JOHN E. GIBSON, Ph.D., was the Commonwealth Distinguished Professor of Systems Management at the School of Engineering and Applied Science, University of Virginia, Charlottesville. He served as Dean of Engineering at the University of Virginia and at Oakland University. Dr. Gibson was working on this book at the time of his death.

WILLIAM T. SCHERER, Ph.D., is a Professor in the Department of Systems and Information Engineering at the University of Virginia, where he teaches courses on systems engineering. Dr. Scherer was a student in Dr. Gibson's classes and later became a colleague. Dr. Scherer has authored and co-authored numerous publications on intelligent decision support systems, stochastic control, systems engineering education, and financial engineering. He is a former President of IEEE Intelligent Transportation Systems (ITS) Society and has won numerous teaching awards while at the University of Virginia.

WILLIAM F. GIBSON, MBA, MPA, is the Senior Managing Director and President of IVY Creek Associates, an international consulting firm for global asset managers, brokerage firms, and banks. He was Global Chief Operating Officer at ING Investment Management, and the Head of Securities and Fund Services Operations—EMEA at Citigroup. Mr. Gibson has led the infrastructure groups of global financial services firms, and is actively engaged in developing and applying new technologies in those domains. He has also been an executive lecturer at the S.C. Johnson Graduate School of Management at Cornell University.

MICHAEL C. SMITH, Ph.D., is the Executive Director of the Accelerated Masters Program in Systems Engineering at the University of Virginia. Prior to joining the University of Virginia, Dr. Smith was a Senior Scientist at Science Applications International Corporation (now Leidos) and also served on the Industrial Engineering faculties at Oregon State University and the University of Missouri. In addition to directing the University of Virginia's Accelerated Master's Program, Dr. Smith teaches an introductory course in systems thinking and the systems approach, drawing on many of the case studies in this book.

Preface ix

Original Preface from Jack Gibson xiii

Acknowledgments xv

About the Companion Website xvii

Part One: Primer

1. Introduction 3

1.1 What is a System? 4

1.2 Terminology Confusion 6

1.3 Systems Analysis Equals Operations Research Plus Policy Analysis 10

1.4 Attributes of Large-Scale Systems 11

1.5 Transportation Systems: An Example of a Large-Scale System 13

1.6 Systems Integration 16

1.7 What Makes a “Systems Analysis” Different? 17

1.8 Distant Roots of Systems Analysis 19

1.9 Immediate Precursors to Systems Analysis 20

1.10 Development of Systems Analysis as a Distinct Discipline: The Influence of RAND 23

References 26

2. Six Major Phases of Systems Analysis 28

2.1 The Systems Analysis Method: Six Major Phases 28

2.1.1 Determine Goals 28

2.1.2 Establish Criteria for Ranking Alternative Candidates 30

2.1.3 Develop Alternative Solutions 31

2.1.4 Rank Alternatives 32

2.1.5 Iterate 34

2.1.6 Action 35

2.2 The Goal-Centered or Top-Down Approach 35

2.3 The Index of Performance Concept 41

2.4 Developing Alternative Scenarios 45

2.5 Ranking Alternatives 47

2.6 Iteration and the “Error-Embracing” Approach 47

2.7 The Action Phase: The Life Cycle of a System 51

References 53

3. Goal Development 55

3.1 Seven Steps in Goal Development 55

3.2 On Generalizing the Question 59

3.3 The Descriptive Scenario 61

3.4 The Normative Scenario 63

3.5 The Axiological Component 63

3.6 Developing an Objectives Tree 67

3.7 Validate 73

3.8 Iterate 74

References 75

4. The Index of Performance 76

4.1 Introduction 76

4.2 Desirable Characteristics for an Index of Performance 78

4.3 Economic Criteria 81

4.4 Four Common Criteria of Economic Efficiency 83

4.5 Is There a Problem with Multiple Criteria? 86

4.6 What is Wrong with the B–C Ratio? 90

4.7 Can IRR be Fixed? 92

4.8 Expected Monetary Value 94

4.9 Nonmonetary Performance Indices 96

References 99

5. Develop and Evaluate Alternative Candidate Solutions 101

5.1 Introduction 101

5.2 The Classical Approach to Creativity 101

5.3 Concepts in Creativity 103

5.4 Brainstorming 104

5.5 Brainwriting 107

5.6 Dynamic Confrontation 109

5.7 Zwicky’s Morphological Box 110

5.8 The Options Field/Options Profile Approach 112

5.9 Computer Creativity 115

5.10 Trade Study Methods 116

5.11 Trade Study Example 120

References 127

6. The 10 Golden Rules of Systems Analysis 130

6.1 Introduction 130

6.2 Rule 1: There Always is a Client 131

6.3 Rule 2: Your Client Does Not Understand His Own Problem 132

6.4 Rule 3: The Original Problem Statement is too Specific: You Must Generalize the Problem to Give it Contextual Integrity 133

6.5 Rule 4: The Client Does Not Understand the Concept of the Index of Performance 135

6.6 Rule 5: You are the Analyst, Not the Decision Maker 137

6.7 Rule 6: Meet the Time Deadline and the Cost Budget 139

6.8 Rule 7: Take a Goal-Centered Approach to the Problem, not a Technology-Centered or Chronological Approach 140

6.9 Rule 8: Non-users Must Be Considered in the Analysis and in the Final Recommendations 141

6.10 Rule 9: The Universal Computer Model is a Fantasy 143

6.11 Rule 10: The Role of Decision Maker in Public Systems is Often a Confused One 143

References 145

Part Two: Casebook

Cases in Systems Engineering 149

Introduction 149

The Case Study Method 151

What is a “Case”? 152

Implementing the Case Study Method 152

Chat Rooms and Polls 152

In-Class Group Activities 153

Case Study Assignments 153

Peer Review 154

The Case Studies 154

Using Case Studies to Build Teamwork and Communications Skills 154

Building the Systems Team 155

Tips on Managing the Team 156

How to Make an Effective Oral Presentation 157

How to Write a Report 162

Aligning Case Studies with the Ten Golden Rules of Systems Analysis 164

To Winnebago or to not Winnebago? 164

How can this Case be Used to Teach and Reinforce Systems Analysis? 169

A Word about the Cases 170

Validation of Learning: Evidence-Based Learning 170

Sample Evaluation Instrument: Exam with Solutions 171

Sample Evaluation Instrument: Exam without Solutions 176

Case 1: Great Buys 183

Case 2: Surf’s Up? 188

Case 3: Extended Engineering Education 189

Case 4: Systems Engineering Majors Proliferating 192

Case 5: Motor Carrier Safety and Compliance 193

Case 6: Is Getting There Half the Fun? 202

Case 7: Is Getting There Half the Fun? (Revisited) 206

Case 8: Which Camper Should We Choose? 210

Case 9: Seat Belt Issue 217

Case 10: Baseball Free Agent Draft—20xx 219

Case 11: For the Birds? 221

Case 12: Wal-Mart Crisis 222

Case 13: Ocean Cleanup 224

Case 14: BRAC 226

Case 15: Opportunity? 227

Case 16: Risky Business 228

Case 17: Corporate Headquarters 230

Case 18: The Ad Forecaster 231

Case 19: For the Birds (Revisited) 232

Case 20: Best MBA? 234

Case 21: Health Insurance? What Health Insurance? 235

Case 22: Social Media in Emergency Management 237

Case 23: Which Bridges to Repair? 241

Case 24: Going-to-the-Sun Road Rehabilitation Project 245

Case 25: HEV versus HOV? 256

Case 26: “Show Me the Money!” 259

Case 27: The Collections Subsidiary 261

Case 28: MNB One Credit Card Portfolio 266

Case 29: Select Collections 273

Case 30: To Distance or Not to Distance? Is That the Question? 278

Index 279

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