Managerial Accounting

 

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.

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.) 38 Senior Capstone: Business 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 over analyze 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.” Senior Capstone: Business 39 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 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 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 themselves with respect to the remainder of the database used for this forecast? Would you rely on this forecast? Table 6 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 40 Senior Capstone: Business 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 adjusting 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?

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

Plot-Salary

MONTH NRVS (X) SALARY (Y) XY X squared Y squared VACATION ADV/TRNG SPLY/LNDRY FREIGHT VEHICLES DEMO'S FLOOR-PLAN TOTAL NRVS 249
1 197 197 52,951 52,951 10,431,347 38,809 2,803,808,401 – 0 22,561 1,118 382 2,052 1,881 (78,173) 2,814,334,280 SALARIES 82,516 A-fixed cost
2 133 133 47,054 47,054 6,258,182 17,689 2,214,078,916 – 0 19,040 3,573 409 1,405 695 28,456 2,220,502,473 VC/UNIT 331.39 B-variable cost
3 132 132 55,372 55,372 7,309,104 17,424 3,066,058,384 – 0 14,373 1,388 742 1,380 469 34,423 3,073,548,431 TOTAL-HIGH 35,217.92
4 141 141 46,114 46,114 6,502,074 19,881 2,126,500,996 – 0 15,022 2,894 675 2,057 125 5,697 2,133,141,649 TOTAL-LOW 35,217.92
5 182 182 48,309 48,309 8,792,238 33,124 2,333,759,481 – 0 19,966 1,896 572 1,603 131 34,599 2,342,740,228
6 156 156 49,643 49,643 7,744,308 24,336 2,464,427,449 – 0 12,019 1,188 407 2,524 1,229 53,737 2,472,366,483 VACATION
7 196 196 55,784 55,784 10,933,664 38,416 3,111,854,656 300 13,217 3,912 643 2,348 1,206 5,507 3,122,965,437
8 178 178 47,957 47,957 8,536,346 31,684 2,299,873,849 – 0 17,303 2,012 605 1,208 436 32,436 2,308,591,793
9 159 159 53,743 53,743 8,545,137 25,281 2,888,310,049 – 0 16,535 2,717 209 2,400 1,476 28,950 2,897,040,240
10 141 141 53,109 53,109 7,488,369 19,881 2,820,565,881 – 0 23,821 1,102 184 2,076 1,168 20,876 2,828,229,576
11 152 152 45,491 45,491 6,914,632 23,104 2,069,431,081 300 14,146 2,630 331 1,677 635 45,278 2,076,524,796
12 31 31 57,479 57,479 1,781,849 961 3,303,835,441 – 0 22,223 7,043 560 2,183 1,014 66,745 3,305,832,977
13 280 280 49,049 49,049 13,733,720 78,400 2,405,804,401 – 0 19,992 1,999 582 1,927 (477) (30,104) 2,419,708,538
14 136 136 46,698 46,698 6,350,928 18,496 2,180,703,204 300 20,251 1,192 603 1,156 1,839 50,583 2,187,241,948
15 174 174 59,790 59,790 10,403,460 30,276 3,574,844,100 200 20,082 1,336 492 1,898 1,260 18,803 3,585,441,487
16 171 171 80,773 80,773 13,812,183 29,241 6,524,277,529 600 26,716 3,873 559 1,808 510 23,080 6,538,337,645
17 167 167 71,130 71,130 11,878,710 27,889 5,059,476,900 9,212 25,223 5,560 356 1,816 2,350 18,774 5,071,589,050
18 161 161 82,490 82,490 13,280,890 25,921 6,804,600,100 6,007 21,106 1,737 439 1,384 (288) 23,802 6,818,126,078
19 173 173 98,172 98,172 16,983,756 29,929 9,637,741,584 500 17,799 1,847 1,628 1,962 1,591 33,848 9,655,010,788
20 161 161 90,685 90,685 14,600,285 25,921 8,223,769,225 2,690 28,038 4,415 (12) 2,446 (3,308) 13,480 8,238,624,550
21 167 167 97,771 97,771 16,327,757 27,889 9,559,168,441 600 37,284 2,827 480 2,296 1,709 22,965 9,575,787,790
22 153 153 87,129 87,129 13,330,737 23,409 7,591,462,641 1,740 24,236 5,836 79 3,175 798 18,898 7,605,045,807
23 201 201 95,910 95,910 19,277,910 40,401 9,198,728,100 2,074 27,244 3,387 188 1,287 (2,025) 38,699 9,218,309,085
24 33 33 109,192 109,192 3,603,336 1,089 11,922,892,864 2,782 20,376 12,132 593 2,563 1,010 68,285 11,926,823,414
25 227 227 89,041 89,041 20,212,307 51,529 7,928,299,681 1,880 26,719 4,383 769 2,205 2,493 (44,140) 7,948,735,908
26 150 150 92,165 92,165 13,824,750 22,500 8,494,387,225 3,602 14,727 10,231 593 2,289 (2,051) 36,311 8,508,484,507
27 142 142 88,981 88,981 12,635,302 20,164 7,917,618,361 744 27,880 7,734 414 1,891 386 19,865 7,930,510,703
28 104 104 95,898 95,898 9,973,392 10,816 9,196,426,404 960 21,872 (684) 425 2,288 178 19,013 9,206,646,460
29 121 121 96,245 96,245 11,645,645 14,641 9,263,100,025 – 0 18,705 8,329 483 2,223 (262) 16,228 9,274,998,507
30 99 99 106,364 106,364 10,530,036 9,801 11,313,300,496 – 0 23,835 2,540 417 1,683 (1,356) 37,637 11,324,117,817
31 150 150 90,564 90,564 13,584,600 22,500 8,201,838,096 1,950 25,605 5,862 222 1,586 486 (1,121) 8,215,660,914
32 144 144 98,418 98,418 14,172,192 20,736 9,686,102,724 1,540 17,763 6,998 49 1,751 (1,924) 34,757 9,700,553,422
33 154 154 110,436 110,436 17,007,144 23,716 12,196,110,096 2,693 32,379 8,131 818 2,082 1,547 26,419 12,213,435,897
34 130 130 102,042 102,042 13,265,460 16,900 10,412,569,764 1,060 19,324 6,026 1,015 1,714 132 21,134 10,426,106,613
35 202 202 124,413 124,413 25,131,426 40,804 15,478,594,569 3,519 22,412 9,120 1,255 2,173 (2,337) 18,578 15,504,070,345
36 51 51 116,897 116,897 5,961,747 2,601 13,664,908,609 1,520 29,998 6,798 68 1,779 1,195 91,520 13,671,239,629
37 148 148 97,083 97,083 14,368,284 21,904 9,425,108,889 1,080 9,112 6,627 565 1,324 1,164 (73,753) 9,439,639,362
38 153 153 104,727 104,727 16,023,231 23,409 10,967,744,529 3,230 38,616 5,892 369 1,523 (1,839) 30,443 10,984,078,857
39 83 83 95,622 95,622 7,936,626 6,889 9,143,566,884 953 22,690 3,450 (182) 2,087 454 17,725 9,151,748,820
40 101 101 96,438 96,438 9,740,238 10,201 9,300,287,844 1,244 14,703 5,259 709 2,095 868 26,402 9,310,282,439
41 140 140 114,995 114,995 16,099,300 19,600 13,223,850,025 – 0 28,764 2,294 1,006 1,304 (1,990) (3,789) 13,240,226,504
42 132 132 105,337 105,337 13,904,484 17,424 11,095,883,569 160 27,253 8,155 521 1,667 1,869 15,090 11,110,070,866
43 112 112 98,989 98,989 11,086,768 12,544 9,798,822,121 2,480 24,419 1,621 514 1,040 329 (945) 9,810,148,869
44 127 127 124,352 124,352 15,792,704 16,129 15,463,419,904 1,800 26,011 902 917 2,880 (1,897) 30,405 15,479,538,459
45 139 139 115,875 115,875 16,106,625 19,321 13,427,015,625 1,417 24,492 5,158 (77) 1,281 2,959 14,781 13,443,423,332
46 156 156 113,035 113,035 17,633,460 24,336 12,776,911,225 1,820 31,158 2,901 450 2,259 417 15,613 12,794,849,709
47 126 126 119,106 119,106 15,007,356 15,876 14,186,239,236 3,338 32,213 14,426 120 1,394 (2,659) 40,968 14,201,590,480
48 33 33 104,199 104,199 3,438,567 1,089 10,857,431,601 1,537 30,177 9,250 819 1,516 4,517 43,189 10,861,170,660
49 209 209 98,938 98,938 20,678,042 43,681 9,788,727,844 1,866 26,737 1,694 853 1,657 601 (20,127) 9,809,660,724
50 124 124 108,606 108,606 13,467,144 15,376 11,795,263,236 3,676 31,084 9,040 498 2,266 (284) 18,236 11,809,027,484
51 131 131 106,396 106,396 13,937,876 17,161 11,320,108,816 1,197 33,278 2,099 605 1,952 668 15,176 11,334,331,620
52 144 144 106,778 106,778 15,376,032 20,736 11,401,541,284 241 32,657 9,328 483 1,852 1,409 25,245 11,417,222,823
53 93 93 124,805 124,805 11,606,865 8,649 15,576,288,025 500 29,794 4,268 788 1,704 (1,771) 6,493 15,588,194,925
54 199 199 110,153 110,153 21,920,447 39,601 12,133,683,409 1,910 38,431 5,407 529 1,882 453 21,851 12,155,934,226
55 170 170 117,276 117,276 19,936,920 28,900 13,753,660,176 800 27,640 9,305 (180) 977 1,310 7 13,773,900,407
56 186 186 112,055 112,055 20,842,230 34,596 12,556,323,025 980 28,657 1,803 (242) 846 (2,844) 17,192 12,577,470,353
57 200 200 114,765 114,765 22,953,000 40,000 13,171,005,225 1,695 36,425 8,839 859 2,856 1,532 14,864 13,194,294,825
58 146 146 128,007 128,007 18,689,022 21,316 16,385,792,049 1,560 27,720 10,944 (492) 1,864 1,400 10,121 16,404,811,518
59 222 222 116,811 116,811 25,932,042 49,284 13,644,809,721 2,249 27,941 5,775 245 1,141 (3,513) 7,946 13,671,066,453
60 73 73 115,899 115,899 8,460,627 5,329 13,432,578,201 1,594 30,950 12,750 717 486 1,746 188,040 13,441,512,238
1830 8796 5,443,506 783,702,813 1,419,510 532,565,292,186 84,100 1,460,714 300,269 28,628 110,148 18,820 1,317,018 533,364,621,218
a= 833,661,258,912 106,866 FIXED COST
7800984
b= (858,909,996) (110.10) VARIABLE COST
7800984
r= (858,909,996) (0.20)
1.8115132686567E+19
4256187576.52514
R sq= 0.041 R-squared

SALARY (Y)

197 133 132 141 182 156 196 178 159 141 152 31 280 136 174 171 167 161 173 161 167 153 201 33 227 150 142 104 121 99 150 144 154 130 202 51 148 153 83 101 140 132 112 127 139 156 126 33 209 124 131 144 93 199 170 186 200 146 222 73 52951 47054 55372 46114 48309 49643 55784 47957 53743 53109 45491 57479 49049 46698 59790 80773 71130 82490 98172 90685 97771 87129 95910 109192 89041 92165 88981 95898 96245 106364 90564 98418 110436 102042 124413 116897 97083 104727 95622 96438 114995 105337 98989 124352 115875 113035 119106 104199 98938 108606 106396 106778 124805 110153 117276 112055 114765 128007 116811 115899

NRVS (X) 197 133 132 141 182 156 196 178 159 141 152 31 280 136 174 171 167 161 173 161 167 153 201 33 227 150 142 104 121 99 150 144 154 130 202 51 148 153 83 101 140 132 112 127 139 156 126 33 209 124 131 144 93 199 170 186 200 146 222 73 197 133 132 141 182 156 196 178 159 141 152 31 280 136 174 171 167 161 173 161 167 153 201 33 227 150 142 104 121 99 150 144 154 130 202 51 148 153 83 101 140 132 112 127 139 156 126 33 209 124 131 144 93 199 170 186 200 146 222 73 SALARY (Y)

52951 47054 55372 46114 48309 49643 55784 47957 53743 53109 45491 57479 49049 46698 59790 80773 71130 82490 98172 90685 97771 87129 95910 109192 89041 92165 88981 95898 96245 106364 90564 98418 110436 102042 124413 116897 97083 104727 95622 96438 114995 105337 98989 124352 115875 113035 119106 104199 98938 108606 106396 106778 124805 110153 117276 112055 114765 128007 116811 115899

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60 Months

MONTH NRVS SALARY VACATION ADV/TRNG SPLY/LNDRY FREIGHT VEHICLES DEMO'S FLOOR-PLAN TOTAL
1 197 52,951 – 0 22,561 1,118 382 2,052 1,881 (78,173) 2,772
2 133 47,054 – 0 19,040 3,573 409 1,405 695 28,456 100,632
3 132 55,372 – 0 14,373 1,388 742 1,380 469 34,423 108,147
4 141 46,114 – 0 15,022 2,894 675 2,057 125 5,697 72,584
5 182 48,309 – 0 19,966 1,896 572 1,603 131 34,599 107,076
6 156 49,643 – 0 12,019 1,188 407 2,524 1,229 53,737 120,747
7 196 55,784 300 13,217 3,912 643 2,348 1,206 5,507 82,917
8 178 47,957 – 0 17,303 2,012 605 1,208 436 32,436 101,957
9 159 53,743 – 0 16,535 2,717 209 2,400 1,476 28,950 106,030
10 141 53,109 – 0 23,821 1,102 184 2,076 1,168 20,876 102,336
11 152 45,491 300 14,146 2,630 331 1,677 635 45,278 110,488
12 31 57,479 – 0 22,223 7,043 560 2,183 1,014 66,745 157,247
13 280 49,049 – 0 19,992 1,999 582 1,927 (477) (30,104) 42,968
14 136 46,698 300 20,251 1,192 603 1,156 1,839 50,583 122,622
15 174 59,790 200 20,082 1,336 492 1,898 1,260 18,803 103,861
16 171 80,773 600 26,716 3,873 559 1,808 510 23,080 137,919
17 167 71,130 9,212 25,223 5,560 356 1,816 2,350 18,774 134,421
18 161 82,490 6,007 21,106 1,737 439 1,384 (288) 23,802 136,677
19 173 98,172 500 17,799 1,847 1,628 1,962 1,591 33,848 157,347
20 161 90,685 2,690 28,038 4,415 (12) 2,446 (3,308) 13,480 138,434
21 167 97,771 600 37,284 2,827 480 2,296 1,709 22,965 165,932
22 153 87,129 1,740 24,236 5,836 79 3,175 798 18,898 141,891
23 201 95,910 2,074 27,244 3,387 188 1,287 (2,025) 38,699 166,764
24 33 109,192 2,782 20,376 12,132 593 2,563 1,010 68,285 216,933
25 227 89,041 1,880 26,719 4,383 769 2,205 2,493 (44,140) 83,350
26 150 92,165 3,602 14,727 10,231 593 2,289 (2,051) 36,311 157,867
27 142 88,981 744 27,880 7,734 414 1,891 386 19,865 147,895
28 104 95,898 960 21,872 (684) 425 2,288 178 19,013 139,950
29 121 96,245 – 0 18,705 8,329 483 2,223 (262) 16,228 141,951
30 99 106,364 – 0 23,835 2,540 417 1,683 (1,356) 37,637 171,120
31 150 90,564 1,950 25,605 5,862 222 1,586 486 (1,121) 125,154
32 144 98,418 1,540 17,763 6,998 49 1,751 (1,924) 34,757 159,352
33 154 110,436 2,693 32,379 8,131 818 2,082 1,547 26,419 184,505
34 130 102,042 1,060 19,324 6,026 1,015 1,714 132 21,134 152,447
35 202 124,413 3,519 22,412 9,120 1,255 2,173 (2,337) 18,578 179,133
36 51 116,897 1,520 29,998 6,798 68 1,779 1,195 91,520 249,775
37 148 97,083 1,080 9,112 6,627 565 1,324 1,164 (73,753) 43,202
38 153 104,727 3,230 38,616 5,892 369 1,523 (1,839) 30,443 182,961
39 83 95,622 953 22,690 3,450 (182) 2,087 454 17,725 142,799
40 101 96,438 1,244 14,703 5,259 709 2,095 868 26,402 147,718
41 140 114,995 – 0 28,764 2,294 1,006 1,304 (1,990) (3,789) 142,584
42 132 105,337 160 27,253 8,155 521 1,667 1,869 15,090 160,052
43 112 98,989 2,480 24,419 1,621 514 1,040 329 (945) 128,447
44 127 124,352 1,800 26,011 902 917 2,880 (1,897) 30,405 185,370
45 139 115,875 1,417 24,492 5,158 (77) 1,281 2,959 14,781 165,886
46 156 113,035 1,820 31,158 2,901 450 2,259 417 15,613 167,653
47 126 119,106 3,338 32,213 14,426 120 1,394 (2,659) 40,968 208,906
48 33 104,199 1,537 30,177 9,250 819 1,516 4,517 43,189 195,204
49 209 98,938 1,866 26,737 1,694 853 1,657 601 (20,127) 112,219
50 124 108,606 3,676 31,084 9,040 498 2,266 (284) 18,236 173,122
51 131 106,396 1,197 33,278 2,099 605 1,952 668 15,176 161,371
52 144 106,778 241 32,657 9,328 483 1,852 1,409 25,245 177,993
53 93 124,805 500 29,794 4,268 788 1,704 (1,771) 6,493 166,581
54 199 110,153 1,910 38,431 5,407 529 1,882 453 21,851 180,616
55 170 117,276 800 27,640 9,305 (180) 977 1,310 7 157,135
56 186 112,055 980 28,657 1,803 (242) 846 (2,844) 17,192 158,447
57 200 114,765 1,695 36,425 8,839 859 2,856 1,532 14,864 181,835
58 146 128,007 1,560 27,720 10,944 (492) 1,864 1,400 10,121 181,124
59 222 116,811 2,249 27,941 5,775 245 1,141 (3,513) 7,946 158,595
60 73 115,899 1,594 30,950 12,750 717 486 1,746 188,040 352,182
TOTAL 5,443,506 84,100 1,460,714 300,269 28,628 110,148 18,820 1,317,018 8,763,203

HighLow

MONTH NRVS SALARY VACATION ADV/TRNG SPLY/LNDRY FREIGHT VEHICLES DEMO'S FLOOR-PLAN TOTAL NRVS 249
1 197 52,951 – 0 22,561 1,118 382 2,052 1,881 (78,173) 2,772 SALARIES 82,516 VEHICLES
2 133 47,054 – 0 19,040 3,573 409 1,405 695 28,456 100,632 VC/UNIT 331.39 VC/UNIT
3 132 55,372 – 0 14,373 1,388 742 1,380 469 34,423 108,147 FIXED-HIGH 35,217.92 FIXED-HIGH
4 141 46,114 – 0 15,022 2,894 675 2,057 125 5,697 72,584 FIXED-LOW 35,217.92 FIXED-LOW
5 182 48,309 – 0 19,966 1,896 572 1,603 131 34,599 107,076
6 156 49,643 – 0 12,019 1,188 407 2,524 1,229 53,737 120,747 VACATION DEMOS
7 196 55,784 300 13,217 3,912 643 2,348 1,206 5,507 82,917 VC/UNIT VC/UNIT
8 178 47,957 – 0 17,303 2,012 605 1,208 436 32,436 101,957 FIXED-HIGH FIXED-HIGH
9 159 53,743 – 0 16,535 2,717 209 2,400 1,476 28,950 106,030 FIXED-LOW FIXED-LOW
10 141 53,109 – 0 23,821 1,102 184 2,076 1,168 20,876 102,336
11 152 45,491 300 14,146 2,630 331 1,677 635 45,278 110,488 ADV/TRNG FLOOR PLAN
12 31 57,479 – 0 22,223 7,043 560 2,183 1,014 66,745 157,247 VC/UNIT VC/UNIT
13 280 49,049 – 0 19,992 1,999 582 1,927 (477) (30,104) 42,968 FIXED-HIGH FIXED-HIGH
14 136 46,698 300 20,251 1,192 603 1,156 1,839 50,583 122,622 FIXED-LOW FIXED-LOW
15 174 59,790 200 20,082 1,336 492 1,898 1,260 18,803 103,861
16 171 80,773 600 26,716 3,873 559 1,808 510 23,080 137,919 SPLY/LNDRY TOTAL
17 167 71,130 9,212 25,223 5,560 356 1,816 2,350 18,774 134,421 VC/UNIT VC/UNIT
18 161 82,490 6,007 21,106 1,737 439 1,384 (288) 23,802 136,677 FIXED-HIGH FIXED-HIGH
19 173 98,172 500 17,799 1,847 1,628 1,962 1,591 33,848 157,347 FIXED-LOW FIXED-LOW
20 161 90,685 2,690 28,038 4,415 (12) 2,446 (3,308) 13,480 138,434
21 167 97,771 600 37,284 2,827 480 2,296 1,709 22,965 165,932 FREIGHT
22 153 87,129 1,740 24,236 5,836 79 3,175 798 18,898 141,891 VC/UNIT
23 201 95,910 2,074 27,244 3,387 188 1,287 (2,025) 38,699 166,764 FIXED-HIGH
24 33 109,192 2,782 20,376 12,132 593 2,563 1,010 68,285 216,933 FIXED-LOW
25 227 89,041 1,880 26,719 4,383 769 2,205 2,493 (44,140) 83,350
26 150 92,165 3,602 14,727 10,231 593 2,289 (2,051) 36,311 157,867
27 142 88,981 744 27,880 7,734 414 1,891 386 19,865 147,895 VC/Unit(Sal) 718.10 31
28 104 95,898 960 21,872 (684) 425 2,288 178 19,013 139,950 total fixed 35,217.92
29 121 96,245 – 0 18,705 8,329 483 2,223 (262) 16,228 141,951 total 57,479.00
30 99 106,364 – 0 23,835 2,540 417 1,683 (1,356) 37,637 171,120 VC/Unit(Sal) 49.40 280
31 150 90,564 1,950 25,605 5,862 222 1,586 486 (1,121) 125,154 total fixed 35,217.92
32 144 98,418 1,540 17,763 6,998 49 1,751 (1,924) 34,757 159,352 total 49,049.00
33 154 110,436 2,693 32,379 8,131 818 2,082 1,547 26,419 184,505
34 130 102,042 1,060 19,324 6,026 1,015 1,714 132 21,134 152,447
35 202 124,413 3,519 22,412 9,120 1,255 2,173 (2,337) 18,578 179,133 VC/Unit(Sal) 635.54 146
36 51 116,897 1,520 29,998 6,798 68 1,779 1,195 91,520 249,775 total 128,007.00
37 148 97,083 1,080 9,112 6,627 565 1,324 1,164 (73,753) 43,202
38 153 104,727 3,230 38,616 5,892 369 1,523 (1,839) 30,443 182,961
39 83 95,622 953 22,690 3,450 (182) 2,087 454 17,725 142,799
40 101 96,438 1,244 14,703 5,259 709 2,095 868 26,402 147,718
41 140 114,995 – 0 28,764 2,294 1,006 1,304 (1,990) (3,789) 142,584
42 132 105,337 160 27,253 8,155 521 1,667 1,869 15,090 160,052
43 112 98,989 2,480 24,419 1,621 514 1,040 329 (945) 128,447
44 127 124,352 1,800 26,011 902 917 2,880 (1,897) 30,405 185,370
45 139 115,875 1,417 24,492 5,158 (77) 1,281 2,959 14,781 165,886
46 156 113,035 1,820 31,158 2,901 450 2,259 417 15,613 167,653
47 126 119,106 3,338 32,213 14,426 120 1,394 (2,659) 40,968 208,906
48 33 104,199 1,537 30,177 9,250 819 1,516 4,517 43,189 195,204
49 209 98,938 1,866 26,737 1,694 853 1,657 601 (20,127) 112,219
50 124 108,606 3,676 31,084 9,040 498 2,266 (284) 18,236 173,122
51 131 106,396 1,197 33,278 2,099 605 1,952 668 15,176 161,371
52 144 106,778 241 32,657 9,328 483 1,852 1,409 25,245 177,993
53 93 124,805 500 29,794 4,268 788 1,704 (1,771) 6,493 166,581
54 199 110,153 1,910 38,431 5,407 529 1,882 453 21,851 180,616
55 170 117,276 800 27,640 9,305 (180) 977 1,310 7 157,135
56 186 112,055 980 28,657 1,803 (242) 846 (2,844) 17,192 158,447
57 200 114,765 1,695 36,425 8,839 859 2,856 1,532 14,864 181,835
58 146 128,007 1,560 27,720 10,944 (492) 1,864 1,400 10,121 181,124
59 222 116,811 2,249 27,941 5,775 245 1,141 (3,513) 7,946 158,595
60 73 115,899 1,594 30,950 12,750 717 486 1,746 188,040 352,182
TOTAL 5,443,506 84,100 1,460,714 300,269 28,628 110,148 18,820 1,317,018 8,763,203

Sample

x y xy x squared y squared
1 43 43 99 99 4257 1849 9801
2 21 21 65 65 1365 441 4225
3 25 25 79 79 1975 625 6241
4 42 42 75 75 3150 1764 5625
5 57 57 87 87 4959 3249 7569
6 59 59 81 81 4779 3481 6561
sum 247 486 20485 11409 40022
a= 484979 = 65.1415715245 fixed
7445
b= 2868 = 0.3852249832 variable
7445
r = 2868 0.0000220451
1.69251843954679E+16 root of B19
130096827
r squared= 0.0000000005

,

READING ASSIGNMENT

Your project must be submitted as a Word document (.docx, .doc)*. Your project will be individually graded by your instructor and therefore will take up to a few weeks to grade.

Be sure that each of your files contains the following information:

· Your name

· Your student ID number

· The exam number

· Your email address

To submit your graded project, follow these steps:

· Log in to your student portal.

· Click on Take Exam next to the lesson you’re working on.

· Find the exam number for your project at the top of the Project Upload page.  

· Follow the instructions provided to complete your exam.

Be sure to keep a backup copy of any files you submit to the school!

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)

Mo

NRVS

Salary

Vacation

Adv/Trng

SplyTls/Lndry

  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)

Mo

Freight

Vehicles

Demo's

Floor-Plan

Total

  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 texts you used in your previous math, economics, or accounting courses. Below is a brief outline of the high-low and regression methods.

An image of a chart demonstrating a brief outline of the high-low and regression methods. 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 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.

An image of a scatterplot graph depicting scatterplot-salaries for Motomart salaries. A Scatterplot Graph for Motomart Salaries An image of a line graph depicting salaries—60 months from 1984 through 1988 for Motomart salaries. A Line 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?

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.

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.

Table 4

SALARY = $106,866.00 – $110.10 NRVS

Predictor

Coefficient

Std Deviation

t-statistic

p-value

Constant

106,866.00

10,793.00

9.90

0.000

NRVS

110.10

70.17

–1.57

0.122

s = 25300        r-sq = 4.1%

Analysis of Variance

SOURCE

DF

SS

MS

F-statistic

p-value

Regression

1

261,795

261,795

0.10

0.754

Error

58

152,801,120

2,634,502

 

 

Total

59

153,062,912

 

 

 

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.

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.

· 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.

· 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.

· There is a “PLOT – SALARY” worksheet that shows how the FC, VC and R-sq figures are calculated for Salary.

· There is also a “high&low” worksheet for help with the high/low method in Step 3.

· 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. 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?

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

Grade

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

· 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. It includes the student’s

· Name and address

· Student number, Course title and number, and project number

 

Total Grade

%

Submitting Your Work

Writing Guidelines

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. Include the following information at the top of your paper:

a. Name and complete mailing address

b. Student number

c. Course title and number (Senior Capstone: Business, BUS 450)

d. Project number (see Format instructions)

e. Project title (Professional Development Activity, Case 1, etc.)

3. Read the assignments carefully and complete each one in the order given.

4. Be specific. Limit your submission to the questions asked and issues mentioned.

5. 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.

6. Proofread your work carefully. Check for correct spelling, grammar, punctuation, and capitalization.

NOTES

Top of Form

Bottom of Form

,

READING ASSIGNMENT

Your project must be submitted as a Word document (.docx, .doc)*. Your project will be individually graded by your instructor and therefore will take up to a few weeks to grade.

Be sure that each of your files contains the following information:

· Your name

· Your student ID number

· The exam number

· Your email address

To submit your graded project, follow these steps:

· Log in to your student portal.

· Click on Take Exam next to the lesson you’re working on.

· Find the exam number for your project at the top of the Project Upload page.  

· Follow the instructions provided to complete your exam.

Be sure to keep a backup copy of any files you submit to the school!

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)

Mo

NRVS

Salary

Vacation

Adv/Trng

SplyTls/Lndry

  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)

Mo

Freight

Vehicles

Demo's

Floor-Plan

Total

  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 texts you used in your previous math, economics, or accounting courses. Below is a brief outline of the high-low and regression methods.

An image of a chart demonstrating a brief outline of the high-low and regression methods. 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 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.

An image of a scatterplot graph depicting scatterplot-salaries for Motomart salaries. A Scatterplot Graph for Motomart Salaries An image of a line graph depicting salaries—60 months from 1984 through 1988 for Motomart salaries. A Line 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?

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.

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.

Table 4

SALARY = $106,866.00 – $110.10 NRVS

Predictor

Coefficient

Std Deviation

t-statistic

p-value

Constant

106,866.00

10,793.00

9.90

0.000

NRVS

110.10

70.17

–1.57

0.122

s = 25300        r-sq = 4.1%

Analysis of Variance

SOURCE

DF

SS

MS

F-statistic

p-value

Regression

1

261,795

261,795

0.10

0.754

Error

58

152,801,120

2,634,502

 

 

Total

59

153,062,912

 

 

 

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.

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.

· 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.

· 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.

· There is a “PLOT – SALARY” worksheet that shows how the FC, VC and R-sq figures are calculated for Salary.

· There is also a “high&low” worksheet for help with the high/low method in Step 3.

· 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. 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?

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

Grade

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

· 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. It includes the student’s

· Name and address

· Student number, Course title and number, and project number

 

Total Grade

%

Submitting Your Work

Writing Guidelines

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. Include the following information at the top of your paper:

a. Name and complete mailing address

b. Student number

c. Course title and number (Senior Capstone: Business, BUS 450)

d. Project number (see Format instructions)

e. Project title (Professional Development Activity, Case 1, etc.)

3. Read the assignments carefully and complete each one in the order given.

4. Be specific. Limit your submission to the questions asked and issues mentioned.

5. 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.

6. Proofread your work carefully. Check for correct spelling, grammar, punctuation, and capitalization.

NOTES

Top of Form

Bottom of Form

,

READING ASSIGNMENT

Your project must be submitted as a Word document (.docx, .doc)*. Your project will be individually graded by your instructor and therefore will take up to a few weeks to grade.

Be sure that each of your files contains the following information:

· Your name

· Your student ID number

· The exam number

· Your email address

To submit your graded project, follow these steps:

· Log in to your student portal.

· Click on Take Exam next to the lesson you’re working on.

· Find the exam number for your project at the top of the Project Upload page.  

· Follow the instructions provided to complete your exam.

Be sure to keep a backup copy of any files you submit to the school!

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)

Mo

NRVS

Salary

Vacation

Adv/Trng

SplyTls/Lndry

  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)

Mo

Freight

Vehicles

Demo's

Floor-Plan

Total

  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 texts you used in your previous math, economics, or accounting courses. Below is a brief outline of the high-low and regression methods.

An image of a chart demonstrating a brief outline of the high-low and regression methods. 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 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.

An image of a scatterplot graph depicting scatterplot-salaries for Motomart salaries. A Scatterplot Graph for Motomart Salaries An image of a line graph depicting salaries—60 months from 1984 through 1988 for Motomart salaries. A Line 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?

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.

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.

Table 4

SALARY = $106,866.00 – $110.10 NRVS

Predictor

Coefficient

Std Deviation

t-statistic

p-value

Constant

106,866.00

10,793.00

9.90

0.000

NRVS

110.10

70.17

–1.57

0.122

s = 25300        r-sq = 4.1%

Analysis of Variance

SOURCE

DF

SS

MS

F-statistic

p-value

Regression

1

261,795

261,795

0.10

0.754

Error

58

152,801,120

2,634,502

 

 

Total

59

153,062,912

 

 

 

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.

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.

· 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.

· 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.

· There is a “PLOT – SALARY” worksheet that shows how the FC, VC and R-sq figures are calculated for Salary.

· There is also a “high&low” worksheet for help with the high/low method in Step 3.

· 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. 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?

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

Grade

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

· 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. It includes the student’s

· Name and address

· Student number, Course title and number, and project number

 

Total Grade

%

Submitting Your Work

Writing Guidelines

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. Include the following information at the top of your paper:

a. Name and complete mailing address

b. Student number

c. Course title and number (Senior Capstone: Business, BUS 450)

d. Project number (see Format instructions)

e. Project title (Professional Development Activity, Case 1, etc.)

3. Read the assignments carefully and complete each one in the order given.

4. Be specific. Limit your submission to the questions asked and issues mentioned.

5. 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.

6. Proofread your work carefully. Check for correct spelling, grammar, punctuation, and capitalization.

NOTES

Top of Form

Bottom of Form

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