1st Edition
Value-Added Decision Making for Managers
Developed from the authors’ longstanding course on decision and risk analysis, Value-Added Decision Making for Managers explores the important interaction between decisions and management action and clarifies the barriers to rational decision making. The authors analyze strengths and weaknesses of the best alternatives, enabling decision makers to improve on these alternatives by adding value and reducing risk.
The core of the text addresses decisions that involve selecting the best alternative from diverse choices. The decisions include buying a car, picking a supplier or home contractor, selecting a technology, picking a location for a manufacturing plant or sports stadium, hiring an employee or selecting among job offers, deciding on the size of a sales force, making a late design change, and sourcing to emerging markets. The book also covers more complex decisions arising in negotiations, strategy, and ethics that involve multiple dimensions simultaneously.
Numerous activities interspersed throughout the text highlight real-world situations, helping readers see how the concepts presented can be used in their own work environment or personal life. Each chapter also includes discussion questions and references.
Web Resource
The book’s website at http://ise.wayne.edu/research/decision.php offers tutorials of Logical Decisions software for multi-objective decisions and Precision Tree software for probabilistic decisions. Directions for downloading student versions of the DecisionTools Suite and Logical Decisions software can be found in the appendices. Password-protected PowerPoint presentations for each chapter and solutions to all of the numeric examples are available for instructors.
STRUCTURING HARD DECISIONS
The Case for a Structured Analytic Decision Process
Goal and Overview
The Challenge
Decision Analysis Effectiveness
Do Not Trust Your Gut
Maximize versus Satisfice
Established Biases
What Makes a Decision Difficult?
Symptoms of a Poor Decision Making Process
Transparent and Efficient Decision Making
Framing Decisions with Influence Diagrams
Goal and Overview
Components of an Influence Diagram
Learn by Simple Example: Automation Investment
Divide and Delay Decision: Plan an RSVP Theater Party
Arrows in Complex Influence Diagram: New Product Late-to-Market
Multiple Objective Influence Diagram: Buying a Used Car
Oglethorpe Power Corporation: Actual Case
Influence Diagram Construction: Review
Solving Influence Diagrams
Recent Articles on Influence Diagrams
Common Decision Templates
Goal and Overview
In-House or Outsource (Make or Buy)
Change (Upgrade) or Keep Status Quo
Products: Launch, Portfolios, and Project Management
Project Management: Product Development
Capacity Planning
Technology Choice
Personnel and Organizational Selection: Hire Faculty
Facility Location: Sports Arena
Bidding: Make Offer
Personal: University Selection
Information Gathering: Market Research, Prototypes, and Pilot Plants
Summary
DECISIONS WITH MULTIPLE OBJECTIVES
Structure Decisions with Multiple Objectives
Goal and Overview
Description of the Overall MAUT Process
Basic Terminology
Fundamental Objectives
Objectives Hierarchy: Examples
Top-Down Approach: Global Facility Location
Bottom-Up Approach: Kitchen Remodeling
Measures
Example: Buy a Used Car
Identify Alternatives
Real-World Applications
Structured Trade-Offs for Multiple Objective Decisions: Multi-Attribute Utility Theory
Goal and Overview
Concepts and Terminology
Compare Alternatives
Trade-Off Conflicting Objectives
Single-Measure Utility Function: Proportional Scores
Aggregate Utility: Total Score for Each Alternative
Assessing Weights Revisited: Large Set of Measures
Assess Individual (Single-Measure) Utility Function: Nonlinear Utility Functions and Constructed Measures
Group Decision Making
Uncertainty
Contractor Selection for Kitchen Remodeling
Real-World Application: Multi-Attribute Risk Analysis in Nuclear Emergency Management
Selection of Best Conformal Coating Process
Nonlinear Additivity: Multiplicative Form
Research Issues with Weight Elicitation
Value and Risk Management for Multi-Objective Decisions
Goal and Overview
Synthesize Weighted Sum
Comparison of Two Alternatives
Robustness of a Decision Using Sensitivity Analysis
Value Enhancement with Hybrid: Lighting Example
Better Alternative through Value Enhancement: Kitchen Remodeling
Value Enhancement: Warehouse Selection
Value Enhancement and Risk Management: Process Selection
Risk Analysis and Management
MAUT and Subject Matter Experts: Process
Applications
Multiple Objective Decisions with Limited Data: Analytical Hierarchy Process
Goal and Overview
AHP Procedure Details and Snow Blower Example
Commercial Snow Throwers Selection
Select a Job
Software Selection
Growth of AHP Pair-Wise Comparison Effort
Comparison of AHP versus MAUT
Application Capsule: Compare AHP with MAUT: A Case Study
DECISIONS AND MANAGEMENT UNDER UNCERTAINTY
Value-Added Risk-Management Framework and Strategies
Goal and Overview
Overview of the Risk Management Process
Risk Identification
Risk Quantification
Systems Risk Analysis
Risk Mitigation Framework
Risk Communication, Perception, and Awareness
Alternative Risk Mitigation and Elimination Strategies
Spreadsheet Simulation for Decisions with Uncertainty
Goal and Overview
Using @Risk Spreadsheet Simulation
Project Acceleration Investment
Profit Forecasting for Drug Development
Global Sourcing Risk Analysis
Real-World Applications @Risk
Decisions with Uncertainty: Decision Trees
Goal and Overview
Early Users of Decision Trees
Concepts
Influence Diagrams and Schematic Trees
Constructing and Analyzing a Simple Decision Tree
Risk Profile/Cumulative Risk Profile
Complex Symmetric Decision Tree: Make or Buy
Asymmetric Tree: Design Change
Sequential Decisions
Robustness of Optimal Solution through Sensitivity Analysis
Real-World Applications
Structured Risk Management and the Value of Information and Delay
Goal and Overview
Identify High-Impact Variables
Risk Profiles and Structured Risk Management
Make or Buy Example: Discrete Decision Tree Analysis
Perfect and Imperfect Information
Imperfect Information: Bayes’ Theorem
Conditional Decisions and Information Seeking Trees: Flu Virus Detection Technology
Contingent Contracts Reduce Risk
Real Options
Risk Attitude and Utility Theory
Goals and Overview
Utility Theory: Concepts and Terminology
Utility Function Assessment
Change the Risk Equation: Insurance and Risk Sharing
Case Study: Phillips Petroleum and Onshore U.S. Oil Exploration
Utility Theory: Practical and Theoretical Challenges
Current Research in Utility Theory
CHALLENGES TO "RATIONAL" DECISIONS
Forecast Bias and Expert Interviews
Goals and Overview
Motivational and Personal Biases
Point Estimate and Narrow Ranges: Overconfidence
Faulty Probability Reasoning
Availability and Representativeness
Confirmation and Interpretation Bias
Expert Interview: How to Identify and Reduce Bias
Research into Probabilistic Forecasts
Decision Bias
Goal and Overview
Sunk Cost and Escalation of Commitment
Framing Bias
Status Quo and Omission Bias
Regret
Fairness
Mood
Groupthink, Optimism, and Miscellaneous Biases
DECISIONS WITH MULTIPLE PERSPECTIVES
Value-Added Negotiations
Goal and Overview
Understanding Negotiations
Challenges to Effective Negotiation
Managing the Negotiation Process
Negotiating a Deal
Negotiating a Dispute
Agents and Multiparty Negotiations
Negotiating across Border
Negotiating Ethically
Conclusion
Ethical Decisions
Goal and Overview
Ethical Decision-Making Framework
Values
Biases, Myopia, and Don’t Want to Know
Pressures Undermine Ethical Balance
Short Cases
Strategic Direction, Planning, and Decision Making
Goal and Overview
Strategic Planning
Elements of Strategic Decisions
Situation Assessment: SWOT Analysis
Basic Tools: Decision Hierarchy and Strategy Table
Strategy Development Steps for Large Organizations
Scenario Planning
Appendix A: Instructions for Downloading the DecisionTools Suite
Appendix B: Instructions for Downloading Logical Decisions
Index
Exercises and References appear at the end of each chapter.
Biography
Kenneth Chelst is a professor of operations research and director of engineering management programs in the Department of Industrial and Systems Engineering at Wayne State University. An Edelman Award finalist, he is also co-principal investigator of the NSF-funded Project MINDSET and a senior consultant for the International City and County Management Association. He earned a Ph.D. in operations research from MIT. His research interests include engineering management, emergency service management, global engineering, and the use of operations research to enhance K-12 mathematics education.
Yavuz Burak Canbolat is a senior manager in the Decision Support Group at Abbott Laboratories. He was previously an associate manager in decision analysis for Merck & Co., Inc., and an instructor in the Industrial Engineering Department at Qafqaz University. He earned a Ph.D. in industrial engineering from Wayne State University. His research interests include decision analysis and operations research techniques in R&D portfolio evaluation and management, strategic planning, financial and economic analysis, global operations and logistics, risk analysis, and capacity planning.
"[The authors] introduce all concepts and methods using realistic decision-making examples to make them relevant to practitioners. This style also makes the description of the processes easy to comprehend and apply. … I was impressed with the presentation and development of the materials. Because it avoids purely technical topics, this book is easy to read and would make an excellent textbook for a practical course on decision making with multiple objectives and under uncertainty."
—Matthias Ehrgott, The University of Auckland, Interfaces, July–August 2013