Spreadsheet Modeling
& Decision Analysis
Introduction to Decision Analysis
• Models help managers gain insight and
understanding, but they can’t make decisions.
• Decision making often remains a difficult task due
to:
– Uncertainty regarding the future
– Conflicting values or objectives
• Consider the following example...
Deciding Between Job Offers
• Company A
– In a new industry that could boom or bust.
– Low starting salary, but could increase rapidly.
– Located near friends, family and favorite sports team.
• Company B
– Established firm with financial strength and commitment
to employees.
– Higher starting salary but slower advancement
opportunity.
– Distant location, offering few cultural or sporting activities.
• Which job would you take?
Good Decisions vs. Good Outcomes
• A structured approach to decision making can
help us make good decisions, but can’t
guarantee good outcomes.
• Good decisions sometimes result in bad
outcomes.
Characteristics of Decision Problems
• Alternatives - different courses of action intended to solve a
problem.
– Work for company A
– Work for company B
– Reject both offers and keep looking
• Criteria - factors that are important to the decision maker
and influenced by the alternatives.
– Salary
– Career potential
– Location
• States of Nature - future events not under the decision
makers control.
– Company A grows
– Company A goes bust
– etc
An Example: Magnolia Inns
• Hartsfield International Airport in Atlanta, Georgia, is one of the
busiest airports in the world.
• It has expanded many times to handle increasing air traffic.
• Commercial development around the airport prevents it from
building more runways to handle future air traffic.
• Plans are being made to build another airport outside the city
limits.
• Two possible locations for the new airport have been identified,
but a final decision will not be made for a year.
• The Magnolia Inns hotel chain intends to build a new facility
near the new airport once its site is determined.
• Land values around both possible sites for the new airport are
increasing as investors speculate that property values will
increase greatly in the vicinity of the new airport.
• See data in file Fig15-1.xls
The Decision Alternatives
1) Buy the parcel of land at location A.
2) Buy the parcel of land at location B.
3) Buy both parcels.
4) Buy nothing.
The Possible States of Nature
1) The new airport is built at location A.
2) The new airport is built at location B.
Constructing a Payoff Matrix
See file Fig15-1.xls
Decision Rules
• If the future state of nature (airport location) were
known, it would be easy to make a decision.
• Failing this, a variety of nonprobabilistic decision rules
can be applied to this problem:
– Maximax
– Maximin
– Minimax regret
• No decision rule is always best and each has its own
weaknesses.
The Maximax Decision Rule
• Identify the maximum payoff for each alternative.
• Choose the alternative with the largest maximum payoff.
• See file Fig15-1.xls
 Weakness
– Consider the following payoff matrix
Decision
A
B
State of Nature
1
2
30
-10000
29
29
MAX
30
29
<--maximum
The Maximin Decision Rule
• Identify the minimum payoff for each alternative.
• Choose the alternative with the largest minimum payoff.
• See file Fig15-1.xls
 Weakness
– Consider the following payoff matrix
Decision
A
B
State of Nature
1
2
1000
28
29
29
MIN
28
29
<--maximum
Probabilistic Methods
• At times, states of nature can be assigned probabilities that
represent their likelihood of occurrence.
• For decision problems that occur more than once, we can often
estimate these probabilities from historical data.
• Other decision problems (such as the Magnolia Inns problem)
represent one-time decisions where historical data for estimating
probabilities don’t exist.
• In these cases, subjective probabilities are often assigned based on
interviews with one or more domain experts.
• Interviewing techniques exist for soliciting probability estimates that
are reasonably accurate and free of the unconscious biases that may
impact an expert’s opinions.
• We will focus on techniques that can be used once appropriate
probability estimates have been obtained.
EMV Caution
• The EMV rule should be used with caution in one-time
decision problems.
 Weakness
– Consider the following payoff matrix
Decision
A
B
Probability
State of Nature
1
2
15,000
-5,000
5,000
4,000
0.5
0.5
EMV
5,000
4,500
<--maximum
A Decision Tree for Magnolia Inns
Land Purchase Decision
Buy A
-18
Buy B
-12
Airport Location
1
2
0
Buy A&B
-30
Buy nothing
0
Payoff
A 31
13
B 6
-12
A 4
-8
B 23
11
A 35
5
B 29
-1
A 0
0
B 0
0
3
4
Rolling Back A Decision Tree
Land Purchase Decision
Airport Location
0.4
Buy A
-18
EMV=-2
1
A 31
13
6
B 0.6
-12
0.4
Buy B
-12
EMV=3.4
2
0
EMV=3.4
A 4
-8
23
B 0.6
11
0.4
Buy A&B
-30
EMV=1.4
A 35
5
B 29
0.6
-1
3
0.4
Buy nothing
0
EMV= 0
Payoff
4
A 0
0
B 0
0
0.6
Using TreePlan
About TreePlan
• TreePlan is a shareware product developed by Dr.
Mike Middleton at the Univ. of San Diego
• TreePlan is an Excel add-in for decision trees.
• If you like this software package and plan to use for
more than 30 days, you are expected to pay a
nominal registration fee.
• Details on registration are available near the end of
the TreePlan help file. See file Fig15-14.xls
Anatomy of TreePlan Decision Tree
Problem: Marketing Cellular Phones
The design and product-testing phase has just been
completed for Sonorola’s new line of cellular phones.
Three alternatives are being considered for a
marketing/production strategy for this product:
1. Aggressive (A)
• Major commitment from the firm
• Major capital expenditure
• Large inventories of all models
• Major global marketing campaign
2. Basic (B)
• Move current production to Osaka
• Modify current line in Tokyo
• Inventories for only most popular items
• Only local or regional advertising
3. Cautious (C)
• Use excess capacity on existing phone
lines to produce new products
• Minimum of new tooling
• Production satisfies demand
• Advertising at local dealer discretion
Management decides to categorize the level of
demand as either strong (S) or weak (W).
Managements best estimate of the
probability of a strong or weak market.
Net profits measured in millions of dollars.
The optimal decision if you are risk-indifferent is to
select B which yields the highest expected payoff.
TreePlan
Lab Problem: DriveTek Problem
• DriveTek Research discovers that a computer
company wants a new storage device for a
proposed computer system
• The company will subcontract the development
to a research firm
• The company has offered a fee of $250,000 for
the best proposal
• DriveTek wants to enter the competition
• Management estimates a cost of $50,000 to
prepare a proposal with a 50-50 chance of
winning the contract
DriveTek Problem continued
• DriveTek’s engineers are not sure about how they
will develop the storage device
• Three alternative approaches can be tried:
1. A mechanical method with a cost of $120,000 and
the engineers are certain they can develop a
successful model with this approach
2. An electronic approach, with an estimated cost of
$50,000 to develop a model. Engineers estimate
only a 50% chance of a satisfactory approach
3. A magnetic component approach which will cost
$80,000 with a 70% chance of success
DriveTek Problem continued
• DriveTek’s can only work on one approach at a
time and has time to try only two approaches.
• If it tries either the magnetic or electronic
method and the attempt fails, the second
choice must be the mechanical method to
guarantee a successful model
• DriveTek needs help in incorporating this
information into a decision to proceed or not.
Class Exercise in Creating a Decision Tree:
A Glass Factory
• Complete the following exercise using TreePlan.
• Vary the inputs to determine when the optimal
decision will change.
Class Exercise: A Glass Factory
A glass factory specializing in crystal is experiencing a substantial
backlog, and the firm's management is considering three courses of
action:
A) Arrange for subcontracting – cost is 12 (thousand)
B) Construct new facilities – cost is 18 (thousand)
C) Do nothing (no change) – cost is 0
The correct choice depends largely upon demand, which may be
low, medium, or high. By consensus, management estimates the
respective demand probabilities as 0.1, 0.5, and 0.4.
Given the payoffs on the next page, create and solve this problem
using a decision tree.
A Glass Factory: The Payoff Table
The management estimates the profits when choosing
from the three alternatives (A, B, and C) under the
differing probable levels of demand. These profits, in
thousands of dollars are presented in the table below:
A
B
C
0.1
Low
10
-120
20
0.5
Medium
50
25
40
0.4
High
90
200
60