Operations forensics: business performance analysis using operations measures and tools
Gespeichert in:
1. Verfasser: | |
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Format: | Buch |
Sprache: | English |
Veröffentlicht: |
Cambridge, Mass. [u.a.]
MIT Press
2013
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Schlagworte: | |
Online-Zugang: | Inhaltsverzeichnis |
Beschreibung: | Includes bibliographical references and index |
Beschreibung: | XV, 309 S. graph. Darst. |
ISBN: | 9780262018661 |
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245 | 1 | 0 | |a Operations forensics |b business performance analysis using operations measures and tools |c Richard Lai |
264 | 1 | |a Cambridge, Mass. [u.a.] |b MIT Press |c 2013 | |
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650 | 4 | |a Industrial management | |
650 | 4 | |a Performance | |
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Datensatz im Suchindex
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adam_text | Titel: Operations forensics
Autor: Lai, Richard
Jahr: 2013
Contents
Preface xvii
Guide for the Reader xix
Acknowledgments xxi
I INTRODUCTION 1
1 Operations Forensics 3
1.1 The Three Components of Operations Forensics 3
1.1.1 Operational Indicators 3
1.1.2 Operational Due Diligence 4
1.1.3 Operational Turnaround 4
1.2 Operations Forensics as a Perspective 5
1.3 Operations Forensics in the Field 6
1.3.1 Analysts 6
Goldman Sachs s Retail Analyst Group 8
1.3.2 Private Equity Firms 12
KKR s Capstone Group 13
Bain Capital 14
1.3.3 Managers and Consultants 15
1.4 Takeaways 15
1.5 Further Reading 15
2 What Financial Statements May or May Not Reveal 17
2.1 What Financial Statements Reveal 18
2.1.1 Inferring Business Model from Asset Intensity 18
Asset-Intensive Business Models 18
Asset-Light Business Models 19
2.1.2 Inferring Product Mix from Days of Inventory 21
2.1.3 Inferring Customer Type from Days of Receivables 22
2.1.4 Inferring the Cash Conversion Cycle from Receivables,
Payables, and Inventory 24
2.1.5 Inferring Margin from Inventory Turn and Vice Versa 25
2.1.6 Inferring the Business Mix 26
2.1.7 Exercise: From Financial Statements to Operations 27
2.2 What Financial Statements Do Not Reveal 29
2.2.1 Risks 29
2.2.2 Contingent Claims 29
2.2.3 Covenants and Rights 29
2.2.4 Reserves 29
2.2.5 Intangible Assets 30
2.2.6 Static and Backward-Looking View 30
2.3 When Might Financial Statements Be Less Accurate? 30
2.3.1 Opportunity 30
2.3.2 Means 32
2.3.3 Motive 33
2.4 Takeaways 35
2.5 Survey of Prior Research in One Paragraph 35
2.6 Further Reading 36
II OPERATIONAL INDICATORS 39
3 Indicators of Accounting Performance 41
3.1 Indicators of Current Performance: ROA Trees 41
3.1.1 Principles for Developing ROA Trees 42
Begin with Industry Language 43
Use as Many Decompositions for a Measure as Is Useful 43
Use a Driver for as Many Measures as Is Useful 43
Exploit Operational Principles in Decomposition 43
Use Different Trees for Different Roles 44
Make Explicit Both Current and Full Potential 44
Make Intangibles Explicit 44
3.1.2 ROA Tree for Airlines 45
Major Operational Indicators of ROA Performance 45
Case: Southwest Airlines 47
Non-US Airlines 49
3.2 Indicators of Future Performance 51
3.2.1 Advanced Topic: Predicting Sales, Earnings, and Margins
Using Inventory Information—the Bernard-Noel Model 52
3.2.2 Predicting Unit Costs Using the Experience Curve 56
3.2.3 Predicting Capital Efficiency 58
Risk Pooling with the Square Root Rule 58
Scaling with the Square-Cube Rule 59
3.3 Takeaways and Toolkit 60
3.4 Survey of Prior Research in One Paragraph 61
3.5 Further Reading 61
4 Indicators of Stock Market Performance 63
4.1 A Perfect World 64
4.2 Opportunity Arising from Information Asymmetry 66
4.3 Means Arising from Managerial Decision Rights 66
4.4 Motives Arising from Valuation-Based Compensation and Short-termism 67
4.5 Implications for Inventory as Indicator for Valuation 68
4.6 Detecting Deviations 70
4.6.1 Statistical Process Control 71
4.6.2 Benford s Law 71
4.6.3 The Beneish Model for Detecting Earnings Manipulation 72
4.7 Takeaways and Toolkit 74
4.8 Survey of Prior Research in One Paragraph 74
4.9 Further Reading 75
5 Indicators of Disruption 77
5.1 Types of Technological Innovations 77
5.1.1 Incremental Innovation 7 8
5.1.2 Radical Innovation 79
5.1.3 Modular Innovation 79
5.1.4 Architectural Innovation 79
5.2 Sustaining and Disruptive Innovations 80
5.3 Takeaways and Toolkit 83
5.4 Survey of Prior Research in One Paragraph 84
5.5 Further Reading 84
6 Indicators of Distress 85
6.1 A Short Note on Terminology and Definition 86
6.2 The Altman Z Score 86
6.2.1 Manufacturing Companies 86
6.2.2 Service and Distribution Companies 87
6.2.3 Private Companies 88
6.3 The Runway 89
6.4 Altman Z s Marriage to the Runway 90
6.5 Takeaways and Toolkit 91
6.6 Survey of Prior Research in One Paragraph 91
6.7 Further Reading 92
III OPERATIONAL DUE DILIGENCE 93
7 The Many Facets of Due Diligence 95
7.1 Why Do We Do Due Diligence? 95
7.2 What Should Due Diligence Seek? 97
7.2.1 Operational Metrics That Drive Financial Measures 98
7.2.2 Operational Metrics That Address Strategic Concerns 98
7.2.3 Operational Metrics to Deduce Other Metrics 100
7.3 When Should It Be Done? 101
7.4 How and By Whom? 103
7.5 Takeaways and Toolkit 105
7.6 Survey of Prior Research in One Paragraph 106
7.7 Further Reading 107
8 Assessing the Customer Base 109
8.1 How Much of Customer Valuation Is Revealed in Financial Statements? 109
8.1.1 How Much of Customer Valuation Is Revealed in Satisfaction
Surveys? 110
8.2 Measuring Customer Profitability 110
8.3 Impact of Customer Defections on Valuation 113
8.3.1 Advanced Topic: Can Reducing Defection Really Double NPV? 115
8.4 Impact of Channel Mix on Valuation 117
8.4.1 Advanced Topic: Does Web Use Really Improve Profitability
and Retention? 118
8.5 Takeaways and Toolkit 120
8.6 Survey of Prior Research in One Paragraph 121
8.7 Further Reading 122
9 Assessing Lean Management 123
9.1 How Much of Process Performance Is Revealed in Financial Statements? 123
9.2 The Toyota Production System (TPS) 124
9.2.1 Limits and Limitations of the TPS 126
9.3 Should a Company Implement Lean Management? 127
9.3.1 Are Lean Management Outcomes Aligned with Strategy? 128
9.3.2 Does Lean Management Work in the Company s Setting? 128
9.4 Verifying a Company s Lean Management Implementation 129
9.4.1 Data Envelopment Analysis 129
9.4.2 Qualitative Verification of Leanness 133
9.5 Takeaways and Toolkit 134
9.6 Survey of Prior Research in One Paragraph 135
9.7 Further Reading 135
10 Assessing Risks 137
10.1 Why Is Risk Assessment Difficult? 138
10.2 Systematic Risk 139
10.3 Total Risk 141
10.3.1 Probability 141
10.3.2 Severity 143
10.3.3 A Typology of Risk Management Methods 144
10.3.4 Risk Management with a Risk Map 145
10.3.5 Advanced Topic: Process Risks 146
One Station 146
Sequential Stations in a Process 148
Pooled Stations in a Process 150
Risk of Inadequate Warranty Reserves 151
10.3.6 One-off Risks and Value at Risk (VaR) 152
Parametric Method 153
Historical Method 155
Monte Carlo Method 155
Comparison and Critique 156
10.4 Takeaways and Toolkit 157
10.5 Survey of Prior Research in One Paragraph 157
10.6 Further Reading 158
11 Assessing Options 161
11.1 Refresher on Valuing Financial Options 162
11.2 Real versus Financial Options 163
11.3 Options to Start or Expand Later 164
11.3.1 Binomial Method Using Replication 165
11.3.2 Advanced Topic: Binomial Method Using Risk-Neutral
Probabilities 166
11.3.3 Binomial Method in Continuous Time 166
11.3.4 Black-Scholes Method 167
11.3.5 Black-Scholes with Deteriorating Assets 168
11.3.6 Example: Accurate Response at Sport Obermeyer 168
11.3.7 Detecting an Option to Start or Expand Later 168
Much Learning over Time 168
The Ticket to Play Is Needed Early 169
11.4 Option to End or Shrink Earlier 169
11.4.1 Example: Staging in Due Diligence and Investing 172
11.4.2 Detecting an Option to End or Shrink Earlier 172
Some Branches Produce Negative NPV 172
Viable Release Clause 172
11.5 Option in Being Flexible 173
11.5.1 Example: Delayed Differentiation 177
11.5.2 Detecting an Option for Being Flexible 177
Multiple Types of Outcomes 177
Imperfectly Correlated Outcomes 177
Similarly Sized Outcomes 178
11.6 Takeaways and Toolkit 178
11.7 Survey of Prior Research in One Paragraph 178
11.8 Further Reading 179
IV OPERATIONAL TURNAROUNDS 181
12 Turning Around Purchasing 183
12.1 Caveats about Rationalization 183
12.1.1 Balancing Short-and Long-Term Impact 183
12.1.2 Prioritizing Opportunities 184
12.1.3 Accounting for Human Considerations 184
12.2 Rationalize Supplier Base 184
12.2.1 Competition versus Commitment 185
12.2.2 Homogeneity versus Diversity 185
12.2.3 Hungry Newbies versus Strong Incumbents 185
12.3 Design for Supply 186
12.3.1 Architect the Right Supply Chain 186
12.3.2 Consider a Full Range of Possible Supplier Roles 188
12.3.3 Outsource or Offshore with Differentiated Capacities 188
12.3.4 Standardize and Modularize Product Requirements 189
12.4 Reconfigure Sourcing Contracts 189
12.5 Reengineer Purchasing Process 194
12.5.1 Design End-to-End Processes, Eliminate Handoffs 194
12.5.2 Balance the Load 194
12.5.3 Differentiate versus Standardize 194
12.5.4 Automate 194
12.5.5 Centralize versus Decentralize 195
12.6 Takeaways 196
12.7 Survey of Prior Research in One Paragraph 196
12.8 Further Reading 196
13 Turning Around Production 199
13.1 Ensuring Process-Product Fit 199
13.2 Building Forecasting Capability with a Consensus Approach 199
13.3 Rationalizing Production Assets with Newsvendor Analysis 200
13.3.1 Additional Rationalization with Pooling 201
13.3.2 Even Smarter Rationalization with Chaining 202
13.4 Rationalizing Service Assets with Queueing Analysis 203
13.4.1 When Customers Cannot Wait 204
13.4.2 When Customers Wait 205
13.5 Rationalizing Capacities with Competitive Capacity Analysis 206
13.6 Driving Down Unit Costs with Experience Curves 209
13.6.1 Competitive Dynamics 210
13.6.2 Advanced Topic: How Long Does It Take to Catch Up on
the Experience Curve? 211
13.6.3 Caveats 213
13.7 Takeaways 213
13.8 Survey of Prior Research in One Paragraph 214
13.9 Further Reading 214
14 Turning Around Distribution 217
14.1 Determining the Right Set of Channels with the Rangan-Zoltners-Becker
Model 218
14.1.1 Embellishments 222
14.2 Matching Customers with Channels 222
14.3 Rationalizing the Delivery Architecture 223
14.4 Takeaways 224
14.5 Survey of Prior Research in One Paragraph 225
14.6 Further Reading 225
15 Sustaining the Turnaround 227
15.1 Operational and Organizational Turnarounds 227
15.2 Quality Management 229
15.2.1 Value-Maximizing Output Control 229
15.2.2 Advanced Topic: Value-Maximizing Process Control 230
15.3 Innovation Management 235
15.3.1 Selecting Projects to Pursue: The LPTU Model 236
15.3.2 Developing Products: The Terwiesch-Xu Model 237
15.3.3 Advanced Topic: Commercializing Products:
The Cohen-Eliashberg-Ho Model 240
15.4 Revenue Management 242
15.4.1 Value-Maximizing Allocation of Capacity to Product Tiers 242
15.4.2 Value-Maximizing Amount of Overbooking 243
15.4.3 Advanced Topic: The Pricing of Warranties 244
15.5 Performance Management 246
15.5.1 The Gonik Incentive Scheme 248
15.5.2 Time Equations and the Process Audit 249
15.5.3 The Balanced Scorecard 250
15.6 Investor Management 251
15.6.1 Tailoring Management by Investor Segment 252
15.6.2 Some Operationally Related Investor Relations Initiatives 254
15.7 Takeaways 255
15.8 Survey of Prior Research in One Paragraph 255
15.9 Further Reading 256
Appendix A Industry ROA Trees 259
A. 1 ROA Tree for Retail Banking 259
A. 1.1 Pricing Deposits and Loans with Interbank Cost and Price of
Funds 259
A. 1.2 FDIC Assessments and Regulatory Capital 261
A. 1.3 Efficiency Ratio and Branch Network Size 261
A.2 ROA Tree for a Restaurant 262
A.2.1 Revenues: Dupes with Coupons and Covers with Differing Tops 262
A.2.2 FOH Expenses: Comps, Food Costs, and Labor 264
A.2.3 BOH Expenses: The Brigade, Dead Food, and Vendor Credits
and Mispicks 265
A.2.4 Assets: Liquor Licenses, PPE, WIP, and Par Level 265
A.3 ROA Tree for Gaming 266
A.3.1 Win, Drop, Hold Ratio, and the House Advantage 266
A.3.2 Croupier Rakeoffs 268
A.3.3 Comps Expense and Credit Losses 268
A.3.4 Labor Expenses: Dealer Leverage and Utilization 268
A.4 ROA Tree for Home Building 268
A.4.1 Backlogs, Cancellation Rate, and Mortgage Capture Rate 269
A.4.2 Lot Banks and Options 269
A.5 ROA Tree for Hotel Groups 270
A.5.1 Occupancy Rate 272
A.5.2 Rack Rates and Discounts 272
A.6 ROA Tree for Healthcare 272
A.6.1 Outcomes: Service, Clinical, and Process 272
A.6.2 Length of Stay: The Demand and Supply Views 272
A.7 ROA Tree for the Semiconductor Industry 274
A.7.1 Book-to-Bill Ratio and Backlogged Orders 274
A.8 ROA Tree for Oil Exploration and Development 275
A.8.1 Netback, FDA, and the Recycle Ratio 277
A.8.2 Reserves and Decline Rate 277
A.9 ROA Tree for Retailing 277
A.9.1 Same-Store Sales Growth 279
A.9.2 Sales Conversion 280
A.9.3 Space Utilization 281
A. 10 ROA Tree for Telecom 282
A. 10.1 ARPU, MOU, POP, and Churn 282
A. 10.2 SAC, SDC, and Depreciation Charges 283
A.l 1 ROA Tree for Life Insurance 284
A. 12 ROA Tree for Securities Brokerage 285
A. 13 ROA Tree for Pharmaceuticals 287
A. 13.1 Risks in the Path from R D to IND Status 289
A. 13.2 Manufacturing Expenses: APIs and Excipients 290
A. 14 Further Reading 290
Appendix B Resources 291
B.l Sample Due Diligence Checklists 291
B.2 Books 292
B.2.1 Operations Management 292
B.2.2 Private Equity, Finance, Accounting 292
B.2.3 Econometrics and Analytics 292
B.3 Journals, Magazines, Academic Research 293
B.4 Consultants and Information Sources 293
B.5 Directories, Trade Associations, Standards 294
B.6 Software 295
B.7 Others 295
Appendix C Glossary 297
Notes 301
Index 305
|
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spelling | Lai, Richard Verfasser aut Operations forensics business performance analysis using operations measures and tools Richard Lai Cambridge, Mass. [u.a.] MIT Press 2013 XV, 309 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Includes bibliographical references and index Production management Industrial management Performance Rechnungslegung (DE-588)4128343-0 gnd rswk-swf Betrug (DE-588)4006249-1 gnd rswk-swf Wirtschaftsprüfung (DE-588)4066505-7 gnd rswk-swf Rechnungslegung (DE-588)4128343-0 s Betrug (DE-588)4006249-1 s Wirtschaftsprüfung (DE-588)4066505-7 s b DE-604 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025917935&sequence=000004&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
spellingShingle | Lai, Richard Operations forensics business performance analysis using operations measures and tools Production management Industrial management Performance Rechnungslegung (DE-588)4128343-0 gnd Betrug (DE-588)4006249-1 gnd Wirtschaftsprüfung (DE-588)4066505-7 gnd |
subject_GND | (DE-588)4128343-0 (DE-588)4006249-1 (DE-588)4066505-7 |
title | Operations forensics business performance analysis using operations measures and tools |
title_auth | Operations forensics business performance analysis using operations measures and tools |
title_exact_search | Operations forensics business performance analysis using operations measures and tools |
title_full | Operations forensics business performance analysis using operations measures and tools Richard Lai |
title_fullStr | Operations forensics business performance analysis using operations measures and tools Richard Lai |
title_full_unstemmed | Operations forensics business performance analysis using operations measures and tools Richard Lai |
title_short | Operations forensics |
title_sort | operations forensics business performance analysis using operations measures and tools |
title_sub | business performance analysis using operations measures and tools |
topic | Production management Industrial management Performance Rechnungslegung (DE-588)4128343-0 gnd Betrug (DE-588)4006249-1 gnd Wirtschaftsprüfung (DE-588)4066505-7 gnd |
topic_facet | Production management Industrial management Performance Rechnungslegung Betrug Wirtschaftsprüfung |
url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025917935&sequence=000004&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
work_keys_str_mv | AT lairichard operationsforensicsbusinessperformanceanalysisusingoperationsmeasuresandtools |