Case: 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 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.

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

REQUIREMENTS

Operating Profits and Semi-Fixed Expenses

Step 1
First, using Tables 3-5, note the pattern of operating profits (or losses) over the five-year period. Then focus only on the semi-fixed expenses contained in Table 3. Do any amounts appear to be odd? 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 4. Are there any unusual or odd patterns you might note in this detailed financial data? There are eight expense items. About five of the eight should immediately catch your 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 4 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. (You could transfer the figures to Excel to use the maximum and minimum functions to assist you in identifying the high and low measures [N=60] for each of the ten columns.)

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.

Finally, summarize your findings with respect to the application of the high-low method to separate mixed costs into their fixed and variable components or the development of a cost equation.

Step 4

Use Table 6 to compute the cost equations and R-squared measures for each of the remaining eight expenses and total expenses. Notice that there's a computed total requirement in the table. This just means that you must total these two columns and compare the computed totals to the Excel- generated measures in the row below. In effect, you're being asked to comment on whether the separate cost formulas are "additive."

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 6, answer the fol- lowing 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 on a single page (250 words or less, double-spaced). Can the Motomart data be used to prepare a reliable financial forecast? Why or why not? 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 them- selves with respect to the remainder of the database used for this forecast? Would you rely on this forecast?

It's common for businesses to keep poor financial records most of the year, because many are trying to reduce the cost of financial record keeping (e.g., the salary of a CPA is higher than that of a bookkeeper). Then, at the year's end, these businesses employ a CPA or accounting firm to make adjust- ing journal entries to correct data for the twelfth months of the year, only to reverse the adjusting journal entries immediately after the annual financials are prepared.

Examine your graphics to identify any seasonal (12-month) patterns. Do any exist? Is there evidence to suggest that the process described above was being employed by Motomart?

Attachment:- Case - Motomart.pdf