1. ISMT 161: Introduction to Operations Management
Decision Analysis
What is the best way to solve your problem?
ISMT 161: Introduction to Operations Management

2. ISMT 161: Introduction to Operations Management
Decision Analysis
Every decision you make uses some kind of model, whether you know it or not.
We will take a more systematic look at the decision process and the underlying theories.
ISMT 161: Introduction to Operations Management

3. ISMT 161: Introduction to Operations Management
The Decision Process
Identify the Problem
Specify objectives and the criteria for choosing a solution
Develop alternatives
Analyze and compare alternatives
ISMT 161: Introduction to Operations Management

4. The Decision Process (Cont)
Select the best alternative
Implement the chosen alternative
Monitor the results
ISMT 161: Introduction to Operations Management

5. Causes of Poor Decisions
Bounded Rationality
The limitations on decision making caused by costs, human abilities, time, technology, and availability of information
ISMT 161: Introduction to Operations Management

6. Causes of Poor Decisions (Cont)
Suboptimization
The result of different departments each attempting to reach a solution that is optimum for that department
ISMT 161: Introduction to Operations Management

7. Decision Environments
Certainty - Environment in which relevant parameters have known values
Risk - Environment in which certain future events have probable outcomes
Uncertainty - Environment in which it is impossible to assess the likelihood of various future events
ISMT 161: Introduction to Operations Management

8. ISMT 161: Introduction to Operations Management
Decision Theory
Decision Theory represents a general approach to decision making which is suitable for a wide range
of operations management decisions, including:
capacity planning
product and
service design
location
planning
equipment
selection
ISMT 161: Introduction to Operations Management

9. Decision Theory Elements
A set of possible future conditions exists that will have a bearing on the results of the decision
A list of alternatives for the manager to choose from
A known payoff for each alternative under each possible future condition
ISMT 161: Introduction to Operations Management

10. Decision Theory Process
Identify possible future conditions called states of nature
Develop a list of possible alternatives, one of which may be to do nothing
Determine the payoff associated with each alternative for every future condition
ISMT 161: Introduction to Operations Management

11. Decision Theory Process (Cont’d)
If possible, determine the likelihood of each possible future condition
Evaluate alternatives according to some decision criterion and select the best alternative
ISMT 161: Introduction to Operations Management

12. ISMT 161: Introduction to Operations Management
Decision situations
under Certainty
under Uncertainty
under Risk
ISMT 161: Introduction to Operations Management

13. ISMT 161: Introduction to Operations Management
Payoff Table
Possible future demand*
*Present value in $ millions
ISMT 161: Introduction to Operations Management

14. Decision Making under Uncertainty - Some Criteria
Maximin - Choose the alternative with the best of the worst possible payoffs
Maximax - Choose the alternative with the best possible payoff
Laplace (weighted average) - Choose the alternative with the best average payoff of any of the alternatives
Minimax Regret - Choose the alternative that has the least of the worst regrets
ISMT 161: Introduction to Operations Management

15. ISMT 161: Introduction to Operations Management
Example - Maximin
Maximin
ISMT 161: Introduction to Operations Management

16. Example - Minimax regret
Regret table (opportunity losses)
Regrets (in $ mil.)
ISMT 161: Introduction to Operations Management

17. ISMT 161: Introduction to Operations Management
Example - EMV
EMV - expected monetary value -The best expected value among the alternatives
Suppose the probabilities for the future demand are: low = 0.3, moderate = .5 and high = .2. Find the EMV for the best alternatives:
EV(small) = .3(10) + .5(10) + .2(10) = 10
EV(medium) = .3(7) + .5(12) + .2(12) = 10.5
EV(large) = .3(-4) + .5(2) + .2(16) = 3
Thus the medium facility has the highest EV.
ISMT 161: Introduction to Operations Management

18. ISMT 161: Introduction to Operations Management
Decision Tree- Schematic representation of the alternatives and their possible consequences
Payoff 1
State of nature 1
Choose A3
Payoff 2
Choose A1 2
State of nature 2
Choose A4
Payoff 3 B 1
Payoff 4
Choose A5
State of nature 1 2
Choose A2
Choose A6
Payoff 5
State of nature 2
Decision Point
Payoff 6
ISMT 161: Introduction to Operations Management
Chance Event

19. Expected Value of Perfect Information
the difference between the expected payoff under certainty and the expected payoff under risk
Expected value of perfect information
= Expected payoff under certainty - expected payoff under risk
ISMT 161: Introduction to Operations Management

20. Constructing a Decision Tree
List all the possible alternatives of decisions
List all the outcomes of random events
Work through the possible decisions and random events chronologically
Fill in final outcomes and payoffs, and probability distributions of random events if necessary
ISMT 161: Introduction to Operations Management

21. ISMT 161: Introduction to Operations Management
Example (p.86, problem 4)
A firm that plans to expand its product line must decide whether to build a small or a large facility to produce the new products. If it builds a small facility and demand is low, the net present value after deducting for building costs will be $400,000. If demand is high, the firm can either maintain the small facility or expand it. Expansion would have a net present value of $50,000.
If a large facility is built and demand is high, the estimated net present value is $800,000. If demand turns out to be low, the net present value will be -$10,000. The probability that demand will be high is estimated to be .60 and that of low would be .40.
(a) Analyze using a tree diagram. (b) Compute the EVPI. How could this information be useful?
ISMT 161: Introduction to Operations Management

22. Constructing the decision tree
Alternatives:
build small,
build large;
expand (for high demand and build small )
maintain (…)
Outcomes: low demand, high demand
ISMT 161: Introduction to Operations Management

23. ISMT 161: Introduction to Operations Management
Example (solutions)
$400,000 (1)
Demand low (.4)
Maintain
$400,000 (2) 2
Build small
Demand high (.6)
Expand
$450,000(3) B 1
- $10,000(4)
Demand low (.4)
Build large
$800,000(5)
Demand high (.6)
ISMT 161: Introduction to Operations Management

24. Example (solution continued)
The expected net present value of the alternatives
(1) .4  400,000 = 160,000
(2) can be eliminated (since its npv is less than expansion)
(3) .6  450,000 = 270,000
(4) .4  (-10,000) = -4,000
(5) .6  800,000 = 480,000
Build small expected npv = =
Build large expected npv = =
Since building a large capacity has the higher expected net present value, select “build large” alternative
ISMT 161: Introduction to Operations Management

25. ISMT 161: Introduction to Operations Management
Rollback approach for EMV
$400,000 (1)
Demand low (.4)
430K
Maintain
$400,000 (2)
450K 2
Build small
Demand high (.6)
Expand
$450,000(3)
476K 1
- $10,000(4)
Demand low (.4)
Build large
$800,000(5)
476K
Demand high (.6)
ISMT 161: Introduction to Operations Management

26. Example (solution continued)
Expected payoff under certainty
= .4(400,000) + .6(800,000) = 640,000
Expected payoff under risk
= 476,000
Expected value of perfect Information
= 640, ,000 = 164,000
ISMT 161: Introduction to Operations Management

27. ISMT 161: Introduction to Operations Management
Sensitivity Analysis
#1 Payoff
#2 Payoff 16 14 12 10 8 6 4 2 B 16 14 12 10 8 6 4 2 A C
B best
C best
A best
Sensitivity analysis: determine the range of probability
for which an alternative has the best expected payoff
ISMT 161: Introduction to Operations Management