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Module 1 – Case
ASSUMED CERTAINTY: PIVOT TABLES AND MULTI-ATTRIBUTE DECISION
MAKING
Pivot Tables and Pivot Charts
Assignment Overview
You are the lead consultant for the Excellent Consulting
Group. It is mid-October. One of your top clients, Buddy’s Floor Barn, has just
closed the books for the first three quarters of the year (January through
September). Buddy’s Floor Barn requests that you analyze the sales performance
of its 5 product lines over this 3-quarter period. From past consulting work
you have done for the company, you know that Buddy’s Floor Barn has 4 regions
and 18 total store locations.
Each Regional Manager at the company has compiled the data
for his/her region. The raw data provided consists of the sales revenue for
each of the 5 premium flooring lines for all 4 regions and 18 locations for the
first three quarters of the current year.
Case Assignment
The data have been provided in list format. Generate a Pivot
Table Report with Charts. Use the Pivot Table and Charts to analyze the data.
Following your in-depth analysis of the data, write a report to Buddy’s Floor
Barn in which you discuss and analyze the data, and make appropriate
recommendations relative to how Buddy’s Floor Barn should improve its sales
performance going forward.
Assignment Expectations
Data: To begin, download the list data here: Data chart for
BUS520 Case 1
Excel Analysis:
Provide accurate and complete Excel analysis (Pivot Table
with Charts).
Written report:
Length requirement: 4–5 pages minimum (not including Cover
and Reference pages). NOTE: You must have 4–5 pages of written discussion and
analysis. This means you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Using the Pivot Table and Pivot Charts, discuss and analyze
the data, noting key highs and lows, trends, etc.
Include charts from your Pivot Table to support your written
analysis. (Please do not use charts as “space fillers.” Instead, use them
strategically to support your written analysis.)
In a “Recommendations” section, give clear, specific, and
meaningful recommendations that Buddy’s Floor Barn should use to improve
overall company sales.
Be sure to consider highs, lows, and trends in the data.
Which cities are the highest performers? Lowest? Which regions and quarter had
the highest sales? Lowest sales? Consider what may be driving the numbers: Poor
marketing? Outstanding marketing strategies? Inventory management? Seasonal
sales? Other? There are innumerable possibilities. Your role is to reflect on
the data, and ultimately, to use the data to give useful recommendations.
Module 1 – SLP
ASSUMED CERTAINTY: PIVOT TABLES AND MULTI-ATTRIBUTE DECISION
MAKING
Assumed Certainty: Multi-Attribute Decision Making (MADM)
Scenario: You are the Vice President of Franchise Services
for the Happy Buns restaurant chain. You have been assigned the task of
evaluating the best location for a new Happy Buns restaurant. The CFO has
provided you with a template that includes 6 criteria (attributes) that you are
required to use in your evaluation of 5 recommended locations. Following are
the 6 criteria that you will use to evaluate this decision:
Traffic counts (avg. thousands/day)—the more traffic, the
more customers, and the greater the potential sales.
Building lease and taxes (thousands $ per year)—the lower
the building lease and taxes, the better.
Size of building (square feet in thousands)—a larger
building is more preferable.
Parking spaces (max number of customers parking)—more
customer parking is preferable.
Insurance costs (thousands $ per year)—lower insurance costs
are preferable.
Ease of access (subjective evaluation from observation)—you
will need to “code” the subjective data. Use Excellent = 4, Good = 3, Fair = 2,
and Poor = 1.
Now that you have collected the data from various sources
(your CFO and COO, local real estate listings, personal observation, etc.), you
have all the data you need to complete an analysis for choosing the best
location. Download the raw data for the 5 locations in this Word document:
BUS520 SLP1V1.docx
Assignment
Review the information and data regarding the different
alternatives for a new restaurant location.
Then do the following in Excel:
Table 1: Develop an MADM table with the raw data.
Table 2: Convert the raw data to utilities (scaled on 0 to
1). Show the utility weights in a second table.
Table 3: Develop a third table with even weights (16.7%) for
each variable.
Evaluate Table 3 for the best alternative.
Table 4: Complete a sensitivity analysis by assigning
weights to each variable.
In a Word document, do the following:
Discuss the process used to put together Tables 1–4 above.
Provide the rationale you used for choosing for each of the
weights you used in Table 4.
Give your recommendation of which location the company
should choose (based on results of Table 4).
SLP Assignment Expectations
Excel Analysis
Complete Excel analysis using MADM (all four tables noted
above must be included).
Accurate Excel analysis (Excel file includes working
formulas showing your calculations; all calculations and results must be
accurate).
Written Report
Length requirements: 2–3 pages minimum (not including Cover
and Reference pages). NOTE: You must submit 2–3 pages of written discussion and
analysis. This means that you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Discuss the steps you used to compile the Excel analysis
(i.e., the four tables).
Discuss the assumptions used to assign weights to each
variable of your sensitivity analysis (Table 4). That is, provide the rationale
for your choice of weights for each variable.
Provide a complete and meaningful recommendation related to
the location that should be chosen as a new site.
Upload both your Excel file and written Word report to the
SLP 1 Dropbox by the assignment due date.

Module 2 – Case
RISK: FREQUENCY DISTRIBUTION, PROBABILITIES, AND EXPECTED
VALUE
Risk: Frequency Distribution, Probabilities, and Expected
Value
Assignment Overview
In the Module 2 Case, you are again engaged on a consulting
basis by Buddy’s Floor Barn. This time, in order to get a better idea of what
might have motivated customers’ buying habits you are asked to analyze the ages
of the customers who have purchased oak flooring over the past 12 months. Past
research done by the Excellent Consulting Group has shown that different age
groups buy certain products for different reasons. Buddy’s Floor Barn has sent
a survey to 200 customers who have previously purchased oak premium flooring,
and 124 customers have responded. The survey includes age data of past customers
who purchased oak flooring in the past year.

Case Assignment
Using Excel, create a frequency distribution (histogram) of
the age data that was captured from the survey. You should consider the width
of the age categories (e.g., 5 years, 10 years, or other). That is, which age
category grouping provides the most useful information? Once you have created
this histogram, determine the mean, median, and mode.
After you have reviewed the data, write a report to your
boss that briefly describes the results that you obtained. Make a
recommendation on how this data might be used for marketing purposes.
Data: Download the Excel-based data file with the age data
of the 124 customers: Data chart for BUS520 Case 2. Use these data in Excel to
create your histogram.
Assignment Expectations
Excel Analysis
Accurate and complete analysis in Excel using the Histogram
function.
Written Report
Length requirements: 4–5 pages minimum (not including Cover
and Reference pages). NOTE: You must submit 4–5 pages of written discussion and
analysis. This means that you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Provide a written analysis that supports your Histogram age
groups (bins).
Based on your analysis of the histogram data, provide
complete and meaningful recommendations as the data relates to Buddy’s Floor
Barn marketing strategy.

Module 2 – SLP
RISK: FREQUENCY DISTRIBUTION, PROBABILITIES, AND EXPECTED
VALUE
Risk: Probabilities and Expected Value
Scenario: You work for a private investment company that
currently has numerous business investments in real estate development,
restaurant franchises, and retail chains. Following an exhaustive search for
new investment opportunities, you have found three possible alternatives, each
of which will pay off in exactly 10 years from the date of initial investment.
Because you only have enough money to invest in one of the three options, you
recognize that you will need to complete a quantitative comparison of the three
alternatives:
Option A: Real estate development.
Option B: Investment in the retail franchise “Just Hats,” a
boutique that sells hats for men and women.
Option C: Investment in “Cupcakes and so forth,” a franchise
that sells a wide variety of cupcakes and a variety other desserts.
Download the raw data for the three investments in this
Excel document: Raw data for BUS520 SLP 2
Assignment
Develop an analysis of these three investments in Excel. Use
expected value to determine which of the three alternatives you should choose.
Write a report to your private investment company,
explaining your Excel analysis, giving your recommendation, and justifying your
decision.
SLP Assignment Expectations
Excel Analysis
Using Excel, make an accurate and complete analysis of the
three investment alternatives.
Written Report
Length requirements: 2–3 pages minimum (not including Cover
and Reference pages). NOTE: You must submit 2–3 pages of written discussion and
analysis. This means that you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Discuss the steps you used in completion of your Excel
analysis.
Based on your Excel analysis, give your recommendation as to
which of the three investment alternatives should be pursued.
Upload both your written report and Excel file to the SLP 2
Dropbox.

Module 3 – Case
LINEAR REGRESSION FORECASTING AND DECISION TREES
Linear Regression Forecasting
Assignment Overview
Scenario: You are a consultant who works for the Excellent
Consulting Group. Your client, the ABC Furniture Company, believes that there
may be a relationship between the number of customers who visit the store
during any given month (“customer traffic”) and the total sales for that same
month. In other words, the greater the customer traffic, the greater the sales
for that month. To test this theory, the client has collected customer traffic
data over the past 12-month period, and monthly sales for that same 12-month
period (Year 1).
Case Assignment
Using the customer traffic data and matching sales for each
month of Year 1, create a Linear Regression (LR) equation in Excel. Use the
Excel template provided (see “Module 3 Case – LR –Year 1” spreadsheet tab), and
be sure to include your LR chart (with a trend line) where noted. Also, be sure
that you include the LR formula within your chart.
After you have developed the LR equation above, you will use
the LR equation to forecast sales for Year 2 (see the second Excel spreadsheet
tab labeled “Year 2 Forecast”). You will note that the customer has collected
customer traffic data for Year 2. Your role is to complete the sales forecast
using the LR equation from Step 1 above.
After you have forecast Year 2 sales, your Professor will
provide you with 12 months of actual sales data for Year 2. You will compare
the sales forecast with the actual sales for Year 2, noting the monthly and
average (total) variances from forecast to actual sales.
To complete the Module 3 Case, write a report for the client
that describes the process you used above, and that analyzes the results for
Year 2. (What is the difference between forecast vs. actual sales for Year 2—by
month and for the year as a whole?) Make a recommendation concerning how the LR
equation might be used by ABC Furniture Company to forecast future sales.
Data: Download the Module 3 Case template here: Data chart
for BUS520 Case 3. Use this template to complete your Excel analysis.
Assignment Expectations
Excel Analysis
Accurate and complete Linear Regression analysis in Excel.
Written Report
Length requirements: 4–5 pages minimum (not including Cover
and Reference pages). NOTE: You must submit 4–5 pages of written discussion and
analysis. This means that you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Your written (Word) analysis should discuss the logic and
rationale used to develop the LR equation and chart.
Provide complete, meaningful, and accurate recommendation(s)
concerning how the ABC Furniture Company might use the LR equation to forecast
future sales. (For example, how reliable is the LR equation in predicting
future sales?) What other recommendations do you have for the client?

Module 3 – SLP
LINEAR REGRESSION FORECASTING AND DECISION TREES
Decision Trees
Scenario: You are a consultant who works for the Excellent
Consulting Group. You have learned about three different investment
opportunities and need to decide which one is most lucrative. Following are the
three investment options and their probabilities:
Option A: Real Estate development. This is a risky
opportunity with the possibility of a high payoff, but also with no payoff at
all. You have reviewed all of the possible data for the outcomes in the next 10
years and these are your estimates of the cash payoff and probabilities:
Required initial investment: $0.75 million
High NPV: $5 million, Pr = 0.5
Medium NPV: $2 million, Pr = 0.3
Low NPV: $0, Pr = 0.2
Option B: Retail franchise for Just Hats, a boutique-type
store selling fashion hats for men and women. This also is a risky opportunity
but less so than Option A. It has the potential for less risk of failure, but
also a lower payoff. You have reviewed all of the possible data for the
outcomes in the next 10 years and these are your estimates of the payoffs and
probabilities:
Required initial investment: $0.55 million
High NPV: $3 million, Pr = 0.75
Medium NPV: $2 million, Pr = 0.15
Low NPV: $1 million, Pr = 0.1
Option C: High Yield Municipal Bonds. This option has low
risk and is assumed to be a Certainty. So there is only one outcome with
probability of 1.0:
Required initial investment: $0.75 million
NPV: $1.5 million, Pr = 1.0
Assignment
Develop an analysis of these three investments, and
determine which of them you should choose. Be sure to account for cash paid for
each of the three alternatives. If you do not recall how to do this, review the
practice exercises in the Background page. Do your analysis in Excel using the
Decision Tree add-in.
Write a report to your private investment company and
explain your analysis and your recommendations. Provide a rationale for your
decision.
Upload both your written report and Excel file with the decision
tree analysis to the SLP 3 Dropbox.
SLP Assignment Expectations
Analysis
Accurate and complete Excel analysis.
Written Report
Length requirements: 2–3 pages minimum (not including Cover
and Reference pages)
Provide a brief introduction to/background of the problem.
Written analysis that supports Excel analysis and provides
thorough discussion of assumptions, rationale, and logic used.
Complete, meaningful, and accurate recommendation(s).

Module 4 – Case
RISK: EXPONENTIAL SMOOTHING FORECASTING AND VALUE OF
INFORMATION
Risk: Simple Exponential Smoothing (SES)
Assignment Overview
Scenario: You are a consultant for the Excellent Consulting
Group (ECG). You have completed the first assignment, developing and testing a
forecasting method that uses Linear Regression (LR) techniques (Module 3 Case).
However, the consulting manager at ECG wants to try a different forecasting
method as well. Now you decide to try Single Exponential Smoothing (SES) to
forecast sales.
Case Assignment
Using this Excel template: Data chart for BUS520 Case 4, do
the following:
Calculate the MAPE for Year 2 Linear Regression forecast
(use the first spreadsheet tab labeled “Year 2 Forecast – MAPE”).
Calculate forecasted sales for Year 2 using SES (use the second
spreadsheet tab labeled “SES – MAPE”). Use 0.15 and 0.90 alphas.
Compare the MAPE calculated for the LR forecast (#1 above)
with the MAPEs calculated using SES.
Then write a report to your boss in which you discuss the
results obtained above. Using calculated MAPE values, make a recommendation
concerning which method appears to be more accurate for the Year 2 data: SES or
Linear Regression.
Assignment Expectations
Analysis
Accurate and complete SES analysis in Excel.
Written Report
Length requirements: 4–5 pages minimum (not including Cover
and Reference pages). NOTE: You must submit 4–5 pages of written discussion and
analysis. This means that you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Complete a written analysis that supports your Excel
analysis, discussing the assumptions, rationale, and logic used to complete
your SES forecast.
Give complete, meaningful, and accurate recommendation(s)
relating to whether LR or SES is more accurate in predicting sales.

Module 4 – SLP
RISK: EXPONENTIAL SMOOTHING FORECASTING AND VALUE OF
INFORMATION
Risk: The Value of Information
Scenario: Using the same situation from the Module 3 SLP,
recall that you are deciding among three investments. You have heard of an
expert who has a highly reliable “track record” in the correct identification
of favorable vs. unfavorable market conditions. You are now considering whether
to consult this “expert.” Therefore, you need to determine whether it would be
worth paying the expert’s fee to get his prediction. You recognize that you
need to do further analysis to determine the value of the information that the
expert might provide.
In order to simplify the analysis, you have decided to look
at two possible outcomes for each alternative (instead of three). You are
interested in whether the market will be Favorable or Unfavorable, so you have
collapsed the Medium and Low outcomes. Here are the three alternatives with
their respective payoffs and probabilities.
Option A: Real estate development. This is a risky
opportunity with the possibility of a high payoff, but also with no payoff at
all. You have reviewed all of the possible data for the outcomes in the next 10
years and these are your estimates of the Net Present Value (NPV) of the
payoffs and probabilities:
High/Favorable NPV: $7.5 million, Pr = 0.5
Unfavorable NPV: $2.0 million, Pr = 0.5
Option B: Retail franchise for Just Hats, a boutique-type
store selling fashion hats for men and women. This also is a risky opportunity
but less so than Option A. It has the potential for less risk of failure, but
also a lower payoff. You have reviewed all of the possible data for the
outcomes in the next 10 years and these are your estimates of the NPV of the
payoffs and probabilities.
High/Favorable NPV: $4.5 million, Pr = 0.75
Unfavorable NPV: $2.5 million, Pr = 0.25
Option C: High Yield Municipal Bonds. This option has low
risk and is assumed to be a Certainty. So there is only one outcome with
probability of 1.0:
NPV: $2.25 million, Pr = 1.0
You have contacted the expert and received a letter stating
his track record which you have checked out using several resources. Here is
his stated track record:
True State of the Market
Expert Prediction
Favorable
Unfavorable
Predicts “Favorable”
.9
.3
Predicts “Unfavorable”
.1
.7
You realize that this situation is a bit complicated since
it requires the expert to analyze and predict the state of two different
markets: the real estate market and the retail hat market. You think through
the issues of probabilities and how to calculate the joint probabilities of
both markets going up, both going down, or one up and the other down. Based on
your original estimates of success, here are your calculations of the single
probabilities and joint probabilities of the markets.

Probabilities
Favorable
Unfavorable
A: Real Estate
0.50
0.50
B: Just Hats
0.75
0.25
Joint Probabilities
A Fav, B Fav (A+, B+)
0.375
A Unf, B Unf (A-, B-)
0.125
A Fav, B Unf (A+, B-)
0.125
A Unf, B Fav (A-, B+)
0.375
Finally, after a great deal of analysis and calculation, you
have determined the Posterior probabilities of Favorable and Unfavorable
Markets for the Real Estate business and the boutique hat business.
Real Estate
Just Hats

F
U
F
U
0.45
says “F/F”
0.75
0.25
0.90
0.10
0.15
says “F/U”
0.75
0.25
0.30
0.70
0.30
says “U/F”
0.125
0.875
0.90
0.10
0.10
says “U/U”
0.125
0.875
0.30
0.70
For example, this table says that there is 45% chance that
the expert will predict Favorable for both markets (F/F), and when he makes
this prediction, there is a 75% chance that the Real Estate market will be
favorable and 25% chance that it won’t, and also a 90% chance that the Hat
market will be Favorable and 10% chance it won’t.

You have developed a Decision Tree showing the original
collapsed solution and also showing an expanded Decision Tree for evaluating
the value of the expert’s information. You need to enter the probabilities into
this tree to see if the expert’s information will increase the overall expected
value of your decision. Download the Excel file with the incomplete Decision
Tree: Decision Tree for BUS520 SLP 4
Assignment
Complete the information in the Decision Tree in the Excel
file. Determine the Expected NPV of the decision if you were to consult the
Expert. Does use of the Expert increase the value of your analysis? If so, by
how much?
Write a report to your private investment company and
explain your analysis and your recommendation. Provide clear rationale/ justification
for your decision.
Upload both your written report and Excel file with the
Decision Tree analysis to the SLP 4 Dropbox.
SLP Assignment Expectations
Analysis
Accurate and complete analysis in Excel.
Required:
Length requirements: 2–3 pages minimum (not including Cover
and Reference pages). NOTE: You must submit 2–3 pages of written discussion and
analysis. This means that you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Written analysis that supports Excel analysis and provides
thorough discussion of assumptions, rationale, and logic used.
Complete, meaningful, and accurate recommendation(s).

Module 1 – Case
ASSUMED CERTAINTY: PIVOT TABLES AND MULTI-ATTRIBUTE DECISION
MAKING
Pivot Tables and Pivot Charts
Assignment Overview
You are the lead consultant for the Excellent Consulting
Group. It is mid-October. One of your top clients, Buddy’s Floor Barn, has just
closed the books for the first three quarters of the year (January through
September). Buddy’s Floor Barn requests that you analyze the sales performance
of its 5 product lines over this 3-quarter period. From past consulting work
you have done for the company, you know that Buddy’s Floor Barn has 4 regions
and 18 total store locations.
Each Regional Manager at the company has compiled the data
for his/her region. The raw data provided consists of the sales revenue for
each of the 5 premium flooring lines for all 4 regions and 18 locations for the
first three quarters of the current year.
Case Assignment
The data have been provided in list format. Generate a Pivot
Table Report with Charts. Use the Pivot Table and Charts to analyze the data.
Following your in-depth analysis of the data, write a report to Buddy’s Floor
Barn in which you discuss and analyze the data, and make appropriate
recommendations relative to how Buddy’s Floor Barn should improve its sales
performance going forward.
Assignment Expectations
Data: To begin, download the list data here: Data chart for
BUS520 Case 1
Excel Analysis:
Provide accurate and complete Excel analysis (Pivot Table
with Charts).
Written report:
Length requirement: 4–5 pages minimum (not including Cover
and Reference pages). NOTE: You must have 4–5 pages of written discussion and
analysis. This means you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Using the Pivot Table and Pivot Charts, discuss and analyze
the data, noting key highs and lows, trends, etc.
Include charts from your Pivot Table to support your written
analysis. (Please do not use charts as “space fillers.” Instead, use them
strategically to support your written analysis.)
In a “Recommendations” section, give clear, specific, and
meaningful recommendations that Buddy’s Floor Barn should use to improve
overall company sales.
Be sure to consider highs, lows, and trends in the data.
Which cities are the highest performers? Lowest? Which regions and quarter had
the highest sales? Lowest sales? Consider what may be driving the numbers: Poor
marketing? Outstanding marketing strategies? Inventory management? Seasonal
sales? Other? There are innumerable possibilities. Your role is to reflect on
the data, and ultimately, to use the data to give useful recommendations.
Module 1 – SLP
ASSUMED CERTAINTY: PIVOT TABLES AND MULTI-ATTRIBUTE DECISION
MAKING
Assumed Certainty: Multi-Attribute Decision Making (MADM)
Scenario: You are the Vice President of Franchise Services
for the Happy Buns restaurant chain. You have been assigned the task of
evaluating the best location for a new Happy Buns restaurant. The CFO has
provided you with a template that includes 6 criteria (attributes) that you are
required to use in your evaluation of 5 recommended locations. Following are
the 6 criteria that you will use to evaluate this decision:
Traffic counts (avg. thousands/day)—the more traffic, the
more customers, and the greater the potential sales.
Building lease and taxes (thousands $ per year)—the lower
the building lease and taxes, the better.
Size of building (square feet in thousands)—a larger
building is more preferable.
Parking spaces (max number of customers parking)—more
customer parking is preferable.
Insurance costs (thousands $ per year)—lower insurance costs
are preferable.
Ease of access (subjective evaluation from observation)—you
will need to “code” the subjective data. Use Excellent = 4, Good = 3, Fair = 2,
and Poor = 1.
Now that you have collected the data from various sources
(your CFO and COO, local real estate listings, personal observation, etc.), you
have all the data you need to complete an analysis for choosing the best
location. Download the raw data for the 5 locations in this Word document:
BUS520 SLP1V1.docx
Assignment
Review the information and data regarding the different
alternatives for a new restaurant location.
Then do the following in Excel:
Table 1: Develop an MADM table with the raw data.
Table 2: Convert the raw data to utilities (scaled on 0 to
1). Show the utility weights in a second table.
Table 3: Develop a third table with even weights (16.7%) for
each variable.
Evaluate Table 3 for the best alternative.
Table 4: Complete a sensitivity analysis by assigning
weights to each variable.
In a Word document, do the following:
Discuss the process used to put together Tables 1–4 above.
Provide the rationale you used for choosing for each of the
weights you used in Table 4.
Give your recommendation of which location the company
should choose (based on results of Table 4).
SLP Assignment Expectations
Excel Analysis
Complete Excel analysis using MADM (all four tables noted
above must be included).
Accurate Excel analysis (Excel file includes working
formulas showing your calculations; all calculations and results must be
accurate).
Written Report
Length requirements: 2–3 pages minimum (not including Cover
and Reference pages). NOTE: You must submit 2–3 pages of written discussion and
analysis. This means that you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Discuss the steps you used to compile the Excel analysis
(i.e., the four tables).
Discuss the assumptions used to assign weights to each
variable of your sensitivity analysis (Table 4). That is, provide the rationale
for your choice of weights for each variable.
Provide a complete and meaningful recommendation related to
the location that should be chosen as a new site.
Upload both your Excel file and written Word report to the
SLP 1 Dropbox by the assignment due date.

Module 2 – Case
RISK: FREQUENCY DISTRIBUTION, PROBABILITIES, AND EXPECTED
VALUE
Risk: Frequency Distribution, Probabilities, and Expected
Value
Assignment Overview
In the Module 2 Case, you are again engaged on a consulting
basis by Buddy’s Floor Barn. This time, in order to get a better idea of what
might have motivated customers’ buying habits you are asked to analyze the ages
of the customers who have purchased oak flooring over the past 12 months. Past
research done by the Excellent Consulting Group has shown that different age
groups buy certain products for different reasons. Buddy’s Floor Barn has sent
a survey to 200 customers who have previously purchased oak premium flooring,
and 124 customers have responded. The survey includes age data of past customers
who purchased oak flooring in the past year.

Case Assignment
Using Excel, create a frequency distribution (histogram) of
the age data that was captured from the survey. You should consider the width
of the age categories (e.g., 5 years, 10 years, or other). That is, which age
category grouping provides the most useful information? Once you have created
this histogram, determine the mean, median, and mode.
After you have reviewed the data, write a report to your
boss that briefly describes the results that you obtained. Make a
recommendation on how this data might be used for marketing purposes.
Data: Download the Excel-based data file with the age data
of the 124 customers: Data chart for BUS520 Case 2. Use these data in Excel to
create your histogram.
Assignment Expectations
Excel Analysis
Accurate and complete analysis in Excel using the Histogram
function.
Written Report
Length requirements: 4–5 pages minimum (not including Cover
and Reference pages). NOTE: You must submit 4–5 pages of written discussion and
analysis. This means that you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Provide a written analysis that supports your Histogram age
groups (bins).
Based on your analysis of the histogram data, provide
complete and meaningful recommendations as the data relates to Buddy’s Floor
Barn marketing strategy.

Module 2 – SLP
RISK: FREQUENCY DISTRIBUTION, PROBABILITIES, AND EXPECTED
VALUE
Risk: Probabilities and Expected Value
Scenario: You work for a private investment company that
currently has numerous business investments in real estate development,
restaurant franchises, and retail chains. Following an exhaustive search for
new investment opportunities, you have found three possible alternatives, each
of which will pay off in exactly 10 years from the date of initial investment.
Because you only have enough money to invest in one of the three options, you
recognize that you will need to complete a quantitative comparison of the three
alternatives:
Option A: Real estate development.
Option B: Investment in the retail franchise “Just Hats,” a
boutique that sells hats for men and women.
Option C: Investment in “Cupcakes and so forth,” a franchise
that sells a wide variety of cupcakes and a variety other desserts.
Download the raw data for the three investments in this
Excel document: Raw data for BUS520 SLP 2
Assignment
Develop an analysis of these three investments in Excel. Use
expected value to determine which of the three alternatives you should choose.
Write a report to your private investment company,
explaining your Excel analysis, giving your recommendation, and justifying your
decision.
SLP Assignment Expectations
Excel Analysis
Using Excel, make an accurate and complete analysis of the
three investment alternatives.
Written Report
Length requirements: 2–3 pages minimum (not including Cover
and Reference pages). NOTE: You must submit 2–3 pages of written discussion and
analysis. This means that you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Discuss the steps you used in completion of your Excel
analysis.
Based on your Excel analysis, give your recommendation as to
which of the three investment alternatives should be pursued.
Upload both your written report and Excel file to the SLP 2
Dropbox.

Module 3 – Case
LINEAR REGRESSION FORECASTING AND DECISION TREES
Linear Regression Forecasting
Assignment Overview
Scenario: You are a consultant who works for the Excellent
Consulting Group. Your client, the ABC Furniture Company, believes that there
may be a relationship between the number of customers who visit the store
during any given month (“customer traffic”) and the total sales for that same
month. In other words, the greater the customer traffic, the greater the sales
for that month. To test this theory, the client has collected customer traffic
data over the past 12-month period, and monthly sales for that same 12-month
period (Year 1).
Case Assignment
Using the customer traffic data and matching sales for each
month of Year 1, create a Linear Regression (LR) equation in Excel. Use the
Excel template provided (see “Module 3 Case – LR –Year 1” spreadsheet tab), and
be sure to include your LR chart (with a trend line) where noted. Also, be sure
that you include the LR formula within your chart.
After you have developed the LR equation above, you will use
the LR equation to forecast sales for Year 2 (see the second Excel spreadsheet
tab labeled “Year 2 Forecast”). You will note that the customer has collected
customer traffic data for Year 2. Your role is to complete the sales forecast
using the LR equation from Step 1 above.
After you have forecast Year 2 sales, your Professor will
provide you with 12 months of actual sales data for Year 2. You will compare
the sales forecast with the actual sales for Year 2, noting the monthly and
average (total) variances from forecast to actual sales.
To complete the Module 3 Case, write a report for the client
that describes the process you used above, and that analyzes the results for
Year 2. (What is the difference between forecast vs. actual sales for Year 2—by
month and for the year as a whole?) Make a recommendation concerning how the LR
equation might be used by ABC Furniture Company to forecast future sales.
Data: Download the Module 3 Case template here: Data chart
for BUS520 Case 3. Use this template to complete your Excel analysis.
Assignment Expectations
Excel Analysis
Accurate and complete Linear Regression analysis in Excel.
Written Report
Length requirements: 4–5 pages minimum (not including Cover
and Reference pages). NOTE: You must submit 4–5 pages of written discussion and
analysis. This means that you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Your written (Word) analysis should discuss the logic and
rationale used to develop the LR equation and chart.
Provide complete, meaningful, and accurate recommendation(s)
concerning how the ABC Furniture Company might use the LR equation to forecast
future sales. (For example, how reliable is the LR equation in predicting
future sales?) What other recommendations do you have for the client?

Module 3 – SLP
LINEAR REGRESSION FORECASTING AND DECISION TREES
Decision Trees
Scenario: You are a consultant who works for the Excellent
Consulting Group. You have learned about three different investment
opportunities and need to decide which one is most lucrative. Following are the
three investment options and their probabilities:
Option A: Real Estate development. This is a risky
opportunity with the possibility of a high payoff, but also with no payoff at
all. You have reviewed all of the possible data for the outcomes in the next 10
years and these are your estimates of the cash payoff and probabilities:
Required initial investment: $0.75 million
High NPV: $5 million, Pr = 0.5
Medium NPV: $2 million, Pr = 0.3
Low NPV: $0, Pr = 0.2
Option B: Retail franchise for Just Hats, a boutique-type
store selling fashion hats for men and women. This also is a risky opportunity
but less so than Option A. It has the potential for less risk of failure, but
also a lower payoff. You have reviewed all of the possible data for the
outcomes in the next 10 years and these are your estimates of the payoffs and
probabilities:
Required initial investment: $0.55 million
High NPV: $3 million, Pr = 0.75
Medium NPV: $2 million, Pr = 0.15
Low NPV: $1 million, Pr = 0.1
Option C: High Yield Municipal Bonds. This option has low
risk and is assumed to be a Certainty. So there is only one outcome with
probability of 1.0:
Required initial investment: $0.75 million
NPV: $1.5 million, Pr = 1.0
Assignment
Develop an analysis of these three investments, and
determine which of them you should choose. Be sure to account for cash paid for
each of the three alternatives. If you do not recall how to do this, review the
practice exercises in the Background page. Do your analysis in Excel using the
Decision Tree add-in.
Write a report to your private investment company and
explain your analysis and your recommendations. Provide a rationale for your
decision.
Upload both your written report and Excel file with the decision
tree analysis to the SLP 3 Dropbox.
SLP Assignment Expectations
Analysis
Accurate and complete Excel analysis.
Written Report
Length requirements: 2–3 pages minimum (not including Cover
and Reference pages)
Provide a brief introduction to/background of the problem.
Written analysis that supports Excel analysis and provides
thorough discussion of assumptions, rationale, and logic used.
Complete, meaningful, and accurate recommendation(s).

Module 4 – Case
RISK: EXPONENTIAL SMOOTHING FORECASTING AND VALUE OF
INFORMATION
Risk: Simple Exponential Smoothing (SES)
Assignment Overview
Scenario: You are a consultant for the Excellent Consulting
Group (ECG). You have completed the first assignment, developing and testing a
forecasting method that uses Linear Regression (LR) techniques (Module 3 Case).
However, the consulting manager at ECG wants to try a different forecasting
method as well. Now you decide to try Single Exponential Smoothing (SES) to
forecast sales.
Case Assignment
Using this Excel template: Data chart for BUS520 Case 4, do
the following:
Calculate the MAPE for Year 2 Linear Regression forecast
(use the first spreadsheet tab labeled “Year 2 Forecast – MAPE”).
Calculate forecasted sales for Year 2 using SES (use the second
spreadsheet tab labeled “SES – MAPE”). Use 0.15 and 0.90 alphas.
Compare the MAPE calculated for the LR forecast (#1 above)
with the MAPEs calculated using SES.
Then write a report to your boss in which you discuss the
results obtained above. Using calculated MAPE values, make a recommendation
concerning which method appears to be more accurate for the Year 2 data: SES or
Linear Regression.
Assignment Expectations
Analysis
Accurate and complete SES analysis in Excel.
Written Report
Length requirements: 4–5 pages minimum (not including Cover
and Reference pages). NOTE: You must submit 4–5 pages of written discussion and
analysis. This means that you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Complete a written analysis that supports your Excel
analysis, discussing the assumptions, rationale, and logic used to complete
your SES forecast.
Give complete, meaningful, and accurate recommendation(s)
relating to whether LR or SES is more accurate in predicting sales.

Module 4 – SLP
RISK: EXPONENTIAL SMOOTHING FORECASTING AND VALUE OF
INFORMATION
Risk: The Value of Information
Scenario: Using the same situation from the Module 3 SLP,
recall that you are deciding among three investments. You have heard of an
expert who has a highly reliable “track record” in the correct identification
of favorable vs. unfavorable market conditions. You are now considering whether
to consult this “expert.” Therefore, you need to determine whether it would be
worth paying the expert’s fee to get his prediction. You recognize that you
need to do further analysis to determine the value of the information that the
expert might provide.
In order to simplify the analysis, you have decided to look
at two possible outcomes for each alternative (instead of three). You are
interested in whether the market will be Favorable or Unfavorable, so you have
collapsed the Medium and Low outcomes. Here are the three alternatives with
their respective payoffs and probabilities.
Option A: Real estate development. This is a risky
opportunity with the possibility of a high payoff, but also with no payoff at
all. You have reviewed all of the possible data for the outcomes in the next 10
years and these are your estimates of the Net Present Value (NPV) of the
payoffs and probabilities:
High/Favorable NPV: $7.5 million, Pr = 0.5
Unfavorable NPV: $2.0 million, Pr = 0.5
Option B: Retail franchise for Just Hats, a boutique-type
store selling fashion hats for men and women. This also is a risky opportunity
but less so than Option A. It has the potential for less risk of failure, but
also a lower payoff. You have reviewed all of the possible data for the
outcomes in the next 10 years and these are your estimates of the NPV of the
payoffs and probabilities.
High/Favorable NPV: $4.5 million, Pr = 0.75
Unfavorable NPV: $2.5 million, Pr = 0.25
Option C: High Yield Municipal Bonds. This option has low
risk and is assumed to be a Certainty. So there is only one outcome with
probability of 1.0:
NPV: $2.25 million, Pr = 1.0
You have contacted the expert and received a letter stating
his track record which you have checked out using several resources. Here is
his stated track record:
True State of the Market
Expert Prediction
Favorable
Unfavorable
Predicts “Favorable”
.9
.3
Predicts “Unfavorable”
.1
.7
You realize that this situation is a bit complicated since
it requires the expert to analyze and predict the state of two different
markets: the real estate market and the retail hat market. You think through
the issues of probabilities and how to calculate the joint probabilities of
both markets going up, both going down, or one up and the other down. Based on
your original estimates of success, here are your calculations of the single
probabilities and joint probabilities of the markets.

Probabilities
Favorable
Unfavorable
A: Real Estate
0.50
0.50
B: Just Hats
0.75
0.25
Joint Probabilities
A Fav, B Fav (A+, B+)
0.375
A Unf, B Unf (A-, B-)
0.125
A Fav, B Unf (A+, B-)
0.125
A Unf, B Fav (A-, B+)
0.375
Finally, after a great deal of analysis and calculation, you
have determined the Posterior probabilities of Favorable and Unfavorable
Markets for the Real Estate business and the boutique hat business.
Real Estate
Just Hats

F
U
F
U
0.45
says “F/F”
0.75
0.25
0.90
0.10
0.15
says “F/U”
0.75
0.25
0.30
0.70
0.30
says “U/F”
0.125
0.875
0.90
0.10
0.10
says “U/U”
0.125
0.875
0.30
0.70
For example, this table says that there is 45% chance that
the expert will predict Favorable for both markets (F/F), and when he makes
this prediction, there is a 75% chance that the Real Estate market will be
favorable and 25% chance that it won’t, and also a 90% chance that the Hat
market will be Favorable and 10% chance it won’t.

You have developed a Decision Tree showing the original
collapsed solution and also showing an expanded Decision Tree for evaluating
the value of the expert’s information. You need to enter the probabilities into
this tree to see if the expert’s information will increase the overall expected
value of your decision. Download the Excel file with the incomplete Decision
Tree: Decision Tree for BUS520 SLP 4
Assignment
Complete the information in the Decision Tree in the Excel
file. Determine the Expected NPV of the decision if you were to consult the
Expert. Does use of the Expert increase the value of your analysis? If so, by
how much?
Write a report to your private investment company and
explain your analysis and your recommendation. Provide clear rationale/ justification
for your decision.
Upload both your written report and Excel file with the
Decision Tree analysis to the SLP 4 Dropbox.
SLP Assignment Expectations
Analysis
Accurate and complete analysis in Excel.
Required:
Length requirements: 2–3 pages minimum (not including Cover
and Reference pages). NOTE: You must submit 2–3 pages of written discussion and
analysis. This means that you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Written analysis that supports Excel analysis and provides
thorough discussion of assumptions, rationale, and logic used.
Complete, meaningful, and accurate recommendation(s).

Module 1 – Case
ASSUMED CERTAINTY: PIVOT TABLES AND MULTI-ATTRIBUTE DECISION
MAKING
Pivot Tables and Pivot Charts
Assignment Overview
You are the lead consultant for the Excellent Consulting
Group. It is mid-October. One of your top clients, Buddy’s Floor Barn, has just
closed the books for the first three quarters of the year (January through
September). Buddy’s Floor Barn requests that you analyze the sales performance
of its 5 product lines over this 3-quarter period. From past consulting work
you have done for the company, you know that Buddy’s Floor Barn has 4 regions
and 18 total store locations.
Each Regional Manager at the company has compiled the data
for his/her region. The raw data provided consists of the sales revenue for
each of the 5 premium flooring lines for all 4 regions and 18 locations for the
first three quarters of the current year.
Case Assignment
The data have been provided in list format. Generate a Pivot
Table Report with Charts. Use the Pivot Table and Charts to analyze the data.
Following your in-depth analysis of the data, write a report to Buddy’s Floor
Barn in which you discuss and analyze the data, and make appropriate
recommendations relative to how Buddy’s Floor Barn should improve its sales
performance going forward.
Assignment Expectations
Data: To begin, download the list data here: Data chart for
BUS520 Case 1
Excel Analysis:
Provide accurate and complete Excel analysis (Pivot Table
with Charts).
Written report:
Length requirement: 4–5 pages minimum (not including Cover
and Reference pages). NOTE: You must have 4–5 pages of written discussion and
analysis. This means you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Using the Pivot Table and Pivot Charts, discuss and analyze
the data, noting key highs and lows, trends, etc.
Include charts from your Pivot Table to support your written
analysis. (Please do not use charts as “space fillers.” Instead, use them
strategically to support your written analysis.)
In a “Recommendations” section, give clear, specific, and
meaningful recommendations that Buddy’s Floor Barn should use to improve
overall company sales.
Be sure to consider highs, lows, and trends in the data.
Which cities are the highest performers? Lowest? Which regions and quarter had
the highest sales? Lowest sales? Consider what may be driving the numbers: Poor
marketing? Outstanding marketing strategies? Inventory management? Seasonal
sales? Other? There are innumerable possibilities. Your role is to reflect on
the data, and ultimately, to use the data to give useful recommendations.
Module 1 – SLP
ASSUMED CERTAINTY: PIVOT TABLES AND MULTI-ATTRIBUTE DECISION
MAKING
Assumed Certainty: Multi-Attribute Decision Making (MADM)
Scenario: You are the Vice President of Franchise Services
for the Happy Buns restaurant chain. You have been assigned the task of
evaluating the best location for a new Happy Buns restaurant. The CFO has
provided you with a template that includes 6 criteria (attributes) that you are
required to use in your evaluation of 5 recommended locations. Following are
the 6 criteria that you will use to evaluate this decision:
Traffic counts (avg. thousands/day)—the more traffic, the
more customers, and the greater the potential sales.
Building lease and taxes (thousands $ per year)—the lower
the building lease and taxes, the better.
Size of building (square feet in thousands)—a larger
building is more preferable.
Parking spaces (max number of customers parking)—more
customer parking is preferable.
Insurance costs (thousands $ per year)—lower insurance costs
are preferable.
Ease of access (subjective evaluation from observation)—you
will need to “code” the subjective data. Use Excellent = 4, Good = 3, Fair = 2,
and Poor = 1.
Now that you have collected the data from various sources
(your CFO and COO, local real estate listings, personal observation, etc.), you
have all the data you need to complete an analysis for choosing the best
location. Download the raw data for the 5 locations in this Word document:
BUS520 SLP1V1.docx
Assignment
Review the information and data regarding the different
alternatives for a new restaurant location.
Then do the following in Excel:
Table 1: Develop an MADM table with the raw data.
Table 2: Convert the raw data to utilities (scaled on 0 to
1). Show the utility weights in a second table.
Table 3: Develop a third table with even weights (16.7%) for
each variable.
Evaluate Table 3 for the best alternative.
Table 4: Complete a sensitivity analysis by assigning
weights to each variable.
In a Word document, do the following:
Discuss the process used to put together Tables 1–4 above.
Provide the rationale you used for choosing for each of the
weights you used in Table 4.
Give your recommendation of which location the company
should choose (based on results of Table 4).
SLP Assignment Expectations
Excel Analysis
Complete Excel analysis using MADM (all four tables noted
above must be included).
Accurate Excel analysis (Excel file includes working
formulas showing your calculations; all calculations and results must be
accurate).
Written Report
Length requirements: 2–3 pages minimum (not including Cover
and Reference pages). NOTE: You must submit 2–3 pages of written discussion and
analysis. This means that you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Discuss the steps you used to compile the Excel analysis
(i.e., the four tables).
Discuss the assumptions used to assign weights to each
variable of your sensitivity analysis (Table 4). That is, provide the rationale
for your choice of weights for each variable.
Provide a complete and meaningful recommendation related to
the location that should be chosen as a new site.
Upload both your Excel file and written Word report to the
SLP 1 Dropbox by the assignment due date.

Module 2 – Case
RISK: FREQUENCY DISTRIBUTION, PROBABILITIES, AND EXPECTED
VALUE
Risk: Frequency Distribution, Probabilities, and Expected
Value
Assignment Overview
In the Module 2 Case, you are again engaged on a consulting
basis by Buddy’s Floor Barn. This time, in order to get a better idea of what
might have motivated customers’ buying habits you are asked to analyze the ages
of the customers who have purchased oak flooring over the past 12 months. Past
research done by the Excellent Consulting Group has shown that different age
groups buy certain products for different reasons. Buddy’s Floor Barn has sent
a survey to 200 customers who have previously purchased oak premium flooring,
and 124 customers have responded. The survey includes age data of past customers
who purchased oak flooring in the past year.

Case Assignment
Using Excel, create a frequency distribution (histogram) of
the age data that was captured from the survey. You should consider the width
of the age categories (e.g., 5 years, 10 years, or other). That is, which age
category grouping provides the most useful information? Once you have created
this histogram, determine the mean, median, and mode.
After you have reviewed the data, write a report to your
boss that briefly describes the results that you obtained. Make a
recommendation on how this data might be used for marketing purposes.
Data: Download the Excel-based data file with the age data
of the 124 customers: Data chart for BUS520 Case 2. Use these data in Excel to
create your histogram.
Assignment Expectations
Excel Analysis
Accurate and complete analysis in Excel using the Histogram
function.
Written Report
Length requirements: 4–5 pages minimum (not including Cover
and Reference pages). NOTE: You must submit 4–5 pages of written discussion and
analysis. This means that you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Provide a written analysis that supports your Histogram age
groups (bins).
Based on your analysis of the histogram data, provide
complete and meaningful recommendations as the data relates to Buddy’s Floor
Barn marketing strategy.

Module 2 – SLP
RISK: FREQUENCY DISTRIBUTION, PROBABILITIES, AND EXPECTED
VALUE
Risk: Probabilities and Expected Value
Scenario: You work for a private investment company that
currently has numerous business investments in real estate development,
restaurant franchises, and retail chains. Following an exhaustive search for
new investment opportunities, you have found three possible alternatives, each
of which will pay off in exactly 10 years from the date of initial investment.
Because you only have enough money to invest in one of the three options, you
recognize that you will need to complete a quantitative comparison of the three
alternatives:
Option A: Real estate development.
Option B: Investment in the retail franchise “Just Hats,” a
boutique that sells hats for men and women.
Option C: Investment in “Cupcakes and so forth,” a franchise
that sells a wide variety of cupcakes and a variety other desserts.
Download the raw data for the three investments in this
Excel document: Raw data for BUS520 SLP 2
Assignment
Develop an analysis of these three investments in Excel. Use
expected value to determine which of the three alternatives you should choose.
Write a report to your private investment company,
explaining your Excel analysis, giving your recommendation, and justifying your
decision.
SLP Assignment Expectations
Excel Analysis
Using Excel, make an accurate and complete analysis of the
three investment alternatives.
Written Report
Length requirements: 2–3 pages minimum (not including Cover
and Reference pages). NOTE: You must submit 2–3 pages of written discussion and
analysis. This means that you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Discuss the steps you used in completion of your Excel
analysis.
Based on your Excel analysis, give your recommendation as to
which of the three investment alternatives should be pursued.
Upload both your written report and Excel file to the SLP 2
Dropbox.

Module 3 – Case
LINEAR REGRESSION FORECASTING AND DECISION TREES
Linear Regression Forecasting
Assignment Overview
Scenario: You are a consultant who works for the Excellent
Consulting Group. Your client, the ABC Furniture Company, believes that there
may be a relationship between the number of customers who visit the store
during any given month (“customer traffic”) and the total sales for that same
month. In other words, the greater the customer traffic, the greater the sales
for that month. To test this theory, the client has collected customer traffic
data over the past 12-month period, and monthly sales for that same 12-month
period (Year 1).
Case Assignment
Using the customer traffic data and matching sales for each
month of Year 1, create a Linear Regression (LR) equation in Excel. Use the
Excel template provided (see “Module 3 Case – LR –Year 1” spreadsheet tab), and
be sure to include your LR chart (with a trend line) where noted. Also, be sure
that you include the LR formula within your chart.
After you have developed the LR equation above, you will use
the LR equation to forecast sales for Year 2 (see the second Excel spreadsheet
tab labeled “Year 2 Forecast”). You will note that the customer has collected
customer traffic data for Year 2. Your role is to complete the sales forecast
using the LR equation from Step 1 above.
After you have forecast Year 2 sales, your Professor will
provide you with 12 months of actual sales data for Year 2. You will compare
the sales forecast with the actual sales for Year 2, noting the monthly and
average (total) variances from forecast to actual sales.
To complete the Module 3 Case, write a report for the client
that describes the process you used above, and that analyzes the results for
Year 2. (What is the difference between forecast vs. actual sales for Year 2—by
month and for the year as a whole?) Make a recommendation concerning how the LR
equation might be used by ABC Furniture Company to forecast future sales.
Data: Download the Module 3 Case template here: Data chart
for BUS520 Case 3. Use this template to complete your Excel analysis.
Assignment Expectations
Excel Analysis
Accurate and complete Linear Regression analysis in Excel.
Written Report
Length requirements: 4–5 pages minimum (not including Cover
and Reference pages). NOTE: You must submit 4–5 pages of written discussion and
analysis. This means that you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Your written (Word) analysis should discuss the logic and
rationale used to develop the LR equation and chart.
Provide complete, meaningful, and accurate recommendation(s)
concerning how the ABC Furniture Company might use the LR equation to forecast
future sales. (For example, how reliable is the LR equation in predicting
future sales?) What other recommendations do you have for the client?

Module 3 – SLP
LINEAR REGRESSION FORECASTING AND DECISION TREES
Decision Trees
Scenario: You are a consultant who works for the Excellent
Consulting Group. You have learned about three different investment
opportunities and need to decide which one is most lucrative. Following are the
three investment options and their probabilities:
Option A: Real Estate development. This is a risky
opportunity with the possibility of a high payoff, but also with no payoff at
all. You have reviewed all of the possible data for the outcomes in the next 10
years and these are your estimates of the cash payoff and probabilities:
Required initial investment: $0.75 million
High NPV: $5 million, Pr = 0.5
Medium NPV: $2 million, Pr = 0.3
Low NPV: $0, Pr = 0.2
Option B: Retail franchise for Just Hats, a boutique-type
store selling fashion hats for men and women. This also is a risky opportunity
but less so than Option A. It has the potential for less risk of failure, but
also a lower payoff. You have reviewed all of the possible data for the
outcomes in the next 10 years and these are your estimates of the payoffs and
probabilities:
Required initial investment: $0.55 million
High NPV: $3 million, Pr = 0.75
Medium NPV: $2 million, Pr = 0.15
Low NPV: $1 million, Pr = 0.1
Option C: High Yield Municipal Bonds. This option has low
risk and is assumed to be a Certainty. So there is only one outcome with
probability of 1.0:
Required initial investment: $0.75 million
NPV: $1.5 million, Pr = 1.0
Assignment
Develop an analysis of these three investments, and
determine which of them you should choose. Be sure to account for cash paid for
each of the three alternatives. If you do not recall how to do this, review the
practice exercises in the Background page. Do your analysis in Excel using the
Decision Tree add-in.
Write a report to your private investment company and
explain your analysis and your recommendations. Provide a rationale for your
decision.
Upload both your written report and Excel file with the decision
tree analysis to the SLP 3 Dropbox.
SLP Assignment Expectations
Analysis
Accurate and complete Excel analysis.
Written Report
Length requirements: 2–3 pages minimum (not including Cover
and Reference pages)
Provide a brief introduction to/background of the problem.
Written analysis that supports Excel analysis and provides
thorough discussion of assumptions, rationale, and logic used.
Complete, meaningful, and accurate recommendation(s).

Module 4 – Case
RISK: EXPONENTIAL SMOOTHING FORECASTING AND VALUE OF
INFORMATION
Risk: Simple Exponential Smoothing (SES)
Assignment Overview
Scenario: You are a consultant for the Excellent Consulting
Group (ECG). You have completed the first assignment, developing and testing a
forecasting method that uses Linear Regression (LR) techniques (Module 3 Case).
However, the consulting manager at ECG wants to try a different forecasting
method as well. Now you decide to try Single Exponential Smoothing (SES) to
forecast sales.
Case Assignment
Using this Excel template: Data chart for BUS520 Case 4, do
the following:
Calculate the MAPE for Year 2 Linear Regression forecast
(use the first spreadsheet tab labeled “Year 2 Forecast – MAPE”).
Calculate forecasted sales for Year 2 using SES (use the second
spreadsheet tab labeled “SES – MAPE”). Use 0.15 and 0.90 alphas.
Compare the MAPE calculated for the LR forecast (#1 above)
with the MAPEs calculated using SES.
Then write a report to your boss in which you discuss the
results obtained above. Using calculated MAPE values, make a recommendation
concerning which method appears to be more accurate for the Year 2 data: SES or
Linear Regression.
Assignment Expectations
Analysis
Accurate and complete SES analysis in Excel.
Written Report
Length requirements: 4–5 pages minimum (not including Cover
and Reference pages). NOTE: You must submit 4–5 pages of written discussion and
analysis. This means that you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Complete a written analysis that supports your Excel
analysis, discussing the assumptions, rationale, and logic used to complete
your SES forecast.
Give complete, meaningful, and accurate recommendation(s)
relating to whether LR or SES is more accurate in predicting sales.

Module 4 – SLP
RISK: EXPONENTIAL SMOOTHING FORECASTING AND VALUE OF
INFORMATION
Risk: The Value of Information
Scenario: Using the same situation from the Module 3 SLP,
recall that you are deciding among three investments. You have heard of an
expert who has a highly reliable “track record” in the correct identification
of favorable vs. unfavorable market conditions. You are now considering whether
to consult this “expert.” Therefore, you need to determine whether it would be
worth paying the expert’s fee to get his prediction. You recognize that you
need to do further analysis to determine the value of the information that the
expert might provide.
In order to simplify the analysis, you have decided to look
at two possible outcomes for each alternative (instead of three). You are
interested in whether the market will be Favorable or Unfavorable, so you have
collapsed the Medium and Low outcomes. Here are the three alternatives with
their respective payoffs and probabilities.
Option A: Real estate development. This is a risky
opportunity with the possibility of a high payoff, but also with no payoff at
all. You have reviewed all of the possible data for the outcomes in the next 10
years and these are your estimates of the Net Present Value (NPV) of the
payoffs and probabilities:
High/Favorable NPV: $7.5 million, Pr = 0.5
Unfavorable NPV: $2.0 million, Pr = 0.5
Option B: Retail franchise for Just Hats, a boutique-type
store selling fashion hats for men and women. This also is a risky opportunity
but less so than Option A. It has the potential for less risk of failure, but
also a lower payoff. You have reviewed all of the possible data for the
outcomes in the next 10 years and these are your estimates of the NPV of the
payoffs and probabilities.
High/Favorable NPV: $4.5 million, Pr = 0.75
Unfavorable NPV: $2.5 million, Pr = 0.25
Option C: High Yield Municipal Bonds. This option has low
risk and is assumed to be a Certainty. So there is only one outcome with
probability of 1.0:
NPV: $2.25 million, Pr = 1.0
You have contacted the expert and received a letter stating
his track record which you have checked out using several resources. Here is
his stated track record:
True State of the Market
Expert Prediction
Favorable
Unfavorable
Predicts “Favorable”
.9
.3
Predicts “Unfavorable”
.1
.7
You realize that this situation is a bit complicated since
it requires the expert to analyze and predict the state of two different
markets: the real estate market and the retail hat market. You think through
the issues of probabilities and how to calculate the joint probabilities of
both markets going up, both going down, or one up and the other down. Based on
your original estimates of success, here are your calculations of the single
probabilities and joint probabilities of the markets.

Probabilities
Favorable
Unfavorable
A: Real Estate
0.50
0.50
B: Just Hats
0.75
0.25
Joint Probabilities
A Fav, B Fav (A+, B+)
0.375
A Unf, B Unf (A-, B-)
0.125
A Fav, B Unf (A+, B-)
0.125
A Unf, B Fav (A-, B+)
0.375
Finally, after a great deal of analysis and calculation, you
have determined the Posterior probabilities of Favorable and Unfavorable
Markets for the Real Estate business and the boutique hat business.
Real Estate
Just Hats

F
U
F
U
0.45
says “F/F”
0.75
0.25
0.90
0.10
0.15
says “F/U”
0.75
0.25
0.30
0.70
0.30
says “U/F”
0.125
0.875
0.90
0.10
0.10
says “U/U”
0.125
0.875
0.30
0.70
For example, this table says that there is 45% chance that
the expert will predict Favorable for both markets (F/F), and when he makes
this prediction, there is a 75% chance that the Real Estate market will be
favorable and 25% chance that it won’t, and also a 90% chance that the Hat
market will be Favorable and 10% chance it won’t.

You have developed a Decision Tree showing the original
collapsed solution and also showing an expanded Decision Tree for evaluating
the value of the expert’s information. You need to enter the probabilities into
this tree to see if the expert’s information will increase the overall expected
value of your decision. Download the Excel file with the incomplete Decision
Tree: Decision Tree for BUS520 SLP 4
Assignment
Complete the information in the Decision Tree in the Excel
file. Determine the Expected NPV of the decision if you were to consult the
Expert. Does use of the Expert increase the value of your analysis? If so, by
how much?
Write a report to your private investment company and
explain your analysis and your recommendation. Provide clear rationale/ justification
for your decision.
Upload both your written report and Excel file with the
Decision Tree analysis to the SLP 4 Dropbox.
SLP Assignment Expectations
Analysis
Accurate and complete analysis in Excel.
Required:
Length requirements: 2–3 pages minimum (not including Cover
and Reference pages). NOTE: You must submit 2–3 pages of written discussion and
analysis. This means that you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Written analysis that supports Excel analysis and provides
thorough discussion of assumptions, rationale, and logic used.
Complete, meaningful, and accurate recommendation(s).

Module 1 – Case
ASSUMED CERTAINTY: PIVOT TABLES AND MULTI-ATTRIBUTE DECISION
MAKING
Pivot Tables and Pivot Charts
Assignment Overview
You are the lead consultant for the Excellent Consulting
Group. It is mid-October. One of your top clients, Buddy’s Floor Barn, has just
closed the books for the first three quarters of the year (January through
September). Buddy’s Floor Barn requests that you analyze the sales performance
of its 5 product lines over this 3-quarter period. From past consulting work
you have done for the company, you know that Buddy’s Floor Barn has 4 regions
and 18 total store locations.
Each Regional Manager at the company has compiled the data
for his/her region. The raw data provided consists of the sales revenue for
each of the 5 premium flooring lines for all 4 regions and 18 locations for the
first three quarters of the current year.
Case Assignment
The data have been provided in list format. Generate a Pivot
Table Report with Charts. Use the Pivot Table and Charts to analyze the data.
Following your in-depth analysis of the data, write a report to Buddy’s Floor
Barn in which you discuss and analyze the data, and make appropriate
recommendations relative to how Buddy’s Floor Barn should improve its sales
performance going forward.
Assignment Expectations
Data: To begin, download the list data here: Data chart for
BUS520 Case 1
Excel Analysis:
Provide accurate and complete Excel analysis (Pivot Table
with Charts).
Written report:
Length requirement: 4–5 pages minimum (not including Cover
and Reference pages). NOTE: You must have 4–5 pages of written discussion and
analysis. This means you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Using the Pivot Table and Pivot Charts, discuss and analyze
the data, noting key highs and lows, trends, etc.
Include charts from your Pivot Table to support your written
analysis. (Please do not use charts as “space fillers.” Instead, use them
strategically to support your written analysis.)
In a “Recommendations” section, give clear, specific, and
meaningful recommendations that Buddy’s Floor Barn should use to improve
overall company sales.
Be sure to consider highs, lows, and trends in the data.
Which cities are the highest performers? Lowest? Which regions and quarter had
the highest sales? Lowest sales? Consider what may be driving the numbers: Poor
marketing? Outstanding marketing strategies? Inventory management? Seasonal
sales? Other? There are innumerable possibilities. Your role is to reflect on
the data, and ultimately, to use the data to give useful recommendations.
Module 1 – SLP
ASSUMED CERTAINTY: PIVOT TABLES AND MULTI-ATTRIBUTE DECISION
MAKING
Assumed Certainty: Multi-Attribute Decision Making (MADM)
Scenario: You are the Vice President of Franchise Services
for the Happy Buns restaurant chain. You have been assigned the task of
evaluating the best location for a new Happy Buns restaurant. The CFO has
provided you with a template that includes 6 criteria (attributes) that you are
required to use in your evaluation of 5 recommended locations. Following are
the 6 criteria that you will use to evaluate this decision:
Traffic counts (avg. thousands/day)—the more traffic, the
more customers, and the greater the potential sales.
Building lease and taxes (thousands $ per year)—the lower
the building lease and taxes, the better.
Size of building (square feet in thousands)—a larger
building is more preferable.
Parking spaces (max number of customers parking)—more
customer parking is preferable.
Insurance costs (thousands $ per year)—lower insurance costs
are preferable.
Ease of access (subjective evaluation from observation)—you
will need to “code” the subjective data. Use Excellent = 4, Good = 3, Fair = 2,
and Poor = 1.
Now that you have collected the data from various sources
(your CFO and COO, local real estate listings, personal observation, etc.), you
have all the data you need to complete an analysis for choosing the best
location. Download the raw data for the 5 locations in this Word document:
BUS520 SLP1V1.docx
Assignment
Review the information and data regarding the different
alternatives for a new restaurant location.
Then do the following in Excel:
Table 1: Develop an MADM table with the raw data.
Table 2: Convert the raw data to utilities (scaled on 0 to
1). Show the utility weights in a second table.
Table 3: Develop a third table with even weights (16.7%) for
each variable.
Evaluate Table 3 for the best alternative.
Table 4: Complete a sensitivity analysis by assigning
weights to each variable.
In a Word document, do the following:
Discuss the process used to put together Tables 1–4 above.
Provide the rationale you used for choosing for each of the
weights you used in Table 4.
Give your recommendation of which location the company
should choose (based on results of Table 4).
SLP Assignment Expectations
Excel Analysis
Complete Excel analysis using MADM (all four tables noted
above must be included).
Accurate Excel analysis (Excel file includes working
formulas showing your calculations; all calculations and results must be
accurate).
Written Report
Length requirements: 2–3 pages minimum (not including Cover
and Reference pages). NOTE: You must submit 2–3 pages of written discussion and
analysis. This means that you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Discuss the steps you used to compile the Excel analysis
(i.e., the four tables).
Discuss the assumptions used to assign weights to each
variable of your sensitivity analysis (Table 4). That is, provide the rationale
for your choice of weights for each variable.
Provide a complete and meaningful recommendation related to
the location that should be chosen as a new site.
Upload both your Excel file and written Word report to the
SLP 1 Dropbox by the assignment due date.





















































































































Module 2 – Case
RISK: FREQUENCY DISTRIBUTION, PROBABILITIES, AND EXPECTED
VALUE
Risk: Frequency Distribution, Probabilities, and Expected
Value
Assignment Overview
In the Module 2 Case, you are again engaged on a consulting
basis by Buddy’s Floor Barn. This time, in order to get a better idea of what
might have motivated customers’ buying habits you are asked to analyze the ages
of the customers who have purchased oak flooring over the past 12 months. Past
research done by the Excellent Consulting Group has shown that different age
groups buy certain products for different reasons. Buddy’s Floor Barn has sent
a survey to 200 customers who have previously purchased oak premium flooring,
and 124 customers have responded. The survey includes age data of past customers
who purchased oak flooring in the past year.















Case Assignment
Using Excel, create a frequency distribution (histogram) of
the age data that was captured from the survey. You should consider the width
of the age categories (e.g., 5 years, 10 years, or other). That is, which age
category grouping provides the most useful information? Once you have created
this histogram, determine the mean, median, and mode.
After you have reviewed the data, write a report to your
boss that briefly describes the results that you obtained. Make a
recommendation on how this data might be used for marketing purposes.
Data: Download the Excel-based data file with the age data
of the 124 customers: Data chart for BUS520 Case 2. Use these data in Excel to
create your histogram.
Assignment Expectations
Excel Analysis
Accurate and complete analysis in Excel using the Histogram
function.
Written Report
Length requirements: 4–5 pages minimum (not including Cover
and Reference pages). NOTE: You must submit 4–5 pages of written discussion and
analysis. This means that you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Provide a written analysis that supports your Histogram age
groups (bins).
Based on your analysis of the histogram data, provide
complete and meaningful recommendations as the data relates to Buddy’s Floor
Barn marketing strategy.



























Module 2 – SLP
RISK: FREQUENCY DISTRIBUTION, PROBABILITIES, AND EXPECTED
VALUE
Risk: Probabilities and Expected Value
Scenario: You work for a private investment company that
currently has numerous business investments in real estate development,
restaurant franchises, and retail chains. Following an exhaustive search for
new investment opportunities, you have found three possible alternatives, each
of which will pay off in exactly 10 years from the date of initial investment.
Because you only have enough money to invest in one of the three options, you
recognize that you will need to complete a quantitative comparison of the three
alternatives:
Option A: Real estate development.
Option B: Investment in the retail franchise “Just Hats,” a
boutique that sells hats for men and women.
Option C: Investment in “Cupcakes and so forth,” a franchise
that sells a wide variety of cupcakes and a variety other desserts.
Download the raw data for the three investments in this
Excel document: Raw data for BUS520 SLP 2
Assignment
Develop an analysis of these three investments in Excel. Use
expected value to determine which of the three alternatives you should choose.
Write a report to your private investment company,
explaining your Excel analysis, giving your recommendation, and justifying your
decision.
SLP Assignment Expectations
Excel Analysis
Using Excel, make an accurate and complete analysis of the
three investment alternatives.
Written Report
Length requirements: 2–3 pages minimum (not including Cover
and Reference pages). NOTE: You must submit 2–3 pages of written discussion and
analysis. This means that you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Discuss the steps you used in completion of your Excel
analysis.
Based on your Excel analysis, give your recommendation as to
which of the three investment alternatives should be pursued.
Upload both your written report and Excel file to the SLP 2
Dropbox.









































Module 3 – Case
LINEAR REGRESSION FORECASTING AND DECISION TREES
Linear Regression Forecasting
Assignment Overview
Scenario: You are a consultant who works for the Excellent
Consulting Group. Your client, the ABC Furniture Company, believes that there
may be a relationship between the number of customers who visit the store
during any given month (“customer traffic”) and the total sales for that same
month. In other words, the greater the customer traffic, the greater the sales
for that month. To test this theory, the client has collected customer traffic
data over the past 12-month period, and monthly sales for that same 12-month
period (Year 1).
Case Assignment
Using the customer traffic data and matching sales for each
month of Year 1, create a Linear Regression (LR) equation in Excel. Use the
Excel template provided (see “Module 3 Case – LR –Year 1” spreadsheet tab), and
be sure to include your LR chart (with a trend line) where noted. Also, be sure
that you include the LR formula within your chart.
After you have developed the LR equation above, you will use
the LR equation to forecast sales for Year 2 (see the second Excel spreadsheet
tab labeled “Year 2 Forecast”). You will note that the customer has collected
customer traffic data for Year 2. Your role is to complete the sales forecast
using the LR equation from Step 1 above.
After you have forecast Year 2 sales, your Professor will
provide you with 12 months of actual sales data for Year 2. You will compare
the sales forecast with the actual sales for Year 2, noting the monthly and
average (total) variances from forecast to actual sales.
To complete the Module 3 Case, write a report for the client
that describes the process you used above, and that analyzes the results for
Year 2. (What is the difference between forecast vs. actual sales for Year 2—by
month and for the year as a whole?) Make a recommendation concerning how the LR
equation might be used by ABC Furniture Company to forecast future sales.
Data: Download the Module 3 Case template here: Data chart
for BUS520 Case 3. Use this template to complete your Excel analysis.
Assignment Expectations
Excel Analysis
Accurate and complete Linear Regression analysis in Excel.
Written Report
Length requirements: 4–5 pages minimum (not including Cover
and Reference pages). NOTE: You must submit 4–5 pages of written discussion and
analysis. This means that you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Your written (Word) analysis should discuss the logic and
rationale used to develop the LR equation and chart.
Provide complete, meaningful, and accurate recommendation(s)
concerning how the ABC Furniture Company might use the LR equation to forecast
future sales. (For example, how reliable is the LR equation in predicting
future sales?) What other recommendations do you have for the client?

















































Module 3 – SLP
LINEAR REGRESSION FORECASTING AND DECISION TREES
Decision Trees
Scenario: You are a consultant who works for the Excellent
Consulting Group. You have learned about three different investment
opportunities and need to decide which one is most lucrative. Following are the
three investment options and their probabilities:
Option A: Real Estate development. This is a risky
opportunity with the possibility of a high payoff, but also with no payoff at
all. You have reviewed all of the possible data for the outcomes in the next 10
years and these are your estimates of the cash payoff and probabilities:
Required initial investment: $0.75 million
High NPV: $5 million, Pr = 0.5
Medium NPV: $2 million, Pr = 0.3
Low NPV: $0, Pr = 0.2
Option B: Retail franchise for Just Hats, a boutique-type
store selling fashion hats for men and women. This also is a risky opportunity
but less so than Option A. It has the potential for less risk of failure, but
also a lower payoff. You have reviewed all of the possible data for the
outcomes in the next 10 years and these are your estimates of the payoffs and
probabilities:
Required initial investment: $0.55 million
High NPV: $3 million, Pr = 0.75
Medium NPV: $2 million, Pr = 0.15
Low NPV: $1 million, Pr = 0.1
Option C: High Yield Municipal Bonds. This option has low
risk and is assumed to be a Certainty. So there is only one outcome with
probability of 1.0:
Required initial investment: $0.75 million
NPV: $1.5 million, Pr = 1.0
Assignment
Develop an analysis of these three investments, and
determine which of them you should choose. Be sure to account for cash paid for
each of the three alternatives. If you do not recall how to do this, review the
practice exercises in the Background page. Do your analysis in Excel using the
Decision Tree add-in.
Write a report to your private investment company and
explain your analysis and your recommendations. Provide a rationale for your
decision.
Upload both your written report and Excel file with the decision
tree analysis to the SLP 3 Dropbox.
SLP Assignment Expectations
Analysis
Accurate and complete Excel analysis.
Written Report
Length requirements: 2–3 pages minimum (not including Cover
and Reference pages)
Provide a brief introduction to/background of the problem.
Written analysis that supports Excel analysis and provides
thorough discussion of assumptions, rationale, and logic used.
Complete, meaningful, and accurate recommendation(s).



















































Module 4 – Case
RISK: EXPONENTIAL SMOOTHING FORECASTING AND VALUE OF
INFORMATION
Risk: Simple Exponential Smoothing (SES)
Assignment Overview
Scenario: You are a consultant for the Excellent Consulting
Group (ECG). You have completed the first assignment, developing and testing a
forecasting method that uses Linear Regression (LR) techniques (Module 3 Case).
However, the consulting manager at ECG wants to try a different forecasting
method as well. Now you decide to try Single Exponential Smoothing (SES) to
forecast sales.
Case Assignment
Using this Excel template: Data chart for BUS520 Case 4, do
the following:
Calculate the MAPE for Year 2 Linear Regression forecast
(use the first spreadsheet tab labeled “Year 2 Forecast – MAPE”).
Calculate forecasted sales for Year 2 using SES (use the second
spreadsheet tab labeled “SES – MAPE”). Use 0.15 and 0.90 alphas.
Compare the MAPE calculated for the LR forecast (#1 above)
with the MAPEs calculated using SES.
Then write a report to your boss in which you discuss the
results obtained above. Using calculated MAPE values, make a recommendation
concerning which method appears to be more accurate for the Year 2 data: SES or
Linear Regression.
Assignment Expectations
Analysis
Accurate and complete SES analysis in Excel.
Written Report
Length requirements: 4–5 pages minimum (not including Cover
and Reference pages). NOTE: You must submit 4–5 pages of written discussion and
analysis. This means that you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Complete a written analysis that supports your Excel
analysis, discussing the assumptions, rationale, and logic used to complete
your SES forecast.
Give complete, meaningful, and accurate recommendation(s)
relating to whether LR or SES is more accurate in predicting sales.






































Module 4 – SLP
RISK: EXPONENTIAL SMOOTHING FORECASTING AND VALUE OF
INFORMATION
Risk: The Value of Information
Scenario: Using the same situation from the Module 3 SLP,
recall that you are deciding among three investments. You have heard of an
expert who has a highly reliable “track record” in the correct identification
of favorable vs. unfavorable market conditions. You are now considering whether
to consult this “expert.” Therefore, you need to determine whether it would be
worth paying the expert’s fee to get his prediction. You recognize that you
need to do further analysis to determine the value of the information that the
expert might provide.
In order to simplify the analysis, you have decided to look
at two possible outcomes for each alternative (instead of three). You are
interested in whether the market will be Favorable or Unfavorable, so you have
collapsed the Medium and Low outcomes. Here are the three alternatives with
their respective payoffs and probabilities.
Option A: Real estate development. This is a risky
opportunity with the possibility of a high payoff, but also with no payoff at
all. You have reviewed all of the possible data for the outcomes in the next 10
years and these are your estimates of the Net Present Value (NPV) of the
payoffs and probabilities:
High/Favorable NPV: $7.5 million, Pr = 0.5
Unfavorable NPV: $2.0 million, Pr = 0.5
Option B: Retail franchise for Just Hats, a boutique-type
store selling fashion hats for men and women. This also is a risky opportunity
but less so than Option A. It has the potential for less risk of failure, but
also a lower payoff. You have reviewed all of the possible data for the
outcomes in the next 10 years and these are your estimates of the NPV of the
payoffs and probabilities.
High/Favorable NPV: $4.5 million, Pr = 0.75
Unfavorable NPV: $2.5 million, Pr = 0.25
Option C: High Yield Municipal Bonds. This option has low
risk and is assumed to be a Certainty. So there is only one outcome with
probability of 1.0:
NPV: $2.25 million, Pr = 1.0
You have contacted the expert and received a letter stating
his track record which you have checked out using several resources. Here is
his stated track record:
True State of the Market
Expert Prediction
Favorable
Unfavorable
Predicts “Favorable”
.9
.3
Predicts “Unfavorable”
.1
.7
You realize that this situation is a bit complicated since
it requires the expert to analyze and predict the state of two different
markets: the real estate market and the retail hat market. You think through
the issues of probabilities and how to calculate the joint probabilities of
both markets going up, both going down, or one up and the other down. Based on
your original estimates of success, here are your calculations of the single
probabilities and joint probabilities of the markets.
























































Probabilities
Favorable
Unfavorable
A: Real Estate
0.50
0.50
B: Just Hats
0.75
0.25
Joint Probabilities
A Fav, B Fav (A+, B+)
0.375
A Unf, B Unf (A-, B-)
0.125
A Fav, B Unf (A+, B-)
0.125
A Unf, B Fav (A-, B+)
0.375
Finally, after a great deal of analysis and calculation, you
have determined the Posterior probabilities of Favorable and Unfavorable
Markets for the Real Estate business and the boutique hat business.
Real Estate
Just Hats























F
U
F
U
0.45
says “F/F”
0.75
0.25
0.90
0.10
0.15
says “F/U”
0.75
0.25
0.30
0.70
0.30
says “U/F”
0.125
0.875
0.90
0.10
0.10
says “U/U”
0.125
0.875
0.30
0.70
For example, this table says that there is 45% chance that
the expert will predict Favorable for both markets (F/F), and when he makes
this prediction, there is a 75% chance that the Real Estate market will be
favorable and 25% chance that it won’t, and also a 90% chance that the Hat
market will be Favorable and 10% chance it won’t.

































You have developed a Decision Tree showing the original
collapsed solution and also showing an expanded Decision Tree for evaluating
the value of the expert’s information. You need to enter the probabilities into
this tree to see if the expert’s information will increase the overall expected
value of your decision. Download the Excel file with the incomplete Decision
Tree: Decision Tree for BUS520 SLP 4
Assignment
Complete the information in the Decision Tree in the Excel
file. Determine the Expected NPV of the decision if you were to consult the
Expert. Does use of the Expert increase the value of your analysis? If so, by
how much?
Write a report to your private investment company and
explain your analysis and your recommendation. Provide clear rationale/ justification
for your decision.
Upload both your written report and Excel file with the
Decision Tree analysis to the SLP 4 Dropbox.
SLP Assignment Expectations
Analysis
Accurate and complete analysis in Excel.
Required:
Length requirements: 2–3 pages minimum (not including Cover
and Reference pages). NOTE: You must submit 2–3 pages of written discussion and
analysis. This means that you should avoid use of tables and charts as “space
fillers.”
Provide a brief introduction to/background of the problem.
Written analysis that supports Excel analysis and provides
thorough discussion of assumptions, rationale, and logic used.
Complete, meaningful, and accurate recommendation(s).




























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