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ACC/ACF 2200 Introduction to Management Accounting Week 4 (Chapter 3) Tutorial Solutions Semester 1, 2018 Note to students: Beware! These solutions are not necessarily model answers. In exams, you will not have demonstrated your understanding of the answers to these exercises if you seek only to memorise them. You are encouraged to use tutorial time to discuss issues that will test and clarify your understanding of these exercises, as well as expanding your analytical and critical-thinking skills.

3.3

Volume-based cost drivers are used in conventional management accounting systems. This assumes that variable costs vary in proportion to production volume and that fixed costs do not change with production volume. ABC allows a range of cost drivers—such as unit level, batch level, product level, and facility level—so that for these various types of cost there is a more realistic link between the cost and its cost driver. The conventional approach only examines variability with production volume—that is, at the unit level.

3.9

(a) Variable cost, assuming that rubber is the only direct material used in the manufacturing process. (b) Unit-level cost. (c) The number of tyres produced determines the quantity of rubber used in production and therefore the total direct material cost. If only the quantity of rubber used is the cost driver, it ignores any abnormal wastage incurred in the process, or the effects of changing supply and/or demand on rubber prices. To identify the cost driver from a cost management perspective, it is necessary to identify the underlying causes of the direct material cost.

3.14 The account classification method of cost estimation involves identifying costs as being of a particular type and analysing their past behaviour to understand the expected cost in the future. For example, a manager may identify the costs that will not change with changing production levels (the fixed costs), and separately address the costs that change with the levels of production (both variable costs and semi-variable costs). This way the estimation of costs is based on expected cost behaviour, especially in relation to levels of activity such as production volumes.

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EXERCISE 3.26 (15 minutes) Estimating cost behaviour; high–low method: manufacturer 1

Variable cost per number of machine hours = Total cost at 61 500 machine hours

$36 150 6 150

Variable cost at 61 500 machine hours (61 500 × $0.10 per machine hour) Fixed cost

$30 000

Cost equation:

Total utilities cost = $30 000 + $0.10X, where X denotes machine hours.

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Cost prediction when 39 000 machine hours are consumed: Utilities cost = $30 000 + ($0.10)(39 000) = $33 900

EXERCISE 3.27 (45 minutes) Estimating cost behaviour; regression analysis: manufacturer

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The calculations to estimate the company’s utilities cost behaviour are shown below, using Excel®. Some of the figures have been rounded.

Regression Statistics R

0.78833

R Square

0.62147

Adjusted R Square

0.58362 1 592.9189

S

12

Total number of observations

ANOVA d.f.

SS

MS

1.

41 658 750.

41 658 750.

Residual

10.

25 373 906.25

2 537 390.625

Total

11.

67 032 656.25

Regression

F

p-level

16.41795

0.00232

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Coefficients Intercept Machine hours

26 306.25 0.19167

From this, the equation to explain cost behaviour is as follows. Y = a + bX, where: X = the independent variable (activity for one month) Y = the dependent variable (cost for one month) Y = $26 306.25 + $0.192X This can be expressed as total cost = fixed costs of $26 306.25 plus $0.192 per machine hour. For comparison, this gives a cost at 39 000 machine hours: $26 306.25 + $0.192 x 39 000 = $33 794

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Given that this question does not assume knowledge of the appendix, the evaluation will focus on R2. In this case, the figure for R2—0.6215— . The higher the R2 figure, the more confident the accountant can be that changes in the dependent variable can be explained in terms of changes in the independent variable. In this case 38 per cent of the variability of utility costs remained unexplained.

CASE 3.42 (45 minutes) Interpreting regression analysis; activity-based costing: service firm

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Drake’s preliminary estimate for overhead of $18.00 per direct labour hour does not distinguish between fixed and variable overhead. This preliminary rate is applicable only to the activity level at which it was computed (36 000 direct labour hours per year) and may not be used to predict total overhead at other activity levels. The overhead rate developed from the least squares regression recognises the relationship between cost and volume in the data. The regression suggests that there is a component of the cost ($26 201 per month) that is unrelated to total direct labour hours. This cost component is the intercept on the vertical axis and is often considered to be the fixed cost as long as the activity level is within the relevant range. Thus, the least squares regression results in a cost function with two components: fixed cost per month and variable cost per direct labour hour. This cost formula can be used to predict total overhead at any activity level within the relevant range.

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2 Direct material

$400.00

Direct labour (5 DLH* × $19.00 per DLH)

95.00

Variable overhead (5 DLH × $9.27 per DLH)

46.35

Total variable cost per 1000 square metres

$541.35

* DLH denotes direct labour hours.

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The minimum bid should include the following incremental costs of the project: Direct material ($400.00 × 50)

$20 000.00

Direct labour ($95.00 × 50)

4 750.00

Variable overhead ($46.35 × 50)

2 317.50

Overtime premium ($9.50 per DLH × 5 DLH × 50 × .3)

712.50

Total variable costs for 50 000 square metres

$27 780.00

Variable costs per 1000 square metres in this bid

$

555.60

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Yes, Greenscape Pty Ltd can rely on the formula as long as Drake recognises that there are some shortcomings. The fact that least squares regression estimates cost behaviour increases the usefulness of rates calculated from cost data. However, the regression is based on historical costs that may change in the future, and Drake must assess whether the cost equation would need to be revised for future cost increases or decreases.

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(a)

Variable OH1 (50 × 5 × $4.10)

$1 025

Variable OH2 (50 × $13.50)

675

Variable OH3 (70 × $6.60)

462

Total incremental variable overhead

$2 162

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(b)

Variable OH1 (50 × 5 × $4.10) Variable OH2 (25 × $13.50)

337.50

Variable OH3 (230 × $6.60)

1 518.00

Total incremental variable overhead

(c)

$1 025.00

$2 880.50

The two scenarios in (a) and (b) differ in terms of the activities to be undertaken. Scenario (a) involves a large amount of seeding activity and relatively little planting activity. Scenario (b) involves considerably less seeding activity, but a great deal more planting activity. An activity-based costing system accounts for the different costs in projects involving different mixes of activity.

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