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Handbook of decision analysis

Author: Gregory S Parnell
Publisher: Hoboken, New Jersey : Wiley, ©2012.
Edition/Format:   eBook : Document : English
Summary:
"Decision analysis provides powerful tools for addressing complex decisions that involve uncertainty and multiple objectives, yet most training materials on the subject overlook the soft skills that are essential for success in the field. This unique resource fills this gap in the decision analysis literature and features both soft personal/interpersonal skills and the hard technical skills involving mathematics and  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Handbook of decision analysis.
Hoboken, N.J. : John Wiley & Sons, ©2012
(DLC) 2012032884
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Gregory S Parnell
ISBN: 9781118515846 1118515846 9781118515839 1118515838 9781118515822 111851582X 9781118515853 1118515854 1118173139 9781118173138
OCLC Number: 806981314
Description: 1 online resource.
Contents: Chapter One. Introduction to Decision Analysis --
Chapter Two. Decision-Making Challenges --
Chapter Three. Foundations of Decision Analysis --
Chapter Four. Decision Analysis Soft Skills --
Chapter Five. Use the Appropriate Decision Process --
Chapter Six. Frame the Decision Opportunity --
Chapter Seven. Craft the Decision Objectives and Value Measures --
Chapter Eight. Design Creative Alternatives. Chapter One. Introduction to Decision Analysis --
1.1. Introduction --
1.2. Decision Analysis Is a Socio-Technical Process --
1.3. Decision Analysis Applications --
1.3.1. Oil and Gas Decision Analysis Success Story: Chevron --
1.3.2. Pharmaceutical Decision Analysis Success Story: SmithKline Beecham --
1.3.3. Military Decision Analysis Success Stories --
1.4. Decision Analysis Practitioners and Professionals --
1.4.1. Education and Training --
1.4.2. Decision Analysis Professional Organizations --
1.4.3. Problem Domain Professional Societies --
1.4.4. Professional Service --
1.5. Handbook Overview and Illustrative Examples --
1.5.1. Roughneck North American Strategy (RNAS) (by Eric R. Johnson) --
1.5.2. Geneptin Personalized Medicine for Breast Cancer (by Sean Xinghua Hu) --
1.5.3. Data Center Location and IT Portfolio (by Gregory S. Parnell and Terry A. Bresnick) --
1.6. Summary --
Chapter Two. Decision-Making Challenges --
2.1. Introduction --
2.2. Human Decision Making --
2.3. Decision-Making Challenges --
2.4. Organizational Decision Processes --
2.4.1. Culture --
2.4.2. Impact of Stakeholders --
2.4.3. Decision Level (Strategic, Operational, and Tactical) --
2.5. Credible Problem Domain Knowledge --
2.5.1. Dispersion of Knowledge --
2.5.2. Technical Knowledge: Essential for Credibility --
2.5.3. Business Knowledge: Essential for Success --
2.5.4. Role of Experts --
2.5.5. Limitations of Experts --
2.6. Behavioral Decision Analysis Insights --
2.6.1. Decision Traps and Barriers --
2.6.2. Cognitive Biases --
2.7. Two Anecdotes: Long-Term Success and a Temporary Success of Supporting the Human Decision-Making Process --
2.8. Setting the Human Decision-Making Context for the Illustrative Example Problems --
2.8.1. Roughneck North American Strategy (by Eric R. Johnson) --
2.8.2. Geneptin Personalized Medicine (by Sean Xinghua Hu) --
2.8.3. Data Center Decision Problem (by Gregory S. Parnell) --
2.9. Summary --
Chapter Three. Foundations of Decision Analysis --
3.1. Introduction --
3.2. Brief History of the Foundations of Decision Analysis --
3.3. Five Rules: Theoretical Foundation of Decision Analysis --
3.4. Scope of Decision Analysis --
3.5. Taxonomy of Decision Analysis Practice --
3.5.1. Terminology --
3.5.2. Taxonomy Division: Single or Multiple Objectives --
3.5.3. Single-Objective Decision Analysis --
3.5.4. Multiple-Objective Decision Analysis --
3.5.5. Taxonomy Division: Addressing Value Trade-Offs and Risk Preference Separately or Together? --
3.5.6. Taxonomy Division: Nonmonetary or Monetary Value Metric? --
3.5.7. Taxonomy Division: Degree of Simplicity in Multidimensional Value Function --
3.6. Value-Focused Thinking --
3.6.1. Four Major VFT Ideas --
3.6.2. The Benefits of VFT --
3.7. Summary --
Chapter Four. Decision Analysis Soft Skills --
4.1. Introduction --
4.2. Thinking Strategically --
4.3. Leading Decision Analysis Teams --
4.4. Managing Decision Analysis Projects --
4.5. Researching --
4.6. Interviewing Individuals --
4.6.1. Before the Interview --
4.6.2. Schedule/Reschedule the Interview --
4.6.3. During the Interview --
4.6.4. After the Interview --
4.7. Conducting Surveys --
4.7.1. Preparing an Effective Survey: Determine the Goals, Survey Respondents, and Means of Distributing and Collecting Survey Data --
4.7.2. Executing a Survey Instrument: Developing the Survey Questions, Testing, and Distributing the Survey --
4.8. Facilitating Groups --
4.8.1. Facilitation Basics --
4.8.2. Group Processes --
4.8.3. Focus Groups --
4.9. Aggregating across Experts --
4.10. Communicating Analysis Insights --
4.11. Summary --
Chapter Five. Use the Appropriate Decision Process --
5.1. Introduction --
5.2. What Is a Good Decision? --
5.2.1. Decision Quality --
5.2.2. The Six Elements of Decision Quality --
5.2.3. Intuitive versus Deliberative Decision Making --
5.3. Selecting the Appropriate Decision Process --
5.3.1. Tailoring the Decision Process to the Decision --
5.3.2. Two Best Practice Decision Processes --
5.3.3. Two Flawed Decision Processes --
5.4. Decision Processes in Illustrative Examples --
5.4.1. Roughneck North American Oil Strategy --
5.4.2. Geneptin Personalized Medicine --
5.4.3. Data Center --
5.5. Organizational Decision Quality --
5.6. Decision Maker's Bill of Rights --
5.7. Summary. Chapter Six. Frame the Decision Opportunity --
6.1. Introduction --
6.2. Declaring a Decision --
6.3. What Is a Good Decision Frame? --
6.4. Achieving a Good Decision Frame --
6.4.1. Vision Statement --
6.4.2. Issue Raising --
6.4.3. Categorization of Issues --
6.4.4. Decision Hierarchy --
6.4.5. Values and Trade-Offs --
6.4.6. Initial Influence Diagram --
6.4.7. Decision Schedule and Logistics --
6.5. Framing the Decision Opportunities for the Illustrative Examples --
6.5.1. Roughneck North American Strategy (RNAS) --
6.5.2. Geneptin Personalized Medicine --
6.5.3. Data Center Decision --
6.6. Summary --
Chapter Seven. Craft the Decision Objectives and Value Measures --
7.1. Introduction --
7.2. Shareholder and Stakeholder Value --
7.2.1. Private Company Example --
7.2.2. Government Agency Example --
7.3. Challenges in Identifying Objectives --
7.4. Identifying the Decision Objectives --
7.4.1. Questions to Help Identify Decision Objectives --
7.4.2. How to Get Answers to the Questions --
7.5. The Financial or Cost Objective --
7.5.1. Financial Objectives for Private Companies --
7.5.2. Cost Objective for Public Organizations --
7.6. Developing Value Measures --
7.7. Structuring Multiple Objectives --
7.7.1. Value Hierarchies --
7.7.2. Techniques for Developing Value Hierarchies --
7.7.3. Value Hierarchy Best Practices --
7.7.4. Cautions about Cost and Risk Objectives --
7.8. Illustrative Examples --
7.8.1. Roughneck North American Strategy (by Eric R. Johnson) --
7.8.2. Geneptin (by Sean Xinghua Hu) --
7.8.3. Data Center Location (by Gregory S. Parnell) --
7.9. Summary --
Chapter Eight. Design Creative Alternatives --
8.1. Introduction --
8.2. Characteristics of a Good Set of Alternatives --
8.3. Obstacles to Creating a Good Set of Alternatives --
8.4. The Expansive Phase of Creating Alternatives --
8.5. The Reductive Phase of Creating Alternatives --
8.6. Improving the Set of Alternatives --
8.7. Illustrative Examples --
8.7.1. Roughneck North American Strategy (by Eric R. Johnson) --
8.7.2. Geneptin Personalized Medicine (by Sean Xinghua Hu) --
8.7.3. Data Center Location (by Gregory S. Parnell) --
8.8. Summary --
9.1. Introduction --
9.2. Planning the Model: Influence Diagrams --
9.3. Spreadsheet Software as the Modeling Platform --
9.4. Guidelines for Building a Spreadsheet Decision Model --
9.4.1. Keep Inputs Separated from Calculations --
9.4.2. Parameterize Everything --
9.4.3. Use Range Names for Readability --
9.4.4. Use Uniform Indexing for Rows and Columns of a Sheet --
9.4.5. Manage the Model Configurations --
9.5. Organization of a Spreadsheet Decision Model --
9.5.1. Value Components --
9.5.2. Decisions --
9.5.3. Uncertainties --
9.5.4. Business Units --
9.5.5. Time --
9.5.6. Representation of Business Units, Value Components, and Time: P & L Calculation Sheet(s) --
9.5.7. Inputs Sheet(s) --
9.6. Spreadsheet Model for the RNAS Illustrative Example --
9.6.1. Selectors --
9.6.2. Inputs and Strategy Table Sheets --
9.6.3. Calculations Sheets --
9.7. Debugging the Model --
9.8. Deterministic Analysis --
9.8.1. Sources of Value --
9.8.2. Deterministic Sensitivity Analysis --
9.8.3. Scenario Analysis --
9.9. Deterministic Modeling Using Monetary Multidimensional Value Functions (Approach 1B) --
9.10. Deterministic Modeling Using Nonmonetary Multidimensional Value Functions (Approach 1A) --
9.10.1. The Additive Value Function --
9.10.2. Single-Dimensional Value Functions --
9.10.3. Swing Weights --
9.10.4. Swing Weight Matrix --
9.10.5. Scoring the Alternatives --
9.10.6. Deterministic Analysis --
9.11. Illustrative Examples --
9.11.1. Geneptin --
9.11.2. Data Center Location --
9.12. Summary. 10.1. Introduction --
10.2. Structure the Problem in an Influence Diagram --
10.3. Elicit and Document Assessments --
10.3.1. Heuristics and Biases --
10.3.2. Reference Events --
10.3.3. Assessment Protocol --
10.3.4. Assessing a Continuous Distribution --
10.3.5. Conditioning Cases --
10.3.6. The Reluctant Expert --
10.4. Illustrative Examples --
10.4.1. Geneptin --
10.5. Summary --
11.1. Introduction --
11.2. Exploration of Uncertainty: Decision Trees and Simulation --
11.2.1. Decision Trees --
11.2.2. Simulation --
11.2.3. Choosing between Monte Carlo Simulation and Decision Trees --
11.2.4. Software for Simulation and Decision Trees --
11.3. The Value Dialogue --
11.3.1. P & L Browsers --
11.3.2. Total Value and Value Components --
11.3.3. Cash Flow over Time --
11.3.4. Direct EV Tornado Diagram --
11.3.5. Delta EV Tornado Diagram --
11.3.6. One-Way and Two-Way Sensitivity Analysis --
11.3.7. Value of Information and Value of Control --
11.3.8. Real Options --
11.3.9. S-Curves (Cumulative Probability Distributions) --
11.3.10. Flying Bar Charts --
11.4. Risk Attitude --
11.4.1. Delta Property --
11.4.2. Exponential Utility --
11.4.3. Assessing Risk Tolerance --
11.4.4. Calculating Certain Equivalents --
11.4.5. Evaluating "Small" Risks --
11.4.6. Going Beyond the Delta Property --
11.5. Illustrative Examples --
11.5.1. Geneptin Example --
11.5.2. Data Center --
11.6. Summary --
12.1. Introduction to Portfolio Decision Analysis --
12.2. Socio-Technical Challenges with Portfolio Decision Analysis --
12.3. Single Objective Portfolio Analysis with Resource Constraints --
12.3.1. Characteristics of Portfolio Optimization --
12.3.2. Greedy Algorithm Using Profitability Index and the Efficient Frontier --
12.3.3. Application to Roughneck North American Strategy Portfolio --
12.3.4. Portfolio Risk Management --
12.3.5. Trading off Financial Goals with Other Strategic Goals --
12.4. Multiobjective Portfolio Analysis with Resource Constraints --
12.4.1. Characteristics of Incremental Benefit/Cost Portfolio Analysis --
12.4.2. Algorithm for Incremental Benefit/Cost Portfolio Analysis --
12.4.3. Application to the Data Center Portfolio --
12.4.4. Comparison with Portfolio Optimization --
12.4.5. Strengths and Weaknesses of Incremental Benefit/Cost Portfolio Analysis --
12.5. Summary --
13.1. Introduction --
13.2. Determining Communication Objectives --
13.3. Communicating with Senior Leaders --
13.4. Communicating Decision Analysis Results --
13.4.1. Tell the Decision Maker the Key Insights and Not the Details --
13.4.2. Communicating Quantitative Information --
13.4.3. Determining and Telling the Story --
13.4.4. Best Practices for Presenting Decision Analysis Results --
13.4.5. Best Practices for Written Decision Analysis Results --
13.5. Communicating Insights in the Illustrative Examples --
13.5.1. Roughneck North America Strategy (by Eric R. Johnson) --
13.5.2. Geneptin (by Sean Xinghua Hu) --
13.5.3. Data Center Location (by Gregory S. Parnell) --
13.6. Summary --
14.1. Introduction --
14.2. Barriers to Involving Decision Implementers --
14.3. Involving Decision Implementers in the Decision Process --
14.4. Using Decision Analysis for Decision and Strategy Implementation --
14.4.1. Using the Decision Model for Decision Implementation --
14.4.2. Using Decision Analysis Models to Support Decision Implementation --
14.4.3. Using Decision Analysis to Assess Strategy Implementation --
14.5. Illustrative Examples --
14.5.1. RNAS (by Eric R. Johnson) --
14.5.2. Data Center (by Gregory S. Parnell) --
14.6. Summary --
15.1. Overview --
15.2. Decision Analysis Helps Answer Important Decision-Making Questions --
15.3. The Purpose of Decision Analysis Is to Create Value for Shareholders and Stakeholders --
15.3.1. Single Objective Value --
15.3.2. Multiple Objective Value --
15.3.3. It Is Important to Distinguish Potential Value and Implemented Value --
15.4. Decision Analysis Is a Socio-Technical Process --
15.4.1. Social --
15.4.2. Technical --
15.5. Decision Analysts Need Decision-Making Knowledge and Soft Skills --
15.5.1. Decision Analysts Need to Understand Decision-Making Challenges --
15.5.2. Decision Analysts Must Develop Their Soft Skills --
15.6. The Decision Analysis Process Must Be Tailored to the Decision and the Organization --
15.6.1. Decision Quality --
15.6.2. Decision Conferencing --
15.6.3. Dialogue Decision Process --
15.7. Decision Analysis Offers Powerful Analytic Tools to Support Decision Making --
15.7.1. Portfolio Resource Allocation --
15.8. Conclusion.
Responsibility: Gregory S. Parnell [and others].

Abstract:

A ONE-OF-A-KIND GUIDE TO THE BEST PRACTICES IN DECISION ANALYSIS Decision analysis provides powerful tools for addressing complex decisions that involve uncertainty and multiple objectives, yet  Read more...

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