ARE 112 –Fall 2016
Class Notes #6 Strategy-Change Management
“Strategy without tactics is the slowest route to victory, tactics without strategy is the noise before
defeat.” —Sun Tsu
I. Class Notes
1.
Exam #1
2.
IBM Book and Reading Notes
3.
Read the Duke Hospital Case for next class – in the course pack
II. Review – Another Lens
Industry
Structure
Competitive
Strategy
Value Chains
Business
Processes
Organizational
Management
III. Strategic Analytical Lenses
A. The four-p’s from www.netmba.com
 Product
 Price
 Promotion
 Placement
 Target markets
B. Boston Consulting Group Growth-Share
Matrix – for cash generation
 Cash cows
 Stars
 Question marks
 Dogs
 Market share
 Market growth
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ARE 112 –Fall 2016
Class Notes #6 Strategy-Change Management
C. SWOT Analysis: Strengths, Weakness, Opportunities and Threats
D. Balanced Scorecard
 Financial
 Customer
 Internal Business Processes
 Learning and Growth
 Metrics
 Initiatives
E. Porter’s Five Forces Model
 Suppliers
 Customers or buyers
 Substitutes
 Potential entrants
 Industry members
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ARE 112 –Fall 2016
Class Notes #6 Strategy-Change Management
Back to Anthony’s hierarchy and the value proposition
F.
IV. Change Management
A. Why change occurs – this is not the same as transformational change – more of general comments
about change but we do see change management in the area of transformational change.
1.
2.
3.
4.
Dissatisfaction with the present situation
External pressures toward change
Momentum toward change
These are not the same as the driving forces for change but
the context of change management
B. Threats to the change process – some examples:
 Degree of change
 Threat to security

Time frame

Redistribution of power

Impact of culture

Disturb existing social networks

Loss of existing benefits

Uncertainty regarding change

Threat to position power

Disruption of routine
C. Power: Used to change beliefs and/or behavior – or attempts to do so
1. Coercive power → the power to punish
2. Legitimate power → the power granted by some authority
3. Expert power → the power of have some specific skill or knowledge not found in others
4. Referent power → the power from admiration or respect
5. Reward power → the power from being able to provide a reward to others
NOTE:
To have authority you need to have power.
 Authority: The ability to command, direct, or influence thought, opinions, or behavior.
 But power alone does not give authority – this is a topic in our leadership section later in
the class.
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ARE 112 – Spring 2017
Class Notes #6 – Change Management and Decisions
V. Change Methods - Examples
A. Phase method
1. Unfreezing – prepare for change
2. Changes
3. Refreezing – change is stabilize
B. Crossover approach
VI. Change strategies
VII.
Strategy
Power Base
Managerial Behavior
Likely Results
Force-Coercion
Use of formal authority
to create change
Legitimate
Reward
Coercive
Direct forcing
Political maneuvering
Faster but may only be
temporary
Rational Persuasion
Creating change thru
rational and empirical
arguments
Expertise
Informational efforts
Highly variable
depending on acceptance
of change
Shared Power
Developing support thru
personal values, beliefs,
and commitments
Referent
Participative efforts
Slower, but able to
internalize the changes
Duke Hospital Case – In Course Pack
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ARE 112 – Spring 2017
Class Notes #6 – Change Management and Decisions
VIII. Decision Making
A. General comment:
1. “The process
2.
by which managers
3.
respond to opportunities and threats (from the SWOT world)
4.
by analyzing options
5.
and making determinations
6.
about specific organizational goals
7.
and courses of action.”
B. Many decision relate to one of the following:
1. Resource acquisition (or disposal)
2.
Resource allocation or withholding resources
3.
Resources utilization
C. One of several frameworks to analyze decision making: structured/unstructured model
1. Structured or programmed decisions
2.
Unstructured or unprogrammed decisions
D. Another framework: Decision outcomes model – the justification for a decision:
1.
Decision framework:
a. Inputs
b. Activities or processes
c. Outputs
d. Activities or processes
e. Outcomes
i. Optimizing outcomes
ii. Satisficing outcomes
2.
Somewhere between inputs and outputs, and between outputs and outcomes is
an activity and it is the activity that gets managed
E. Decision environment
1. Bounded rationality
5.
Ambiguous information
2.
Risk
6.
Time constraints
3.
Uncertainty
7.
Information costs
4.
Information symmetry
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ARE 112 – Winter 2017 ANOVA – Analysis of Variance and Chi Square and Probit – Analysis Project
F. Information technology and the decision-making process – the MIS world – management
information systems
1. Decision support systems – DSS
2.
Group decision support system - GDS
3.
Executive information system – EIS
4.
Delphi technique – support by MIS applications but not a pure MIS application
IX. Analysis Project
1.
To see the application of statistical analysis to organizational issues.
2.
Data files and instructions including a “how to” video will be posted to Canvas
X. ANOVA – Analysis of Variance
A. Purpose: To see an example of fact-based, analysis-based information to then be used in decision
making
B. Converting Data to Information
1. Likert scale to convert qualitative responses to quantitative or measurable values
a. Use a scale of five to seven responses ranging from “strongly disagree to strongly agree” and
usually the middle value is neither agree nor disagree
b. Generally limited to five to nine questions in the survey
c. And need to characterize the respondents by attributes to be tested such as age category,
economic status, education and the like.
2.
Now apply statistical analysis to the data: one example is ANOVA – analysis of variance
3.
Here we want to see if there is a
difference among groups in the
general population. Here is what we
want to test:
Using Hypothesis Testing – ANOVA
A single-factor ANOVA derives its name from
the fact that the test deals with one independent
variable; in this case, we discuss the population
mean. The question that the ANOVA attempts to
ask is this: are the samples really of the same population, or is there enough variance in the sample means to
suggest that the samples were taken from independent populations? The type of test we shall consider in a
moment deals with the comparison of two or more sample means. The sample sizes themselves need not be
equal
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ARE 112 – Winter 2017 ANOVA – Analysis of Variance and Chi Square and Probit – Analysis Project
State the null and alternative hypothesis.
For ANOVA the null hypothesis is stated as:
H0: All population means are equal.
For example, if we are testing three populations, then we would state:
H0: µ1 = µ2 = µ3 or all treatments are the same
The alternative hypothesis is stated as:
Ha: Not all population means are equal or at lease two treatments differ
It is important to note that ANOVA testing by itself does not tell you which mean does not equal the
other means, or the combination of means that are not equal. It will only tell you that at least one
mean does not equal the other means.
It is the Test of Homogeneity that gives us the resultant populations.
ANOVA
MPG
MPG
Between Groups
W ithin Groups
Total
Sum of
Squares
17.049
8.028
25.077
df
2
12
14
Mean Square
8.525
.669
F
12.742
Sig.
.001
2.
N
5
5
5
Subset for alpha = .05
1
2
33.980
34.920
36.560
.206
1.000
Means for groups in homogeneous subsets are displayed.
a. Us es Harmonic Mean Sample Size = 5.000.
XI. Chi-Square
1. Formula:
The statistic
The calculation
(O – E)2

∑
 =
E
Tukey HSD a
Gas_Code
3
1
2
Sig.
The rationale
As the observed frequency gets closer to the expected frequency
(no difference) the value gets smaller.
Data and output:
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ARE 112 – Winter 2017 ANOVA – Analysis of Variance and Chi Square and Probit – Analysis Project
XI. Probit – Probability Unit Model
The model: Yi = β0 + β1 Xi + εi where Yi = 1, 0 a binary response where 1 – Yes, and 0 – No.
2.
Data:
Actual and fitted Accept versus Gender
1
Analysis:
0.8
0.6
Accept
3.
fitted
actual
0.4
0.2
0
0
1
Gender
Actual and fitted Accept versus Chem
1
fitted
actual
0.8
0.6
Accept
1.
0.4
0.2
0
2
4
6
8
Chem
8
10
12
14