MotomartDemoWord.docx

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. 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 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 “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 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.

Table 5

Column

Expense

FC

VC

R-sq

1

Salaries

$106,866

–$110

4.10%

2

Vacation

 

 

 

3

Advertising and training

 

 

 

4

Supplies/tools/laundry

 

 

 

5

Freight

 

 

 

6

Vehicles

 

 

 

7

Demonstrators

 

 

 

8

Floor planning

 

 

 

 

Computed total

 

 

 

9

Total

 

 

 

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?

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 2

SElECTED HISTORICAl INCOME STATEMENT AND RElATED MEASURES

 

1984

1985

1986

1987

1988

Net Variable Revenues*

2,885,969

3,828,255

4,086,667

3,940,799

4,298,748

Semi-Fixed (S-F) Expenses:

Salaries

 613,006

   968,789

1,211,464

1,289,758

1,360,489

Vacation

       600

     26,705

     19,468

     19,059

    18,268

Advertising & Training

210,226

   288,347

   281,219

   309,608

  371,314

Supplies/Tools/Laundry

   31,473

    46,141

     75,468

     65,935

    81,252

Freight

    5,719

     5,987

        6,528

       5,731

      4,663

Vehicle

   22,913

    23,718

      23,664

     20,370

    19,483

Demonstrators

   10,465

     4,969

        -1,513

       4,192

        707

Floor-Planning

 278,531

  301,113

    276,201

    156,129

  305,044

Total S-F Expenses

1,172,933

1,665,769

 1,892,499

1,870,782

2,161,220

Fixed Expenses:

Total Fixed Expenses

1,449,208

2,050,172

2,290,867

2,164,362

2,653,620

Operating Profit/(Loss)**

   263,828

    112,314

   -96,699

   -94,345

 -516,092

New Retail Vehicles Sold

       1,798

        1,977

       1,674

      1,450

      1,897

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. Semifixed 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).

Table 3
SEMI-FIXED (MIXED) EXPENSES FOR THE 60-MONTH PERIOD (FY 1984 THROUGH 1988)

  1

197

$  52,951

$           –

$   22,561

$    1,118

  2

133

$  47,054

$           –

$   19,040

$    3,573

  3

 132

$ 55,372

$           –

$   14,373

$    1,388

  4

 141

$ 46,114

$           –

$   15,022

$    2,894

  5

 182

$ 48,309

$           –

$   19,966

$    1,896

  6

 156

$ 49,643

$           –

$   12,019

$    1,188

  7

  196

$ 55,784

$      300

$   13,217

$    3,912

  8

 178

$ 47,957

$           –

$   17,303

$    2,012

  9

  159

$ 53,743

$           –

$   16,535

$    2,717

10

141

$ 53,109

$           –

$   23,821

$    1,102

11 

 152

$ 45,491

$      300

$   14,146

$    2,630

12

 31

$ 57,479

$           –

$   22,223

$    7,043

13

 280

$ 49,049

$           –

$   19,992

$    1,999

14 

 136

$ 46,698

$      300

$   20,251

$    1,192

15

 174

$ 59,790

$      200

$   20,082

$    1,336

16

  171

$ 80,773

$      600

$   26,716

$    3,873

17 

 167

$ 71,130

$   9,212

$   25,223

$    5,560

18

161

$ 82,490

$   6,007

$   21,106

$    1,737

19

173

$ 98,172

$      500

$   17,799

$    1,847

 20

161

$ 90,685

$   2,690

$   28,038

$    4,415

21 

 167

$ 97,771

$      600

$   37,284

$    2,827

22

153

$ 87,129

$   1,740

$   24,236

$    5,836

23 

201

$ 95,910

$   2,074

$   27,244

$    3,387

24

33

$ 09,192

$   2,782

$   20,376

$  12,132

25 

 227

$ 89,041

$   1,880

$   26,719

$    4,383

26 

 150

$ 92,165

$   3,602

$   14,727

$  10,231

27

142

$ 88,981

$      744

$   27,880

$    7,734

28

 104

$ 95,898

$      960

$   21,872

$    (684)

29 

121

$ 96,245

$           –

$   18,705

$    8,329

30

99

$ 106,364

$           –

$   23,835

$    2,540

 31

150

$ 90,564

$   1,950

$   25,605

$    5,862

32

144

$ 98,418

$   1,540

$   17,763

$    6,998

33 

154

$ 110,436

$   2,693

 32,379

$    8,131

34

130

$ 102,042

$   1,060

$   19,324

$    6,026

35 

202

$ 124,413

$   3,519

$   22,412

$    9,120

36

51

$ 116,897

$   1,520

$   29,998

$    6,798

37

148

$ 97,083

$   1,080

$   9,112

$    6,627

38 

153

$ 104,727

$   3,230

$   38,616

$    5,892

39

 83

$ 95,622

$      953

$   22,690

$    3,450

40

101

$ 96,438

$   1,244

$   14,703

$    5,259

41

140

$ 114,995

$           –

$   28,764

$    2,294

42

132

$ 105,337

$      160

$   27,253

$    8,155

43

112

$ 98,989

$   2,480

$   24,419

$    1,621

 44

127

$ 124,352

$   1,800

$   26,011

$       902

45

139

$ 115,875

$   1,417

$   24,492

$    5,158

46

156

$ 113,035

$   1,820

$   31,158

$    2,901

47

126

$ 119,106

$   3,338

$   32,213

$  14,426

48

 33

$ 104,199

$   1,537

$   30,177

$    9,250

49

209

$ 98,938

$   1,866

$   26,737

$    1,694

50 

124

$ 108,606

$   3,676

$   31,084

$    9,040

51

131

$ 106,396

$   1,197

$   33,278

$    2,099

52

144

$ 106,778

$      241

$   32,657

$    9,328

53 

 93

$ 124,805

$      500

$   29,794

$    4,268

54

199

$ 110,153

$   1,910

$   38,431

$    5,407

55

170

$ 117,276

$      800

$   27,640

$    9,305

56 

186

$ 112,055

$      980

$   28,657

$    1,803

57

200

$ 114,765

$   1,695

$   36,425

$    8,839

58

 146

$ 128,007

$   1,560

$   27,720

$  10,944

59 

222

$ 116,811

$   2,249

$   27,941

$    5,775

60

73

$ 115,899

$   1,594

$   30,950

$  30,950

Table 3 Continued
SEMI-FIXED (MIXED) EXPENSES FOR THE 60-MONTH PERIOD (FY 1984 THROUGH 1988)

  1

$     382

$   2,052

$     1,881

$   (78,173)

$     2,772

  2

$     409

$   1,405

$        695

$     28,456

$ 100,632

  3

$     742

$   1,380

$        469

$     34,423

$ 108,147

  4

$     675

$   2,057

$        125

$       5,697

$   72,584

  5

$     572

$   1,603

$        131

$     34,599

$ 107,076

  6

$     407

$   2,524

$     1,229

$     53,737

$ 120,747

  7

$     643

$   2,348

$     1,206

$       5,507

$   82,917

  8

$     605

$   1,208

$        436

$     32,436

$ 101,957

  9

$     209

$   2,400

$     1,476

$     28,950

$ 106,030

10

$     184

$   2,076

$     1,168

$     20,876

$ 102,336

11 

$     331

$   1,677

$        635

$     45,278

$ 110,488

12

$     560

$   2,183

$     1,014

$     66,745

$ 157,247

13

$     582

$   1,927

$     (477)

$   (30,104)

$   42,968

14 

$     603

$   1,156

$     1,839

$     50,583

$ 122,622

15

$     492

$   1,898

$     1,260

$     18,803

$ 103,861

16

$     559

$   1,808

$        510

$     23,080

$ 137,919

17 

$     356

$   1,816

$     2,350

$     18,774

$ 134,421

18

$     439

$   1,384

$     (288)

$     23,802

$ 136,677

19

$   1,628

$   1,962

$     1,591

$     33,848

$ 157,347

 20

$     (12)

$   2,446

$  (3,308)

$     13,480

$ 138,434

21 

$     480

$   2,296

$     1,709

$     22,965

$ 165,932

22

$       79

$   3,175

$        798

$     18,898

$ 141,891

23 

$     188

$   1,287

$   (2,025)

$     38,699

$ 166,764

24

$     593

$   2,563

$     1,010

$     68,285

$ 216,933

25 

$     769

$   2,205

$     2,493

$   (44,140)

$ 83,350

26 

$     593

$   2,289

$   (2,051)

$     36,311

$ 157,867

27

$     414

$   1,891

$        386

$     19,865

$ 147,895

28

$     425

$   2,288

$        178

$     19,013

$ 139,950

29 

$     483

$   2,223

$      (262)

$     16,228

$ 141,951

30

$     417

$   1,683

$   (1,356)

$     37,637

$ 171,120

 31

$     222

$   1,586

$        486

$     (1,121)

$ 125,154

32

$       49

$   1,751

$   (1,924)

$     34,757

$ 159,352

33 

$     818

$   2,082

$     1,547

$     26,419

$ 184,505

34

$  1,015

$   1,714

$        132

$     21,134

$   52,447

35 

$  1,255

$   2,173

$   (2,337)

$     18,578

$ 179,133

36

$       68

$   1,779

$     1,195

$     91,520

$ 249,775

37

$     565

$   1,324

$     1,164

$   (73,753)

$   43,202

38 

$     369

$   1,523

$   (1,839)

$     30,443

$ 182,961

39

$  (182)

$   2,087

$        454

$     17,725

$ 142,799

40

$     709

$   2,095

$        868

$     26,402

$ 147,718

41

$  1,006

$   1,304

$   (1,990)

$      (3,789

$ 142,584

42

$     521

$   1,667

$     1,869

$     15,090

$ 160,052

43

$     514

$   1,040

$        329

$       (945)

$ 128,447

 44

$     917

$   2,880

$   (1,897)

$     30,405

$ 185,370

45

$     (77

$   1,281

$     2,959

$     14,781

$ 165,886

46

$     450

$   2,259

$        417

$     15,613

$ 167,653

47

$     120

$   1,394

$   (2,659)

$     40,968

$ 208,906

48

$     819

$   1,516

$     4,517

$     43,189

$ 195,204

49

$     853

$   1,657

$        601

$   (20,127)

$ 112,219

50 

$     498

$   2,266

$      (284)

$     18,236

$ 173,122

51

$     605

$   1,952

$        668

$     15,176

$ 161,371

52

$     483

$   1,852

$     1,409

$     25,245

$ 177,993

53 

$     788

$   1,704

$   (1,771)

$       6,493

$ 166,581

54

$     529

$   1,882

$        453

$     21,851

$ 180,616

55

$   (180)

$   977

$     1,310

$              7

$ 157,135

56 

$    242)

$   846

$   (2,844)

$     17,192

$ 158,447

57

$     859

$   2,856

$     1,532

$     14,864

$ 181,835

58

$  (492)

$   1,864

$     1,400

$     10,121

$ 181,124

59 

$    245

$   1,141

$   (3,513)

$       7,946

$ 158,595

60

$    717

$   486

$     1,746

$   188,040

$ 352,182

Recall the cost function applying to the high-low and regression methods, which are provided in a variety of forms, depending on the …