Presentation is loading. Please wait.

Presentation is loading. Please wait.

Introduction to Decision Analysis

Similar presentations

Presentation on theme: "Introduction to Decision Analysis"— Presentation transcript:

1 Introduction to Decision Analysis
Decision analysis studies the process of making difficult decisions The objective is to update, model, and document the intuition of managers A structured approach to decision making is especially critical in group decision making Key importance in the case of resource decisions (operations strategy)

2 Why are decisions difficult?
Complexity Simply keeping all the issues in mind at one time is nearly imposible Uncertainty Making a decision is especially difficult when you are not sure about one decision variable’s state Multiple objectives Different perspectives lead to different conclusions

3 Example Winter of 1985: The Oregon Department of Agriculture (ODA) faced an infestation of gypsy moth in Lane County in Western Oregon Forest industry representative call for an aggressive eradication campaign

4 Alternatives Use BT, a bacterial insecticide
target specific ecologically safe reasonably effective Use Orthene, a chemical spray registered as acceptable for home garden use questions about its ultimate ecological effects possible danger to humans Possible to use both

5 Opinions Forestry officials: Environmentalists: Others Others...
Argue Orthene is more potent and is necessary to ensure eradication Environmentalists: Orthene potentially too dangerous Others Already too late anyway Others... Still time but decision/implementation has to be made now

6 Subjective Judgments In decisional contexts such as the one faced by ODA objective data is lacking a procedure determining an « optimal » decision derived from objective data is of little use... personal statements about uncertainty and value become important inputs (no choice...) Discovering and finalizing these judgments is a key issue in decision analysis Instead of criticizing them, we will learn how to better assess and use them

7 The Decision Analysis Process
Identify the decision situation and understand objectives Identify alternatives Decompose and model the problem model of problem structure model of uncertainty model of preferences Choose the best alternative Sensitivity analysis Is further analysis needed? yes/no? Implement the chosen alternative

8 Requisite Decision Models
A model can be considered requisite only when no new intuitions emerge about the problem or when it contains everything that is essential for solving the problem

9 Elements of a Decision Problem
Values and objectives Decisions to make Uncertain events Consequences

10 Values and Objectives Value: used in its general sense « things that matter to you » Objective: Specific thing that you want to achieve The set of objectives taken up together make up the values Values are the reason for making the decision in the first place They define the decision context

11 Objectives for Boeing’s Supercomputer
Cost Five-year costs Cost of improved performance Management Issue Vendor Health US Ownership Commitment to supercomputer Performance Speed Throughput Memory Size Disk Size On-site performance User Needs Installation date Roll in/Roll out Ease of Use Software compatibility Mean time between failures Operational Needs Square footage Water cooling Operator tools Telecommuni- -cations Vendor support

12 Decision to Make Given a decisional context, one (or several) decision(s) has to be made In some cases, several decisions may have to be made in a sequence Time Decision 1 Decision 2 Decision 3

13 Uncertain Events Uncertain events are either linked to chance or are linked to a probability distribution Uncertain events have outcome It is important to position uncertain events appropriately between decisions Decision 1 Decision 2 Decision 3 Time

14 Consequences After the last decision has been made and the last uncertain event has been resolved, the decision maker’s fate is finally determined Time Decision 1 Decision 2 Decision 3 Consequence

15 Example Consequence: Cost $ Environmental damage PR damage Accident
Weather for Cleanup Weather Accident Cost Location Environmental Damage Cause Consequence: Cost $ Environmental damage PR damage Accident Management Decisions Policy Decision Time

16 Making Choices Decision Trees Example: Texaco vs. Pennzoil
Decision trees and expected value certainty equivalent

17 Decision Trees Decision trees are a graphical representation of a decision problem Large return Venture succeeds Invest Funds lost Venture fails Do not invest Typical return earned on less risky investment

18 Decision Tree Safety Cost Evacuate Safe High Storm hits Miami Forecast
Danger Low Stay Safe Low Storm misses Miami

19 Cash Flows and Probabilities
To each branch of the tree, we can attach a probability and/or, a cash flow or any measure replacing monetary values for a specific problem

20 Case Study: Texaco vs. Pennzoil
In early 1984, Pennzoil and Getty Oil agreed to the terms of a merger Before the signature of the formal agreement, Texaco offered Getty a substantially better price , and Gordon Getty (majority stockholder) defected on Pennzoil and sold to Texaco

21 Case Study: Texaco vs. Pennzoil
Pennzoil felt this was unfair practice and filed a lawsuit against Texaco, alleging that Texaco had interfered illegally in the the Pennzoil-Getty negotiations Pennzoil won the case in late 1985 and was awarded $11.1 billion – the largest settlement in the US at this point in time Texaco appealed and the settlement was reduced by $2 billion – but interest and penalty got the amount back to $10.3 billion

22 Case Study: Texaco vs. Pennzoil
Kinnear, Texaco’s CEO, announced that Texaco would file for bankruptcy if Pennzoil obtained court permission to secure the judgment by filing liens against Texaco’s assets Kinnear promised to fight the case all the way to the Supreme Court

23 Texaco’s Offer In April 1987, just before Pennzoil started filing liens, Texaco offered to pay Pennzoil $2billion to settle the entire case Liedtke, chairman of Pennzoil, announced that his advisors estimated that a settlement of 3-5 billions would be fair What should Liedtke do?

24 Decision Tree 2 5 10.3 5 10.3 5 3 Settlement Amount ($billion)
Accepts $2 billion 2 Texaco accepts $5 billion 5 Counteroffer $5 billion 10.3 Texaco refuses counteroffer Final Court Decision 5 10.3 Note: Several estimates are included in this decision tree and decision have in effect, already been made: If Pennzoil counteroffer, it will be for a settlement of $5billion Texaco could counter-offer with another value than $3billion! The court judgment is any value between 0 and 10.3 billion – the value of 5 is a compromise judgment – this, also, is an estimation Final Court Decision Texaco counteroffers $3 billion 5 Refuse Accepts $3 billion 3

25 Subjective Probabilities
In the decision tree, we are missing probability estimates of the each event For this lecture, we will take these probability values for granted

26 Decision Tree 2 5 10.3 5 10.3 5 3 Settlement Amount ($billion)
Accepts $2 billion 2 Texaco accepts $5 billion 5 (0.17) (0.2) 10.3 Counteroffer $5 billion Texaco refuses counteroffer Final Court Decision (0.5) 5 (0.3) (0.50) (0.2) 10.3 (0.33) Final Court Decision (0.5) Texaco counteroffers $3 billion 5 Refuse (0.3) Accepts $3 billion 3

27 Expected Monetary Value
Computing an expected monetary value is a way of selecting among risky alternative Computing expected values bring the problem back to a « certainty equivalent » What is the expected value of the court judgment?

28 Expected Value of the Court Judgment
EV = 0.2 * * * 0 EV = $ 4.56 billion (0.2) 10.3 Final Court Decision (0.5) 5 (0.3) It is possible to reduce the tree with this certainty equivalent

29 Reduced Tree 2 5 4.56 4.56 Eliminated 3 Accepts $2 billion
Texaco accepts $5 billion 5 (0.17) Counteroffer $5 billion Texaco refuses counteroffer 4.56 (0.50) (0.33) 4.56 Texaco counteroffers $3 billion Refuse Accepts $3 billion Eliminated 3

30 Expected Monetary Value of the Counteroffer
What is the expected monetary value of Pennzoil $5 billion counter offer: EV = P(Texaco accepts) * 5 + P(Texaco refuse) * P(Texaco counteroffers) * 4.56 EV = 4.63 Liedtke should not accept the $2 billion offer, and should counter-offer $5 billion. If Texaco refuses, then the matter should be taken to court

31 Reducing the Decision Tree
In practice, we do not reduce the decision tree but report expected values on the nodes

32 Resolved Decision Tree
Accepts $2 billion 2 Texaco accepts $5 billion 5 (0.17) Counteroffer $5 billion (0.2) 10.3 Texaco refuses counteroffer Final Court Decision (0.5) 4.56 5 (0.3) 4.63 (0.50) (0.2) 10.3 (0.33) Final Court Decision (0.5) Texaco counteroffers $3 billion 4.56 5 Refuse (0.3) Accepts $3 billion 3

33 Suggested Homework Problem S2-10, p. 70 Problem S2-13, p. 71

Download ppt "Introduction to Decision Analysis"

Similar presentations

Ads by Google