INTRODUCTION to DECISION ANALYSIS
Lecture Outline

1. Why Decision Analysis?
   1. Complexity in the modern world
   2. Information quantity
   3. Uncertainty and Risk
   4. Group decision requirements
   5. Multiple, conflicting objectives

   => To provide a rational decision making framework

2. Where does Decision Analysis fit into Design?
   1. Everywhere!
   2. A critical aspect of all engineering, medicine, business, and ...
   3. Severe lack of numeracy by critical decision makers.
   4. Overlays math programming, stochastic systems, dynamic systems, etc.
   5. Diverse mathematical skills involved in decision theory.
   6. Severe lack of decision-making skills!

3. III. Simple Examples of Decision Analysis
   1. Ranking Basketball Teams.
   2. St. Petersburg Paradox.
   3. Packaging Weapon Systems.
   4. Allais Paradox.
   5. Behavioral Factors.
   6. Medical Decision making.

4. Decision Analysis -Should it be descriptive or prescriptive (normative)?
   1. Are decision makers capable (unaided) of making good decisions?
   2. What is needed?
      1. A set of rules for decision making must be defined in order that we may know what it is to be rational.
      2. The rules must address the values of the problem-owners - It must be possible to articulate their preferences and perceptions.
      3. The rules must state what it is to be rational in the face of perceptions of uncertainty.
      4. The rules must provide a calculus for steering the thinking of the decision makers through complex problems.

5. Goal of Decision Analysis?
   • To give guidance, information, insight, and structuring in the decision making process in order that better, more "rational", decisions can be made.

   
   

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   INTRODUCTION to DECISION ANALYSIS
   Lecture Outline

   
   
6. Current Practice of Decision Analysis: What do we have?
   1. Many diverse theories and approaches.
   2. Range from the highly mathematical utility theory to voodoo.
   3. Varied applications in many different fields.
   4. Successes and failures.
   5. Considerable confusion.

7. Major Topics to be Covered in Lecture (time permitting)
   1. Decision Making Under Strict Uncertainty
      Definitions:
      1. Decisions Under Risk
      2. Decisions Under Certainty
      3. Decisions Under Uncertainty
   2. Axioms for Rational Decision Making
   3. Value Functions => decisions under certainty
   4. Multi-Attribute Value Theory => decisions under certainty
   5. Utility Theory => decisions under risk
   6. Probability Revisited => decisions under risk
   7. Multi-Stage Decision Making => decisions under risk
   8. Group Decision Making => under certainty and risk
   9. Measurement Issues: Retrospective look at issues
   10. Non-Bayesian (non-traditional) Approaches => under certainty and risk

French, Simon, Decision Theory: An Introduction to the Mathematics of Rationality, Ellis Horwood Limited and John Wiley&Sons, New York, 1988. [Excellent Textbook]

Keeney, R.L., and Raiffa, H., Decisions With Multiple Objectives: Preferences and Value Trade-offs, John Wiley&Sons, New York, 1976. [Classic Work in Decision Analysis]

Watson, Stephen R., and Buede, Dennis M., Decision Synthesis: The Principles and Practice of Decision Analysis, Cambridge University Press, NY, NY, 1987.

Zeeleny, M., Multiple Criteria Decision Making, McGraw-Hill, New York, 1982.