1. OPERATIONS MANAGEMENT: Creating Value Along the Supply Chain,
Canadian Edition
Robert S. Russell, Bernard W. Taylor III, Ignacio Castillo, Navneet Vidyarthi
CHAPTER 1 SUPPLEMENT
Decision Analysis

2. Lecture Outline Decision Analysis
Decision Making without Probabilities
Decision Analysis with Excel
Decision Analysis with OM Tools
Decision Making with Probabilities
Expected Value of Perfect Information
Sequential Decision Tree

3. Decision Analysis Quantitative methods Decision analysis
a set of tools for operations manager
Decision analysis
a set of quantitative decision-making techniques for decision situations in which uncertainty exists
Example of an uncertain situation
demand for a product may vary between 0 and 200 units, depending on the state of market

4. Decision Making Without Probabilities
States of nature
Events that may occur in the future
Examples of states of nature:
high or low demand for a product
good or bad economic conditions
Decision making under risk
probabilities can be assigned to the occurrence of states of nature in the future
Decision making under uncertainty
probabilities can NOT be assigned to the occurrence of states of nature in the future

5. Payoff Table Payoff table Payoff
method for organizing and illustrating payoffs from different decisions given various states of nature
Payoff
outcome of a decision

6. Decision Making Criteria Under Uncertainty
Maximax
choose decision with the maximum of the maximum payoffs
Maximin
choose decision with the maximum of the minimum payoffs
Minimax regret
choose decision with the minimum of the maximum regrets for each alternative

7. Decision Making Criteria Under Uncertainty
Hurwicz
choose decision in which decision payoffs are weighted by a coefficient of optimism, alpha
coefficient of optimism is a measure of a decision maker’s optimism, from 0 (completely pessimistic) to 1 (completely optimistic)
Equal likelihood (La Place)
choose decision in which each state of nature is weighted equally

8. Southern Textile Company

9. Decision: Maintain status quo
Maximax Solution
Decision: Maintain status quo

10. Maximin Solution
Decision: Expand

11. Minimax Regret Solution
Decision: Expand

12. Hurwicz Criteria
Decision: Expand

13. Equal Likelihood Criteria
Decision: Expand

14. Decision Analysis with Excel

15. Decision Analysis with OM Tools

16. Decision Making with Probabilities
Risk involves assigning probabilities to states of nature
Expected value
a weighted average of decision outcomes in which each future state of nature is assigned a probability of occurrence

17.  Expected Value EV (x) = p(xi)xi n i =1 where xi = outcome i
p(xi) = probability of outcome i

18. Decision Making with Probabilities

19. Decision Making with Probabilities: Excel

20. Expected Value of Perfect Information
EVPI
maximum value of perfect information to the decision maker
maximum amount that would be paid to gain information that would result in a decision better than the one made without perfect information

21. EVPI Good conditions will exist 70% of the time
choose maintain status quo with payoff of $1,300,000
Poor conditions will exist 30% of the time
choose expand with payoff of $500,000
Expected value given perfect information = $1,300,000 (0.70) + 500,000 (0.30) = $1,060,000
Recall that expected value without perfect information was $865,000 (maintain status quo)
EVPI = $1,060, ,000 = $195,000

22. Sequential Decision Trees
A graphical method for analyzing decision situations that require a sequence of decisions over time
Decision tree consists of
Square nodes - indicating decision points
Circles nodes - indicating states of nature
Arcs - connecting nodes

23. Evaluations at Nodes Compute EV at nodes 6 & 7
EV(node 6)= 0.80($3,000,000) ($700,000) = $2,540,000
EV(node 7)= 0.30($2,300,000) ($1,000,000)= $1,390,000
Decision at node 4 is between $2,540,000 for Expand and $450,000 for Sell land
Choose Expand
Repeat expected value calculations and decisions at remaining nodes

24. Decision Tree Analysis

25. COPYRIGHT
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