How to Do Systems Analysis

John E. Gibson, PhD, was the Commonwealth Distinguished Professor of Systems Management at the School of  Engineering and Applied Science, University of Virginia, Charlottesville. He was the past dean of engineering at two universities: The University of Virginia and Oakland University. His research was in manufactruring strategy and management and in total quality leadership. Dr. Gibson received his PhD from Yale University.William T. Scherer, PhD, is Professor in the Department of Systems and Information Engineering at the University of Virginia where he teaches courses on systems engineering. He has authored and co-authored numerous publications on intelligent decision support systems, combinatorial optimization, and stochastic control. He is an associate editor for International Abstracts in Operations Research and reviewer for Operations Research, Annals of Operations Research, and IEEE Trans-actions on Intelligent Transportation Systems (ITS). He has held the Lucien Carr III Professorship of Engineering, recognition of his excellence in undergraduate education.

• Preface xiA Personal Note from William T. Scherer xvA Personal Note from William F. Gibson xviiA Personal Note from Scott F. Ferber xixOriginal Preface from Jack Gibson xxiAcknowledgments xxiii1 Introduction 11.1 What Is a System? 21.2 Terminology Confusion 41.3 Systems Analysis Equals Operations Research Plus Policy Analysis 61.4 Attributes of Large-Scale Systems 71.5 Intelligent Transportation Systems (ITS): An Example of a Large-Scale System 81.6 Systems Integration 111.7 What Makes a “Systems Analysis” Different? 121.8 Distant Roots of Systems Analysis 141.9 Immediate Precursors to Systems Analysis 151.10 Development of Systems Analysis As a Distinct Discipline: The Influence of RAND 17Historical Case Study: IIASA (A) 20Exercises 24Case Study: Fun at Six Flags? 25Historical Case Study: IIASA (B) 262 Six Major Phases of Systems Analysis 292.1 The Systems Analysis Method: Six Major Phases 292.2 The Goal-centered or Top-Down Approach 352.3 The Index of Performance Concept 402.4 Developing Alternative Scenarios 442.5 Ranking Alternatives 452.6 Iteration and the “Error-embracing” Approach 462.7 The Action Phase: The Life Cycle of a System 48Exercises 50Case Study: Methodologies or Chaos? Part A 51Case Study: Methodologies or Chaos? Part B 52Case Study: Wal-Mart Crisis! 533 Goal Development 553.1 Seven Steps in Goal Development 553.2 On Generalizing the Question 593.3 The Descriptive Scenario 613.4 The Normative Scenario 623.5 The Axiological Component 633.6 Developing an Objectives Tree 663.7 Fitch’s Goals for an Urbanizing America: An Example of Objectives Tree Construction 733.8 Content Analysis of Fitch’s Goals 793.9 Validate 823.10 Iterate 83Case Study: Distance Learning in the Future? 84Historical Case Study: Goals of 4C, Inc. 854 The Index of Performance 894.1 Introduction 894.2 Desirable Characteristics for an Index of Performance 914.3 Economic Criteria 954.4 Compound Interest 964.5 Four Common Criteria of Economic Efficiency 984.6 Is There a Problem with Multiple Criteria? 1004.7 What Is Wrong with the B–C Ratio? 1054.8 Can IRR Be Fixed? 1074.9 Expected Monetary Value 1094.10 Nonmonetary Performance Indices 111Exercises 114Case Study: Sky High Airlines 116Case Study: Bridges—Where to Spend the Security Dollars? 122Case Study: Measuring the Process and Outcomes of Regional Transportation Collaboration 122Case Study: Baseball Free Agent Draft 1235 Develop Alternative Candidate Solutions 1295.1 Introduction 1295.2 The Classical Approach to Creativity 1295.3 Concepts in Creativity 1315.4 Brainstorming 1325.5 Brainwriting 1355.6 Dynamic Confrontation 1375.7 Zwicky’s Morphological Box 1375.8 The Options Field/Options Profile Approach 1395.9 Computer Creativity 1435.10 Computer Simulation: a Tool in Option Development 1445.11 Why a Dynamic Simulation for Creating Options? 1455.12 Context-Free Simulation Models? 1475.13 Bottom-Up Simulation or Top-Down? 1485.14 Lessons from the Susquehanna River Basin Model 1515.15 The Forrester Urban Model (FUM) and Societal Values 1535.16 Extensions and Variations 1575.17 Where to go from Here? 159Exercises 159Case Study: Winnebago 160Case Study: Distance Learning in the Future? 160Historical Case Study: Real-Time Television Link with Mars Orbiter 160Historical Case Study: A Highway Vehicle Simulator RFP From DOT 1806 Rank Alternative Candidates 1856.1 Introduction 1856.2 Rating and Ranking Methods 1866.3 Condorcet and Arrow Voting Paradoxes 1886.4 A MultiStage Rating Process 1926.5 Decision Analysis 1976.6 Basic Axioms of Decision Theory 1996.7 Properties of Utility Functions 2036.8 Constructing a Utility Curve 2056.9 Some Decision Analysis Classic Examples 2076.10 Estimation Theory in Decision Analysis 2136.11 Some Practical Problems with Decision Analysis 2216.12 Practical Trade Studies 224Exercises 231Case Study: Training Center Location 234Case Study: Corporate Headquarters Location 235Case Study: Business School Selection 2367 Iteration and Transition 2397.1 Iteration 2397.2 Segment and Focus 2417.3 The Transition Scenario 2417.4 The Gantt Chart 2427.5 Interaction Matrices 2437.6 The Delta Chart 2487.7 The Audit Trail 2507.8 Cost of Failure to Stay on Schedule 2527.9 Responsibilities of Major Actors 2537.10 Sign-Offs by Cooperating Groups 253Exercises 2548 Management of the Systems Team 2578.1 Introduction 2578.2 Personal Style in an Interdisciplinary Team 2578.3 “Out-Scoping” and “In-Scoping” in a System Study 2608.4 Building the Systems Team 2618.5 Tips on Managing the Team 2638.6 Functional or Project Management? 2648.7 How to Make an Effective Oral Presentation 2668.8 How to Write a Report 2739 Project Management 2779.1 Introduction 2779.2 Project Management Versus Process Management 2799.3 The Hersey–Blanchard Four-Mode Theory 2819.4 Relation of Management Style to Project Management 2859.5 Preliminary Project Planning 2869.6 Dealing with Conflict in Project Management 2879.7 Life-Cycle Planning and Design 2889.8 PERT/CPM Program Planning Method: An Example 2929.9 Quality Control in Systems Projects 297Case Study: Project Management 29810 The 10 Golden Rules of Systems Analysis 30110.1 Introduction 30110.2 Rule 1: There Always Is a Client 30210.3 Rule 2: Your Client Does Not Understand His Own Problem 30310.4 Rule 3: The Original Problem Statement is too Specific: You Must Generalize the Problem to Give it Contextual Integrity 30410.5 Rule 4: The Client Does Not Understand the Concept of the Index of Performance 30610.6 Rule 5: You are the Analyst, Not the Decision-Maker 30910.7 Rule 6: Meet the Time Deadline and the Cost Budget 31010.8 Rule 7: Take a Goal-Centered Approach to the Problem, Not a Technology-Centered or Chronological Approach 31110.9 Rule 8: Nonusers Must be Considered in the Analysis and in the Final Recommendations 31210.10 Rule 9: The Universal Computer Model is a Fantasy 31410.11 Rule 10: The Role of Decision-Maker in Public Systems is Often a Confused One 314References 319Index 331

"[The] book is solidly grounded in the application of theory … .A very comprehensive book that junior or student systems analysts would find helpful for fundamental concepts." (The Computer Journal, January 2009) "…a real-world view of systems and how best to analyze them…recommended." (CHOICE, December 2007)