Operations and Supply Chain Management

ModuleA-DesionMakingtools.pptx

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Operations Management: Sustainability and Supply Chain Management

Week 5

Module A: Decision-Making Tools

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Learning Objectives

1 Create a simple decision tree

2 Build a decision table

3 Explain when to use three types of decision-making environments

4 Calculate an expected monetary value (E M V)

5 Compute the expected value of perfect information (E V P I)

6 Evaluate the nodes in a decision tree

7 Create a decision tree with sequential decisions

The Decision Process in Operations

Clearly define the problem and the factors that influence it

Develop specific and measurable objectives

Develop a model

Evaluate each alternative solution

Select the best alternative

Implement the decision and set a timetable for completion

Fundamentals of Decision Making

Symbols used in a decision tree:

– Decision node from which one of several alternatives may be selected.

– A state-of-nature node out of which one state of nature will occur

Terms:

Alternative – a course of action or strategy that may be chosen by the decision maker

State of nature – an occurrence or a situation over which the decision maker has little or no control

Decision Tree Example

Decision Table Example

Decision Table with Conditional Values for

Decision-Making Environments

Three types

Decision making under uncertainty

Complete uncertainty as to which state of nature may occur

Cannot assess probabilities for each possible outcome

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

Uncertainty

Maximax	Maximin	Equally likely
Find the alternative that maximizes the maximum outcome for every alternative	Find the alternative that maximizes the minimum outcome for every alternative	Find the alternative with the highest average outcome
Pick the outcome with the maximum number	Pick the outcome with the minimum number	Pick the outcome with the maximum number
Highest possible gain	Least possible loss	Assumes each state of nature is equally likely to occur
This has been called an optimistic decision criteria	This has been called a pessimistic decision criteria

Type 1: Decision Table Under Uncertainty

Maximax choice is to construct a large plant

Maximin choice is to do nothing

Equally likely choice is to construct a small plant

Type 2: Decision Making Under Risk

Each possible state of nature has an assumed probability

States of nature are mutually exclusive

Probabilities must sum to 1

Determine the expected monetary value (E M V) for each alternative

Expected Monetary Value

EMV (Alternative i)	=	(Payoff of 1st state of nature) × (Probability of 1st state of nature)
Blank	+	(Payoff of 2nd state of nature) × (Probability of 2nd state of nature)
Blank	+… +	(Payoff of last state of nature) × (Probability of last state of nature)

Decision Table Example

Best Option

Type 3: Decision Making Under Certainty

Expected value with perfect information (EVwPI)	=	(Best outcome or consequence for 1st state of nature) × (Probability of 1st state of nature)
Blank	+	Best outcome for 2nd state of nature) × (Probability of 2nd state of nature)
Blank	+… +	Best outcome for last state of nature) × (Probability of last state of nature)

Is the cost of perfect information worth it?

Determine the expected value of perfect information (E V P I)

EVPI = the payoff under certainty - the payoff under risk

EVPI = expected value with perfect information – Maximum EMV

E V P I Example

The best outcome for the state of nature "favorable market" is

"build a large facility" with a payoff of $200,000.

The best outcome for "unfavorable“ is

"do nothing" with a payoff of $0.

The maximum E M V is $52,000, which is the expected outcome without perfect information. Thus:

The most the company should pay for perfect information is

$68,000