Senior capstone business Motomart.

The Motomart case is designed to supplement your Managerial/ Cost Accounting textbookcoverage of cost behavior and variable costing using real-world cost data and an auto-industry
accepted cost driver. Unlike textbook problems, this data is real. It won’t necessarily produce a
clear solution when you attempt to analyze cost behavior and apply scatter-plot, high-low, and
regression methods to separate mixed costs into their fixed and variable components. This case
also illustrates that Financial Accounting decisions and methods can have an influence on Cost
Accounting and Managerial applications and decisions.
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Summarize your findings in the motomart case
Your project must be submitted as a Word document (.docx, .doc)*.
This case is based on real financial data provided by a retail automobile dealership (Motomart)
seeking to relocate closer to an existing retail dealership. You’ll examine the mixed cost data
from Motomart and apply both high-low and regression to attempt to separate mixed costs into
their fixed and variable components for break-even and contribution margin computations.
You’ll find that the data is flawed because Motomart was a single observation in a larger
database. Don’t attempt to correct the data (e.g., remove outliers or influential outliers). You’ll
be producing a scatterplot and apply high-low and regression methods to the extent practicable
and writing a summary report of the findings.
Motomart operates a retail automobile dealership. The manufacturer of Motomart products, like
all automobile manufacturers, produces forecasts. It has long been an industry practice to use
variable costing-based/break-even analyses as the foundation for these forecasts, to examine their
cost behavior as it relates to the new retail vehicles sold (NRVS) cost driver. In preparing this
financial information, a common financial statement format and accounting procedures manual
are provided to each retail auto dealership. The dealership is required to produce monthly
financial statements using the guidelines provided by this common accounting procedures
manual, and then furnish these financial statements to the manufacturer. General Motors, Ford,
Nissan, and all other automobile manufacturers employ similar procedures manuals.
The use of a common format facilitates the development of composite financial statements that
can be used to estimate costs and produce financial forecasts for future or proposed retail
dealership sites (Cataldo and Kruck 1998). Zimmerman (2003) suggests that as many as 77
percents of manufacturers divide costs into variable and fixed components and that managers
arrive at these estimates by classifying individual accounts as being primarily fixed or primarily
variable (67).
For this case, you’ll examine mixed costs as defined by the manufacturer. Using the scatterplot,
high-low, and regression methods, separate these mixed costs into their fixed and variable
components. The data is problematic, and a clear solution won’t exist. Don’t attempt to correct
the data by removing outliers, but make observations based on any patterns you observe. The
case will expose you to actual data and require you to summarize your findings, including any
conclusions you’re able to reach and why the financial data makes it impossible to separate the
mixed costs into their fixed and variable components.
Motomart: A Litigation Support Engagement
The Motomart case evolved from a litigation support engagement. The lead author of this case
was hired to analyze the data and provide expert testimony. His report and testimony was made
available to the public (for a fee to cover reproduction costs). A broad description of the relevant
points for the Motomart case follows.
Motomart wanted to move their retail automobile dealership, blaming their location for declining
profits and increasing losses. They provided financial projections, using variable costing, to
show that after the relocation both Motomart and the existing dealership would be profitable.
They created these financial projections using a database provided by the manufacturer, which
included all North American retail automobile dealerships. Motomart was one of the
observations or retail automobile dealerships included in the database used to create these
financial projections. You’ll be examining portions of Motomart’s historical financial data.
The relocation site was quite close to the existing dealership (which we’ll refer to as Existing
Dealer), and Existing Dealer felt that, if the relocation was permitted, one or both of the
dealerships would fail to break even and eventually go bankrupt, leading to poor service, or what
the industry refers to as “orphaned” owners of these automobiles.
Antitrust laws provided Existing Dealer with the means to block the relocation requested by
Motomart, but only if it could prove that the relocation wasn’t in the best interest of the
consuming public. Generally, the only way to prove this is to prove that there’s simply not
enough business for both retail automobile dealerships to break even (or generate a reasonable
return on investment, given the risks associated with the industry). Again, the manufacturer, in
support of the proposed Motomart relocation, supplied financial projections showing that both
retail automobile dealerships would be profitable after the relocation.
The expert witness hired to investigate the merits of the relocation was given the Motomart data,
but not the entire database that included the Motomart data. The Motomart data was in such poor
form that it wasn’t possible to produce a financial forecast. An alternative forecast, not included
in this case, was produced. This alternative forecast did not support the relocation of Motomart
to a site closer to Existing Dealer. The alternative forecast showed that the market simply
couldn’t support two retail automobile dealerships. The implication was that, as the weaker of
the two dealerships, Motomart was losing business to Existing Dealer. In conclusion, the
relocation request by Motomart was denied.
Income and Expense Data
The following tables give you information such as income statements, semi-fixed expenses, and
salaries for Motomart. Look for unusual entries or discrepancies in their records and, where you
can, note the cause of the problems.
Table 3 summarizes financial and cost driver information produced by Motomart, where new
retail vehicles sold (NRVS) is the cost driver. The account classification method has resulted in
three cost behavior classifications: variable, semi-fixed, and fixed costs. Semi-fixed is the
automobile industry-specific term used for mixed costs. We’ll assume that Motomart’s
classifications of variable costs (VCs) and fixed costs (FCs) are correct, and focus our analysis
on Motomart’s semi-fixed or mixed costs.
Table 3 provides five years of monthly data (N=60) for NRVS and the related semi-fixed or
mixed cost measures. Semifixed costs were significant. Recall that they ranged from nearly $1.2
million for calendar and fiscal year (FY) 2014 to almost $2.2 million for FY 2018 (see Table 2).
Recall the cost function applying to the high-low and regression methods, which are provided in
a variety of forms, depending on the texts you used in your previous math, economics, or
accounting courses. Below is a brief outline of the high-low and regression methods.
Preparing Graphs
The single cost driver and nonfinancial measure in Table 3 is new retail vehicles sold (NRVS or
X in the above cost function). There are eight financial measures (salary; vacation; advertising
and training; supplies, tools, and laundry; freight; vehicles; demonstrators; and floor-planning
[also known in the automobile retail industry as interest expense relating to new car inventory]),
as well as a total (aggregate measure) provided for all eight financial measures (or the Y in the
above cost function).
Using NRVS, the only available cost-driver, use Excel to prepare nine separate scatter plots and
cost function-based trend lines and nine separate line graphs for each of the financial measures
provided in Table 3. The images below are an example of completed graphs for salaries.
Now examine, on a preliminary basis, the pattern or trend (or lack thereof) for each of the “X”
(NRVS) and “Y” (financial measure) data pairs and consider the following questions:
You’re observing these data pairs for a 60-month period (i.e., five years); are any annual
or other seasonal patterns or trends immediately apparent?
• Do the slopes of the trend lines (i.e., variable costs) make sense?
In the case of salaries (see the graphs above), there’s no apparent trend or pattern. It’s odd that
salaries decrease as NRVS increases—in fact, this doesn’t make any sense. However, it’s
consistent with the high-low results, which also didn’t make sense. But remember, since this data
came from Motomart, the firm attempting to relocate, it’s real and from an actual litigation
support engagement (not a textbook problem), so it won’t necessarily work out perfectly.
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The cost equation in Table 4 shows fixed costs (FC) at $106,866.00 and variable costs to be used
to “reduce” total costs (TC) by $110.10 per NRVS. Compare the salary figures and coefficients
(in bold type) to the scatterplot graph for Motomart Salaries. Notice that if you extended the
trend line in Figure 4, it would hit the y-axis intercept at $106,866.00 (the fixed cost). Also,
notice that the R-squared (R-sq) measure in Table 4 equals 4.1 percent.
Your math and statistics courses probably reviewed the use of the t-statistic, overall F-statistic,
and related p-values, as well as some of the other measures presented here. Our application is a
very simple one, so we’ll focus on only the R-squared measure. The other measures are provided
in this example only for completeness.
Because the high-low technique didn’t work, it makes sense that the regression technique
wouldn’t work well, either. Therefore, the results for high-low and regression are consistent. The
advantage of the regression technique is that it mathematically quantifies the level of the problem
or difficulty with the data. In this case, one of simple regression, the R-squared measure tells the
story. Still focusing on the salaries example in Figure 5, the R-squared measure tells us that only
4.1 percent of the total or mixed or semi-fixed cost is explained by NRVS. This means that that
cost equation developed from this historical data isn’t helpful in predicting future costs, as nearly
96 percent of the cost behavior, through use of this equation, remains unexplained.
Requirements
The project requires five steps to be presented.
Step 1 – Provide comments on a 5-year Income Statement.
Step 2 – Discuss patterns in expense items.
Step 3 – Identify High/Low activity levels.
Step 4 – Compute cost equations.
Step 5 – Summarize your findings.
In one Word document, provide individual sections for each Step. This Word document along
with the Excel file (described below).
This Senior Capstone project highlights your knowledge and the skills you have developed over
the course of your education. There is nothing “new” to be learned here.
The knowledge and skills required for this project include English Composition, Financial
Accounting, Managerial Accounting, Business Statistics and the abilities to think critically and to
present your work in a professional manner.
If you are unsure or don’t understand something about the project, then go back to your previous
subjects to review. For example, if you don’t remember how to use the High/Low Method, the
revisit your Managerial Accounting to refresh your memory on how to use the High/Low
Method
Remember, there is nothing “new” here. Everything about this project you should already know
how to do.
At the beginning of the assignment, on the right-hand side under “Optional Study Materials”
select the “PPMC Excel Spreadsheet” menu item to download the required Excel spreadsheet.
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The Excel file provides a detailed example of what needs to be done for one of the
expenses in order to fill out the figures required in Steps 3 & 4. You will include this
Excel file as part of your project submission along with the Word document you create to
present this project.
o There is a “60 Months” worksheet that has the 60 months of data already entered.
There is also a “Sample” worksheet that an example of how to calculate the R-sq.
o There is a “PLOT – SALARY” worksheet that shows how the FC, VC and R-sq
figures are calculated for Salary.
o There is also a “high&low” worksheet for help with the high/low method in Step
3.
o Complete and include the Excel spreadsheet. You will need to create new
worksheets for each of the other expenses following the example to calculate the
figures needed for Table 5.
Operating Profits and Semi-Fixed Expenses
Step 1
First, using Tables 2–4, note the pattern of operating profits (or losses) over the five-year period.
Then focus only on the semi-fixed expenses contained in Table 2. Do any amounts appear to be
odd? (Think about whether the figures are right or wrong. What is it about the individual
numbers that is not “right”?) Next, briefly comment on the five-year pattern or trend for
operating profit/loss measures. You should be able to respond to this step in a few well-written
sentences.
Step 2
Focus only on the detailed semi-fixed expense contained in Table 3. Are there any unusual or
odd patterns you might note in this detailed financial data? There are 5 expenses that have an
oddity about them which doesn’t make sense. Similar to Step 1, what is it about the individual
numbers that are not “right”? There are 4 expenses that “stick out” as not being correct and one
that has an unusual pattern. You should be able to respond to this requirement in a few wellwritten sentences. Briefly comment on only the most obvious or apparent measures or patterns,
by expense item.
Step 3
Identify the high and low measures in each column, just as you would in preparation for the
application of the high-low method or technique. For example, in Table 3 the high measure for
the cost driver (NRVS) is 280 NRVS in month 13 and the low measure is 31 NRVS in month 12.
Repeat this process for each of the eight separate semi-fixed expense columns and also for the
total expense column. Insert a table for Step 3 to present your findings. The table should have
three columns;
1. Expense
2. High Figure
3. Low Figure
After the high and low measures have been identified in each column, try to match each expense
column’s high and low measure, separately, to the highs and lows identified in the NRVS
column. They won’t match. Don’t try to correct the data, but comment on the potential for
application of the high-low technique. What happens when the high and low activity level
doesn’t match the high and low expense measure? Does this prevent you from correctly applying
the high-low technique?
Don’t overanalyze this data, because there’s a problem with it and you don’t have sufficient
information to correct it. Merely summarize your observations and unsuccessful attempts to
match the high and low NRVS months (identified above), separately, with each of the high and
low expense measure months. You should be able to do this in a very few well-written sentences.
Step 4
Using the Excel file ” – Motomart Excel Spreadsheet” as per the instructions found above under
the “Project Requirements”, reproduce and complete the following Table 5 and answer the four
questions. The Excel file provides an example of how to arrive at the figures that need to be
entered into the Table. You will create new worksheets for each of the remaining expenses. Do
the work to arrive at the figures for each expense. Be sure to include the Excel file as part of your
submission to “backup” the data presented in the Table in the Word document being submitted.
The Excel spreadsheet, while it will be included in your submission for the project, will not be
graded. It is supporting documentation for what is being presented in the Word document. Only
the information that is in the Word document will be graded.
The FC and VC should be rounded to the nearest dollar. The R-sq is a percentage figure carried
out to 2 decimal places.
Complete the cost equations for the table. Use the R-squared as the single measure of “goodness
of fit.” Don’t attempt to improve your results with the elimination of “outliers” or “influential
outliers.” As you complete Table 5, answer the following questions:
1. What problems did you encounter?
2. Are the R-squared measures high or low?
3. Are the slopes negative or positive?
4. Are your conclusions consistent with those from the high-low effort?
Step 5
Summarize your findings by answering the following questions:
1. Can the Motomart data be used to prepare a reliable financial forecast? Why or why not?
2. If Motomart is included in the very large database used to prepare the financial forecast
that supports the relocation of Motomart closer to Existing Dealer, what concerns might
present themselves with respect to the remainder of the database used for this forecast?
3. Would you rely on this forecast?
Writing Guidelines
Refer to the “Submitting Your Work” section at the end of this book for details on submission
requirements for the Motomart Case assignment.
Grading Criteria
Your assignment will be evaluated according to the following criteria:
Content
80 percent
Written Communication
10 percent
Format
10 percent
Criteria
Content 80 pts
Step 1 – Provides comments on 5-year income statement (worth 10 points)
Step 2 – Discuss patterns in expense items (worth 10 points)
Step 3 – Identify high and low activity levels (worth 10 points)
Step 4 – Compute cost equations (worth 30 points)
Step 5 – Summarize your findings (worth 20 points)
Written Communication 10 pts
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Answers each question in complete sentences leading to well-structured responses to
each Step listed above.
• Uses correct grammar, spelling, punctuation, and sentence structure
• Provides clear organization by using words like first, however, on the other hand, and
so on, consequently, since, next, and when
• Makes sure the paper contains no typographical errors
Format 10 pts The paper is double-spaced, typed in font size 12.
Grade
1. Type your submission, double-spaced, in a standard print font, size 12. Use a standard
document format with 1-inch margins. (Do not use any fancy or cursive fonts.)
2. Read the assignments carefully and complete each one in the order given.
3. Be specific. Limit your submission to the questions asked and issues mentioned.
4. If you include quotes or ideas from textbooks or other sources, provide a reference page
in either APA or MLA style. On this page, list books, Web sites, journals, or any other
references used in preparing the paper.
5. Proofread your work carefully. Check for correct spelling, grammar, punctuation, and
capitalization.
Motomart Excel Spreadsheet
Click the link to download the Motomart Excel Spreadsheet
Motomart Excel Spreadsheet