Purchasing department cost drivers, activity-based costing, simple regression analysis.

Flashy Fashion operates a chain of ten retail department stores. Each department store makes its own purchasing decisions. Sherry Jones, assistant to the president of Flashy Fashion, is interested in better understanding the drivers of purchasing department costs. For many years, Flashy Fashion has allocated purchasing department costs to products on the basis of the dollar value of merchandise purchased. An item costing $100 is allocated ten times as much overhead costs associated with the purchasing department as an item costing $10 is allocated.

Jones recently attended a seminar titled “Cost Drivers in the Retail Industry.” In a presentation at the seminar, Couture Fabrics, a leading competitor that implemented activitybased costing, reported the number of purchase orders and the number of suppliers to be the two most important cost drivers of purchasing department costs. The dollar value of merchandise purchased on each purchase order was not found to be a significant cost driver.

Jones interviewed several members of the purchasing department at the Flashy Fashion store in ‘Toronto. These people told Jones that they believed that Couture Fabrics’ conclusions also applied to their purchasing department.

Jones collects the following data for the most recent year for Flashy Fashion’s ten retail department stores:

REQUIRED 1. Compare and evaluate the three simple regression models estimated by Jones. Graph each one. Evaluate the information summarized in the three outputs from the three regressions.
2. Do the regression results support the Couture Fabrics presentation about purchasing department cost drivers? Which of these cost drivers would you recommend in designing an activity-based cost system?
3. How might Jones gain additional evidence on drivers of purchasing department costs at each of Flashy Fashion’s stores?LO1

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y Department Purchasing Department Costs (PDC) X Dollar Value Merchandise Purchased (MPS) X3 Number Purchase Orders (no. of POs) Number of Suppliers (no. of Ss) Store Saskatoon $1,523,000 $ 68,315,000 4,357 132 Chicago 1,100,000 33,456,000 2,550 222 Victoria 547,000 121,160,000 1,433 11 Miami 2,049,000 119,566,000 5,944 190 New York 1,056,000 33,505,000 2,793 23 Calgary 529,000 29,854,000 1,327 33 Seattle 1,538,000 102,875,000 7,586 104 St. Louis 1,754,000 38,648,000 3,617 119 Toronto 1,612,000 139,312,000 1,707 208 Vancouver 1,257,000 130,944,000 4,731 201 Jones decides to use simple regression analysis to examine whether one or more of three variables (the last three columns in the table) are cost drivers of purchasing department costs. Summary results for these regressions are as follows: