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Senior Capstone - Motomart 500896

Criteria Grade

Content 80 pts ■ Step 1 – Provides comments on 5 year income statement (worth 10 points) 8 points ■ Step 2 – Discuss patterns in expense items (worth 10 points) 0 points ■ Step 3 – Identify high and low activity levels (worth 10 points) 10 points ■ Step 4 – Compute cost equations (worth 30 points) 0 points ■ Step 5 - Summarize your findings (worth 20 points) 20 points	38 %
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	8 %
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	10 %
Total Grade	56 %
Since this is a failing grade, you are required to rework and resubmit the project for final grading. For Step 4: You included the Excel file; however, the file does not show the work necessary to support the figures presented in Step 4. (So how did you arrive at those figures?) No work (Excel file included as part of the submission) to support the figures – no credit given.

Case 2 - Motomart

Step 1 Comment by Burcicki, Jim: Missing what is wrong with the data.

Year	1984	1985	1986	1987	1988
Trend of Operating Profit	263,828	112,314	-96,699	-94,345	-526,092
Trend of SF Expense	1,172,933	1,665,769	1,892,499	1,870,782	2,161,220
Trend in Net Variable Revenues	2,885,969	3,828,255	4,086,667	3,940,799	4,298,748
Trend in Total Fixed Expense	1,449,208	2,050,172	2,290,867	2,164,362	2,653,620

Using data from Table 2-4 that presents the financial and cost driver information produced by Motomart, the company`s operating profits are seen to decline drastically from 1984 to 1988 resulting in high losses, but in 1987, the company`s loss slightly reduced compared to the 1986 figure before further and more heavy losses in 1988. When looking at the semi-fixed expenses highlighted in Table 2, the S-F expenses appear to be significantly increasing from 1984 to 1988. Also, in this case, 1987 presents a slightly different result of reducing costs before the trend resumed in 1988. This declining pattern went from 43% to a (-196%). The increasing trend of semi-fixed expenses is because of the increase in net variable revenues. Besides, the net variables revenues do not increase as fast as the total fixed expenses, and thus the fixed costs had a high impact on the trend of the semi-fixed expenses.

Step 2 Comment by Burcicki, Jim: Did not identify the unusual pattern with the data nor the 4 items which are wrong with the data.

In looking at Table 3, the semi-fixed expenses highlight odd patterns that are unexpected. All the semi-fixed expenses are expected to increase as the net variable expenses increase; however, some of the costs do not decline or increased and later fell. For instance, vacation reduced from 1985 to 1988 after increasing only in 1984 despite the net variable revenues increase. Besides, the demonstrators’ expense presented a declining and mixed trends throughout the five-year period. The 1st month total expenses increased by $97,860, and then in the 2nd month another $7,475. Then a decline in the 4th month to $75,584.

Semi-Fixed (S-F) Expenses: Comment by Burcicki, Jim: Why is this here? It is not a part of Step 2.	1984	1985	1986	1987	1988
Salaries	613006	968789	1211464	1289758	1360489
Vacation	600	26705	19468	19058	18268
Advertising	210226	288347	281219	309608	371314
Supplies/Tools/Laundry	31473	46141	75468	65935	81252
Freight	5719	5987	6528	5731	4663
Vehicle	22913	23718	23664	20370	19483
Demonstrators	10465	4969	-1513	4192	707
Floor-Planning	278531	301113	276201	156129	305044
Total SF Expense	1172933	1665769	1892499	1870781	2161220

Step 3

The semi-fixed expenses` high and low points do not represent the five-year activity and the separation into a variable, and the fixed element will not be correct if the high and low points methods of the fixed expenses are matched with the NRV`s high and low points.

Semi fixed expenses	High	Low
NVR	280	31
Salaries	128,007	45,491
Vacation	9,212	0
Advertising	38,616	9,112
Supplies/Tools/Laundry	14,426	(684)
Freight	1,628	(492)
Vehicle	3,175	486
Demonstrators	4,517	(3,513)
Floor-Planning	188,040	(78,173)
Total	387,901	2,772

A different option of determining the fixed and variable elements of semi-fixed expenses would be by using the total amount of semi-fixed expenses. The figures from 1998 and 1984 can be utilized as high points and low points respectively. Using the equation y = a + bx, whereas a represents the fixed costs while b accounts for the variable costs, but when the high-low point method is used, the variable cost would be 70% of net variable revenues while the fixed cost could present negative figures. The fixed costs will be 1172933- 2885969*.7 = -847245 and the variable cost = 988287/1412779 = 70%. In conclusion, the statistical method is best suited to determine the fixed and variable cost elements when compared to the high-low method.

	NVR	SF
High	4298748	2161220
Low	2885969	1172933
Difference	1412779	988287

Another choice to decide settled and variable component of SF costs is to consider aggregate of the SF costs. The 1988 figures will be utilized as high point and 1984 will be utilized as low 16 ounces. The condition of y = a + bx will be utilized, the b will be the variable cost and the a will be the settled cost, yet when we utilize the high low point strategy the variable cost is around 70% of net variable incomes and the settled cost comes in negative. The low and high expenses provide values for the company that can be used to estimate the fixed and the variable costs of the total semi fixed expenses but, not the real data as it only compares the two extremes.

Step 4

	FC	VC	R-Sq
1 Salaries	$106,866	-$110	4.07
2 Vacation	-$3,022	-$1	0.17%
3 Advertising and training	$21,654	-$8	0.00%
4 Supplies/tools/laundry	$6,849	-$16	9.28%
5 Freight	$709	$ 1	1.17%
6 Vehicles	$1,576	$ -	0.03 %
7 Demonstrators	$23,182	-$128	3.85%
8 Floor planning	$105,247	-$428	28.31%
9 Total	$263,059	-$692	24.67%

The major problem encountered was the fact that there the variable costs presented negative figures, and the data was too many for a quick and error-free analysis. Moreover, the NRV was used as a base instead of units of output, a factor which was not an accurate representation of the actual activity.

The R-squared measures are low and other times they dropped to zero, signifying that using the NRV as a base was not an appropriate base. Most of the slopes were negative. The conclusions are not consistent with the high-low effort as the high-low effort shows fixed costs in negative form as the use of regression produced negative variable costs.

Step 5

In looking at the financial data of Motomart, the change of semi-fixed expenses cannot only be linked to an activity change. For instance, if an individual cost of a product or service is increased yearly after a particular agreement and the producing firm manufacturers the same quantity in the next year, there will be an increase in the fixed cost. It implies that the change associated with the fixed cost cannot be tied to the change in the number of units produced(Dontoh, Ronen &Sarath, 2013). Thus, when there is a presentation of next year`s costs it means that the cost is variable, but this is not the case observed in Motomart. Furthermore, the case of Motomart has incorporated the use of NRV in determining both fixed and variable elements of semi-fixed expenses, which is not suitable. Hence, determining the fixed and variable elements of the semi-fixed expenses of Motomart using high low and regression methods was not possible. Thus, the data of the company cannot be used to come up with a reliable and appropriate financial forecast. Besides, if Motomart were included in the extensive database required to prepare the financial forecast that supports the relocation, the information would not be reliable. An appropriate means of determining the elements would be to use the machine hours, labor hours, or some units produced to come up with a clear image of the elements. It is not possible to ascertain that Motomart was not maintaining its financial records to be used as an appropriate development to produce economic forecasts and estimate costs for proposed or future retail dealership sites. It cannot also be determined if Motomart reverses its adjusting journal entries after preparing the annual financials.