Beauville Furniture Corporation produces sofas, recliners, and lounge chairs. Beauville is located in a medium-sized community in the southeastern part of the United States. It is a major employer in the community. In fact, the economic well-being of the community is tied very strongly to Beauville. Beauville operates a sawmill, a fabric plant, and a furniture plant in the same community. The sawmill buys logs from independent producers. The sawmill then processes the logs into four grades of lumber: firsts and seconds, No. 1 common, No. 2 common, and No. 3 common. All costs incurred in the mill are common to the four grades of lumber. All four grades of lumber are used by the furniture plant. The mill transfers everything it produces to the furniture plant, and the grades are transferred at cost. Trucks are used to move the lumber from the mill to the furniture plant. Although no outside sales exist, the mill could sell to external customers, and the selling prices of the four grades are known. The fabric plant is responsible for producing the fabric that is used by the furniture plant. To produce three totally different fabrics (identified by fabric ID codes FB60, FB70, and FB80, respectively), the plant has three separate production operationsone for each fabric. Thus, production of all three fabrics occurs at the same time in different locations in the plant. Each fabrics production operation has two processes: the weaving and pattern process and the coloring and bolting process. In the weaving and pattern process, yarn is used to create yards of fabric with different designs. In the next process, the fabric is dyed, cut into 25-yard sections, and wrapped around cardboard rods to form 25-yard bolts. The bolts are transported by forklift to the furniture plants Receiving Department. All of the output of the fabric plant is used by the furniture plant (to produce the sofas and chairs). For accounting purposes, the fabric is transferred at cost to the furniture plant. The furniture plant produces orders for customers on a special-order basis. The customers specify the quantity, style, fabric, lumber grade, and pattern. Typically, jobs are large (involving at least 500 units). The plant has two production departments: Cutting and Assembly. In the Cutting Department, the fabric and wooden frame components are sized and cut. Other components are purchased from external suppliers and are removed from stores as needed for assembly. After the fabric and wooden components are finished for the entire job, they are moved to the Assembly Department. The Assembly Department takes the individual components and assembles the sofas (or chairs). Beauville Furniture has been in business for over two decades and has a good reputation. However, during the past five years, Beauville experienced eroding profits and declining sales. Bids were increasingly lost (even aggressive bids) on the more popular models. Yet, the company was winning bids on some of the more-difficult-to-produce items. Lance Hays, the owner and manager, was frustrated. He simply couldnt understand how some of his competitors could sell for such low prices. On a common sofa job involving 500 units, Beauvilles bids were running $25 per unit, or $12,500 per job more than the winning bids (on average). Yet, on the more difficult items, Beauvilles bids were running about $60 per unit less than the next closest bid. Gisela Berling, vice president of finance, was assigned the task of preparing a cost analysis of the companys product lines. Lance wanted to know if the companys costs were excessive. Perhaps the company was being wasteful, and it was simply costing more to produce furniture than it was costing its competitors. Gisela prepared herself by reading recent literature on cost management and product costing and attending several conferences that explored the same issues. She then reviewed the costing procedures of the companys mill and two plants and did a preliminary assessment of their soundness. The production costs of the mill were common to all lumber grades and were assigned using the physical units method. Since the output and production costs were fairly uniform throughout the year, the mill used an actual costing system. Although Gisela had no difficulty with actual costing, she decided to explore the effects of using the sales-value-at-split-off method. Thus, cost and production data for the mill were gathered so that an analysis could be conducted. The two plants used normal costing systems. The fabric plant used process costing, and the furniture plant used job-order costing. Both plants used plantwide overhead rates based on direct labor hours. Based on her initial reviews, she concluded that the costing procedures for the fabric plant were satisfactory. Essentially, there was no evidence of product diversity. A statistical analysis revealed that about 90 percent of the variability in the plants overhead cost could be explained by direct labor hours. Thus, the use of a plantwide overhead rate based on direct labor hours seemed justified. What did concern her, though, was the material waste that she observed in the plant. Maybe a standard cost system would be useful for increasing the overall cost efficiency of the plant. Consequently, as part of her report to Lance, she decided to include a description of the fabric plants costing proceduresat least for one of the fabric types. She also decided to develop a standard cost sheet for the chosen fabric. The furniture plant, however, was a more difficult matter. Product diversity was present and could be causing some distortions in product costs. Furthermore, statistical analysis revealed that only about 40 percent of the variability in overhead cost was explained by the direct labor hours. She decided that additional analysis was needed so that a sound product costing method could be recommended. One possibility would be to increase the number of overhead rates. Thus, she decided to include departmental data so that the effect of moving to departmental rates could be assessed. Finally, she also wanted to explore the possibility of converting the sawmill and fabric plant into profit centers and changing the existing transfer pricing policy. With the cooperation of the cost accounting manager for the mill and each

plants controller, she gathered the following data for last year:

Joint manufacturing costs: $900,000 Fabric Plant: Budgeted overhead: $1,200,000 (50\% fixed) Practical volume (direct labor hours): 120,000 hours Actual overhead: $1,150,000 (50\% fixed) Actual hours worked: Departmental data on Fabric FB70 (actual costs and actual outcomes): Proposed standard cost sheet for Fabric FB70 (for the Coloring and Bolting Department only): Furniture Plant: Departmental data (budgeted): After some discussion with the furniture plant controller, Gisela decided to use machine hours to calculate the overhead rate for the Cutting Department and direct labor hours for the Assembly Department rate (the Cutting Department was more automated than the Assembly Department). As part of her report, she wanted to compare the effects of plantwide rates and departmental rates on the cost of jobs. She wanted to know if overhead costing could be the source of the pricing problems the company was experiencing. To assess the effect of the different overhead assignment procedures, Gisela decided to examine two prospective jobs. One job, Job A500, could produce 500 sofas, using a frequently requested style and Fabric FB70. Bids on this type of job were being lost more frequently to competitors. The second job, Job B75, would produce 75 specially designed recliners. This job involved a new design and was more difficult for the workers to build. It involved some special cutting requirements and an unfamiliar assembly. Recently, the company seemed to be winning more bids on jobs of this type. To compute the costs of the two jobs, Gisela assembled the following information on the two jobs: Job A500: Joh R7E. a. Complete the following table by calculating the sawmill's cost per board foot for each grade using both the physical units method and the sales-value-at-split-off method (round to three decimal places): b. Given that the sawmill provides lumber at cost to the furniture plant, using the sales-value-at-splitoff method (select: increases, decreases) the cost of Job A500 by $ and (select: increases, decreases) the cost of Job B75 by $ c. The physical units method, often used in the lumber industry, essentially assumes that it costs (select: the same, more) to produce each board foot (select: regardless of, depending on) the grade. Thus, (select: the same, a higher) cost of lumber would be assigned to a sofa or chair (select: regardless of, depending on) which grade is used. This approach has some drawbacks. Intuitively, the higher grades should cost (select: the same, more). Certainly, if the company was buying this input from suppliers, there would be (select: a cost difference, no cost difference) for sofas and chairs (select: regardless of, depending on) the grade of lumber purchased, because the higher grades have a (select: higher, lower) selling price. The relative sales value method assigns (select: the same, a higher) cost to grades that have a (select: lower, higher) market value. Thus, the cost assigned to sofas and chairs (select: would differ, be the same) (select: according to, regardless of) the grade of lumber used. d. Review the data analytic concepts and metrics found in Exhibits 2.5 and 2.6. What are the data analytic models being considered for the Sawmill? Which of the data analytic types is being used in Part a of Requirement 1 ? And for Part b? Part c? Note: More than one data analytic type may apply. Which of the data analytic models in play would you recommend for assigning the joint manufacturing sawmill costs? Explain