Handbook of Decision Analysis, 2nd Edition

11Perform Probabilistic Analysis and Identify Insights

An organization's ability to learn, and translate that learning into action rapidly, is the ultimate competitive advantage.

—Jack Welch

CHAPTER MENU

• 11.1 Introduction
• 11.2 Exploration of Uncertainty: Simulation, Decision Trees, and Influence Diagrams
  • 11.2.1 Software for Simulation, Decision Trees, and Influence Diagrams
  • 11.2.2 Simulation
  • 11.2.3 TechnoMagic New Product Launch Monte Carlo Simulation
  • 11.2.4 Decision Trees
  • 11.2.5 Influence Diagrams
  • 11.2.6 Choosing Between Monte Carlo Simulation and Decision Trees
• 11.3 Value of Information and Value of Control
  • 11.3.1 Introduction
  • 11.3.2 Value of Information
  • 11.3.3 New Product Problem
  • 11.3.4 Perfect Information
  • 11.3.5 Expected Value of Control
  • 11.3.6 Imperfect Information
  • 11.3.7 Comparison of Information and Control
• 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
• Key Terms
• References

11.1 Introduction

Previous chapters discuss the initial development of a composite perspective on what drives value for the decision. To improve and exploit the composite perspective, we must find ways to understand the behavior of value that emerges from this model and test these against individuals' perspectives. Chapter 10 provided methods ...