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  • 1. A - 1© 2011 Pearson Education, Inc. publishing as Prentice HallA Decision-MakingToolsPowerPoint presentation to accompanyHeizer and RenderOperations Management, 10ePrinciples of Operations Management, 8ePowerPoint slides by Jeff Heyl
  • 2. A - 2© 2011 Pearson Education, Inc. publishing as Prentice HallOutline The Decision Process inOperations Fundamentals of Decision Making Decision Tables
  • 3. A - 3© 2011 Pearson Education, Inc. publishing as Prentice HallOutline – Continued Types of Decision-MakingEnvironments Decision Making Under Uncertainty Decision Making Under Risk Decision Making Under Certainty Expected Value of PerfectInformation (EVPI)
  • 4. A - 4© 2011 Pearson Education, Inc. publishing as Prentice HallOutline – Continued Decision Trees A More Complex Decision Tree Using Decision Trees in EthicalDecision Making The Poker Decision Problem
  • 5. A - 5© 2011 Pearson Education, Inc. publishing as Prentice HallLearning ObjectivesWhen you complete this module youshould be able to:1. Create a simple decision tree2. Build a decision table3. Explain when to use each of the threetypes of decision-makingenvironments4. Calculate an expected monetaryvalue (EMV)
  • 6. A - 6© 2011 Pearson Education, Inc. publishing as Prentice HallLearning ObjectivesWhen you complete this module youshould be able to:5. Compute the expected value ofperfect information (EVPI)6. Evaluate the nodes in a decision tree7. Create a decision tree with sequentialdecisions
  • 7. A - 7© 2011 Pearson Education, Inc. publishing as Prentice HallDecision to Go All In
  • 8. A - 8© 2011 Pearson Education, Inc. publishing as Prentice HallThe Decision Process inOperations1. Clearly define the problems and thefactors that influence it2. Develop specific and measurableobjectives3. Develop a model4. Evaluate each alternative solution5. Select the best alternative6. Implement the decision and set atimetable for completion
  • 9. A - 9© 2011 Pearson Education, Inc. publishing as Prentice HallFundamentals ofDecision Making1. Terms:a. Alternative – a course of action orstrategy that may be chosen by thedecision makerb. State of nature – an occurrence ora situation over which the decisionmaker has little or no control
  • 10. A - 10© 2011 Pearson Education, Inc. publishing as Prentice HallFundamentals ofDecision Making2. Symbols used in a decision tree:a.  – decision node from which oneof several alternatives may beselectedb.  – a state-of-nature node out ofwhich one state of nature willoccur
  • 11. A - 11© 2011 Pearson Education, Inc. publishing as Prentice HallDecision Tree ExampleFavorable marketUnfavorable marketFavorable marketUnfavorable marketConstructsmall plantA decision node A state of nature nodeFigure A.1
  • 12. A - 12© 2011 Pearson Education, Inc. publishing as Prentice HallDecision Table ExampleTable A.1State of NatureAlternatives Favorable Market Unfavorable MarketConstruct large plant $200,000 –$180,000Construct small plant $100,000 –$ 20,000Do nothing $ 0 $ 0
  • 13. A - 13© 2011 Pearson Education, Inc. publishing as Prentice HallDecision-MakingEnvironments Decision making under uncertainty Complete uncertainty as to whichstate 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
  • 14. A - 14© 2011 Pearson Education, Inc. publishing as Prentice HallUncertainty1. Maximax Find the alternative that maximizesthe maximum outcome for everyalternative Pick the outcome with the maximumnumber Highest possible gain This is viewed as an optimisticapproach
  • 15. A - 15© 2011 Pearson Education, Inc. publishing as Prentice HallUncertainty2. Maximin Find the alternative that maximizesthe minimum outcome for everyalternative Pick the outcome with the minimumnumber Least possible loss This is viewed as a pessimisticapproach
  • 16. A - 16© 2011 Pearson Education, Inc. publishing as Prentice HallUncertainty3. Equally likely Find the alternative with the highestaverage outcome Pick the outcome with the maximumnumber Assumes each state of nature isequally likely to occur
  • 17. A - 17© 2011 Pearson Education, Inc. publishing as Prentice HallUncertainty Example1. Maximax choice is to construct a large plant2. Maximin choice is to do nothing3. Equally likely choice is to construct a small plantMaximax Maximin EquallylikelyStates of NatureFavorable Unfavorable Maximum Minimum RowAlternatives Market Market in Row in Row AverageConstructlarge plant $200,000 -$180,000 $200,000 -$180,000 $10,000Constructsmall plant $100,000 -$20,000 $100,000 -$20,000 $40,000Do nothing $0 $0 $0 $0 $0
  • 18. A - 18© 2011 Pearson Education, Inc. publishing as Prentice HallRisk Each possible state of nature has anassumed probability States of nature are mutually exclusive Probabilities must sum to 1 Determine the expected monetary value(EMV) for each alternative
  • 19. A - 19© 2011 Pearson Education, Inc. publishing as Prentice HallExpected Monetary ValueEMV (Alternative i) = (Payoff of 1st state ofnature) x (Probability of 1ststate of nature)+ (Payoff of 2nd state ofnature) x (Probability of 2ndstate of nature)+…+ (Payoff of last state ofnature) x (Probability oflast state of nature)
  • 20. A - 20© 2011 Pearson Education, Inc. publishing as Prentice HallEMV Example1. EMV(A1) = (.5)($200,000) + (.5)(-$180,000) = $10,0002. EMV(A2) = (.5)($100,000) + (.5)(-$20,000) = $40,0003. EMV(A3) = (.5)($0) + (.5)($0) = $0Table A.3States of NatureFavorable UnfavorableAlternatives Market MarketConstruct large plant (A1) $200,000 -$180,000Construct small plant (A2) $100,000 -$20,000Do nothing (A3) $0 $0Probabilities .50 .50
  • 21. A - 21© 2011 Pearson Education, Inc. publishing as Prentice HallEMV Example1. EMV(A1) = (.5)($200,000) + (.5)(-$180,000) = $10,0002. EMV(A2) = (.5)($100,000) + (.5)(-$20,000) = $40,0003. EMV(A3) = (.5)($0) + (.5)($0) = $0Best OptionTable A.3States of NatureFavorable UnfavorableAlternatives Market MarketConstruct large plant (A1) $200,000 -$180,000Construct small plant (A2) $100,000 -$20,000Do nothing (A3) $0 $0Probabilities .50 .50
  • 22. A - 22© 2011 Pearson Education, Inc. publishing as Prentice HallCertainty Is the cost of perfect informationworth it? Determine the expected value ofperfect information (EVPI)
  • 23. A - 23© 2011 Pearson Education, Inc. publishing as Prentice HallExpected Value ofPerfect InformationEVPI is the difference between the payoffunder certainty and the payoff under riskEVPI = –Expected valuewith perfectinformationMaximumEMVExpected value withperfect information(EVwPI)= (Best outcome or consequence for 1st stateof nature) x (Probability of 1st state of nature)+ Best outcome for 2nd state of nature)x (Probability of 2nd state of nature)+ … + Best outcome for last state of nature)x (Probability of last state of nature)
  • 24. A - 24© 2011 Pearson Education, Inc. publishing as Prentice HallEVPI Example1. The best outcome for the state of nature“favorable market” is “build a largefacility” with a payoff of $200,000. Thebest outcome for “unfavorable” is “donothing” with a payoff of $0.Expected valuewith perfectinformation= ($200,000)(.50) + ($0)(.50) = $100,000
  • 25. A - 25© 2011 Pearson Education, Inc. publishing as Prentice HallEVPI Example2. The maximum EMV is $40,000, which isthe expected outcome without perfectinformation. Thus:= $100,000 – $40,000 = $60,000EVPI = EVwPI – MaximumEMVThe most the company should pay forperfect information is $60,000
  • 26. A - 26© 2011 Pearson Education, Inc. publishing as Prentice HallDecision Trees Information in decision tables can bedisplayed as decision trees A decision tree is a graphic display of thedecision process that indicates decisionalternatives, states of nature and theirrespective probabilities, and payoffs foreach combination of decision alternativeand state of nature Appropriate for showing sequentialdecisions
  • 27. A - 27© 2011 Pearson Education, Inc. publishing as Prentice HallDecision Trees
  • 28. A - 28© 2011 Pearson Education, Inc. publishing as Prentice HallDecision Trees1. Define the problem2. Structure or draw the decision tree3. Assign probabilities to the states ofnature4. Estimate payoffs for each possiblecombination of decision alternatives andstates of nature5. Solve the problem by working backwardthrough the tree computing the EMV foreach state-of-nature node
  • 29. A - 29© 2011 Pearson Education, Inc. publishing as Prentice HallDecision Tree Example= (.5)($200,000) + (.5)(-$180,000)EMV for node 1= $10,000EMV for node 2= $40,000 = (.5)($100,000) + (.5)(-$20,000)Payoffs$200,000-$180,000$100,000-$20,000$0Constructsmall plantFavorable market (.5)Unfavorable market (.5)1Favorable market (.5)Unfavorable market (.5)2Figure A.2
  • 30. A - 30© 2011 Pearson Education, Inc. publishing as Prentice HallComplexDecisionTreeExampleFigure A.3
  • 31. A - 31© 2011 Pearson Education, Inc. publishing as Prentice HallComplex Example1. Given favorable survey resultsEMV(2) = (.78)($190,000) + (.22)(-$190,000) = $106,400EMV(3) = (.78)($90,000) + (.22)(-$30,000) = $63,600The EMV for no plant = -$10,000 so,if the survey results are favorable,build the large plant
  • 32. A - 32© 2011 Pearson Education, Inc. publishing as Prentice HallComplex Example2. Given negative survey resultsEMV(4) = (.27)($190,000) + (.73)(-$190,000) = -$87,400EMV(5) = (.27)($90,000) + (.73)(-$30,000) = $2,400The EMV for no plant = -$10,000 so,if the survey results are negative,build the small plant
  • 33. A - 33© 2011 Pearson Education, Inc. publishing as Prentice HallComplex Example3. Compute the expected value of themarket surveyEMV(1) = (.45)($106,400) + (.55)($2,400) = $49,200The EMV for no plant = $0 so, givenno survey, build the small plant4. If the market survey is not conductedEMV(6) = (.5)($200,000) + (.5)(-$180,000) = $10,000EMV(7) = (.5)($100,000) + (.5)(-$20,000) = $40,000
  • 34. A - 34© 2011 Pearson Education, Inc. publishing as Prentice HallDecision Trees in EthicalDecision Making Maximize shareholder value andbehave ethically Technique can be applied to anyaction a company contemplates
  • 35. A - 35© 2011 Pearson Education, Inc. publishing as Prentice HallYesNoYesNoDecision Trees in EthicalDecision MakingYesIs it ethical? (Weigh theaffect on employees,customers, suppliers,community versesshareholder benefit)NoIs it ethical not to takeaction? (Weigh theharm to shareholdersverses benefits to otherstakeholders)NoYesDoes actionmaximizecompanyreturns?Isactionlegal?Figure A.4Do itDon’tdo itDon’tdo itDo it,but notifyappropriatepartiesDon’tdo itAction outcome
  • 36. A - 36© 2011 Pearson Education, Inc. publishing as Prentice HallThe Poker Design ProcessIf T. J. folds,If T. J. calls,EMV = (.80)($99,000)= $79,200EMV = .20[(.45)($853,000) - Phillips’ bet of $422,000]= .20[$383,850 - $422,000]= .20[-$38,150] = -$7,630Overall EMV = $79,200 - $7,630 = $71,750
  • 37. A - 37© 2011 Pearson Education, Inc. publishing as Prentice HallAll rights reserved. No part of this publication may be reproduced, stored in a retrievalsystem, or transmitted, in any form or by any means, electronic, mechanical, photocopying,recording, or otherwise, without the prior written permission of the publisher.Printed in the United States of America.

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