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<p>PREFACE xiii</p> <p>USING THIS BOOK xix</p> <p>ACKNOWLEDGMENTS xxiii</p> <p>ACKNOWLEDGMENTS FOR CASES xxv</p> <p>ABOUT THE AUTHORS xxvii</p> <p><b>PART I 1</b></p> <p><b>1. Introduction 3</b><br /> 1.0 Models and Modeling 3<br /> 1.1 Well-Structured versus Ill-Structured Problems 4<br /> 1.2 Modeling versus Problem Solving 5<br /> 1.3 Modeling for Insight 6<br /> 1.4 Novice Modelers and Expert Modelers 7<br /> 1.5 Craft Skills in Modeling 8<br /> 1.6 A Structured Modeling Process 9<br /> 1.7 Modeling Tools 9<br /> 1.8 Summary 10</p> <p><b>2. Foundations of Modeling for Insight 11</b><br /> 2.0 Introduction 11<br /> 2.1 The Modeling Process 11<br /> 2.2 Tools for Modeling 19<br /> 2.3 Presentation Skills 26<br /> 2.4 Summary 34</p> <p><b>3. Spreadsheet Engineering 36</b><br /> 3.0 Why Use Spreadsheets? 36<br /> 3.1 Spreadsheet Engineering 37<br /> 3.2 Summary 49</p> <p><b>PART II 51</b></p> <p><b>4. A First Example—The Red Cross Problem 53</b><br /> 4.0 Introduction 53<br /> 4.1 The Red Cross Problem 53<br /> 4.2 Bringing Blood Quality into the Analysis 69<br /> 4.3 Improving and Iterating 78<br /> 4.4 Summary 79</p> <p><b>5. Retirement Planning Problem 80</b><br /> 5.0 Introduction 80<br /> 5.1 Retirement Planning (A) 80<br /> 5.2 Retirement Planning (B) 99<br /> 5.3 Retirement Planning (C) 107<br /> 5.4 Presentation of Results 112<br /> 5.5 Summary 122</p> <p><b>6. Technology Option 122</b><br /> 6.0 Introduction 122<br /> 6.1 Technology Option (A) 122<br /> 6.2 Technology Option (B) 131<br /> 6.3 Additional Refi nements 138<br /> 6.4 Presentation of Results 147<br /> 6.5 Summary 152</p> <p><b>PART III 155</b></p> <p><b>7. MediDevice 157</b><br /> 7.0 Introduction 157<br /> 7.1 MediDevice Case (A) 157<br /> 7.2 Revising the Model 172<br /> 7.3 MediDevice Case (B) 178<br /> 7.4 Presentation of Results 184<br /> 7.5 Summary 190</p> <p><b>8. Draft Commercials 194</b><br /> 8.0 Introduction 194<br /> 8.1 Draft Commercials Case 194<br /> 8.2 Frame the Problem 196<br /> 8.3 Diagram the Problem 198<br /> 8.4 M1 Model and Analysis 200<br /> 8.5 M2 Model and Analysis 205<br /> 8.6 M3 Model and Analysis 207<br /> 8.7 M4 Model and Analysis 216<br /> 8.8 Presentation of Results 222<br /> 8.9 Summary 232</p> <p><b>9. New England College Skiway 233</b><br /> 9.0 Introduction 233<br /> 9.1 New England College Skiway Case 233<br /> 9.2 Frame the Problem 234<br /> 9.3 Diagram the Problem 237<br /> 9.4 M1 Model and Analysis 239<br /> 9.5 Analyzing Mountain Capacity 246<br /> 9.6 M2 Model and Analysis 250<br /> 9.7 M3 Model and Analysis 256<br /> 9.8 Considering Uncertainty 273<br /> 9.9 Presentation of Results 274<br /> 9.10 Summary 283</p> <p><b>10. National Leasing, Inc. 285</b><br /> 10.0 Introduction 285<br /> 10.1 National Leasing Case 286<br /> 10.2 Frame the Problem 289<br /> 10.3 Diagram the Problem 291<br /> 10.4 M1 Model and Analysis 293<br /> 10.5 M2 Model and Analysis 304<br /> 10.6 M3 Model and Analysis 313<br /> 10.7 M4 Model and Analysis 319<br /> 10.8 Presentation of Results 324<br /> 10.9 Summary 333</p> <p><b>11. Pharma X and Pharma Y 334</b><br /> 11.0 Introduction 334<br /> 11.1 The Pharma X and Pharma Y Case 334<br /> 11.2 Frame the Problem 338<br /> 11.3 Diagram the Problem 339<br /> 11.4 Expected Value or Simulation? 340<br /> 11.5 M1 Model and Analysis 341<br /> 11.6 M2 Model and Analysis 354<br /> 11.7 M3 Model and Analysis 366<br /> 11.8 Presentation of Results 372<br /> 11.9 Summary 380</p> <p><b>12. Invivo Diagnostics, Inc. 381</b><br /> 12.0 Introduction 381<br /> 12.1 Invivo Diagnostics Case 381<br /> 12.2 Frame and Diagram the Problem 384<br /> 12.3 M1 Model and Analysis 388<br /> 12.4 M2 Model and Analysis 394<br /> 12.5 M3 Model and Analysis 406<br /> 12.6 M4 Model and Analysis 426<br /> 12.7 Presentation of Results 434<br /> 12.8 Summary 443</p> <p>Appendix A: Guide to Solver 445</p> <p>Appendix B: Guide to Crystal Ball 451</p> <p>Appendix C: Guide to the Sensitivity Toolkit 456</p> <p>INDEX 464</p>

<b>STEPHEN G. POWELL, PhD,</b> is Professor at the Tuck School of Business at Dartmouth College. The recipient of the 2001 INFORMS Prize for the Teaching of Operations Research/Management Science Practice, Dr. Powell teaches and conducts research on modeling for business decision making. He is the coauthor of <i>Management Science: The Art of Modeling with Spreadsheets</i>, Second Edition, also published by Wiley. <p><b>ROBERT J. BATT, MEM, MBA,</b> is Tuck Fellow and researcher at the Tuck School of Business at Dartmouth College. With experience in both academia and industry, his work focuses on operations management and finance.</p>

<b>Praise for <i>Modeling for Insight</i></b> <p>"Most books on modeling are either too theoretical or too focused on the mechanics of programming. Powell and Batt's emphasis on using simple spreadsheet models to gain business insight (which is, after all, the name of the game) is what makes this book stand head and shoulders above the rest. This clear and practical book deserves a place on the shelf of every business analyst."<br /> —Jonathan Koomey, PhD, Lawrence Berkeley National Laboratory and Stanford University, author of <i>Turning Numbers into Knowledge: Mastering the Art of Problem Solving</i></p> <p>Most business analysts are familiar with using spreadsheets to organize data and build routine models. However, analysts often struggle when faced with examining new and ill-structured problems. <i>Modeling for Insight</i> is a one-of-a-kind guide to building effective spreadsheet models and using them to generate insights. With its hands-on approach, this book provides readers with an effective modeling process and specific modeling tools to become a master modeler.</p> <p>The authors provide a structured approach to problem-solving using four main steps: frame the problem, diagram the problem, build a model, and generate insights. Extensive examples, graduated in difficulty, help readers to internalize this modeling process, while also demonstrating the application of important modeling tools, including:</p> <ul> <li> <p>Influence diagrams</p> </li> <li> <p>Spreadsheet engineering</p> </li> <li> <p>Parameterization</p> </li> <li> <p>Sensitivity analysis</p> </li> <li> <p>Strategy analysis</p> </li> <li> <p>Iterative modeling</p> </li> </ul> <p>The real-world examples found in the book are drawn from a wide range of fields such as financial planning, insurance, pharmaceuticals, advertising, and manufacturing. Each chapter concludes with a discussion on how to use the insights drawn from these models to create an effective business presentation. Microsoft Office Excel and PowerPoint are used throughout the book, along with the add-ins Premium Solver, Crystal Ball, and Sensitivity Toolkit. Detailed appendices guide readers through the use of these software packages, and the spreadsheet models discussed in the book are available to download via the book's related Web site. <i>Modeling for Insight</i> is an ideal book for courses in engineering, operations research, and management science at the upper-undergraduate and graduate levels. It is also a valuable resource for consultants and business analysts who often use spreadsheets to better understand complex problems.</p>

"Most books on modeling are either too theoretical or too focused on the mechanics of programming. Powell and Batt's emphasis on using simple spreadsheet models to gain business insight (which is, after all, the name of the game) is what makes this book stand head and shoulders above the rest. This clear and practical book deserves a place on the shelf of every business analyst."<br /> —<b>Jonathan Koomey, PhD</b>, Lawrence Berkeley National Laboratory and Stanford University<i>,</i> author <i>Turning Numbers into Knowledge: Mastering the Art of Problem Solving</i>

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