To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Supplement A Decision Making.

Slides:



Advertisements
Similar presentations
To Accompany Krajewski & Ritzman Operations Management: Strategy and Analysis, Seventh Edition © 2004 Prentice Hall, Inc. All rights reserved. Decision.
Advertisements

© 2007 Pearson Education Decision Making Supplement A.
Operations Management
To Accompany Krajewski & Ritzman Operations Management: Strategy and Analysis, Sixth Edition © 2002 Prentice Hall, Inc. All rights reserved. Chapter 8.
To accompany Quantitative Analysis for Management, 9e by Render/Stair/Hanna 3-1 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Prepared by.
Chapter 3 Decision Analysis.
Decision Analysis Chapter 3
Module 16 – Decision Theory
20- 1 Chapter Twenty McGraw-Hill/Irwin © 2005 The McGraw-Hill Companies, Inc., All Rights Reserved.
McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved. 5S Decision Theory.
Introduction to Decision Analysis
Decision Process Identify the Problem
Operations Management
Chapter 3 Decision Analysis.
Copyright © 2011 The McGraw-Hill Companies, All Rights Reserved CHAPTER 4 Strategic Capacity Management.
1 IES 303 Supplement A: Decision making Week 3 Nov 24, 2005 Objective: - Amazon.com Case discussion: competitive advantage - Understand practical techniques.
Decision Theory Chapter 5 Supplement June 26, 2012.
A – 1 Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall. Decision Making A For Operations Management, 9e by Krajewski/Ritzman/Malhotra.
Part 3 Probabilistic Decision Models
Supplement A Decision Making.
5s-1Decision Theory McGraw-Hill/Irwin Operations Management, Eighth Edition, by William J. Stevenson Copyright © 2005 by The McGraw-Hill Companies, Inc.
ISMT 161: Introduction to Operations Management
Decision Analysis Chapter 3
Decision Making Under Uncertainty and Under Risk
Decision Analysis Chapter 3
IES 303 Supplement A: Decision making Week 3 Nov 24, 2005 Objective:
© 2008 Prentice Hall, Inc.A – 1 Operations Management Module A – Decision-Making Tools PowerPoint presentation to accompany Heizer/Render Principles of.
5s-1 McGraw-Hill Ryerson Operations Management, 2 nd Canadian Edition, by Stevenson & Hojati Copyright © 2004 by The McGraw-Hill Companies, Inc. All rights.
To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 3-1 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ Chapter 3 Fundamentals.
Decision Analysis Chapter 3
Supplement E - Special Inventory Models. Special Inventory Models Production quantity Demand during production interval Maximum inventory Production and.
To Accompany Krajewski & Ritzman Operations Management: Strategy and Analysis, Sixth Edition © 2002 Prentice Hall, Inc. All rights reserved. Supplement.
© 2006 Prentice Hall, Inc.A – 1 Operations Management Module A – Decision-Making Tools © 2006 Prentice Hall, Inc. PowerPoint presentation to accompany.
Decision Analysis A. A. Elimam College of Business San Francisco State University.
8-1 CHAPTER 8 Decision Analysis. 8-2 LEARNING OBJECTIVES 1.List the steps of the decision-making process and describe the different types of decision-making.
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved. Chapter 6 Capacity.
To reach your goal you must take the first step. There is only one boss. The CUSTOMER! And he can fire anyone in the company from the chairman on down,
A – 1 Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall. Decision Making A For Operations Management, 9e by Krajewski/Ritzman/Malhotra.
McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved. 5 Capacity Planning For Products and Services.
© 2007 Pearson Education Decision Making Supplement A.
Breakeven Analysis Improving Productivity. Break-Even Analysis Break-even analysis has TWO forms: – A. CVP (cost-volume-profit): to determine the volume.
Decision Analysis Mary Whiteside. Decision Analysis Definitions Actions – alternative choices for a course of action Actions – alternative choices for.
A - 1© 2011 Pearson Education, Inc. publishing as Prentice Hall A A Decision-Making Tools PowerPoint presentation to accompany Heizer and Render Operations.
© 2008 Prentice Hall, Inc.A – 1 Decision-Making Environments  Decision making under uncertainty  Complete uncertainty as to which state of nature may.
Welcome Unit 4 Seminar MM305 Wednesday 8:00 PM ET Quantitative Analysis for Management Delfina Isaac.
Decision Theory McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved.
Lecture 6 Decision Making.
Decision Theory Copyright © 2015 McGraw-Hill Education. All rights reserved. No reproduction or distribution without the prior written consent of McGraw-Hill.
1-1 Steps to Good Decisions  Define problem and influencing factors  Establish decision criteria  Select decision-making tool (model)  Identify and.
BUAD306 Chapter 5S – Decision Theory. Why DM is Important The act of selecting a preferred course of action among alternatives A KEY responsibility of.
Decision Theory McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved.
Decision Analysis.
To Accompany Krajewski & Ritzman Operations Management: Strategy and Analysis, Seventh Edition © 2004 Prentice Hall, Inc. All rights reserved. Special.
SUPPLEMENT TO CHAPTER TWO Irwin/McGraw-Hill © The McGraw-Hill Companies, Inc., 1999 DECISION MAKING 2S-1 Chapter 2 Supplement Decision Making.
5s-1Decision Theory CHAPTER 5s Decision Theory McGraw-Hill/Irwin Operations Management, Eighth Edition, by William J. Stevenson Copyright © 2005 by The.
A – 1 Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall. Decision Making A For Operations Management, 9e by Krajewski/Ritzman/Malhotra.
DECISION THEORY & DECISION TREE
Chapter 5 Supplement Decision Theory.
Chapter 5S – Decision Theory
Determinants of Effective Capacity
Steps to Good Decisions
Decision Analysis Chapter 12.
Supplement: Decision Making
نظام التعليم المطور للانتساب
نظام التعليم المطور للانتساب
Special Inventory Models
Learning Curve Analysis
Decision Making Supplement A
Acceptance Sampling Plans
Presentation transcript:

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Supplement A Decision Making

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Learning Objectives Be able to apply concepts in learning goals Be able to use decision-making solvers manually –Breakeven analysis –Decision theory –Preference matrix Be able to formulate a decision tree manually and solve for optimum expected value

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Learning Objectives Understand & be able to apply the following formulas

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Break-Even Analysis 400 – 300 – 200 – 100 – 0 – Patients (Q) Dollars (in thousands) |||| Example A.1 QuantityTotal AnnualTotal Annual (patients)Cost ($)Revenue ($) (Q)(100, Q)(200Q) 0100, ,000400,000

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Break-Even Analysis 400 – 300 – 200 – 100 – 0 – Total annual revenues Patients (Q) Dollars (in thousands) |||| (2000, 400) Example A.1 QuantityTotal AnnualTotal Annual (patients)Cost ($)Revenue ($) (Q)(100, Q)(200Q) 0100, ,000400,000

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Break-Even Analysis Total annual revenues Total annual costs Patients (Q) Dollars (in thousands) 400 – 300 – 200 – 100 – 0 – |||| Fixed costs (2000, 400) (2000, 300) Example A.1 QuantityTotal AnnualTotal Annual (patients)Cost ($)Revenue ($) (Q)(100, Q)(200Q) 0100, ,000400,000

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Break-Even Analysis Total annual revenues Total annual costs Patients (Q) Dollars (in thousands) 400 – 300 – 200 – 100 – 0 – |||| Fixed costs Break-even quantity (2000, 400) (2000, 300) Profits Loss Example A.1 QuantityTotal AnnualTotal Annual (patients)Cost ($)Revenue ($) (Q)(100, Q)(200Q) 0100, ,000400,000

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Break-Even Analysis 400 – 300 – 200 – 100 – 0 – Figure A.1 Total annual revenues Total annual costs Patients (Q) Dollars (in thousands) |||| Fixed costs Break-even quantity (2000, 400) (2000, 300) Profits Loss

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Sensitivity Analysis 400 – 300 – 200 – 100 – 0 – Total annual revenues Total annual costs Patients (Q) Dollars (in thousands) |||| Fixed costs Profits Loss Example A.2

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Sensitivity Analysis 400 – 300 – 200 – 100 – 0 – Example A.2 Total annual revenues Total annual costs Patients (Q) Dollars (in thousands) |||| Fixed costs Profits Loss Forecast = 1,500

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Sensitivity Analysis 400 – 300 – 200 – 100 – 0 – Total annual revenues Total annual costs Patients (Q) Dollars (in thousands) |||| Fixed costs Profits Loss Example A.2 Forecast = 1,500 pQ – ( F + cQ )

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Sensitivity Analysis 400 – 300 – 200 – 100 – 0 – Total annual revenues Total annual costs Patients (Q) Dollars (in thousands) |||| Fixed costs Profits Loss Example A.2 Forecast = 1,500 pQ – ( F + cQ ) 200(1500) – [100, (1500)] $50,000

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Preference Matrix PerformanceWeightScoreWeighted Score Criterion(A)(B)(A x B) Market potential Unit profit margin Operations compatibility Competitive advantage Investment requirement Project risk Threshold score =.800

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Preference Matrix PerformanceWeightScoreWeighted Score Criterion(A)(B)(A x B) Market potential.30 Unit profit margin.20 Operations compatibility.20 Competitive advantage.15 Investment requirement.10 Project risk.05 Threshold score =.800

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Preference Matrix PerformanceWeightScoreWeighted Score Criterion(A)(B)(A x B) Market potential.30.8 Unit profit margin Operations compatibility.20.6 Competitive advantage Investment requirement.10.2 Project risk.05.4 Threshold score =.800

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Preference Matrix PerformanceWeightScoreWeighted Score Criterion(A)(B)(A x B) Market potential Unit profit margin Operations compatibility Competitive advantage Investment requirement Project risk Threshold score =.800

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Preference Matrix PerformanceWeightScoreWeighted Score Criterion(A)(B)(A x B) Market potential Unit profit margin Operations compatibility Competitive advantage Investment requirement Project risk Weighted score =.750 Threshold score =.800

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Preference Matrix PerformanceWeightScoreWeighted Score Criterion(A)(B)(A x B) Market potential Unit profit margin Operations compatibility Competitive advantage Investment requirement Project risk Weighted score =.750 Threshold score =.800 < 800

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Preference Matrix PerformanceWeightScoreWeighted Score Criterion(A)(B)(A x B) Market potential Unit profit margin Operations compatibility Competitive advantage Investment requirement Project risk Weighted score =.750 Threshold score =.800 Not At This Time

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Under Certainty AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Under Certainty AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand If future demand will be low —

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Under Certainty AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand If future demand will be low—Choose the small facility.

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Under Certainty AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand If future demand will be low—Choose the small facility.

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Under Uncertainty AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Under Uncertainty AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand Maximin —

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Under Uncertainty AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand Maximin— Best of the worst

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Under Uncertainty AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand Maximin—Small Best of the worst

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Under Uncertainty AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand Maximin - Small Maximax -

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Under Uncertainty AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand Maximin—Small Maximax— Best of the best

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Under Uncertainty AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand Maximin—Small Maximax—Large Best of the best

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Under Uncertainty AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand Maximin—Small Maximax—Large Laplace—

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Under Uncertainty AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand Maximin—Small Maximax—Large Laplace— Best weighted payoff Small facility0.5(200) + 0.5(270) = 235

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Under Uncertainty AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand Maximin—Small Maximax—Large Laplace— Best weighted payoff Small facility0.5(200) + 0.5(270) = 235 Large facility0.5(160) + 0.5(800) = 480

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Under Uncertainty AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand Maximin—Small Maximax—Large Laplace—Large Best weighted payoff Small facility0.5(200) + 0.5(270) = 235 Large facility0.5(160) + 0.5(800) = 480

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Under Uncertainty AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand Maximin—Small Maximax—Large Laplace—Large Minimax Regret—

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Under Uncertainty AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand Maximin—Small Maximax—Large Laplace—Large Minimax Regret— Best worst regret Regret Low DemandHigh Demand Small facility200 – 200 = 0800 – 270 = 530

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Under Uncertainty AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand Maximin—Small Maximax—Large Laplace—Large Minimax Regret— Best worst regret Regret Low DemandHigh Demand Small facility200 – 200 = 0800 – 270 = 530 Large facility200 – 160 = – 800 = 0

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Under Uncertainty AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand Maximin—Small Maximax—Large Laplace—Large Minimax Regret—Large Best worst regret Regret Low DemandHigh Demand Small facility200 – 200 = 0800 – 270 = 530 Large facility200 – 160 = – 800 = 0

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Under Uncertainty AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand Maximin—Small Maximax—Large Laplace—Large Minimax Regret—Large

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Under Risk AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand P low = 0.4 P high = 0.6

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Under Risk AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand P low = 0.4 P high = 0.6 AlternativeExpected Value Small facility0.4(200) + 0.6(270) = 242

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Under Risk AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand P low = 0.4 P high = 0.6 AlternativeExpected Value Small facility0.4(200) + 0.6(270) = 242 Large facility0.4(160) + 0.6(800) = 544

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Under Risk Highest Expected Value AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand P low = 0.4 P high = 0.6 AlternativeExpected Value Small facility0.4(200) + 0.6(270) = 242 Large facility0.4(160) + 0.6(800) = 544

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Perfect Information AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand P low = 0.4 P high = 0.6

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Perfect Information AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand P low = 0.4 P high = 0.6 EventBest Payoff Low demand200 High demand800

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Perfect Information EventBest Payoff Low demand200EV perfect = 200(0.4) + 800(0.6) = 560 High demand800 AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand P low = 0.4 P high = 0.6

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Perfect Information AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand P low = 0.4 P high = 0.6 EventBest Payoff Low demand200EV perfect = 200(0.4) + 800(0.6) = 560 High demand800EV imperfect = 160(0.4) + 800(0.6) = 544

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Perfect Information AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand P low = 0.4 P high = 0.6 EventBest Payoff Low demand200EV perfect = 200(0.4) + 800(0.6) = 560 High demand800EV imperfect = 160(0.4) + 800(0.6) = 544 Value of perfect information = $560,000 - $544,000

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Perfect Information AlternativeLowHigh Small facility Large facility Do nothing00 Possible Future Demand P low = 0.4 P high = 0.6 EventBest Payoff Low demand200EV perfect = 200(0.4) + 800(0.6) = 560 High demand800EV imperfect = 160(0.4) + 800(0.6) = 544 Value of perfect information = $16,000

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Decision Trees = Event node = Decision node E i = Event i P(E i ) = Probability of event i 1st decision Possible 2nd decision Payoff 1 Payoff 2 Payoff 3 Alternative 3 Alternative 4 Alternative 5 Payoff 1 Payoff 2 Payoff 3 E 1 [P(E 1 )] E 2 [P(E 2 )] E 3 [P(E 3 )] E 2 [P(E 2 )] E 3 [P(E 3 )] E 1 [P(E 1 )] Alternative 1 Alternative 2 Payoff 1 Payoff 2 12

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Decision Trees Small facility Large facility 1

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Decision Trees Small facility Large facility Low demand [0.4] Don’t expand Expand $200 $223 $270 High demand [0.6] 1 2

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Decision Trees Low demand [0.4] Small facility Large facility Low demand [0.4] Don’t expand Expand Do nothing Advertise $200 $223 $270 $40 $800 Modest response [0.3] Sizable response [0.7] $20 $220 High demand [0.6] 1 2 3

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Decision Trees Low demand [0.4] Small facility Large facility Low demand [0.4] Don’t expand Expand Do nothing Advertise $200 $223 $270 $40 $800 Modest response [0.3] Sizable response [0.7] $20 $220 High demand [0.6] 1 2 3

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Decision Trees Low demand [0.4] Small facility Large facility Low demand [0.4] Don’t expand Expand Do nothing Advertise $200 $223 $270 $40 $800 Modest response [0.3] Sizable response [0.7] $20 $220 High demand [0.6] (20) + 0.7(220)

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Decision Trees $160 Low demand [0.4] Small facility Large facility Low demand [0.4] Don’t expand Expand Do nothing Advertise $200 $223 $270 $40 $800 Modest response [0.3] Sizable response [0.7] $20 $220 High demand [0.6] (20) + 0.7(220)

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Decision Trees $160 Low demand [0.4] $160 Small facility Large facility Low demand [0.4] Don’t expand Expand Do nothing Advertise $200 $223 $270 $40 $800 Modest response [0.3] Sizable response [0.7] $20 $220 High demand [0.6] $270

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Decision Trees ($160) Low demand [0.4] $270 $160 Small facility Large facility Low demand [0.4] Don’t expand Expand Do nothing Advertise $200 $223 $270 $40 $800 Modest response [0.3] Sizable response [0.7] $20 $220 High demand [0.6] (200) + 0.6(270) 0.4(160) + 0.6(800)

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Decision Trees ($160) Low demand [0.4] $270 $160 Small facility Large facility $242 $544 Low demand [0.4] Don’t expand Expand Do nothing Advertise $200 $223 $270 $40 $800 Modest response [0.3] Sizable response [0.7] $20 $220 High demand [0.6] (200) + 0.6(270) 0.4(160) + 0.6(800)

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Decision Trees $160 Low demand [0.4] $270 $160 Small facility Large facility $544 $242 $544 Low demand [0.4] Don’t expand Expand Do nothing Advertise $200 $223 $270 $40 $800 Modest response [0.3] Sizable response [0.7] $20 $220 High demand [0.6] 1 2 3

To Accompany Ritzman & Krajewski Foundations of Operations Management, © 2003 Prentice Hall, Inc. All rights reserved. Decision Trees $160 Low demand [0.4] $270 $160 Small facility Large facility $544 $242 $544 Low demand [0.4] Don’t expand Expand Do nothing Advertise $200 $223 $270 $40 $800 Modest response [0.3] Sizable response [0.7] $20 $220 High demand [0.6] 1 2 3