There are four items, each with four parts. Each part is worth six points. (Four points are free.)
1. The management of Wheeler Company has decided to develop cost formulas for its major overhead activities. Wheeler uses a highly automated manufacturing process, and power costs are a significant manufacturing cost. They have debated whether the power cost should be treated as fixed, variable, or both. Using the following data you are charged to settle this issue and determine the best cost formula for Wheeler.
Quarter
|
Machine Hrs.
|
Power Cost
|
1
|
20000
|
26000
|
2
|
25000
|
38000
|
3
|
30000
|
42500
|
4
|
22000
|
37000
|
5
|
21000
|
34000
|
6
|
18000
|
29000
|
7
|
24000
|
36000
|
8
|
28000
|
40000
|
1. Find the estimated fixed cost associated with the machine hours.
2. Find the estimated variable cost associated with the machine hours.
3. Discuss your confidence in the use of these estimates.
4. Would you recommend using this cost function? Explain.
2. You are asked to predict orders for the next two periods. You have information available for the overtime hours used for each quarter.
Quarter
|
Orders
|
Overtime
|
1
|
53
|
22
|
2
|
56
|
23
|
3
|
52
|
25
|
4
|
62
|
31
|
5
|
47
|
21
|
6
|
46
|
22
|
7
|
48
|
20
|
8
|
57
|
29
|
9
|
43
|
23
|
10
|
45
|
12
|
11
|
46
|
22
|
12
|
53
|
26
|
13
|
38
|
16
|
14
|
35
|
17
|
1. Find the best method to predict orders.
2. Discuss the model fit.
3. Predict the orders for the next two periods
4. Would you recommend using this model? Explain
3. The data below are weekly figures from Herbert Hooley's Happy House (except for the quarterly error figures). They sell radios, TVs, and VCRs in their electronics department. He needs you to help him with a few things, which he will indicate to you.
Profit
|
Revenue
|
Radios
|
TVs
|
VCRs
|
|
Quarter
|
Errors
|
6318.96
|
8395.91
|
36
|
65
|
48
|
|
|
|
4721.57
|
6300.28
|
26
|
48
|
39
|
|
|
|
5049.16
|
6747.55
|
33
|
51
|
40
|
|
2000 - 3
|
32
|
5249.44
|
7028.56
|
29
|
53
|
45
|
|
4
|
46
|
5290.08
|
7116.41
|
32
|
52
|
49
|
|
2001 - 1
|
19
|
5924.41
|
7951.00
|
41
|
58
|
52
|
|
2
|
23
|
5251.97
|
7031.09
|
36
|
52
|
44
|
|
3
|
34
|
4805.72
|
6462.88
|
31
|
47
|
44
|
|
4
|
49
|
5278.60
|
7162.42
|
46
|
49
|
51
|
|
2002 - 1
|
22
|
5301.77
|
7136.35
|
43
|
51
|
46
|
|
2
|
20
|
6121.98
|
8249.84
|
45
|
59
|
56
|
|
3
|
31
|
5416.63
|
7244.79
|
29
|
55
|
46
|
|
4
|
51
|
6552.89
|
8718.21
|
43
|
67
|
48
|
|
2003 - 1
|
16
|
6352.93
|
8494.02
|
46
|
63
|
51
|
|
2
|
26
|
6693.01
|
8881.75
|
55
|
68
|
43
|
|
3
|
37
|
5761.97
|
7669.10
|
48
|
58
|
39
|
|
4
|
48
|
5419.50
|
7265.38
|
33
|
54
|
47
|
|
2004 -1
|
22
|
5474.64
|
7302.97
|
35
|
55
|
44
|
|
2
|
24
|
4650.87
|
6335.89
|
41
|
42
|
49
|
|
|
|
4781.91
|
6438.23
|
48
|
45
|
39
|
|
|
|
1. "Doug, I could surely use some help. I would like to find a useful profit formula for my department. Please let me know if it is a good model, and if there are any potential issues I should consider." Note that the numbers of radios, TVs, and VCRs represent the number held on hand for the week. Please find the best model for Herb.
2. Discuss the model.
3. Are there other issues to consider here? Explain
4. What is your recommendation regarding use of this model? Explain
4. The Bubble Up Bottling Company of Brussels, Belgium, is interested in forecasting regional sales of Bubble Up over the next two years. The company has analyzed Bubble Up's market share for its region over the past twenty quarters. Market share has generally been growing as indicated in the following table:
Year
|
Season
|
Bubble Up's Market Share (in %)
|
1
|
Winter
|
6.42
|
1
|
Spring
|
6.58
|
1
|
Summer
|
6.99
|
1
|
Fall
|
6.82
|
2
|
Winter
|
7.15
|
2
|
Spring
|
7.33
|
2
|
Summer
|
7.45
|
2
|
Fall
|
7.55
|
3
|
Winter
|
7.66
|
3
|
Spring
|
7.69
|
3
|
Summer
|
7.71
|
3
|
Fall
|
7.81
|
4
|
Winter
|
7.85
|
4
|
Spring
|
7.84
|
4
|
Summer
|
7.88
|
4
|
Fall
|
7.93
|
5
|
Winter
|
7.99
|
5
|
Spring
|
8.04
|
5
|
Summer
|
8.04
|
5
|
Fall
|
8.05
|
During the same five-year period, total soft drink sales in the region (as measured in 100,000s of cases) have been as follows:
Year
|
Season
|
Sales in Region (in 100,000s of cases)
|
1
|
Winter
|
114
|
1
|
Spring
|
130
|
1
|
Summer
|
158
|
1
|
Fall
|
131
|
2
|
Winter
|
114
|
2
|
Spring
|
146
|
2
|
Summer
|
177
|
2
|
Fall
|
142
|
3
|
Winter
|
124
|
3
|
Spring
|
151
|
3
|
Summer
|
175
|
3
|
Fall
|
146
|
4
|
Winter
|
132
|
4
|
Spring
|
160
|
4
|
Summer
|
184
|
4
|
Fall
|
144
|
5
|
Winter
|
134
|
5
|
Spring
|
166
|
5
|
Summer
|
205
|
5
|
Fall
|
148
|
The company wants to forecast sales for the next two years (6 and 7).
1. What approach will you use for this problem? Explain.
2. Obtain forecasts for the next two years.
3. Discuss the performance of your method.
4. What is your recommendation regarding the use of your method?