MSCI_100_-_10-1_-_Decision_Making

# MSCI_100_-_10-1_-_Decision_Making - Introduction to...

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Unformatted text preview: Introduction to Decision Modeling How to systematically make better decisions (Andrews 15.5 covers preference matrix) 1 10-1: Decision Modelling • Decision making • Choosing between alternatives • Types of decisions – Routine, Structured • Can often be programmed/automated by computer or by a set of bureaucratic procedures/rules – Nonroutine, Unstructured • First step is to formulate appropriate structure to the decision 2 10-1: Decision Modelling Mathematical decision modeling • Any decision model is inherently a simplification of reality treat decision with caution, recognizing its limitations. • Assumptions about rationality in decision models – Objective rationality • Complete information about potential alternatives, payoffs (costs/benefits), decision criteria • i.e., unrealistic, but mathematically tractable – Bounded rationality • Incomplete information • i.e., more realistic, but mathematically complex or intractable 3 10-1: Decision Modelling Techniques • Linear programming • Preference matrix • Breakeven analysis • Decision trees 10-1: Decision Modelling 4 • Decision under “certainty” – i.e., deterministic world: variables and outcomes are known – can still use LP under uncertainty to establish bounds: e.g., “based on these assumptions, you can’t do better than X/ worse than Y” • Optimization of an objective function, given...
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MSCI_100_-_10-1_-_Decision_Making - Introduction to...

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