# Module 4 Modeling Decisions: MAKING CHOICES - PowerPoint PPT Presentation

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Module 4 Modeling Decisions: MAKING CHOICES. Topics: Creating case study decision tree Solving a decision tree Risk profiles Dominance of alternatives Attributes and scales Using multiple objectives. Introduction. Module 3: Structure values and objectives Identify performance measures

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Module 4 Modeling Decisions: MAKING CHOICES

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#### Presentation Transcript

Module 4

Modeling Decisions:

MAKING CHOICES

Topics:

Creating case study decision tree

Solving a decision tree

Risk profiles

Dominance of alternatives

Attributes and scales

Using multiple objectives

### Introduction

• Module 3:

• Structure values and objectives

• Identify performance measures

• Structure decision tree and influence diagram models

• Module 4:

• Solve decision trees

• Approach for multiple objectives

• Module 4 software tutorial

### Making ChoicesLearning Objectives

• Create decision tree from case study

• Solve a decision tree

• Expected value preference criterion

• Create and interpret

• Risk profiles

• Cumulative risk profiles

• Concept of dominance

• Definition and identification

• Decision problem simplification

### Making ChoicesLearning Objectives

• Develop

• Constructed attributes

• Constructed scales

• Formulate multiple objectives problems

• Common scales

• Composite consequences

### Making Choices

• Analysis of structured problems

• graphing

• calculating

• examining results

### “Texaco versus Pennzoil”

• Pennzoil and Getty Oil agreed to a merger

• Texaco made better offer to Getty

• Getty reneged on Pennzoil and sold to Texaco

• Pennzoil sued Texaco for interference

• Pennzoil won and was awarded the \$11.1 billion

### “Texaco versus Pennzoil”

• Texaco appealed; award reduced to \$10.3 billion

• Texaco threatened bankruptcy if Pennzoil filed liens

• Texaco also threatened to take case to Supreme Court

### “Texaco versus Pennzoil”

• Texaco offered to settle out of court by paying Pennzoil \$2 billion

• Pennzoil believed fair settlement between \$3 and \$5 billion

### “Texaco versus Pennzoil”

• What should Pennzoil do?

• Accept \$2 billion settlement

• Make counteroffer

• Assume objective is to maximize settlement

### Decision Trees and Expected Monetary Value

• Expected Monetary Value (EMV); i.e., select alternative with highest expected value

• “Folding back the tree” or “rolling back” procedure

### Decision Trees and Expected Monetary Value

Folding Back:

• Start at the endpoints of the branches on the far right-hand-side and move to the left

• Calculate expected values at a chance node

• Choose the branch with the highest value or expected value at a decision node.

### Expected Monetary Value

• Weighted average of outcomes at chance node

• Sum of the product of each outcome and its probability

### Pennzoil’s Decision Tree

• Pennzoil’s final decision tree

figure 4.7

• What has been decided?

• Pennzoil should reject Texaco’s offer and make a \$5 billion counteroffer

• If Texaco then makes a \$3 billion counteroffer, Pennzoil should take its chances in court

### Solving Influence Diagrams

• More cumbersome than decision trees

• Conversion to symmetric decision tree

• Software packages used

### Risk Profiles

• Graph illustrating chances of possible payoffs or consequences

• One profile for each strategy

graph 4.18

### Risk Profiles

• Creation is straightforward process, but tedious

• Can create for strategies and specific sequences

• Only strategies for first one or two decisions examined

### Risk Profiles

• Three steps to follow:

• Determine probabilities of paths

• Determine probabilities of payoffs

• Create charts for strategies

### Dominance

• Dominating alternative always preferred over another alternative

• Dominating alternative always has higher EV than other alternative

### Dominance

• May enable elimination of alternatives early in the process

• Elimination simplifies and reduces cost of the process

### Dominance

Approaches:

• Inspection

• Cumulative distribution function

• Cumulative risk profile

• Sensitivity analysis

### Attributes and Scales

Measurement of fundamental objectives

• Measurement crucial to evaluation of consequences

• Methods must be consistent with objectives

• Attributes and attribute scales define measurement

• Different types of attributes

### Attributes and Scales

• Purpose: Explore attributes and scales

that measure achievement of

objectives

• Major field of study and in-depth exploration beyond scope of cource

### Attributes and Scales

• Attribute: measure of performance or merit

• Scale: defined graduated series or specified scheme

• Scale frequently implicit in attribute definition

### Types of Attributes

Keeney identifies three types of attributes:

• Natural attributes

• generally known and have common meaning

• for example, centimeters

• Constructed attributes

• created when no natural attributes exists

• for example, qualitative ratings

• Proxy attributes

• indirect measures (either natural or constructed) when no direct measures exist

• for example, use “sulphur dioxide concentration” for “acid rain damage to sculptures”

### Constructed Attributes

• Intellectually challenging and demanding

• Requires depth of knowledge and understanding of decision situation and objectives

• Three properties

• measurable: define objective in detail

• operational: describe possible consequences

• understandable: no ambiguity

### Constructed Attributes

• Frequently needed and most challenging

• A constructed attribute of site biological impact

### Constructed Attributes

• Implied scale may not reflect measures needed

• Nominal values in rank order may not correspond to rational scale

• For example

(level 2 – level 1) ?≠? (level 4 – level 3)

• Use subjective judgment to rate nominal values on rational scale

### Constructed Attributes

• Define constructed attributes from natural attributes

• Need to compare or combine constructed and natural attributes

• Convert natural attributes to constructed scale using proportions

### Multiple Objectives

Problems require:

• Common scale for measurement of consequences

• Single composite consequence

### Multiple Objectives

Common scale for consequences:

• Select common scale

• May be one used for an objective

• May be one not already used

• May be natural or constructed

• Tendency toward constructed with utility values

• Convert consequence measures for each objective to common scale

### Multiple Objectives

• Value between zero and one

• Sum to unity

• Consider consequence range

• Reflect relative importance of objectives

• Consistent with objectives hierarchy

### Multiple Objectives

Composite consequence for final outcomes:

• Linear combination of individual consequences

### Summary

• Creation of decision tree from case study

• Solution of case study decision tree

• Construction and use of risk profiles

• Definition and use of dominance

• Attributes and attribute scales, particularly constructed attributes

• Formulation and solution of a multiple objectives problem