Motomart's Income Statement, Patterns in Expense Items, and the High/Low Activity Levels

Motomart

INTRODUCTION

The Motomart case is designed to supplement your Managerial/ Cost Accounting textbook coverage 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 scatterplot, 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.

OBJECTIVES

When you complete this case, you’ll be able to

• Explain the importance of accrual accounting and proper application of the matching principle for the computation of contribution margins and break-even points


• Apply knowledge of generally accepted accounting principles (GAAP) to a specific real-world example


• Integrate statistical analyses and scatter plots, line graphs, and regression to determine the reliability of financial information prepared for external use


• Use analytical review procedures to examine a firm’s financial statements


• Apply critical-thinking skills to real-world business circumstances

CASE BACKGROUND

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 is 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 percent of manufactur- ers 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

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Notes:

* Revenues less variable costs equal Net Variable Revenues (or Contribution Margin, in aggregate).

** Net Variable Revenue less Total S-F Expenses less Total Fixed Expenses equals Operating Profit/(Loss).

Table 3 provides five years of monthly data (N=60) for NRVS and the related semi-fixed or mixed cost measures. Semi- fixed costs were significant. Recall that they ranged from nearly $1.2 million for calendar and fiscal year (FY) 1984 to almost $2.2 million for FY 1988 (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. Figure 3 is a brief outline of the high-low and regression methods.

FIGURE 3—For the high-low method to work, the $H and #H and the $L and #L measures must be from the same accounting period.

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 auto- mobile 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. See Figure 4 and Figure 5 for a examples of completed graphs for salaries.

FIGURE 4—A Scatterplot Graph for Motomart 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?

FIGURE 5—A Line Graph for Motomart Salaries

In the case of salaries (see Figures 4 and 5), there’s no appar- ent 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.

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 Figure 4. 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) will be uploaded when you click on the Take Exam button on your Student Portal to submit your project (described under “Submitting Your Assignment” later in the instructions).

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.

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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 is not “right”? There are 4 expenses that “stick out” as not being correct and one that has an unusual pattern. attention. You should be able to respond to this requirement in a few well-written 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 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.

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Step 4

Using the Excel file “Exam 500896 - 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 pro- vides 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 spread sheet, while it will be included in your sub- mission 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.

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