Jill Goldstein has been collecting data over the last year in an effort to understand the cost drivers of distribution costs at Waterloo Corporation, a manufacturer of brass door handles. Distribution costs include the costs of organizing different shipments as well as physically handling and moving packaged units. Goldstein believes that, because the product is heavy, number of units moved will affect distribution costs significantly but she is not certain that this is the case.
Goldstein collects the following monthly data for the past 12 months:
Goldstein estimates the following regression equations:
y = $5,187.72 + ($0,533 x Number of packaged units moved)
y = $9,073.11 + ($88.71 x Number of shipments made)
1. Using Excel, produce plots of the monthly data and the regression lines underlying each of the following cost functions:
a. Predicted distribution costs y = a + bX (where X = Number of packaged units moved)
b. Predicted distribution costs y = a + bX (where X = Number of shipments made)
Which cost driver for support overhead costs would you choose? Explain your answer briefly based on the graphs and statistics provided by the analysis.
2. Goldstein anticipates moving 40,000 units in 220 shipments next month. Using the cost function you chose in requirement 1, what distribution costs should Goldstein budget?
3. If Ms. Goldstein chose the wrong cost function—the cost function other than the one you chose in requirement 1—and 40,000 units were moved in 220 shipments, would you expect actual costs to be lower than, to be greater than, or to closely approximate the predictions made using the “wrong” cost driver and cost function? Explain your answer briefly and discuss any other implications of choosing the “wrong” cost driver and cost function.
4. What problem is common to both estimations of predicted cost pool values based on changes in either cost driver and what can Goldstein do now?

  • CreatedJuly 31, 2015
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