Decision Making

# Decision Making

## Decision Making

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##### Presentation Transcript

1. Decision Making

2. Introduction • What: Decision making tools • Where: Making business decisions • Why: We want to avoid making bad decisions

3. Steps in Decision Making • Define the problem • Develop specific objectives • Develop a model • Evaluate each alternative solution • Select the best alternative • Implement the decision

4. A Decision Example • Should the Stampede Flapjack Company build a new factory to produce its new line of pancake mixes, or use part of its existing facility? • The factory will cost \$15M to build. • Probability of successful product is 65%

5. Our Forecast • If the factory is built, and if the new line is a success, sales will be worth \$25M. If it is not a success, overall sales will be worth \$5M. • If the factory is not built, and if the new line is a success, sales will be worth \$8M. If it is not a success, sales will be worth \$6M.

6. A Decision Tree A Decision Node Construct Plant Existing Plant

7. Adding the Construction Outcomes Successful (65%) - \$25M Unsuccessful (35%) - \$5M Construct Plant Existing Plant

8. Adding the No Construction Outcomes Successful (65%) - \$25M Unsuccessful (35%) - \$5M Construct Plant Successful (65%) - \$8M Existing Plant Unsuccessful (35%) - \$2M

9. Expected Monetary Value (EMV) Successful (65%) - \$25M Unsuccessful (35%) - \$5M EMV = \$25M x 0.65 + \$5M x 0.35 = \$18M

10. What is the Better Choice? \$18M Successful (65%) - \$25M Unsuccessful (35%) - \$5M Construct Plant \$7.3M Successful (65%) - \$8M Existing Plant Unsuccessful (35%) - \$6M

11. Result \$18M Successful (65%) - \$25M Unsuccessful (35%) - \$5M Construct Plant \$18M \$7.3M Successful (65%) - \$8M Existing Plant Unsuccessful (35%) - \$6M

12. In Other Words… • Because the result for building the factory gives us a higher EMV, we choose it. • Because the EMV is greater than the cost of constructing the factory, we will build it.

13. A Decision Table

14. Calculating EMV’s

15. Expected Value of Perfect Information (EVPI) • What would we be willing to pay for perfect information – to know the future? • EVPI = EV Under Certainty – Max EMV

16. Expected Value Under Certainty • Expected Value Under Certainty = • Best outcome for first state x probability of first state • + • Best outcome for second state x probability of second state

17. Expected Value Under Certainty

18. Expected Value Under Certainty • EV = \$25M x 65% + \$6M x 35% • EV = \$18.35

19. Expected Value of Perfect Information • EVPI = EV Under Certainty – Max EMV • EVPI = \$18.35M - \$18M • EVPI = 0.35M • So we would pay, for example, a maximum of \$350K for a marketing study