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Value-Added Decision Making for Managers [Hardback]

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(Abbott Laboratories, Abbott Park, Illinois, USA), (Wayne State University, Detroit, Michigan, USA)
  • Formāts: Hardback, 578 pages, height x width: 254x178 mm, weight: 1202 g, 200 Tables, black and white; 219 Illustrations, black and white
  • Izdošanas datums: 05-Oct-2011
  • Izdevniecība: Chapman & Hall/CRC
  • ISBN-10: 1420075721
  • ISBN-13: 9781420075724
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Value-Added Decision Making for ManagersPalielināt
  • Formāts: Hardback, 578 pages, height x width: 254x178 mm, weight: 1202 g, 200 Tables, black and white; 219 Illustrations, black and white
  • Izdošanas datums: 05-Oct-2011
  • Izdevniecība: Chapman & Hall/CRC
  • ISBN-10: 1420075721
  • ISBN-13: 9781420075724
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9781420075724.html
Keywords:

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.

Recenzijas

"[ 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, JulyAugust 2013

Preface xi
Acknowledgments xvii
Authors xix
Part I Structuring Hard Decisions
1(76)
1 The Case for a Structured Analytic Decision Process
3(26)
1.1 Goal and Overview
3(1)
1.2 The Challenge
3(2)
1.3 Decision Analysis Effectiveness
5(2)
1.4 Do Not Trust Your Gut
7(4)
1.5 Maximize versus Satisfice
11(2)
1.6 Established Biases
13(1)
1.7 What Makes a Decision Difficult?
14(3)
1.8 Symptoms of a Poor Decision-Making Process
17(5)
1.9 Transparent and Efficient Decision Making
22(7)
Appendix 1.A Other Modeling Tools
23(1)
1.A.1 Probabilistic Models
24(1)
1.A.2 Deterministic Models
24(1)
Exercises
25(1)
Complete
Chapter Activities
25(1)
Discuss the Factors That Made the Following Decisions Difficult
26(1)
References
27(2)
2 Influence Diagrams: Framing Multi-Objective and Uncertain Decisions
29(22)
2.1 Goal and Overview
29(1)
2.2 Components of an Influence Diagram
30(5)
2.3 Learn by Simple Example: Automation Investment
35(1)
2.4 Divide and Delay Decision: Plan an RSVP Theater Party
36(1)
2.5 Arrows in Complex Influence Diagram: New Product Late-to-Market
37(5)
2.6 Multiple Objective Influence Diagram: Buying a Used Car
42(2)
2.7 Oglethorpe Power Corporation: Actual Case
44(1)
2.8 Influence Diagram Construction: Review
45(1)
2.9 Solving Influence Diagrams
46(1)
2.10 Recent Articles on Influence Diagrams
46(5)
Exercises
47(2)
References
49(2)
3 Common Decision Templates
51(26)
3.1 Goal and Overview
51(1)
3.2 In-House or Outsource (Make or Buy)
51(3)
3.3 Change (Upgrade) or Keep Status Quo
54(2)
3.4 Products: Launch, Portfolios, and Project Management
56(3)
3.5 Project Management: Product Development
59(1)
3.6 Capacity Planning
60(2)
3.7 Technology Choice
62(2)
3.8 Personnel and Organizational Selection: Hire Faculty
64(2)
3.9 Facility Location: Sports Arena
66(2)
3.10 Bidding: Make Offer
68(2)
3.11 Personal: University Selection
70(1)
3.12 Information Gathering: Market Research, Prototypes, and Pilot Plants
71(1)
3.13 Summary
72(5)
Exercises
73(1)
References
73(4)
Part II Decisions with Multiple Objectives
77(158)
4 Structure Decisions with Multiple Objectives
79(36)
4.1 Goal and Overview
79(2)
4.2 Description of the Overall MAUT Process
81(3)
4.3 Basic Terminology
84(1)
4.4 Fundamental Objectives
85(2)
4.5 Objectives Hierarchy: Examples
87(2)
4.6 Top-Down Approach: Global Facility Location
89(2)
4.7 Bottom-Up Approach: Kitchen Remodeling
91(3)
4.8 Measures
94(4)
4.9 Example: Buy a Used Car
98(2)
4.10 Identify Alternatives
100(2)
4.11 Real-World Applications
102(13)
Exercises
111(1)
Complete
Chapter Activities
111(1)
Cases
111(2)
References
113(2)
5 Structured Trade-Offs for Multiple Objective Decisions: Multi-Attribute Utility Theory
115(54)
5.1 Goal and Overview
115(2)
5.2 Concepts and Terminology
117(2)
5.3 Compare Alternatives
119(1)
5.4 Trade-Off Conflicting Objectives
120(5)
5.5 Single-Measure Utility Function: Proportional Scores
125(1)
5.6 Aggregate Utility: Total Score for Each Alternative
126(4)
5.7 Assessing Weights Revisited: Large Set of Measures
130(7)
5.8 Assess Individual (Single-Measure) Utility Function: Nonlinear Utility Functions and Constructed Measures
137(6)
5.9 Group Decision Making
143(4)
5.10 Uncertainty
147(1)
5.11 Contractor Selection for Kitchen Remodeling
148(2)
5.12 Real-World Application: Multi-Attribute Risk Analysis in Nuclear Emergency Management
150(3)
5.13 Selection of Best Conformal Coating Process
153(5)
5.14 Nonlinear Additivity: Multiplicative Form
158(2)
5.15 Research Issues with Weight Elicitation
160(9)
Exercises
161(1)
Complete
Chapter Activities
161(1)
Cases
162(2)
Background Information
164(3)
References
167(2)
6 Value and Risk Management for Multi-Objective Decisions
169(34)
6.1 Goal and Overview
169(3)
6.2 Synthesize Weighted Sum
172(4)
6.3 Comparison of Two Alternatives
176(1)
6.4 Robustness of a Decision Using Sensitivity Analysis
176(2)
6.5 Value Enhancement with Hybrid: Lighting Example
178(1)
6.6 Better Alternative through Value Enhancement: Kitchen Remodeling
179(3)
6.7 Value Enhancement: Warehouse Selection
182(4)
6.8 Value Enhancement and Risk Management: Process Selection
186(2)
6.9 Risk Analysis and Management
188(4)
6.10 MAUT and Subject Matter Experts: Process
192(2)
6.11 Applications
194(9)
Exercises
198(1)
References
199(4)
7 Multiple Objective Decisions with Limited Data: Analytical Hierarchy Process
203(32)
7.1 Goal and Overview
203(2)
7.2 AHP Procedure Details and Snow Blower Example
205(8)
7.3 Commercial Snow Throwers Selection
213(4)
7.4 Select a Job
217(5)
7.5 Software Selection
222(1)
7.6 Growth of AHP Pair-Wise Comparison Effort
223(2)
7.7 Comparison of AHP vs. MAUT
225(3)
7.8 Application Capsule: Compare AHP with MAUT: A Case Study
228(7)
Appendix 7.A Consistency Ratio
230(1)
7.A.1 Consistency Measurement
230(1)
Exercises
231(2)
References
233(2)
Part III Decisions and Management under Uncertainty
235(156)
8 Value-Added Risk Management Framework and Strategies
237(20)
8.1 Goal and Overview
237(2)
8.2 Overview of the Risk Management Process
239(1)
8.3 Risk Identification
240(3)
8.4 Risk Quantification
243(3)
8.5 Systems Risk Analysis
246(1)
8.6 Risk Mitigation Framework
247(2)
8.7 Risk Communication, Perception, and Awareness
249(1)
8.8 Alternative Risk Mitigation and Elimination Strategies
250(7)
Exercises
254(1)
References
255(2)
9 Spreadsheet Simulation for Decisions with Uncertainty
257(20)
9.1 Goal and Overview
257(1)
9.2 Using @Risk Spreadsheet Simulation
258(1)
9.3 Project Acceleration Investment
258(4)
9.4 Profit Forecasting for Drug Development
262(3)
9.5 Global Sourcing Risk Analysis
265(6)
9.6 Real-World Applications @Risk
271(6)
Exercises
272(2)
References
274(3)
10 Decisions with Uncertainty: Decision Trees
277(48)
10.1 Goal and Overview
277(1)
10.2 Early Users of Decision Trees
278(1)
10.3 Concepts
279(1)
10.4 Influence Diagrams and Schematic Trees
280(5)
10.5 Constructing and Analyzing a Simple Decision Tree
285(5)
10.6 Risk Profile/Cumulative Risk Profile
290(1)
10.7 Complex Symmetric Decision Tree: Make or Buy
291(9)
10.8 Asymmetric Tree: Design Change
300(2)
10.9 Sequential Decisions
302(4)
10.10 Robustness of Optimal Solution through Sensitivity Analysis
306(4)
10.11 Real World Applications
310(15)
Basic Terminology/Glossary of Terms
313(1)
Exercises
314(1)
Complete
Chapter Activities
314(1)
Decision Tree Examples
314(6)
Decision Trees: Cases
320(3)
References
323(2)
11 Structured Risk Management and the Value of Information and Delay
325(38)
11.1 Goal and Overview
325(1)
11.2 Identify High-Impact Variables
326(3)
11.3 Risk Profiles and Structured Risk Management
329(3)
11.4 Make or Buy Example: Discrete Decision Tree Analysis
332(3)
11.5 Perfect and Imperfect Information
335(5)
11.6 Imperfect Information: Bayes' Theorem
340(11)
11.7 Conditional Decisions and Information Seeking Trees: Flu Virus Detection Technology
351(1)
11.8 Contingent Contracts Reduce Risk
351(4)
11.9 Real Options
355(8)
Exercises
358(3)
References
361(2)
12 Risk Attitude and Utility Theory
363(28)
12.1 Goals and Overview
363(1)
12.2 Utility Theory: Concepts and Terminology
364(5)
12.3 Utility Function Assessment
369(4)
12.4 Change the Risk Equation: Insurance and Risk Sharing
373(7)
12.5 Case Study: Phillips Petroleum and Onshore U.S. Oil Exploration
380(1)
12.6 Utility Theory: Practical and Theoretical Challenges
381(3)
12.7 Current Research in Utility Theory
384(7)
Exercises
386(1)
Complete
Chapter Activities
386(1)
Utility Theory Examples
386(1)
References
387(4)
Part IV Challenges to "Rational" Decisions
391(54)
13 Forecast Bias and Expert Interviews
393(30)
13.1 Goals and Overview
393(2)
13.2 Motivational and Personal Biases
395(2)
13.3 Point Estimate and Narrow Ranges: Overconfidence
397(6)
13.4 Faulty Probability Reasoning
403(1)
13.5 Availability and Representativeness
404(2)
13.6 Confirmation and Interpretation Bias
406(1)
13.7 Expert Interview: How to Identify and Reduce Bias
407(10)
13.8 Research into Probabilistic Forecasts
417(6)
Appendix 13.A: Phrases: Bad Alternative to Actual Quantification
418(1)
Appendix 13.B
419(1)
Exercises
419(1)
Complete
Chapter Activities
419(1)
References
420(3)
14 Decision Bias
423(22)
14.1 Goal and Overview
423(1)
14.2 Sunk Cost and Escalation of Commitment
424(3)
14.3 Framing Bias
427(2)
14.4 Status Quo and Omission Bias
429(2)
14.5 Regret
431(2)
14.6 Fairness
433(2)
14.7 Mood
435(2)
14.8 Groupthink, Optimism, and Miscellaneous Biases
437(8)
Exercises
438(1)
Complete
Chapter Activities
438(1)
References
439(6)
Part V Decisions with Multiple Perspectives
445(96)
15 Value-Added Negotiations
Hal Stack
447(1)
15.1 Goal and Overview
447(1)
15.2 Understanding Negotiations
448(2)
15.3 Challenges to Effective Negotiation
450(3)
15.4 Managing the Negotiation Process
453(7)
15.5 Negotiating a Deal
460(2)
15.6 Negotiating a Dispute
462(1)
15.7 Agents and Multiparty Negotiations
463(1)
15.8 Negotiating across Border
464(5)
15.9 Negotiating Ethically
469(2)
15.10 Conclusion
471(6)
Exercises
471(1)
Complete
Chapter Activities
471(1)
Additional Exercises
472(2)
References
474(3)
16 Ethical Decisions
Dean W. Pichette
477(1)
16.1 Goal and Overview
477(2)
16.2 Ethical Decision-Making Framework
479(1)
16.3 Values
480(6)
16.4 Biases, Myopia, and Don't Want to Know
486(6)
16.5 Pressures Undermine Ethical Balance
492(7)
16.6 Short Cases
499(16)
Exercises
509(1)
Complete
Chapter Activities
509(1)
Case
510(1)
Alternatives
511(1)
Whistle Blowing/Speaking Out
511(1)
References
512(3)
17 Strategic Direction, Planning, and Decision Making
515(26)
17.1 Goal and Overview
515(1)
17.2 Strategic Planning
515(2)
17.3 Elements of Strategic Decisions
517(3)
17.4 Situation Assessment: SWOT Analysis
520(5)
17.5 Basic Tools: Decision Hierarchy and Strategy Table
525(2)
17.6 Strategy Development Steps for Large Organizations
527(6)
17.7 Scenario Planning
533(8)
Exercises
538(1)
Complete
Chapter Activities
538(1)
Elements of Scenario Planning Trends and Uncertainties
539(1)
References
539(2)
Appendix A Instructions for Downloading the DecisionTools Suite 541(2)
Appendix B Instructions for Downloading Logical Decisions 543(2)
Index 545
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.