ADM 2304 Lecture Notes - Lecture 22: Multicollinearity, Minitab, Dialog Box
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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 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 didnât 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
â product diversity was not recognized by the existing base(s) used for overhead
distribution,
â the amount of overhead was significant, and
â 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 âfifthâ activity that she called âgeneral operations.â 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 departmentâs resources.
But in the end, she chose direct labor, partly because she thought it did measure the productâs 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.
