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Management by hitt back porter CH09

Chapter 9
Individual and
Group Decision
Making
PowerPoint slides by
R. Dennis Middlemist
Colorado State University


Learning Objectives
After studying this chapter, you should be
able to:






2

Explain the traditional model of decision

making.
Recognize and account for the limits of
rationality in the decision process.
Describe the role of risk and uncertainty in
decision making.

©2005


Learning Objectives
After studying this chapter, you should be
able to:






3

List the conditions when decisions are best
made individually and when they are best
made collectively.
Name the steps to facilitate group
participation in decision making.
Describe the barriers to effective decision
making and ways to overcome them.

©2005


Decision Making Concepts


Decision Making Process




4



Specifying the nature of a
particular problem or opportunity
and
Selecting among available
alternatives how to solve a
problem or capture an opportunity

©2005


Two Phases of Decision
Making
Decision
Formulation
Making







5

Identifying a problem or
opportunity
Acquiring information
Developing desired
performance expectations
Diagnosing causes and
relationships among
factors affecting the
problem

©2005








Solution
Generating alternatives
Selecting the preferred
solution
Implementing the
decided course of action
Monitoring the situation
to ensure successful
implementation


Individual Decision Making

6



Rational/classic model



Administrative, or bounded rationality
model



Retrospective decision‑making model

©2005


Identify Decision
Situations

Rational (Classical)
Decision-Making Model
Step 1


Identify decision
situations





7

©2005

Problems
Opportunities

Role of perception

Adapted from Exhibit 9.1: Classical Decision-Making Model


Identify Decision
Situations
Develop
Objectives and
Criteria

Rational (Classical)
Decision-Making Model
Step 2


Develop
objectives and
criteria





8

©2005

Specific criteria
Relative weightings

Criteria (what is
important in the
outcome)
Adapted from Exhibit 9.1: Classical Decision-Making Model


Identify Decision
Situations
Develop
Objectives and
Criteria
Generate
Alternatives

Rational (Classical)
Decision-Making Model
Step 3


Generate
alternatives



9

©2005

Past solutions
Creative new
solutions

Adapted from Exhibit 9.1: Classical Decision-Making Model


Identify Decision
Situations
Develop
Objectives and
Criteria
Generate
Alternatives
Analyze
Alternatives

Rational (Classical)
Decision-Making Model
Step 4


Analyze
Alternatives





10

©2005

Minimally
acceptable results
Feasibility
Best results

Adapted from Exhibit 9.1: Classical Decision-Making Model


Identify Decision
Situations
Develop
Objectives and
Criteria
Generate
Alternatives
Analyze
Alternatives

Rational (Classical)
Decision-Making Model
Step 5


Select Alternative


Subjectively
expected utility

Select
Alternative

11

©2005

Adapted from Exhibit 9.1: Classical Decision-Making Model


Identify Decision
Situations
Develop
Objectives and
Criteria
Generate
Alternatives
Analyze
Alternatives

Rational (Classical)
Decision-Making Model
Step 6


Implement
Decision


Select
Alternative



Implement
Decision




12

©2005

Sources and reasons
for resistance
Chronology and
sequence of actions
Required resources
Delegation of tasks
Adapted from Exhibit 9.1: Classical Decision-Making Model


Identify Decision
Situations
Develop
Objectives and
Criteria
Generate
Alternatives
Analyze
Alternatives
Select
Alternative
Implement
Decision
Monitor and
Evaluate Results
13

©2005

Rational (Classical)
Decision-Making Model
Step 7


Monitor and
Evaluate Results



Gather information
Compare results
to objectives and
standards set at
the beginning
Adapted from Exhibit 9.1: Classical Decision-Making Model


Assumptions of Classical Model

14



Problems are clear



Objectives are clear



People agree on criteria and weights



All alternatives are known



All consequences can be anticipated



Decision makers are rational

©2005


Applying Criteria in Analyzing
Alternatives
Candidate Criteria
Rating
Martha
Motivation
8
Interpersonal
1.50
Sales Knowledge
1.75
Product Knowledge
1.20
Candidate
Criteria
Rating
Jane
Motivation
9
=
6.85
Interpersonal
2.00
Sales Knowledge
1.50
Product Knowledge
1.00
15

©2005

X Weight= Score
x
.30 =
2.40
6
x
.25 =
7
x
.25 =
6
X
x
8
6
5

x
.20 =
Weight = Score
.30
2.70
Total =Score
x
.25 =
x
.25 =
x

.20

=

Total Score

Adapted from Exhibit 9.2: Applying Criteria in Analyzing Alternatives


Factors that Inhibit Accurate
Problem Identification and Analysis

16

Factor

Description

Illustration

Information
Bias

A reluctance to
give or receive
negative
information

You favor Jane as the
candidate; dismiss information
about performance problem on
her last job

Uncertainty
Absorption

A tendency for
information to lose
its uncertainty as it
is passed along

Not clear how well Martha did in
previous job. When feedback
gets to you, she is described as
a poor performer

©2005

Adapted from Exhibit 9.3: Factors that Inhibit Accurate Problem Identification and Analysis


Factors that Inhibit Accurate
Problem Identification and Analysis

17

Factor

Description

Illustration

Selective
Perception

A tendency to
ignore or avoid
certain (especially
ambiguous)
information

Jane may have several
employment alternatives and
may even be considering going
back to school, but you ignore
all this in making her the offer

Stereotyping

Deciding about an
alternative on the
basis of
characteristics
ascribed by others

Not clear how well Martha did in
Jane graduated from a private
high school and went to a highly
rated college on a partial
scholarship, so you figure she
must be a great hire

©2005

Adapted from Exhibit 9.3: Factors that Inhibit Accurate Problem Identification and Analysis


Factors that Inhibit Accurate
Problem Identification and Analysis

18

Factor

Description

Illustration

Cognitive
Complexity

A Limits on the
amount of
information people
can process at
one time

You initially have 200 applicants
for the position but decide to
eliminate anyone with less than
three years sales experience

Stress

Reduction of
people’s ability to
cope with
informational
demands

Your company’s market share is
slipping because you don’t have
enough sales people in the field,
so you feel you just can’t look at
every bit of information on every
candidate

©2005

Adapted from Exhibit 9.3: Factors that Inhibit Accurate Problem Identification and Analysis


Bounded Rationality Model
First Mechanism


Possible solutions examined
time





19

one at a

If alternative is unworkable it is discarded
When acceptable (not necessarily best)
solution is found, it is likely to be accepted
Thus search and analysis effort is likely to
stop at first acceptable solution

©2005


Bounded Rationality Model
Second Mechanism


Explicit criteria and weights
used to evaluate
alternatives



Decision makers use heuristics


20

not

A rule that guides the search for alternatives
into areas that have a high probability for
yielding success

©2005


Bounded Rationality Model
Third Mechanism


Satisficing




21

Selection of a minimally
acceptable solution
Rather than being an optimizer, this model
sees him or her as being a satisficer

©2005


Retrospective Decision Model


Implicit favorite is identified early in decision
process



Perceptual distortion of information occurs




22

Decision rules are adopted that favor the
implicit favorite
Positive features of the implicit favorite
highlighted over the alternative

©2005


Types of Decisions
Programmed
Decision








23

Decisions
Simple/routine
problem
High levels of
certainty
Rules and
procedures
Standard operating
procedures (SOP)

©2005






Nonprogrammed
Decision
Poorly
defined or
novel problem
No alternative is
clearly correct
Past decisions of
little help
Gresham’s law of
planning


Decision-Maker Level and
Type of Decision
Top
Managers
Middle
Managers
Lower-Level
Managers
Non-programmed Decisions
Programmed Decisions
24

©2005

Adapted from Exhibit 9.4: Decision-Maker Level and Type of Decision


Gresham’s Law and Decisions
Many
important
decisions
are here

Nonprogrammed
Decisions
Programmed
Decisions
Urgent

25

©2005

Not Urgent

Adapted from Exhibit 9.5: Gresham’s Law and Decisions


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