18-5 Wang.doc

Table of ContentsIssue1Facts1Analysis4Conclusion910Issue1. Why was Dakotas existing pricing system inadequate for its current operating environment?2. a. What is the activity-based cost system for Dakota Office Products (DOP) based on Year 2000 data? b. What is the activity cost-driver rate for each DOP activity in 2000?3. Using your answer to Question 2, what was the profitability of Customer A and Customer B?4. What explains any difference in profitability between the two customers?5. What are the limitations, if any, to the estimates of the profitability of the two customers?6. Is there any additional information you would like to have to explain the relative profitability of the two customers?7. a. Assume that Dakota applies the analysis done in Question 3 to its entire customer base. b. How could such information help the Dakota managers increase company profits?8. Suppose that a major customer switched from placing all its orders manually to placing all its orders over the internet site. a. How should this affect the activity cost driver rates calculated in Question 2? b. How would the switch affect Dakotas profitability?FactsJohn Malone, General Manager of Dakota Office Product (DOP) was concerned about the financial results for calendar year 2000. Despite a sales increase from the prior year, the company had just suffered from the first loss in its history. In year 2000, sales were $ 42,500,000 which was 121.4% of the prior year, but net income before taxes was minus $ 470,000.Dakota Office Products was a regional distribution of office supplies to institutions and commercial businesses. It offered a comprehensive product line ranging from simple writing implements to specialty paper for modern high-speed copiers. DOP had an excellent reputation for customer service. DOP operated several distribution centers in which personnel unloaded truckload shipments of products from manufactures, and moved the cartons into designated storage locations until customers requested the items.Typically, DOP shipped products to customers using commercial truckers. Recently, DOP had attracted new business by offering a “desk top “option by delivering the package of supplies directly to individual locations at the customers site. It operated a small fleet of trucks and assigned warehouse personnel as drivers to make the desktop deliveries. Dakota charged a small price premium (up to an additional 2% markup) for the service provided to customers.DOP ordered supplies from many different manufacturers. It priced products to its end-use customers by first marking up the purchased product cost by about 15% to cover the cost of warehousing, distribution and freight. Then it added another markup to cover the approximate cost for general and selling expenses, plus an allowance for profit.Dakota had introduced electronic data interchange (EDI) in 1999, and a new Internet site in 2000, which allowed customer orders to arrive automatically. Several customers had switched to this electronic service because of the convenience to them. Yet Dakotas costs continued to rise.Malone turned to his controller, Melissa, and they went into the field of distribution center. They identified four primary activities done at the distribution center- process cartons in and out of the facility, the new desk top delivery service, order handing, and data entry.There were some details.The amount of warehouse space they needed and people to move cartons just depend on the number of cartons. All items have about the same inventory turnover so space and handling costs are proportional to the number of cartons that go through the facility.They used commercial freight for normal shipments, and the cost is based more on volume than on anything else. Of course, any carton that they deliver themselves, through their new desktop delivery service, avoids the commercial shipping charges. Desktop delivery attracted increased business, but they had to ass people since existing personnel already had more than enough to do.They next checked on the expenses of entering and validating customers order data. The order entry expenses included the data processing system and the data entry operators. All the operator did were entering the customer ID, validating customer information and and what really matters was how many lines the operator had to enter. This validity check talked about the same time for all electronic orders: it doesnt depend on the number of item ordered.Melissa and Tim collected information from company data bases and learned the following: The distribution centers processed 80,000 cartons in year 2000. 75,000 cartons were shipped by commercial freight. The remaining 5,000were shipped under the desktop delivery option. DOP made 2,000 desktop deliveries during the year. This total amount of handling, processing and shipping was about the capacity that could be handled with existing resources.The data entry operators process 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. Data entry operators were operating at capacity rates with the existing business.They formed two small projects 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 identifies.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 were associated with the receipt, storage, and handling of cartons. The delivery trucks were used only for desktop delivery orders. These estimates were felt to be representative of operations not only in the current year, but in the past year (2000) as well.Analysis1. The data entry team learned that the operators worked 10,000 hours during year 2000. 2,000 hours were spent in setting on manual customers order, 7,500 hours were spent in entering individual order lines in an order, and 500 hours were used to validate an EDO order.Melisall looked through the customer accounts and found two typical accounts of similar size and activity volumes. Customers A & B had each generated sales in year 2000 slightly above $ 100,000. The costs of the products ordered were also identified at $ 85,000. The overall markups (21.2% for Customer A, and 22.4% for B) were in the range of markups targeted by DOP. Both customers had ordered 200 cartons during the year. Both customers generated a contribution margin sufficient to cover normal general and selling expense and return a profit for the company. However, they were different on the service demands made on Dakota. Customer A placed a few large orders, and had started to use EDI to place its orders. Customer B, placed many more orders, so its average size of order was much smaller than for A. Also, all of Bs orders were paper or phone orders, requiring manual data entry; and 25% of Bs orders requested the desktop delivery option. Melissa also notices that A generally paid its bills within 30 days, while B often took 90 or more days to pay its bills. The average accounts receivable balance during year for A was $ 9,000, while it as $3,000 for B. Dakota paid interest of 10 % per year.2. a. What is the activity-based cost system for Dakota Office Products (DOP) based on Year 2000 data?There were four primary activities done at the distribution center-process cartons in and out of the facility, the new desk top delivery service, order handling, and data entry. Based on the report of distribution center team, 90% of the workers process cartons in and out of the facility, the remaining 10% of workers were assigned to the desktop delivery service. So, for the total of $ 2,400,000 warehouse personnel expense, $ 2,160,000 ($ 2,400,000*90%) would go to process cartons and $ 240,000 ($2,400,000 *10%) would be expenses of desktop delivery service. All of the other warehouse expenses were associated with handling of cartons, so warehouse expense (excluding personnel ) The delivery trucks were used only for desktop delivery orders, obviously, as was shown in exhibit 1, delivery truck expenses were $200,000, added to $240,000, total desktop delivery expenses were $440,000. About the activity of order handling, order entry expenses which were $800,000, plus $2,000,000, so expenses of order handling would be $2,800,000. The data entry expenses included the data processing system and the data entry operators. Because operators worked 10,000 hours during year 2000, and order entry expenses were $80, data entry expense per hour was $ 80,000. Thus, it can be concluded that costs of set up a manual customer order were $ 160,000, enter individual order lines in an order were $ 600,000, and validate an EDI/ Internet order were $ 40,000. b. What is the activity cost-driver rate for each DOP activity in 2000?Cost-driver rate equals assignment divided by activity quantity.Primary ActivityActivity in detailsAssigned costActivity quantityCost-driver rateProcess cartons in and out of facilityWarehouse personnel (90%)$2,160,000$80,000$464.5per cartonCost of items purchased35,000,000Desktop delivery serviceWarehouse personnel (10%)240,0002000$220per cartonDelivery truck200,000Order handlingFreight450,00024,000$102.08 per orderWarehouse expense(excluding personnel)2,000,000Data entryOrder entry expense800,000150,0005.33 Per lineData entry operatorsSet up a manual customer order160,00010,000$80 per hourEnter individual order lines in an order600,000Validate an EDI/Internet order40,0003. Because the number of cartons ordered had been given and cost-driver rate from question 2, warehouse, distribution and order entry expenses can be calculated as follows: A: Process cartons: 200*$464.5=$92900, Desktop delivery: 0Order handling: (6+6)*102.08=$1224.96, Data entry: 60*5.33=$319.8B: Process cartons: 200*$464.5=$92900, Desktop delivery: 25*220=$5500 Order handling: 100*102.08=$10208, Data entry: 180*5.33=$959.4So, cost of item purchased forA were: $ (92900+0+1224.96+319.8) = $94444.76; For B were; $ (92900+5500+10208+959.4) = $109567.4Contribution to general and selling expenses =number of cartons ordered * (general and selling expenses + Interest expenses)/cartons processed, so, Contribution to genera and selling expense is (2,000,000+120,000)200/80,000= $5300In this case, Customer profitability report would beCustomer ACustomer BSales103,000104,000Cost of item purchased (94,444.76) (109,567.4)Contribution to genera and selling expense$5300$5300Profit3255.24(10867.4)So, as shown in illustration, Profitability for A and B were 3255.24 and minus 10867.4.4. According to the Exhibit 3, custom B chooses 150 numbers of cartons shipped commercial freight, which means customer B chooses much more expensive delivery for 50 cartons than customer A. A has 60 of line items, manual , and B has 180. So B spent more order entry expense than A. A had 6 manual orders and 6 EDI orders for 200 cartons. Customer B had 100 manual orders for 200 cartons. Order handling is $102.08 per order. So Customer A spent $1224.96 and Customer B spent $10,208. And it is obvious that $8983.04 more money spent on Customer B.5. “desktop” delivery per Labor Hour cant be computed because each time there is different distance from the warehouse which makes different labor cost per delivery. The wage of a manual customer order and an EDI order cant be computed because the number of each order line is not sure. So the order entry expense cant be computed.6. I would like to know delivery per labor hour and the wages or number of personnel and the number of personnel working in manual customer order, EDI order.7. If Dakota applies the analysis done in question 3to its entire customer base, he would discover that delivery cost has some problem and the price for “desktop” delivery should be adjusted by the distance from the warehouse. Place higher prices and Give a discount to the customers who have made big order.8. a. Suppose that major customer switched from placing all its orders manually to placing all its orders over the interest site. Process cartons in and out of facility rate will change, because of Warehouse personnel has changed. EDI Orders 8,000 divided by EDI Labor Hours 500, which means16 orders per hour. The total Orders24000, so it would 1500 hours of work and compare to 10,000 hours spend in data entry operators time 8,500 hour less. Therefore, the data entry rate is also changed because the order line changed.b. According to the question a, two of four activity cost driver have declined so the customer would improve the profit .Conclusion1. The data entry team learned that the operators worked 10,000 hours during year 2000. 2,000 hours were spent in setting on manual customers order, 7,500 hours were spent in entering individual order lines in an order, and 500 hours were used to validate an EDO order. Melissa also notices that A generally paid its bills within 30 days, while B often took 90 or more days to pay its bills. The average accounts receivable balance during year for A was $ 9,000, while it as $3,000 for B. Dakota paid interest of 10 % per year.2. a. There were four primary activities done at the distribution center-process cartons in and out of the facility, the new desk top delivery service, order handling, and data entry. Based on the report of distribution center team, 90% of the workers process cartons