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**ISMT 161: Introduction to Operations Management**

Decision Analysis What is the best way to solve your problem? ISMT 161: Introduction to Operations Management

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**ISMT 161: Introduction to Operations Management**

Decision Analysis Every decision you make uses some kind of model, whether you know it or not. We will take a more systematic look at the decision process and the underlying theories. ISMT 161: Introduction to Operations Management

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**ISMT 161: Introduction to Operations Management**

The Decision Process Identify the Problem Specify objectives and the criteria for choosing a solution Develop alternatives Analyze and compare alternatives ISMT 161: Introduction to Operations Management

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**The Decision Process (Cont)**

Select the best alternative Implement the chosen alternative Monitor the results ISMT 161: Introduction to Operations Management

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**Causes of Poor Decisions**

Bounded Rationality The limitations on decision making caused by costs, human abilities, time, technology, and availability of information ISMT 161: Introduction to Operations Management

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**Causes of Poor Decisions (Cont)**

Suboptimization The result of different departments each attempting to reach a solution that is optimum for that department ISMT 161: Introduction to Operations Management

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**Decision Environments**

Certainty - Environment in which relevant parameters have known values Risk - Environment in which certain future events have probable outcomes Uncertainty - Environment in which it is impossible to assess the likelihood of various future events ISMT 161: Introduction to Operations Management

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**ISMT 161: Introduction to Operations Management**

Decision Theory Decision Theory represents a general approach to decision making which is suitable for a wide range of operations management decisions, including: capacity planning product and service design location planning equipment selection ISMT 161: Introduction to Operations Management

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**Decision Theory Elements**

A set of possible future conditions exists that will have a bearing on the results of the decision A list of alternatives for the manager to choose from A known payoff for each alternative under each possible future condition ISMT 161: Introduction to Operations Management

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**Decision Theory Process**

Identify possible future conditions called states of nature Develop a list of possible alternatives, one of which may be to do nothing Determine the payoff associated with each alternative for every future condition ISMT 161: Introduction to Operations Management

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**Decision Theory Process (Cont’d)**

If possible, determine the likelihood of each possible future condition Evaluate alternatives according to some decision criterion and select the best alternative ISMT 161: Introduction to Operations Management

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**ISMT 161: Introduction to Operations Management**

Decision situations under Certainty under Uncertainty under Risk ISMT 161: Introduction to Operations Management

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**ISMT 161: Introduction to Operations Management**

Payoff Table Possible future demand* *Present value in $ millions ISMT 161: Introduction to Operations Management

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**Decision Making under Uncertainty - Some Criteria**

Maximin - Choose the alternative with the best of the worst possible payoffs Maximax - Choose the alternative with the best possible payoff Laplace (weighted average) - Choose the alternative with the best average payoff of any of the alternatives Minimax Regret - Choose the alternative that has the least of the worst regrets ISMT 161: Introduction to Operations Management

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**ISMT 161: Introduction to Operations Management**

Example - Maximin Maximin ISMT 161: Introduction to Operations Management

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**Example - Minimax regret**

Regret table (opportunity losses) Regrets (in $ mil.) ISMT 161: Introduction to Operations Management

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**ISMT 161: Introduction to Operations Management**

Example - EMV EMV - expected monetary value -The best expected value among the alternatives Suppose the probabilities for the future demand are: low = 0.3, moderate = .5 and high = .2. Find the EMV for the best alternatives: EV(small) = .3(10) + .5(10) + .2(10) = 10 EV(medium) = .3(7) + .5(12) + .2(12) = 10.5 EV(large) = .3(-4) + .5(2) + .2(16) = 3 Thus the medium facility has the highest EV. ISMT 161: Introduction to Operations Management

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**ISMT 161: Introduction to Operations Management**

Decision Tree- Schematic representation of the alternatives and their possible consequences Payoff 1 State of nature 1 Choose A3 Payoff 2 Choose A1 2 State of nature 2 Choose A4 Payoff 3 B 1 Payoff 4 Choose A5 State of nature 1 2 Choose A2 Choose A6 Payoff 5 State of nature 2 Decision Point Payoff 6 ISMT 161: Introduction to Operations Management Chance Event

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**Expected Value of Perfect Information**

the difference between the expected payoff under certainty and the expected payoff under risk Expected value of perfect information = Expected payoff under certainty - expected payoff under risk ISMT 161: Introduction to Operations Management

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**Constructing a Decision Tree**

List all the possible alternatives of decisions List all the outcomes of random events Work through the possible decisions and random events chronologically Fill in final outcomes and payoffs, and probability distributions of random events if necessary ISMT 161: Introduction to Operations Management

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**ISMT 161: Introduction to Operations Management**

Example (p.86, problem 4) A firm that plans to expand its product line must decide whether to build a small or a large facility to produce the new products. If it builds a small facility and demand is low, the net present value after deducting for building costs will be $400,000. If demand is high, the firm can either maintain the small facility or expand it. Expansion would have a net present value of $50,000. If a large facility is built and demand is high, the estimated net present value is $800,000. If demand turns out to be low, the net present value will be -$10,000. The probability that demand will be high is estimated to be .60 and that of low would be .40. (a) Analyze using a tree diagram. (b) Compute the EVPI. How could this information be useful? ISMT 161: Introduction to Operations Management

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**Constructing the decision tree**

Alternatives: build small, build large; expand (for high demand and build small ) maintain (…) Outcomes: low demand, high demand ISMT 161: Introduction to Operations Management

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**ISMT 161: Introduction to Operations Management**

Example (solutions) $400,000 (1) Demand low (.4) Maintain $400,000 (2) 2 Build small Demand high (.6) Expand $450,000(3) B 1 - $10,000(4) Demand low (.4) Build large $800,000(5) Demand high (.6) ISMT 161: Introduction to Operations Management

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**Example (solution continued)**

The expected net present value of the alternatives (1) .4 400,000 = 160,000 (2) can be eliminated (since its npv is less than expansion) (3) .6 450,000 = 270,000 (4) .4 (-10,000) = -4,000 (5) .6 800,000 = 480,000 Build small expected npv = = Build large expected npv = = Since building a large capacity has the higher expected net present value, select “build large” alternative ISMT 161: Introduction to Operations Management

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**ISMT 161: Introduction to Operations Management**

Rollback approach for EMV $400,000 (1) Demand low (.4) 430K Maintain $400,000 (2) 450K 2 Build small Demand high (.6) Expand $450,000(3) 476K 1 - $10,000(4) Demand low (.4) Build large $800,000(5) 476K Demand high (.6) ISMT 161: Introduction to Operations Management

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**Example (solution continued)**

Expected payoff under certainty = .4(400,000) + .6(800,000) = 640,000 Expected payoff under risk = 476,000 Expected value of perfect Information = 640, ,000 = 164,000 ISMT 161: Introduction to Operations Management

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**ISMT 161: Introduction to Operations Management**

Sensitivity Analysis #1 Payoff #2 Payoff 16 14 12 10 8 6 4 2 B 16 14 12 10 8 6 4 2 A C B best C best A best Sensitivity analysis: determine the range of probability for which an alternative has the best expected payoff ISMT 161: Introduction to Operations Management

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Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin 20- 1 Chapter Twenty An Introduction to Decision Making GOALS.

Copyright © 2002 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin 20- 1 Chapter Twenty An Introduction to Decision Making GOALS.

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