To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-1 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Prepared by Lee Revere and John Large Chapter 3 Decision Analysis

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-2 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Learning Objectives Students will be able to: 1.List the steps of the decision-making process. 2.Describe the types of decision-making environments. 3.Make decisions under uncertainty. 4.Use probability values to make decisions under risk. 5.Develop accurate and useful decision trees. 6.Revise probabilities using Bayesian analysis. 7.Use computers to solve basic decision- making problems. 8.Understand the importance and use of utility theory in decision theory.

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-3 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Chapter Outline 3.1 Introduction 3.2 The Six Steps in Decision Theory 3.3 Types of Decision-Making Environments 3.4 Decision Making under Uncertainty 3.5 Decision Making under Risk 3.6 Decision Trees 3.7 How Probability Values Are Estimated by Bayesian Analysis 3.8 Utility Theory

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-4 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Introduction  Decision theory is an analytical and systematic way to tackle problems.  A good decision is based on logic.

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-5 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ The Six Steps in Decision Theory 1.Clearly define the problem at hand. 2.List the possible alternatives. 3.Identify the possible outcomes. 4.List the payoff or profit of each combination of alternatives and outcomes. 5.Select one of the mathematical decision theory models. 6.Apply the model and make your decision.

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-6 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ John Thompson’s Backyard Storage Sheds Define problemTo manufacture or market backyard storage sheds List alternatives1.Construct a large new plant 2.A small plant 3.No plant at all Identify outcomesThe market could be favorable or unfavorable for storage sheds List payoffsList the payoff for each state of nature/decision alternative combination Select a modelDecision tables and/or trees can be used to solve the problem Apply model and make decision Solutions can be obtained and a sensitivity analysis used to make a decision

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-7 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Decision Table for Thompson Lumber Alternative State of Nature Favorable Market ($) Unfavorable Market ($) Construct a large plant 200, ,000 Construct a small plant 100,000-20,000 Do nothing00

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-8 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Types of Decision- Making Environments  Type 1: Decision making under certainty.  Decision maker knows with certainty the consequences of every alternative or decision choice.  Type 2: Decision making under risk.  The decision maker does know the probabilities of the various outcomes.  Decision making under uncertainty.  The decision maker does not know the probabilities of the various outcomes.

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-9 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Decision Making under Uncertainty  Maximax  Maximin  Equally likely (Laplace)  Criterion of realism  Minimax

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-10 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Decision Table for Thompson Lumber Alternative State of Nature Favorable Market ($) Unfavorable Market ($) Construct a large plant 200, ,000 Construct a small plant 100,000-20,000 Do nothing00  Maximax: Optimistic Approach  Find the alternative that maximizes the maximum outcome for every alternative.

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-11 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Thompson Lumber: Maximax Solution Alternative State of Nature Maximax Favorable Market ($) Unfavorable Market ($) Construct a large plant 200, ,000200,000 Construct a small plant 100,000-20,000100,000 Do nothing000

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-12 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Decision Table for Thompson Lumber Alternative State of Nature Favorable Market ($) Unfavorable Market ($) Construct a large plant 200, ,000 Construct a small plant 100,000-20,000 Do nothing00  Maximin: Pessimistic Approach  Choose the alternative with maximum minimum output.

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-13 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Thompson Lumber: Maximin Solution Alternative State of Nature Maximin Favorable Market ($) Unfavorable Market ($) Construct a large plant 200, ,000 Construct a small plant 100,000-20,000 Do nothing000

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-14 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Thompson Lumber: Hurwicz  Criterion of Realism (Hurwicz)  Decision maker uses a weighted average based on optimism of the future. Alternative State of Nature Favorable Market ($) Unfavorable Market ($) Construct a large plant 200, ,000 Construct a small plant 100,000-20,000 Do nothing00

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-15 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Thompson Lumber: Hurwicz Solution CR = α*(row max)+(1- α)*(row min) Alternative State of Nature Criterion of Realism or Weighted Average (α = 0.8) ($) Favorable Market ($) Unfavorable Market ($) Construct a large plant 200, ,000124,000 Construct a small plant 100,000-20,00076,000 Do nothing000

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-16 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Decision Making under Uncertainty  Equally likely (Laplace)  Assume all states of nature to be equally likely, choose maximum Average. Alternative State of Nature Favorable Market ($) Unfavorable Market ($) Construct a large plant 200, ,000 Construct a small plant 100,000-20,000 Do nothing00

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-17 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Decision Making under Uncertainty Alternative State of Nature Avg. Favorable Market ($) Unfavorable Market ($) Construct a large plant 200, ,00010,000 Construct a small plant 100,000-20,00040,000 Do nothing000

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-18 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Thompson Lumber; Minimax Regret  Minimax Regret:  Choose the alternative that minimizes the maximum opportunity loss. Alternative State of Nature Favorable Market ($) Unfavorable Market ($) Construct a large plant 200, ,000 Construct a small plant 100,000-20,000 Do nothing00

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-19 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Thompson Lumber: Opportunity Loss Table Alternative State of Nature Favorable Market ($) Unfavorable Market ($) Construct a large plant 200,000 – 200,000 = 0 0- (-180,000) = 180,000 Construct a small plant 200, ,000 = 100, (-20,000) = 20,000 Do nothing200,000 – 0 = 00 – 0 = 0

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-20 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Thompson Lumber: Minimax Regret Solution Alternative State of Nature Maximum Opportunity Loss Favorable Market ($) Unfavorable Market ($) Construct a large plant 0180,000 Construct a small plant 100,00020,000100,000 Do nothing200,0000

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-21 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ In-Class Example 1  Let’s practice what we’ve learned. Use the decision table below to compute (1) Mazimax (2) Maximin (3) Minimax regret Alternative State of Nature Good Market ($) Average Market ($) Poor Market ($) Construct a large plant 75,00025,000-40,000 Construct a small plant 100,00035,000-60,000 Do nothing000

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-22 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ In-Class Example 1: Maximax Alternative State of Nature Maximax Good Market ($) Average Market ($) Poor Market ($) Construct a large plant 75,00025,000-40,00075,000 Construct a small plant 100,00035,000-60,000100,000 Do nothing0000

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-23 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ In-Class Example 1: Maximin Alternative State of Nature Maximin Good Market ($) Average Market ($) Poor Market ($) Construct a large plant 75,00025,000-40,000 Construct a small plant 100,00035,000-60,000 Do nothing0000

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-24 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ In-Class Example 1: Minimax Regret Opportunity Loss Table Alternative State of Nature Maximum Opp. Loss Good Market ($) Average Market ($) Poor Market ($) Construct a large plant 25,00075,00040,000 Construct a small plant 0060,000 Do nothing100,00035, ,000

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-25 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Decision Making under Risk Expected Monetary Value: In other words: EMV Alternative n = Payoff 1 * P Alt. 1 + Payoff 2 * P Alt. 2 + … + Payoff n * P Alt. n

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-26 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Thompson Lumber: EMV Alternative State of Nature EMV Favorable Market ($) Unfavorable Market ($) Construct a large plant 200, , ,000*0.5 + (-180,000)*0.5 = 10,000 Construct a small plant 100,000-20, ,000*0.5 + (-20,000)*0.5 = 40,000 Do nothing000* *0.5 = 0 Probabilities0.50

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-27 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Thompson Lumber: EV|PI and EMV Solution Alternative State of Nature EMV Favorable Market ($) Unfavorable Market ($) Construct a large plant 200, ,00010,000 Construct a small plant 100,000-20,00040,000 Do nothing000 EV ׀ PI 200,000* 0.5 = 100,000 0*0.5 = 0

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-28 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Expected Value of Perfect Information (EVPI)  EVPI places an upper bound on what one would pay for additional information.  EVPI is the expected value with perfect information minus the maximum EMV.

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-29 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Expected Value with Perfect Information (EV|PI) In other words EV ׀ PI = Best Outcome of Alt 1 * P Alt. 1 + Best Outcome of Alt 2 * P Alt. 2 +… + Best Outcome of Alt n * P Alt. n

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-30 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Expected Value of Perfect Information EVPI = EV|PI - maximum EMV Expected value with perfect information Expected value with no additional information

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-31 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Thompson Lumber: EVPI Solution EVPI EMV EVPI = expected value with perfect information - max(EMV) = $200,000* * $40,000 = $60,000 From previous slide

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-32 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ In-Class Example 2 Let’s practice what we’ve learned. Using the table below compute EMV, EV ׀ PI, and EVPI. Alternative State of Nature Good Market ($) Average Market ($) Poor Market ($) Construct a large plant 75,00025,000-40,000 Construct a small plant 100,00035,000-60,000 Do nothing000

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-33 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ In-Class Example 2: EMV and EV׀PI Solution Alternative State of Nature EMV Good Market ($) Average Market ($) Poor Market ($) Construct a large plant 75,00025,000-40,00021,250 Construct a small plant 100,00035,000-60,00027,500 Do nothing0000

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-34 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ In-Class Example 2: EVPI Solution EVPI EMV EVPI = expected value with perfect information - max(EMV) = $100,000* ,000* *0.25 = $ 42, ,500 = $ 15,000

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-35 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Expected Opportunity Loss  EOL is the cost of not picking the best solution. EOL = Expected Regret

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-36 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Thompson Lumber: EOL The Opportunity Loss Table Alternative State of Nature Favorable Market ($) Unfavorable Market ($) Construct a large plant 200,000 – 200, (-180,000) Construct a small plant 200, ,000 0 – (-20,000) Do nothing200, Probabilities0.50

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-37 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Thompson Lumber: EOL Table Alternative State of Nature Favorable Market ($) Unfavorable Market ($) Construct a large plant 200, ,000 Construct a small plant 100,000-20,000 Do nothing00 Probabilities0.50

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-38 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Thompson Lumber: EOL Solution

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-39 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Thompson Lumber: Sensitivity Analysis EMV(Large Plant): = $200,000P - (1-P)$180,000 EMV(Small Plant): = $100,000P - $20,000(1-P) EMV(Do Nothing): = $0P + 0(1-P)

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-40 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Thompson Lumber: Sensitivity Analysis (continued) Values of P EMV Values Point 1 Point 2 Small Plant Large Plant EMV

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-41 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Marginal Analysis  P = probability that demand > a given supply.  1-P = probability that demand < supply.  MP = marginal profit.  ML = marginal loss.  Optimal decision rule is:  P*MP  (1-P)*ML or

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-42 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Marginal Analysis - Discrete Distributions Steps using Discrete Distributions : P.  Determine the value for P.  Construct a probability table and add a cumulative probability column. P.  Keep ordering inventory as long as the probability of selling at least one additional unit is greater than P.

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-43 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Café du Donut: Marginal Analysis Café du Donut sells a dozen donuts for $6. It costs $4 to make each dozen. The following table shows the discrete distribution for Café du Donut sales.

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-44 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Café du Donut: Marginal Analysis Solution Marginal profit = selling price - cost = $6 - $4 = $2 Marginal loss = cost Therefore:

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-45 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Café du Donut: Marginal Analysis Solution

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-46 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ In-Class Example 3 Let’s practice what we’ve learned. You sell cases of goods for $15/case, the raw materials cost you $4/case, and you pay $1/case commission.

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-47 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ In-Class Example 3: Solution MP = $15-$4-$1 = $10 per caseML = $4 P>= $4 / $10+$4 =.286

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-48 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Marginal Analysis Normal Distribution     = average or mean sales     = standard deviation of sales  MP  MP = marginal profit  ML  ML = Marginal loss

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-49 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Marginal Analysis - Discrete Distributions Steps using Normal Distributions:  Determine the value for P.  Locate P on the normal distribution. For a given area under the curve, we find Z from the standard Normal table.  Using we can now solve for:    * X Z MPML P   X*

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-50 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Marginal Analysis: Normal Curve Review

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-51 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Marginal Analysis - Normal Curve Review area =.30 Use table to find Z area =.70 MPML.3  

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-52 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Joe’s Newsstand Example Joe sells newspapers for $1.00 each. Papers cost him $.40 each. His average daily demand is 50 papers with a standard deviation of 10 papers. Assuming sales follow a normal distribution, how many papers should Joe stock?  ML  ML = $0.40  MP  MP = $0.60     = Average demand = 50 papers per day     = Standard deviation of demand = 10

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-53 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Joe’s Newsstand Example (continued) Step 1:    . MP ML ML P     .

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-54 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Joe’s Newsstand Example (continued) Step 2: Look on the Normal table for PZ P = 0.6 (i.e., 1 -.4)  Z = 0.25, and or: *X X * = 10 * = 52.5 or 53 newspapers

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-55 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Joe’s Newsstand Example B  Joe also offers his clients the “Times” for $1.00. This paper is flown in from out of state, which greatly increases its costs. Joe pays $.80 for the “Times.” The “Times” has average daily sales of 100 papers with a standard deviation of 10. Assuming sales follow a normal distribution, how many “Times” papers should Joe stock?  ML  ML = $0.80  MP  MP = $0.20     = Average demand = 100 papers per day     = Standard deviation of demand = 10

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-56 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Joe’s Newsstand Example B (continued) Step 1:   . MP ML ML P     .

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-57 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Step 2: Z = 0.80 = for an area of 0.80 And or: X= or 92 newspapers  *X Joe’s Newsstand Example B (continued)

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-58 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Decision Making with Uncertainty: Using the Decision Trees Decision trees Decision trees enable one to look at decisions: alternativesstates of nature,  With many alternatives and states of nature,  which must be made in sequence.

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-59 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Five Steps to Decision Tree Analysis 1.Define the problem. 2.Structure or draw the decision tree. 3.Assign probabilities to the states of nature. 4.Estimate payoffs for each possible combination of alternatives and states of nature. 5.Solve the problem by computing expected monetary values (EMVs) for each state of nature node.

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-60 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Structure of Decision Trees A graphical representation where:  A decision node from which one of several alternatives may be chosen.  A state-of-nature node out of which one state of nature will occur.

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-61 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Thompson’s Decision Tree 1 2 A Decision Node A State of Nature Node Favorable Market Unfavorable Market Favorable Market Unfavorable Market Construct Large Plant Construct Small Plant Do Nothing Step 1: Define the problem Lets re-look at John Thompson’s decision regarding storage sheds. This simple problem can be depicted using a decision tree. Step 2: Draw the tree

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-62 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Thompson’s Decision Tree 1 2 A Decision Node A State of Nature Node Favorable (0.5) Market Unfavorable (0.5) Market Favorable (0.5) Market Unfavorable (0.5) Market Construct Large Plant Construct Small Plant Do Nothing $200,000 -$180,000 $100,000 -$20,000 0 Step 3: Assign probabilities to the states of nature. Step 4: Estimate payoffs.

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-63 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Thompson’s Decision Tree 1 2 A Decision Node A State of Nature Node Favorable (0.5) Market Unfavorable (0.5) Market Favorable (0.5) Market Unfavorable (0.5) Market Construct Large Plant Construct Small Plant Do Nothing $200,000 -$180,000 $100,000 -$20,000 0 EMV=$40,000 EMV=$10,000 Step 5: Compute EMVs and make decision.

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-64 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Thompson’s Decision: A More Complex Problem  John Thompson has the opportunity of obtaining a market survey that will give additional information on the probable state of nature. Results of the market survey will likely indicate there is a percent change of a favorable market. Historical data show market surveys accurately predict favorable markets 78 % of the time. Thus P(Fav. Mkt / Fav. Survey Results) =.78  Likewise, if the market survey predicts an unfavorable market, there is a 13 % chance of its occurring. P(Unfav. Mkt / Unfav. Survey Results) =.13  Now that we have redefined the problem (Step 1), let’s use this additional data and redraw Thompson’s decision tree (Step 2).

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-65 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Thompson’s Decision Tree

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-66 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Thompson’s Decision Tree Step 3: Assign the new probabilities to the states of nature. Step 4: Estimate the payoffs.

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-67 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Thompson’s Decision Tree Step 5: Compute the EMVs and make decision.

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-68 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ John Thompson Dilemma John Thompson is not sure how much value to place on market survey. He wants to determine the monetary worth of the survey. John Thompson is also interested in how sensitive his decision is to changes in the market survey results. What should he do?  Expected Value of Sample Information  Sensitivity Analysis

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-69 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Expected Value of Sample Information with Expected value of best decision with sample information, assuming no cost to gather it without Expected value of best decision without sample information EVSI EVSI = EVSI for Thompson Lumber = $59,200 - $40,000 = $19,200 Thompson could pay up to $19,200 and come out ahead.

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-70 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Calculations for Thompson Lumber Sensitivity Analysis 2,400$104,000 ($2,400)($106,400)1) EMV(node   p )p(p  EMV Equating the EMV(node 1) to the EMV of not conducting the survey, we have 0.36 $104,000 $37,600 or $37,600$104,000 $40,000$2,400$104,000     p p p

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-71 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ In-Class Problem 3 Let’s practice what we’ve learned Leo can purchase a historic home for $200,000 or land in a growing area for $50,000. There is a 60% chance the economy will grow and a 40% change it will not. If it grows, the historic home will appreciate in value by 15% yielding a $30,00 profit. If it does not grow, the profit is only $10,000. If Leo purchases the land he will hold it for 1 year to assess the economic growth. If the economy grew during the first year, there is an 80% chance it will continue to grow. If it did not grow during the first year, there is a 30% chance it will grow in the next 4 years. After a year, if the economy grew, Leo will decide either to build and sell a house or simply sell the land. It will cost Leo $75,000 to build a house that will sell for a profit of $55,000 if the economy grows, or $15,000 if it does not grow. Leo can sell the land for a profit of $15,000. If, after a year, the economy does not grow, Leo will either develop the land, which will cost $75,000, or sell the land for a profit of $5,000. If he develops the land and the economy begins to grow, he will make $45,000. If he develops the land and the economy does not grow, he will make $5,000.

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-72 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ In-Class Problem 3: Solution Purchase historic home Purchase land Economy grows (.6) No growth (.4) Economy grows (.6) No growth (.4) Build house Economy grows (.8) No growth (.2) Sell land Develop land Sell land Economy grows (.3) No growth (.7)

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-73 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ In-Class Problem 3: Solution Purchase historic home Purchase land $35,000 $22,000 Economy grows (.6) $30,000 No growth (.4) $10,000 Economy grows (.6) No growth (.4) $35,000 $47,000 Build house $47,000 Economy grows (.8) $55,000 $15,000 No growth (.2) Sell land $15,000 $17,000 Develop land Sell land $5,000 Economy grows (.3) No growth (.7) $45,000 $5,000 $17,000

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-74 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Estimating Probability Values with Bayesian  Management experience or intuition  History  Existing data  Need to be able to revise probabilities based upon new data Posterior probabilities Prior probabilities New data Baye’s Theorem

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-75 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Bayesian Analysis Market Survey Reliability in Predicting Actual States of Nature Result of Survey Favorable Market (FM) Unfavorable Market (UM) Positive (predicts favorable market for product) P (survey positive|FM) = 0.70 P (survey positive|UM) = 0.20 Negative (predicts unfavorable market for product) P(survey negative|FM) = 0.30 P(survey negative|UM) = 0.80 The probabilities of a favorable / unfavorable state of nature can be obtained by analyzing the Market Survey Reliability in Predicting Actual States of Nature.

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-76 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Bayesian Analysis (continued): Favorable Survey Probability Revisions Given a Favorable Survey Conditional Probability Posterior Probability State of Nature P(Survey positive|State of Nature Prior Probability Joint Probability FM 0.70* = 0.78 UM 0.20 * =

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-77 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Bayesian Analysis (continued): Unfavorable Survey Probability Revisions Given an Unfavorable Survey Conditional Probability Posterior Probability State of Nature P(Survey negative|State of Nature) Prior Probability Joint Probability FM 0.30* = 0.27 UM0.80* =

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-78 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Decision Making Using Utility Theory  Utility assessment assigns the worst outcome a utility of 0, and the best outcome, a utility of 1.  A standard gamble is used to determine utility values.  When you are indifferent, the utility values are equal.

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-79 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Standard Gamble for Utility Assessment Best outcome Utility = 1 Worst outcome Utility = 0 Other outcome Utility = ?? (p)(p) (1-p) Alternative 1 Alternative 2

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-80 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Simple Example: Utility Theory $5,000,000 $0 $2,000,000 Accept Offer Reject Offer Heads (0.5) Tails (0.5) Let’s say you were offered $2,000,000 right now on a chance to win $5,000,000. The $5,000,000 is won only if you flip a coin and get tails. If you get heads you lose and get $0. What should you do?

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-81 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Real Estate Example: Utility Theory Jane Dickson is considering a 3-year real estate investment. There is an 80 % chance the real estate market will soar and a 20 % chance it will bust. In a good market the real estate investment will pay $10,000, in an unfavorable market it is $0. Of course, she could leave her money in the bank and earn a $5,000 return. What should she do?

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-82 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Real Estate Example: Solution $10,000 U($10,000) = U(0)=0 $5,000 U($5,000)=p =0.80 p= 0.80 (1-p)= 0.20 Invest in Real Estate Invest in Bank

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-83 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Utility Curve for Jane Dickson

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-84 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Preferences for Risk Monetary Outcome Risk Avoider Risk Seeker Risk Indifference Utility

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-85 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Decision Facing Mark Simkin Tack lands point up (0.45) Tack lands point down (0.55) $10,000 -$10,000 0 Alternative 1 Mark plays the game Alternative 2 Mark does not play the game

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-86 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Utility Curve for Mark Simkin

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-87 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Thompson Decision Tree Problem Using QM for Windows

To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-88 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Thompson Decision Tree Problem Using Excel