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Decision Tree Modeling

Decision Tree Modeling. Decision Trees Software demonstration Introduction to ICI case. Decision Analysis.

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Decision Tree Modeling

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  1. Decision Tree Modeling • Decision Trees • Software demonstration • Introduction to ICI case

  2. Decision Analysis • Decision Analysis is useful when managers face situations where their actions can lead to uncertain outcomes. This type of analysis helps in managing the risks associated with such actions. • Despite the wide applicability of Decision Analysis, few managers actually use it! • Perhaps, easy to use software might encourage greater use of these concepts and tools.

  3. Quote for the Day He who does not understand the relative importance of the available decision options begins to regard as important the decision he actually makes. Adapted from C. Northcote Parkinson

  4. Decision Analysis Procedure • Structure decision problem • Alternatives courses of action • Outcomes (attributes that define outcomes) • Temporal order of events • Quantify preferences for outcomes (i.e., payoffs) • Quantify uncertainties (i.e., Assign probabilities to chance events) • Evaluate alternative actions

  5. Basic Concepts • Time sequence of events • Decision nodes, chance nodes, payoff (terminal) nodes. • Conditional probability • Expected value of perfect information • “Folding back” of decision tree

  6. QRS Example Described in the Text

  7. QRS Example Described in the Text

  8. Expected Value of Perfect Information (EVPI) • E : Expected Value (in monetary terms or in utils) if we make decisions with perfect information, obtained at no cost, about the actual event(s) that will occur. • E:Expected Value if we make decisions with only the best available a priori information without obtaining additional information. • EVPI = E - E

  9. More Sophisticated Analysis • Use variables to represent probabilities and payoffs • Specify distribution of values for variables • Sensitivity analyses • One-way analysis • Tornado diagram

  10. Potential Benefits and Limits • Useful as a communication tool. • Imposes structured thinking by helping managers to separate uncertainties and preferences. • Allows managers to incorporate subjective data. • Does not extend easily to support multiple decision makers with differing payoffs.

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