Data Driven Decisions – Systems Engineering to Understand Corporate Value and Intangible Assets

JOSHUA JAHANI teaches Systems Engineering at Cornell University and owns Jahani and Associates, a firm headquartered in New York City that provides investment banking advisory, investment banking transaction, and corporate development expertise to clients from around the globe.

Foreword xi Prologue xiii Introduction 1 Part I: Intangible Assets 7 Chapter 1: When Intangibles Matter Most 9 Chapter 2: Examples of Intangible Assets 13 Chapter 3: The Rise of Intangible Economies 15 Chapter 4: Defining Intangibles 19 Chapter 5: Valuing Intangible Assets 23 Chapter 6: EBITDA Is Not the Best Way to Value Intangible- Heavy Companies 27 Chapter 7: Separability, Measurability, and Predictability 33 Chapter 8: Why Systems Engineering Is Relevant for Corporate Valuations and Intangible Assets 41 Chapter 9: What Intangibles Matter Most for Corporate Valuation 45 Chapter 10: What Intangibles Matter Most for Corporate Expansion 55 Chapter 11: Buy-Side Intangibles 59 Chapter 12: PE Ratios 63 Chapter 13: The Business Moat as an Intangible Asset 67 Chapter 14: How Investors Think About Intangibles 71 Chapter 15: Intangible Assets in Branded Consumer Products 75 Chapter 16: Intangible Assets in Healthcare 79 Part II: Systems Engineering Tools and Examples 83 Chapter 17: Systems Engineering Tools 85 Chapter 18: Customer Affinity and Context Diagrams 89 Chapter 19: Context Diagrams and Context Matrices 97 Chapter 20: Use Cases and Behavioral Diagrams 103 Chapter 21: Originating Requirements 109 Chapter 22: Decision Matrix 117 Chapter 23: GQM - Goal Question Metric Analysis 123 Chapter 24: Analytical Hierarchy 131 Chapter 25: Precedence Matrix 133 Chapter 26: Failure Mode and Effect Analysis 137 Chapter 27: Interface Matrix 143 Chapter 28: House of Quality 147 Chapter 29: Operations Description Template 153 Chapter 30: Interface Tracking 157 Chapter 31: Conclusion to Tools 159 Chapter 32: GQM, Decision Matrix, and Analytical Hierarchy for Ad-Tech Industries 161 Chapter 33: GQM, Decision Matrix, and Analytical Hierarchy for Logistics Industries 167 Chapter 34: GQM, Decision Matrix, and Analytical Hierarchy for Manufacturing Industries 171 Part III: Geographical Application 173 Chapter 35: Introduction 175 Chapter 36: The MENA Region 179 Chapter 37: The ASEAN Region 187 Chapter 38: The Latin American Region 195 Chapter 39: Case Studies: Bringing It All Together 205 Chapter 40: Case Studies: LATAM Expanding to the United States 209 Chapter 41: Case Studies: MENA Medical Devices 213 Chapter 42: Case Studies: ASEAN Aerospace Schema - Context Diagram 217 Chapter 43: Case Studies: In Conclusion 221 Chapter 44: Summary 223 Bibliography 225 Index 235