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Topics Covered Today

First 10 minutesPlease read the Class Discussion (Upjohn Marketing) example and draw the basic structure of the tree for Q2. Go through the story with your neighbour and agree on the structure and the values to insert. There is no need to solve the tree.. Decision Analysis: UpJohn. solution.

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Topics Covered Today

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    1. Topics Covered Today Multi-stage Decision Tree AWZ 7.2 Value of information(EVSI) AWZ 7.5.1 Value of information(EVPI) AWZ 7.5.2

    3. Decision Analysis: UpJohn Note no need to use Bayes. We have been given required probabilities. Actually, for this case Pr(T|S)=Pr(S|T)Note no need to use Bayes. We have been given required probabilities. Actually, for this case Pr(T|S)=Pr(S|T)

    4. Decision Analysis: Upjohn Conclusion was: Better to release product now because this gives mean profit of k$160 which is k$12 more than if we purchase the market information. What is the cost of uncertainty. How much of this loss am I retrieving with the market info?What is the cost of uncertainty. How much of this loss am I retrieving with the market info?

    5. Value of Sample Information

    6. Decision Analysis: Upjohn

    7. Decision Analysis: Upjohn Not always so easy. Contingent costs as in VOI. Or valuing decision branches to the right of this.Not always so easy. Contingent costs as in VOI. Or valuing decision branches to the right of this.

    8. Decision Analysis: Upjohn

    10. What if you could know the outcome first then make the decision? How much would it be worth to you? What is the value of perfect hindsight? Value of Perfect Information Max you would pay for further info. Cost of uncertainty. Ask about real estate auctions.Max you would pay for further info. Cost of uncertainty. Ask about real estate auctions.

    11. What if you could know the outcome first then make the decision? How much would it be worth to you? What is the value of perfect hindsight? Value of Perfect Information Max you would pay for further info. Cost of uncertainty. Ask about real estate auctions.Max you would pay for further info. Cost of uncertainty. Ask about real estate auctions.

    14. EMV0: What would you do if you knew which products were good and which were bad? Out of 100 products how much would you expect to make on average. Therefore what is the EMV? EVPI: UpJohn

    15. Example. EMV1 = k$198 EMV2 = k$160 EMV0 = k$300 EVPI: UpJohn Actually equals 40% of the k$350 loss. But not always so easy.Actually equals 40% of the k$350 loss. But not always so easy.

    16. EVPI: The Producer 479 479

    17. EVPI: The Producer . .

    18. EVPI: The Producer

    19. EVPI: The Producer $425=85% of $500 but not always that simple. $425=85% of $500 but not always that simple.

    20. Class Exercise Ask about real estate auctionsAsk about real estate auctions

    21. Class Exercise Ask about real estate auctionsAsk about real estate auctions

    22. Class Exercise Ask about real estate auctionsAsk about real estate auctions

    23. KEY TAKE AWAYS FROM CLASS Decision trees are a formal structure for finding optimal decisions in an uncertain environment EVSI – describes value of a decision to seek further information. Measured by difference in EMV with decision node removed compared to when information is free. EVPI – describes the value of information about uncertain outcome i.e. loss of unpredictability. Measure by increase in value when decisions come after uncertain outcome.

    24. Midterm Facts 15 mins reading + 100 mins writing Topics? Three Q’s – answer them all. Download data file for Q1 from Announcements. Each question includes a * question. No electronic submission. Write in booklet. Come by noon Put your materials on a USB or CDROM Save your worksheets.

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