Richard Ellis, the director of cost operations of Ontario Micro Devices, wishes to develop an accurate cost function to explain and predict support costs in the company’s printed circuit board assembly operation. Mr. Ellis is concerned that the cost function that he currently uses—based on direct labour costs—is not accurate enough for proper planning and control of support costs. Mr. Ellis directed one of his financial analysts to obtain a random sample of 25 weeks of support costs and three possible cost drivers in the circuitboard assembly department: direct labour hours, number of boards assembled, and average cycle time of boards assembled. (Average cycle time is the average time between start and certified completion—after quality testing—of boards assembled during a week.) Much of the effort in this assembly operation is devoted to testing for quality and reworking defective boards, all of which increase the average cycle time in any period. Therefore, Mr. Ellis believes that average cycle time will be the best support cost driver. Mr. Ellis wants his analyst to use regression analysis to demonstrate which cost driver best explains support costs. (Note: This chapter’s Excel Application Exercise provides a tutorial on using Excel 2007 to obtain regression estimates.)

1. Plot support costs, Y, versus each of the possible cost drivers, X1, X2, and X3.

2. Use regression analysis to measure cost functions using each of the cost drivers.

3. According to the criteria of plausibility and reliability, which is the best cost driver for support costs in the circuit-board assembly department?

4. Interpret the economic meaning of the best cost function.

Transcribed Image Text:

Number of Boards Hours, X1 Completed, X2 Average Cycle Time (Hours), X3 Direct Circuit Board Labour Week Assembly Support Costs, Y $66,402 7,619 2,983 186.44 2 56,943 7,678 2,830 139.14 7,816 3 60,337 2,413 151.13 2,221 4 50,096 7,659 138.30 2,701 64,241 7,646 158.63 7,765 60,846 2,656 148.71 7,685 43,119 2,495 105.85 63,412 7,962 2,128 174.02 59,283 7,793 2,127 155.30 10 60,070 7,732 2,127 162.20 2,338 11 53,345 7,771 142.97 7,842 2,685 12 65,027 176.08 13 58,220 7,940 2,602 150.19 7,750 14 65,406 2,029 194.06 7,954 15 35,268 2,136 100.51 7,768 7,764 2,046 16 46,394 71,877 137.47 17 2,786 197.44 61,903 18 7,635 2,822 164.69 7,849 19 50,009 2,178 141.95 20 49,327 7,869 7,576 2,244 123.37 2,195 21 44,703 128.25 2,370 22 45,582 7,557 106.16 7,569 131.41 23 43,818 2,016 24 62,122 7,672 2,515 154.88 52,403 7,653 2,942 25 140.07