1. Chapter 5 Supplement
Decision Theory

2. Decision Theory Elements
A set of possible future conditions exists that will have a bearing on the results of the decision
A list of alternatives for the manager to choose from
A known payoff for each alternative under each possible future condition

3. Decision Theory Process
Identify possible future conditions called states of nature
Develop a list of possible alternatives, one of which may be to do nothing
Determine the payoff associated with each alternative for every future condition

4. Decision Theory Process (Cont’d)
If possible, determine the likelihood of each possible future condition
Evaluate alternatives according to some decision criterion and select the best alternative

5. Causes of Poor Decisions
Bounded Rationality
The limitations on decision making caused by costs, human abilities, time, technology, and availability of information

6. Causes of Poor Decisions (Cont’d)
Suboptimization
The result of different departments each attempting to reach a solution that is optimum for that department

7. Decision Environments
Certainty - Environment in which relevant parameters have known values
Risk - Environment in which certain future events have probable outcomes
Uncertainty - Environment in which it is impossible to assess the likelihood of various future events

8. product and service design
Decision Theory
Decision Theory represents a general approach to decision making which is suitable for a wide range of operations management decisions, including:
capacity planning
product and service design
equipment
selection
location
planning

9. Possible future demand*
Payoff Table
Possible future demand*
Present value in $ millions

10. Decision Making under Uncertainty
Maximin - Choose the alternative with the best of the worst possible payoffs
Maximax - Choose the alternative with the best possible payoff
Laplace - Choose the alternative with the best average payoff of any of the alternatives
Minimax Regret - Choose the alternative that has the least of the worst regrets

11. Format of a Decision Tree
State of nature 1 B
Payoff 1
State of nature 2
Payoff 2
Payoff 3 2
Choose A’1
Choose A’2
Payoff 6
Payoff 4
Payoff 5
Choose A’3
Choose A’4
Choose A’ 1
Decision Point
Chance Event

12. Expected Value of Perfect Information
Expected value of perfect information the difference between the expected payoff under certainty and the expected payoff under risk Expected value of Expected payoff Expected payoff perfect information under certainty under risk _ =

13. Sensitivity Analysis Example 8 16 14 12 10 8 6 4 2A B C
A best
C best
B best
#1 Payoff
#2 Payoff
Sensitivity analysis: determine the range of probability for which an alternative has the best expected payoff
Example 8

14. Solved Problem 5