Related to the ' Dakota office products" cases.

Q: The cost item order entry expenses $800,000 (Exhibit 1) consists solely of fixed annual salaries of data-entry personnel. Critically evaluate the appropriateness of allocating this cost using the available data.

- The distribution centers processed 80,000 cartons in year 2000. Of these, 75,000 cartons were shipped by commercial freight. The remaining 5,000 cartons were shipped under the desktop delivery option. DOP made 2,000 desktop deliveries during the year. - People felt this total amount of handling, processing and shipping was about the capacity that could be handled with existing resources. - The data entry operators processed 16,000 manual orders, and validated 8,000 EDI orders. The 16,000 manual orders had an average of nearly 10 items per order, or 150,000 order lines in total. As with the carton handling, shipping, and delivery personnel, supervisors felt that the data entry operators were operating at capacity rates with the existing business. They then formed two small project teams, one made up of distribution center personnel and the other of data entry operators, to estimate the amount of time people spent on the various activities they had identified. The teams conducted interviews, asked some people to keep track of their time for several days, and observed other people as they went about their daily jobs. The distribution center team reported that 90% of the workers processed cartons in and out of the facility. The remaining 10% of workers were assigned to the desktop delivery service. All of the other warehouse expenses (rent, building and equipment depreciation, utilities, insurance, and property taxes) were associated with the receipt, storage, and handling of cartons. The delivery trucks were used only for desktop delivery orders. These estimates were reviewed by supervisors and felt to be representative of operations not just in the current year, but in the past year (2000) as well. The data entry team, from monitoring computer records, learned that operators worked 10,000 hours during year 2000 . Further analysis of the records revealed the following distribution of time for each of the activities performed by data entry operators. Understanding Customer Profitability Melissa looked through the customer accounts and found two typical accounts of similar size and activity volumes. Customers A and B had each generated sales in year 2000 slightly above $100,000. The costs of the products ordered were also identical at $85,000. The overall markups (21.2\% for Customer A, and 22.4% for B ) were in the range of markups targeted by Dakota Office Products. The markup for Customer B was slightly higher because of the premium charges for desktop delivery. Both customers had ordered 200 cartons during the year. The existing customer profitability system (see Exhibit 2) indicated that both customers generated a contribution margin sufficient to cover normal general and selling expenses and return a profit for the company. Melissa noticed, however, that the two accounts differed on the service demands made on Dakota. Customer A placed a few large orders, and had started to use EDI to place its orders (half its orders, in year 2000, arrived electronically). Customer B, in contrast, placed many more orders, so its average size of order was much smaller than for Customer A. Also, all of Customer B's orders were either paper or phone orders, requiring manual data entry; and 25% of B's orders requested the desktop delivery option. Melissa, concerned about increases in Dakota's borrowings from the bank, also noticed that Customer A generally paid its bills within 30 days, while Customer B often took 90 or more days to pay its bills. A quick study revealed that the average accounts receivable balance during the year for A was $9,000, while it was $30,000 for B. With Dakota paying interest of 10% per year on its working capital line of credit, Melissa thought this difference might be significant. Exhibit 3 shows Melissa's summary of the actual ordering, delivery and payment statistics for the two customers. She believed she was now ready to assess the actual profitability of customers, and make recommendations about how to reverse Dakota's recent profit slide. Exhibit 1 Dakota Office Products: Income Statement CY2000 - The distribution centers processed 80,000 cartons in year 2000. Of these, 75,000 cartons were shipped by commercial freight. The remaining 5,000 cartons were shipped under the desktop delivery option. DOP made 2,000 desktop deliveries during the year. - People felt this total amount of handling, processing and shipping was about the capacity that could be handled with existing resources. - The data entry operators processed 16,000 manual orders, and validated 8,000 EDI orders. The 16,000 manual orders had an average of nearly 10 items per order, or 150,000 order lines in total. As with the carton handling, shipping, and delivery personnel, supervisors felt that the data entry operators were operating at capacity rates with the existing business. They then formed two small project teams, one made up of distribution center personnel and the other of data entry operators, to estimate the amount of time people spent on the various activities they had identified. The teams conducted interviews, asked some people to keep track of their time for several days, and observed other people as they went about their daily jobs. The distribution center team reported that 90% of the workers processed cartons in and out of the facility. The remaining 10% of workers were assigned to the desktop delivery service. All of the other warehouse expenses (rent, building and equipment depreciation, utilities, insurance, and property taxes) were associated with the receipt, storage, and handling of cartons. The delivery trucks were used only for desktop delivery orders. These estimates were reviewed by supervisors and felt to be representative of operations not just in the current year, but in the past year (2000) as well. The data entry team, from monitoring computer records, learned that operators worked 10,000 hours during year 2000 . Further analysis of the records revealed the following distribution of time for each of the activities performed by data entry operators. Understanding Customer Profitability Melissa looked through the customer accounts and found two typical accounts of similar size and activity volumes. Customers A and B had each generated sales in year 2000 slightly above $100,000. The costs of the products ordered were also identical at $85,000. The overall markups (21.2\% for Customer A, and 22.4% for B ) were in the range of markups targeted by Dakota Office Products. The markup for Customer B was slightly higher because of the premium charges for desktop delivery. Both customers had ordered 200 cartons during the year. The existing customer profitability system (see Exhibit 2) indicated that both customers generated a contribution margin sufficient to cover normal general and selling expenses and return a profit for the company. Melissa noticed, however, that the two accounts differed on the service demands made on Dakota. Customer A placed a few large orders, and had started to use EDI to place its orders (half its orders, in year 2000, arrived electronically). Customer B, in contrast, placed many more orders, so its average size of order was much smaller than for Customer A. Also, all of Customer B's orders were either paper or phone orders, requiring manual data entry; and 25% of B's orders requested the desktop delivery option. Melissa, concerned about increases in Dakota's borrowings from the bank, also noticed that Customer A generally paid its bills within 30 days, while Customer B often took 90 or more days to pay its bills. A quick study revealed that the average accounts receivable balance during the year for A was $9,000, while it was $30,000 for B. With Dakota paying interest of 10% per year on its working capital line of credit, Melissa thought this difference might be significant. Exhibit 3 shows Melissa's summary of the actual ordering, delivery and payment statistics for the two customers. She believed she was now ready to assess the actual profitability of customers, and make recommendations about how to reverse Dakota's recent profit slide. Exhibit 1 Dakota Office Products: Income Statement CY2000