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© 2006 Prentice Hall, Inc.A – 1 Operations Management Module A – Decision-Making Tools © 2006 Prentice Hall, Inc. PowerPoint presentation for Operations.

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Presentation on theme: "© 2006 Prentice Hall, Inc.A – 1 Operations Management Module A – Decision-Making Tools © 2006 Prentice Hall, Inc. PowerPoint presentation for Operations."— Presentation transcript:

1 © 2006 Prentice Hall, Inc.A – 1 Operations Management Module A – Decision-Making Tools © 2006 Prentice Hall, Inc. PowerPoint presentation for Operations Management Class Updated and extended by Prof. Dedeke

2 © 2006 Prentice Hall, Inc.A – 2 Outline  Fundamentals of Decision Making  Decision Tables  Types of Decision-Making Environments  Decision Making Under Uncertainty  Decision Making Under Risk  Decision Making Under Certainty  Expected Value of Perfect Information (EVPI)

3 © 2006 Prentice Hall, Inc.A – 3 Introduction  Decision Making Approaches  Structured  Unstructured

4 © 2006 Prentice Hall, Inc.A – 4 Structured Decision Making Process 1.Clearly define the problem and the factors that influence it 2.Develop the specific goals to be achieved 3.Develop quantitative measures that relate the goals to the problem 4.Develop alternate solutions to problem 5.Compare the alternate solutions using a model or structured methodology and the quantitative measures from step 3 6.Select the best alternative 7.Implement the decision and set a timetable for completion

5 © 2006 Prentice Hall, Inc.A – 5 Decision Making Environment DecisionsunderuncertaintyDecisionsunderrisk DecisionsunderriskDecisionsundercertainty Estimate-able Known Partial Total Value or Size of outcomes and consequences Level of confidence about occurrence of outcomes and consequences

6 © 2006 Prentice Hall, Inc.A – 6 Decision-Making Environments  Decision making under uncertainty  Complete uncertainty as to which state of nature may occur  Decision making under risk  Several states of nature may occur  Each has a probability of occurring  Decision making under certainty  State of nature is known

7 © 2006 Prentice Hall, Inc.A – 7 Decision Making Under Certainty 1.EMV(A 1 ) = (1)($200,000) + (0)(-$180,000) = $200,000 2.EMV(A 2 ) = (1)($100,000) + (0)(-$90,000) = $100,000 States of Nature FavorableUnfavorable Alternatives Market Market Construct large plant (A1)$200,000-$180,000 Construct small plant (A2)$100,000-$90,000 Do nothing (A3)$0$0 Probabilities10 From Table A.3 The preferable option is A1 The preferable option is A1

8 © 2006 Prentice Hall, Inc.A – 8 Decision Making Under Risk 1.EMV(A 1 ) = (0.3)($200,000) + (0.7)(-$180,000) = -$66,000 2.EMV(A 2 ) = (0.3)($100,000) + (0.7)(-$90,000) = -$33,000 3.EMV(A 3 ) = (0.3)($0) + (0.7)($0) = $0 States of Nature FavorableUnfavorable Alternatives Market Market Construct large plant (A1)$200,000-$180,000 Construct small plant (A2)$100,000-$90,000 Do nothing (A3)$0$0 Probabilities From Table A.3 A3 is the option to choose. If A3 is excluded, The preferable option is A2 If A3 is excluded, The preferable option is A2

9 © 2006 Prentice Hall, Inc.A – 9 Decision Making Under Risk (2) In some cases the states of nature expected are certain, however the values of each states are uncertain. States of Demand Seasonal Ticket Occasional Alternatives Prob. Market Prob. Market Seasonal Ticket Occasional Alternatives Prob. Market Prob. Market Sell 100 tickets now (A1) 0.7 $200, $50,000 Sell 100 tickets later (A2) 0.3 $150, $300,000 Do nothing (A3) $0 $0 1.EMV(A 1 ) = (0.7)($200,000) + (0.3)($50,000) = $155,000 2.EMV(A 2 ) = (0.3)($150,000) + (0.7)($300,000) = $255,000 3.EMV(A 3 ) = (0)($0) + (0)($0) = $0 The preferable option is A2 The preferable option is A2

10 © 2006 Prentice Hall, Inc.A – 10 Risk  Each possible state of nature has an assumed probability  States of nature are mutually exclusive  Probabilities must sum to 1  Determine the expected monetary value (EMV) for each alternative

11 © 2006 Prentice Hall, Inc.A – 11 Expected Monetary Value EMV (Alternative i) = (Payoff of 1 st state of nature) x (Probability of 1 st state of nature) + (Payoff of 2 nd state of nature) x (Probability of 2 nd state of nature) +…+ (Payoff of last state of nature) x (Probability of last state of nature)

12 © 2006 Prentice Hall, Inc.A – 12 Decision Making Under Uncertainty States of Nature FavorableUnfavorableMaximumMinimumRow AlternativesMarketMarketin Rowin RowAverage Construct large plant $200,000-$180,000$200,000-$180,000$10,000 Construct small plant $100,000 -$20,000$100,000 -$20,000$40,000 Do nothing $0$0$0$0$0 1.Maximax choice is to construct a large plant 2.Maximin choice is to do nothing 3.Equally likely choice is to construct a small plant Maximax Maximin Equally likely

13 © 2006 Prentice Hall, Inc.A – 13 Using Decision Trees to Solve Decision Making Under Risk 2.Symbols used in a decision tree: a.  —decision node from which one of several alternatives may be selected b.  —a state-of-nature node out of which one state of nature will occur

14 © 2006 Prentice Hall, Inc.A – 14 Decision Tree Example Favorable market Unfavorable market Favorable market Unfavorable market Construct small plant Do nothing A decision node A state of nature node Construct large plant Figure A.1

15 © 2006 Prentice Hall, Inc.A – 15 Decision Table Example State of Nature AlternativesFavorable MarketUnfavorable Market Construct large plant$200,000–$180,000 Construct small plant$100,000–$ 20,000 Do nothing$ 0 $ 0 Table A.1

16 © 2006 Prentice Hall, Inc.A – 16 Decision Tree Example = (.5)($200,000) + (.5)(-$180,000) EMV for node 1 = $10,000 EMV for node 2 = $40,000 = (.5)($100,000) + (.5)(-$20,000) Payoffs$200,000 -$180,000 $100,000 -$20,000 $0 Construct large plant Construct small plant Do nothing Favorable market (.5) Unfavorable market (.5) 1 Favorable market (.5) Unfavorable market (.5) 2 Figure A.2

17 © 2006 Prentice Hall, Inc.A – 17 Complex Decision Tree Example Figure A.3

18 © 2006 Prentice Hall, Inc.A – 18 Decision Trees in Ethical Decision Making  Maximize shareholder value and behave ethically  Technique can be applied to any action a company contemplates

19 © 2006 Prentice Hall, Inc.A – 19YesNo Yes No Decision Trees in Ethical Decision Making Yes Is it ethical? (Weigh the affect on employees, customers, suppliers, community against shareholder benefit) No Is it ethical not to take action? (Weigh the harm to shareholders vs. the benefits to other stakeholders) Do it Don’t do it Do it, but notify appropriate parties Don’t do it No Yes Does action maximize company returns? Is action legal? Figure A.4

20 © 2006 Prentice Hall, Inc.A – 20 Operations decisions often involve selection of suppliers, vendors, markets, products and so on. In most of these cases, one has to define priorities.Operations decisions often involve selection of suppliers, vendors, markets, products and so on. In most of these cases, one has to define priorities. StepsSteps –Identify attributes to rank or compare, skill, age –Have a scale to use for ranking, e.g. 1, 2, 3, 4, 5 –Choose a scale for priorities, e.g. 0.1, 0.3, 0.9… –Use system to compare alternatives Qualitative Decision Making: Factoring Priorities

21 © 2006 Prentice Hall, Inc.A – 21 Example: Priorities and Decision Making Employee A Employee B Weight (W) Score (S 1 ) W x S 1 Score (S 2 ) W x S 2 Language Analytical Technical Salary Expect Degree TOTAL

22 © 2006 Prentice Hall, Inc.A – 22 Example: Priorities and Decision Making Employee A Employee B Weight (W) Score (S 1 ) W x S 1 Score (S 2 ) W x S 2 Language Analytical Technical Salary Expect Degree TOTAL

23 © 2006 Prentice Hall, Inc.A – 23 Review Chapter 8, Example 1, page & 258 Solved problem 8.1, page 263Review Chapter 8, Example 1, page & 258 Solved problem 8.1, page 263 See problem 8.1 in Excel spreadsheet Qualitative Decision Making: Location Strategies


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