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Part II: Dana Boar, controller of Digital Electronics Canada, developed the figures requested by her boss and president of Digital Electronics Canada, Hans Fritz. The

Part II:

Dana Boar, controller of Digital Electronics Canada, developed the figures requested by her boss and president of Digital Electronics Canada, Hans Fritz. The numbers allowed her to see how the projected sales volume for 2017 related to breakeven, and examine the relative profitability of the two products, DELTA1 and DELTA2. Boar thought the figures were OK as far has her analysis went, but she began to wonder about some of the assumptions built into her calculations.

For example, she had used direct labor as a base for distributing indirect manufacturing overhead because that was the system traditionally used by the parent company. She recognized that the assumption on which that system was based was that the amount of direct labor used by a product was a good predictor of the amount of overhead that should be charged to it.

Company Information

In early, 2016, Digital Electronics, a large New Zealand manufacturer of transmission equipment, had set up a subsidiary in Canada to manufacture two products Digital had successfully marketed to Europe. One was a miniature signaling device used primarily for remote operation of garage doors. These DELTA1 units consisted of a signal sender, about half the size of a pack of cards, and a receiver, which was a bit larger.

Digital also had designed a similar device that could be used by a household to turn on inside lights when arriving after dark. This unit, called DELTA2, was slightly more expensive to make since the receiving part was a complete plug-in device while the DELTA1 receiver was a component of the garage door unit. Initially, Digital expected to sell the DELTA2 unit primarily through mail order catalogues.

The Allocation of Overhead

On reflection, Boar didnt think that direct labor was a very good predictor of the amount of overhead that should be charged to a product. She considered whether units might be a good predictor, and decided that units worked well as a predictor of supplied usage. Supplies consisted of wire, connectors, solder, some general types of resistors, and other parts and pieces. To measure how each product actually consumed supplies would be tedious; she thought a reasonable estimate could be made. She would deal with that later.

Although Boar thought units worked well for supplies, units did not seem to make any better sense than direct labor for use as a base for distribution of the other types of overhead. Equipment maintenance, for example, had more to do with the types of equipment used than with the units produced or direct labor; she recognized that ore units would probably cause more maintenance expenses.

She had heard from one of her former Yorkville University professors about activity-based-costing (ABC). Boar decided to consider whether ABC would have any value in her situation. In rereading her notes about ABC, she learned that it was more useful when

product diversity was not recognized by the existing base(s) used for overhead distribution, the amount of overhead was significant, and the competitive situation was such that accurate product costs would be helpful to company strategy.

Boar concluded that the amount of overhead was significant and that the competitive situation could well mean accurate product costs would be important. She was not sure, however, about the product diversity requirement. She wondered where, if at all, might use of direct labor as a base for overhead distribution introduce a distortion in product costs?

To get at that question, she decided she had to examine the processes used to manufacture each product. This was actually quite easy for her since she was very familiar with plant operations. Each product went through three kinds of processes:

1) Fabrication, where equipment operators made components such as insulated platforms for electronic parts and housings for the unit. The operation was quite highly automated with large punch presses and special molds together with belts and robots for moving and positioning parts.

2) Assembly, which was not so highly automated but did use some small machines and moving belts.

3) Packing and shipping, in which units were packed in preprinted boxes. The DELTA1 unit had one configuration of packaging for its single customer. The DELTA2 unit was currently being shipped to four mail order companies with a total of six configurations.

In addition, there was a significant quality control/production engineering activity and a number of activities related to production, such as purchasing, maintenance, payroll, and receivables/payables accounting. She decided to use the areas she thought might have some diversity between the products, and more important, she admitted to herself, those areas on which data would be the easiest to get. She considered her analytical approach to be a matrix, and began filling in the numbers as she obtained or estimated them. On the top, she listed the four activities she decided to work on first. Down the left side, she listed the budgeted expenses in the existing accounting categories. Her analysis then spread the budgeted expenses across the activities (Exhibit I).

She had decided to treat the supplies expense differently from the other overhead expenses, since it was a variable expense and was likely to vary with unit volume. For her earlier calculation, she used a flat $1.40 per unit ($21,000/15,000 units). Now she thought that number should be sharpened when it came to computing the cost of each product. Her knowledge of the process told her that the DELTA2 unit was a bit more complicated and would use slightly more supplies. After some more analysis, she decided that a more accurate per unit figure would be $1.37 per unit for the DELTA1 and $1.46 per unit for the DELTA2.

Along the way, she realized that some budgeted overhead expenses could not be distributed to the activities using any rational connection. Or put another way, there was not a clear relationship between the activities and the budgeted expense. So rather than force an artificial distribution, she designed a fifth activity that she called general operations. She thought that later on, she might remove some of the expenses in general operations and assign them to a newly designed activity. To make that work, however, she knew she would have to be able to relate the new activities to the products. Purchasing for example, might be a new activity, but how to relate purchasing to products was a problem she was not ready to tackle. So the purchasing expenses were left in the general operations activity.

Boar distributed the overhead expenses to the activities using the most logical method she could think of: square feet for occupancy expenses, estimates of time and parts costs for equipment maintenance expense, and equipment book values for depreciation. She filled in her spreadsheet with the resulting numbers.

Boar decided that the quality control/production engineering expense was driven more by the production activities than by any distinctive product characteristics. Therefore, she decided that the $19,000 total would be distributed to the three production activities. After talking with the people involved in quality control/production engineering about what caused their work, she made the distribution to the three main production activities as shown in Exhibit I.

She was now ready to distribute the total activities cost to the two products. To do that, she wanted to consider what linkage reflected best the way product characteristics caused the activity. She thought of three possibilities: units of product, direct labor used by the product, or as a wild card, elapsed time in the activity. She discarded the units measure because she knew that, at least in fabrication, a DELTA2 unit used a lot more fabrication resources than an DELTA1 unit. Either direct labor or elapsed time would reflect that difference. Elapsed time, she thought, was interesting because it reflected not only the time items were worked on, but also the time they waited in a queue, which has some relationship to the way their complexity used the departments resources. But in the end, she chose direct labor, partly because she thought it did measure the products use of the activities resources, and partly because the data were easily available.

With a little work extracting existing data on direct labor use in the activities, Boar constructed the table shown in Exhibit II and prepared to carry out the final step to compute the revised manufacturing cost of the two products. She would distribute each of the three overhead amounts for activities in proportion to direct labor in that activity. She would distribute the general operations overhead of $39,000 in proportion to total direct labor for all three activities.

Exhibit 1 Distribution of direct labour and overhead to activities

Expense Total Qulity control Fabrication Assembly Pakaging&shipping General operations
Direct labour 56,000 18,500 30,000 7,500
Overhead:
Occupancy 15,000 1,000 3,000 5,000 4,000 2,000
Equipment maintenance 17,000 1,000 10,000 4,000 1,000 1,000
Equipment depreciation 8,000 2,000 4,000 1,000 1,000
Quality control 15,000 15,000 0 0 0
Manufacturing admin 36,000 0 0 0 0 36,000
Total 91,000 19,000 17,000 10,000 6,000 39,000
Quality control 0 (19,000) 11,000 7,000 1,000 0
Total 91,000 0 28,000 17,000 7,000 39,000
Supplies 21,000
total overhead 112,000

Exhibit 2

Estimated Direct labour per month by activity and product

Total Delta 1 (10,000 units) Delta 2( 5,000 units)
Fabrication 18,500 10,000 8,500
Assembly 30,000 21,000 9,000
Pakaging & Shipping 7,500 4,000 3,500
Total 56,000 35,000 21,000

Quantitative questions that need to be addressed:

1) Recompute product costs for DELTA1 and DELTA2 by completing the work Dana Boar has started.

Please solve the case leveraging the case headings provided.

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