnormal income-based approach makes a clearer representation on how the enterprise value of a firm is established. According to economics theory, long-term profit of a firm will diminish as intense competition among market players will drag down the firm’s abnormal profit to the Table 4.4 Valuation using economic profit approach Year (In $M)

Exp. Invested capital (t − 1)

Expected NOPAT

Charge cost @ 8%

Exp. Econ. Profit

PV factor @8%

PV of Econ. Profit

a

b

c

d = b × 8%

E=c−d

f

g=e×f

1

475.00

57.00

38.00

19.00

0.9259

17.59

2

503.50

60.42

40.28

20.14

0.8573

17.27

3

533.71

64.05

42.70

21.35

0.7938

16.95

4

565.73

67.89

45.26

22.63

0.7350

16.63

5

599.68

71.96

47.97

23.99

0.6806

16.33

299.88

0.6806

204.09

Terminal value** (t = 5) Invested Capital (t = 0) Total

475.00

321.31

214.21

406.98

763.86

4.6 Abnormal Income-Based Approach

83

normal profit (equal to opportunity cost) in the long run. From this angle, terminal value of economic profit should not be perpetual in the long run. In fact, both free cash flow approach and economic profit approaches are two common methodologies in conducting income-based valuation. FCF or economic profit are theoretically identical in making valuation computation. Mathematically, IC × (ROIC − WACC) FCF = IC + WACC − g WACC − g The left hand side of the equation represents free cash flow model while right hand side represents economic profit model. Both expressions of the equations can be proved identical mathematically.5 4.1 Focus Pre-money valuation, post-money valuation, and stock dilution Pre-money and post-money values in a start-up business are often a salient topic when founders of the firms and investors (e.g. angel investors or prospective investors) sit down to discuss the other round of fund raising. Pre-money valuation refers to the company value prior to new fundraising. Post-money valuation means pre-money valuation plus new monies invested. The equation is as simple as that: Post - money valuation = Pre - money valuation + new money injected Pre-money valuation can be a formal business valuation when the business has reached a certain milestone, or it is just a number in the air which comes with its early plan. Pre-money value has impact on the additional money that potential investors have to pay on their invested shareholding. For example, a pre-money valuation of $1M and a total 10,000 shares has a price per share of $100. A new fundraising of $0.25M means a new issue of 25,000 shares Post - money valuation = $1M + $0.25M = $1.25M Investors use pre-money valuation to determine the amount of equity they pay in exchange for new issues. However, the case is more complex in the next round finance In this round, pre-money valuation may be higher (called up round) or lower (called down round) than the prior post-money valuation. Up round premoney value implies that the new firm is going in the right direction with equal or higher firm value where new investors pay more price per share for the new issues. In contrast, a down round pre-money value in this round finance

5

Mathematical proof adopted from the Appendix B of Koller et al. (2005).

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4 Valuing Business—Concepts and Techniques

reflects the business is not going in the right track, resulting in a deteriorating firm value. The firm needs to issue more new shares (with a lower PPS) to match the required funds. The shareholding of existing shareholders (including founders and previous investors) is being diluted as a result Let me illustrate this dilution issue in two scenarios using the same example as above. Let me assume the pre-money value for this round finance as $1.3M and the firm issues 12,500 shares for founders and early investors. This is an up round scenario as pre-money value for this round is higher than last postmoney value ($1.3M vs $1.25M) where PPS is $104 per share. A new capital injection of $0.25M will generate new shares of 2,404 ($0.25M/$104). The new investor gets less new share compared to the early investors Instead in a down round scenario, Pre-money value is assumed at $1.1M, the value lower than the last post-money value. With the same capital inject of $0.25M, the revised PPS becomes $88 per share and new investor can acquire 2,841 shares with the same amount of money injection ($0.25M). Let’s summarize the numbers in the table below. As noted below, a series of finances will dilute shareholding of existing shareholders. However, it becomes serious in a down round scenario than an up round where existing shareholders suffer more in the relative change of the pre and post money valuation. 1st round

2nd round (up round)

2nd round (down round)

Founder

Shares: 10,000 Share%: 80

Shares: 10,000 Share%: 67.1

Shares: 10,000 Share%: 65.2

Early Investors

Shares: 2,500 Share%: 20

Shares: 2,500 Share%: 16.8

Shares: 2,500 Share%: 16.3

Shares: 2,404 Share%: 16.1

Shares: 2,841 Share%: 18.5

Prospective Investors

In conclusion, the concepts of pre-money value and post-money value are easy to understand and calculate. However, their relative values in subsequent rounds have impact on a critical dilution level of the existing investors. It adds an urgent issue to existing investors in future rounds in how to minimize the dilution effects.

Cost Approach

4.7 Cost Method

85

4.7 Cost Method Cost method is the most conservative approach among all approaches. It is based on the substitution principle from the economics in which the buyer is willing to pay the value not more than the amount of reconstructing or replacing the asset in the similar capacity and functionality. Cost valuation approach is applicable in such situations where there is no market value for the assets or companies being acquired, or it is the requirement by law the value is required to value with the highest certainty (e.g. liquidation). Theoretically, cost valuation approach is valued on the “going concern” basis and a fair value principle is applied. In addition, assets are assumed to generate economic benefits with reasonable certainty. However, it is very likely that assets values are outdated or distorted in the balance sheet that necessitates impairment loss to restore to the fair value principle. Asset distortion confounds economic value of the asset. It also misleads the performance measure (i.e. rate of return or economic profit) as the basis of valuation. It is therefore necessary to rectify the value prior to applying cost valuation. Let’s discuss two contrary effects in the asset distortion—asset overstatement and asset understatement.

4.7.1 Asset Overstatement Asset overstatement arises when the fair value of asset is below the book value, resulting that both assets and prior reported earnings are being overstated. Balance sheet and its reported earnings are required to make adjustments accordingly to reflect the economic reality of the transaction. Asset overstatement may include the following: • • • • • • •

Physical or functional deterioration of the assets are severe than the actual state; Obsolete inventory Unrecoverable receivables or debts Underestimated allowances Accelerated recognition of revenues Deferred liability taxes Contingent liabilities

Decrease in book value and reduction in reported profits are necessarily adjusted in the corresponding balance sheet items and the shareholders’ account.

4.7.2 Asset Understatement Asset understatement can also arise when conservative accounting rules disallow some expenses which have future economic benefits to be capitalized; managers

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have intention to accelerate write-offs; balance sheet does not capture the value of the intangible assets which have economic benefits in future. These understated assets or omitted assets have to be reflected in cost valuation. The following are some examples of these transactions. • • • • • • •

Accelerated depreciation for tax benefits R&D expenses with future economic benefits Overprovision of allowances, e.g. debts Leased assets in which the lessee is the ultimate owner Sales of receivable with risk recourse Off balance sheet intellectual rights and brands Contingent claims

Increase in book value and the reported profits are necessarily adjusted in the corresponding balance sheet items and the shareholders’ account. Example V—Cost Valuation Dundee Ltd. is near to the completed negotiation of a deal in which 100% of shareholding is offered for sale. Both parties agree that the price of the deal is a multiple of the total net assets book value of the company, after making necessary adjustments in some items of the balance sheet. Below is the latest balance sheet of Dundee Ltd. Assets ($000) Cash and cash equivalents Acct. receivable Inventory

Share Capital and Liabilities ($000) 9,500

Share Capital

13,200

Long-term debts

50,307

Short-term debts

Fixed assets (net)

249,000

Acct. payables & others

Total

322,007

Total

294,007 2,300 9,070 16,630 322,007

Both parties agree to the following book value adjustments. • • • • • •

10% of the acct. receivable cannot be recovered; 15% of the inventory is required to be written off due to obsolescence; A machine with a net cost of $3.5 million could not continue the service; Dundee has a deferred tax liability of $1 million not being shown in book: Prior R&D expenses of $4.5 million could produce economic benefit in future; A litigation which may in the end cost Dundee a legal claim of $6 million.

Let’s first sum up the net asset book value of Dundee Ltd. prior to the adjustments. Cash & cash equivalent should not be considered in the deal. It should be excluded from the net asset value. Net asset value is equivalent to share capital minus cash and cash equivalent which is $284,507,000. The table below summarizes the adjusted net asset value after making the following adjustment. Therefore, $269,641,000 is the adjusted net asset value for further value computation.

4.8 Multiple Comparable

87

Book Value Adjustments ($000) Net asset value (at book)

284,507

10% Receivable w/o

−1,320

15% inventory w/o

−7,546

Machine w/o

−3,500

Deferred tax

−1,000

R&D capitalized

4,500

Legal claim contingency

−6,000

Adjusted Net Asset Value

269,641

Market Approach

4.8 Multiple Comparable DCF techniques are regarded the best approach to explore the intrinsic value of the business from cash flow stream and fundamental business performance. For this approach, forecast information is taken internally. The extent of accuracy is conditioned on the accessibility of corporate information. In reality, the approach is bound to have valuation errors due to the forecast nature. For example, it is unlikely to gather all accessible information for forecast analysis as some information may be omitted or ignored for some reasons (i.e. selective bias). Forecast is a future oriented exercise based on business strategies, market perceptions, and operational knowledge. However, all is subject to value judgement and cognitive bias in developing forecast assumptions. Using external valuation method, forecast errors are magnified as internal information is difficult to be accessible. Therefore, there is a practical need to employ multiple valuation techniques to check accuracy and improve credibility of the valuation. Through the market perspective, DCF valuation of the target firm can be compared against market comparable for validation checks and causality search. Multiple comparable method is an important valuation tool that would improve the credibility of valuation. Multiple comparable is a type of comparable analysis in which different comparable firms are selected to compare against the target firm pertaining to share price, earnings, growth operating performance indicators…etc. The purpose of comparison is aimed at establishment of a benchmark among these companies so that share price of the target firm can be gauged from the market price of those benchmark companies. The estimated share price is employed to establish a justifiable equity value for shareholders and also entity value for the entire firm after incorporating other non-equity items in the balance sheet (e.g. corporate debt, non-operating asset). The first step of comparable analysis is selection of a set of proper candidates. It is therefore important to have a clear list of candidates for comparison. The best candidates for comparison are those with high similarity. For example, they have

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4 Valuing Business—Concepts and Techniques

similar company size, same market segment, business models, company history…etc. Alibaba and JD.com are the best candidates for comparison as both firms provides the same internet sale platform and operated the commerce platform for a long time. Xiaomi and Apple are also a proper pair as they are two top-tier phone makers in the world. However, their P/E and key ratios are not the same. JD.com and Alibaba have different sources of revenue and their sales focus are not alike (JD.com strong in electronic appliances whereas Alibaba in apparels and others). Similarly, Apple and Xiaomi differ in their business direction. Apples emphasizes on phone product innovation (hardware making) while Xiaomi stresses on developing internet platform with its own brand (like Amazon). Therefore, comparable analysis aims to explore plausibility of comparable, areas of differentiation, degree of diversity among those peer firms. This is the basis to determine discount and premium when assessing the share price of the target firm. To facilitate clarity of execution, the following outlines a few directional guidelines for the comparable analysis. • Select appropriate candidate companies for comparative analysis. It is preferred to have comparable firms with similar characteristics. • Emphasize forward-looking estimates. • Use both enterprise and entity approaches for different purposes. • Focus on three key comparative dimensions: earnings, growth, and cash flow. • Identify four important valuation ratios: P/E, PEG, P/B, and P/C.

4.8.1 Candidates for Comparison It is important for the target firm to sort out a checklist of peer firms for comparable analysis. The first thing comes to our mind is the industry benchmark such as industry P/E, profit margin, or growth %. This is the general information which gives a very basic background about the market environment. However, key analysis aims at close candidates which are our direct competitors or close rivals competing for the similar market segments. Therefore, it is the best practice to find a few firms which possess high similarity. As mentioned earlier, there is unlikely to have a comparable which is exactly alike. The process of comparable analysis is not only exploring and identifying the similar characteristics but also their differences that attribute to divergence in business valuation. The investigation is aimed at finding persuasive reasons for different multiples in these peer firms. There are distinct dimensions that require detailed investigation. Market similarity is a prime area: market segment, product range, pricing strategy, customer base, business strategy, and competitive advantages. More recent decades, institutional factors have been drawn from business analysts. This new dimension shapes the market power of firms. e.g. industrial policy, technological support, funding subsidies, tax preferential treatments, to name a few. Have particular sectors of the market possessed discriminated favors or not? Have some licensed firms gained protection shield at the expenses of other firms? Furthermore, internal resources are

4.8 Multiple Comparable

89

the third key dimensions. Resource endowment of these peer firms embeds high intangible value in the organization: management team, employee talents, organizational technological skills, market knowledge, and culture and history…etc. These are topics of further study. Actually, these investigative areas are important when considering a candidate list of peer groups. I am going to demonstrate how a candidate list is selected and how they are compared and form the valuation basis. Comparable Analysis I conducted a comparable analysis from external market information to evaluate the share price of e-commerce firm in China. For this external analysis, the most reliability source of information comes from public listed companies. I selected top 10 firms in China from a credible website survey.6 I made a screening exercise and found two firms were being delisted from the stock exchange, one due to privatization and the other due to inactive trading. One web company was a private company, and two e-commerce portals (Tmall and Taobao) come from the same group—Alibaba. It remains six commerce firms to be selected for investigation. Table 4.5 presents 6 peer firms that were categorized by their product offerings. All firms have been established for more than 10 years (the year of IPO was put against each firm). Along those firms, I have selected sales, earnings performance, growth, and some popular multiple indicators (EPS, P/E…etc.). Categorization of peer group is a good practice because it provides additional meaningful information about the group. For example, comprehensive group have a higher P/E than other classes. Home appliance is the worse because of its specialized product areas. In fact, Gomei and Suning are market leaders for home appliance in old days where physical retailed outlets were popular. Therefore, they have a very high O2O network but also carry high operation costs in the physical network. PDD is a collective bargain eportal providing very attractive price discount for group purchase. It has continuous loss but high sale growth rate represents rapid business growth. VIPS is a discount house for branded goods. It has a normal business operation with reasonable profit margin, and sales growth. At this junction, I would recommend to provide forward looking estimates, e.g. forecast profit is preferred to history records. The above comparable analysis suggests that very large mega e-commerce portals have a P/E of around 20+. Medium scale of business operation shows a P/E of 10 to 14. The similar P/E would apply to loss-making firms which has exceptional high growth potential. Obviously, e-firms with loss making and low growth prospect would earn a low P/E. The above comparable analysis provides a clue to set benchmarks for valuation exercises. Due to a small no. of firms having profits, the peer group list may need to be expanded to the firms of a broader market segments or to other geographical locations (e.g. Amazon). More information can expand explanatory power of multiples in relation to their performance attributes. In fact, we should admit that loss-making businesses are a general phenomenon of e-businesses partly because of untested new business models or partly because of these firm beings at their early stage of business development.

6

This survey was based on the market Information of Futu.com, a e-finance intermediary platform.

Sales

7458.02

594.92

JD.com (Y2014)

PDD (Y2018)

*Replaced by P/S

VIPS (Y2012)

1018.58

2522.96

Suning.com (Y2013)

Discount house

441.19

Gomei (Y1992)

Home appliance

7172.89

Alibaba (Y2017)

Comprehensive group

(RMB 100 Million)

9.53%

−6.29%

−2.12%

3.67%

−7.50%

97.37%

−12.07%

−16.33%

29.28%

40.72%

Growth%

6.62%

2.09%

NM%

Table 4.5 Peers firms for comparable analysis

3.60%

0.59%

−88.44%

−4.74%

0.39%

4.76%

ROA

875.00%

−46.00%

−5.00%

−604.00%

3270.00%

835.00%

EPS

226.00%

64.00%

336.00%

1220.00%

352.00%

298.00%

P/B

57.00%

20.00%

37.00%

1060.00%

87.00%

377.00%

P/S

10.75

−15.04

−2.36

−305.75

21.64

19.67

P/E(TTM)

10.77−14.18

0.2−0.24*

0.37−0.53*

9.72−13.6*

13.9−16.0

22.1−25.7

Rec. P/E

90 4 Valuing Business—Concepts and Techniques

4.8 Multiple Comparable

91

In sum, comparable analysis provides basis for valuation after a careful investigation of the related multiples (P/E, P/S…etc.). These multiples are often employed by financial analysts to benchmark against selected peer group companies. These multiples are referred to different dimensions of the firm. I will continue to elaborate key multiple ratios. In fact, there are two application approaches for market multiples—equity approach and entity approach. Equity approach focuses on per share basis of the target firm while entity considers enterprise value of the business. I will discuss in a greater detail these two approaches in the coming section.

4.8.2 Equity Approach Five key multiple ratios are selected for detailed elaboration. They are price-earnings ratios (P/E), price-earnings to growth ratio (PEG), price-book ratio (P/B), price-sales ratio (P/S), and price-cash flow ratio (P/CF). I. Price-To-Earnings Ratio (P/E) P/E =

Shar e pr i ce × d i l ut ed no. o f shar es M ar ket cap = N O P AT Earni ngs per shar e (E P S)

Share price is taken from the current price and diluted shares include issued shares and share options. In fact, information can be accessible from financial websites. Market cap is a general term that reflects share price times no. of fully no. diluted shares. Earnings per share is in fact NOPAT after deducting all expenses and losses. Usually, it is recommended to use forecast earnings (if possible) to reflect the immediate future earnings (next year results) than historical earnings. Illustration: B&M’s current share price is $15 and has a fully diluted no. of shares of 150,450,236. The consensus from financial analysts about the forecast earnings of next year is expected to be $260,500,000, an increase of 6% compared with the last year results. What is the P/E ratio and its implications? Market cap = $15 × 150450236 = $2, 256, 753, 540 EPS = $260, 500, 000/150450236 = $1.731 Both methods can be employed to arrive at the P/E ratio, which is 8.66. It can also interpret that it takes 8.66 years to make the payback. As a general rule, P/E ratio indicates the value of the share. High P/E ratio means expensive purchase while low P/E ratio implies cheap purchase. P/E ratio reflects how market expectations about the business. Different industries have different average P/E ratio which varies substantially depending on the market prospect and growth potential. In the B&M case, a P/E ratio of about 9 is an acceptable rate. In fact, the inverse of P/E indicates the yield of the investment.

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Yield (Inverse of P/E) =

EPS $ 1.731 = = 0.1154 Price per share $ 15

As seen above, it represents a good investment yield at 11.54%, assuming that annual earnings are consistent over the investment period. In fact, 8.66 × PE can be justified by a reasonable growth in earnings at 6% (given). P/E ratio is the multiple that gives intuitive feelings about valuation, whether it is reasonable, over or underestimated. II. Price-Earnings-To-Growth (PEG) P EG =

P/E r at i o Ex pect ed Gr owt h i n earni ngs

As mentioned above, investors are willing to pay extra money when the business has a reasonable growth potential, even though the current earnings performance is yet to be delivered. PEG helps to justify whether the P/E ratio is a fair value, supported by the expected earnings in growth rate. It is better to judge whether the growth in earnings is reasonable but also consistent. It is particularly relevant to a start-up firm which is under rapid development but with low earnings. Using PEG to supplement P/E ratio provides more fair value in the valuation exercise because P/E omits the growth component. Customarily, a value of 1 is regarded fair value, a value >1 is regarded under-valued and a value