Internal Business Processes
–
Average number of errors per tax return
Ratio of billable hours to total hours
Average time needed to prepare a return
+
–
Learning
And Growth
Percentage of job offers accepted
Employee morale
+
+
Amount of compensation paid above industry average
Average number of years to be promoted
+
–
Exercise 10-13 (continued)
2. The hypotheses underlying the balanced scorecard are indicated by the arrows in the diagram. Reading from the bottom of the balanced scorecard, the hypotheses are:
° If the amount of compensation paid above the industry average increases, then the percentage of job offers accepted and the level of employee morale will increase.
° If the average number of years to be promoted decreases, then the percentage of job offers accepted and the level of employee morale will increase.
° If the percentage of job offers accepted increases, then the ratio of billable hours to total hours should increase while the average number of errors per tax return and the average time needed to prepare a return should decrease.
° If employee morale increases, then the ratio of billable hours to total hours should increase while the average number of errors per tax return and the average time needed to prepare a return should decrease.
° If employee morale increases, then the customer satisfaction with service quality should increase.
° If the ratio of billable hours to total hours increases, then the revenue per employee should increase.
° If the average number of errors per tax return decreases, then the customer satisfaction with effectiveness should increase.
° If the average time needed to prepare a return decreases, then the customer satisfaction with efficiency should increase.
° If the customer satisfaction with effectiveness, efficiency and service quality increases, then the number of new customers acquired should increase.
° If the number of new customers acquired increases, then sales should increase.
° If revenue per employee and sales increase, then the profit margin should increase.
Exercise 10-13 (continued)
Each of these hypotheses can be questioned. For example, Ariel’s customers may define effectiveness as minimizing their tax liability which is not necessarily the same as minimizing the number of errors in a tax return. If some of Ariel’s customers became aware that Ariel overlooked legal tax minimizing opportunities, it is likely that the “customer satisfaction with effectiveness” measure would decline. This decline would probably puzzle Ariel because, although the firm prepared what it believed to be error-free returns, it overlooked opportunities to minimize customers’ taxes. In this example, Ariel’s internal business process measure of the average number of errors per tax return does not fully capture the factors that drive the customer satisfaction. The fact that each of the hypotheses mentioned above can be questioned does not invalidate the balanced scorecard. If the scorecard is used correctly, management will be able to identify which, if any, of the hypotheses are invalid and then modify the balanced scorecard accordingly.
3. The performance measure “total dollar amount of tax refunds generated” would motivate Ariel’s employees to aggressively search for tax minimization opportunities for its clients. However, employees may be too aggressive and recommend questionable or illegal tax practices to clients. This undesirable behavior could generate unfavorable publicity and lead to major problems for the company as well as its customers. Overall, it would probably be unwise to use this performance measure in Ariel’s scorecard.
However, if Ariel wanted to create a scorecard measure to capture this aspect of its client service responsibilities, it may make sense to focus the performance measure on its training process. Properly trained employees are more likely to recognize viable tax minimization opportunities.
Exercise 10-13 (continued)
4. Each office’s individual performance should be based on the scorecard measures only if the measures are controllable by those employed at the branch offices. In other words, it would not make sense to attempt to hold branch office managers responsible for measures such as the percent of job offers accepted or the amount of compensation paid above industry average. Recruiting and compensation decisions are not typically made at the branch offices. On the other hand, it would make sense to measure the branch offices with respect to internal business process, customer, and financial performance. Gathering this type of data would be useful for evaluating the performance of employees at each office.
Exercise 10-14 (20 minutes)
1. If the total variance is $330 unfavorable, and if the rate variance is $150 favorable, then the efficiency variance must be $480 unfavorable, since the rate and efficiency variances taken together always equal the total variance.
Knowing that the efficiency variance is $480 unfavorable, one approach to the solution would be:
Efficiency Variance = SR (AH – SH)
$6 per hour (AH – 420 hours*) = $480 U
$6 per hour × AH – $2,520 = $480**
$6 per hour × AH = $3,000
AH = 500 hours
-
*
168 batches × 2.5 hours per batch = 420 hours
**
When used with the formula, unfavorable variances are positive and favorable variances are negative.
2. Knowing that 500 hours of labor time were used during the week, the actual rate of pay per hour can be computed as follows:
Rate Variance = AH (AR – SR)
500 hours (AR – $6 per hour) = $150 F
500 hours × AR – $3,000 = -$150*
500 hours × AR = $2,850
AR = $5.70 per hour
-
*
When used with the formula, unfavorable variances are positive and favorable variances are negative.
Exercise 10-14 (continued)
An alternative approach to each solution would be to work from known to unknown data in the columnar model for variance analysis:
-
Actual Hours of Input, at the Actual Rate
Actual Hours of Input, at the Standard Rate
Standard Hours Allowed for Output, at the Standard Rate
(AH × AR)
(AH × SR)
(SH × SR)
500 hours × $5.70 per hour
500 hours × $6 per hour*
420 hours§ × $6 per hour*
= $2,850
= $3,000
= $2,520
Rate Variance, $150 F*
Efficiency Variance, $480 U
Total Variance, $330 U*
§168 batches × 2.5 hours per batch = 420 hours
*Given
Exercise 10-15 (45 minutes)
1. a.
-
Actual Quantity of Inputs, at Actual Price
Actual Quantity of Inputs, at Standard Price
Standard Quantity Allowed for Output, at Standard Price
(AQ × AP)
(AQ × SP)
(SQ × SP)
7,000 feet × $5.75 per foot
7,000 feet × $6.00 per foot
5,250 feet* × $6.00 per foot
= $40,250
= $42,000
= $31,500
Price Variance, $1,750 F
6,000 feet × $6.00 per foot
= $36,000
Quantity Variance, $4,500 U
*1,500 units × 3.5 feet per unit = 5,250 feet
Alternatively:
Materials Price Variance = AQ (AP – SP)
7,000 feet ($5.75 per foot – $6.00 per foot) = $1,750 F
Materials Quantity Variance = SP (AQ – SQ)
$6.00 per foot (6,000 feet – 5,250 feet) = $4,500 U
Exercise 10-15 (continued)
b. The journal entries would be:
|
Raw Materials (7,000 feet × $6 per foot) |
42,000 |
|
|
Materials Price Variance (7,000 feet × $0.25 F per foot) |
|
1,750 |
|
Accounts Payable (7,000 feet × $5.75 per foot) |
|
40,250 |
|
|
|
|
|
Work in Process (5,250 feet × $6 per foot) |
31,500 |
|
|
Materials Quantity Variance (750 feet U × $6 per foot) |
4,500 |
|
|
Raw Materials (6,000 feet × $6 per foot) |
|
36,000 |
2. a.
-
Actual Hours of Input, at the Actual Rate
Actual Hours of Input, at the Standard Rate
Standard Hours Allowed for Output, at the Standard Rate
(AH × AR)
(AH × SR)
(SH × SR)
$8,120
725 hours × $10 per hour
600 hours* × $10 per hour
= $7,250
= $6,000
Rate Variance, $870 U
Efficiency Variance, $1,250 U
Total Variance, $2,120 U
*1,500 units × 0.4 hour per unit = 600 hours
Alternatively:
Labor Rate Variance = AH (AR – SR)
725 hours ($11.20 per hour* – $10.00 per hour) = $870 U
*$8,120 ÷ 725 hours = $11.20 per hour
Labor Efficiency Variance = SR (AH – SH)
$10 per hour (725 hours – 600 hours) = $1,250 U
Exercise 10-15 (continued)
b. The journal entry would be:
|
Work in Process (600 hours × $10 per hour) |
6,000 |
|
|
Labor Rate Variance (725 hours × $1.20 U per hour) |
870 |
|
|
Labor Efficiency Variance (125 U hours × $10 per hour) |
1,250 |
|
|
Wages Payable (725 hours × $11.20 per hour) |
|
8,120 |
3. The entries are: (a) purchase of materials; (b) issue of materials to production; and (c) incurrence of direct labor cost.
Raw Materials |
|
Accounts Payable |
||||||
(a) |
42,000 |
(b) |
36,000 |
|
|
|
(a) |
40,250 |
Bal. |
6,0001 |
|
|
|
|
|
|
|
Materials Price Variance |
|
Wages Payable |
||||||
|
|
(a) |
1,750 |
|
|
|
(c) |
8,120 |
|
|
|
|
|
|
|
|
|
Materials Quantity Variance |
|
Labor Rate Variance |
||||||
(b) |
4,500 |
|
|
|
(c) |
870 |
|
|
|
|
|
|
|
|
|
|
|
Work in Process |
|
Labor Efficiency Variance |
||||||
(b) |
31,5002 |
|
|
|
(c) |
1,250 |
|
|
(c) |
6,0003 |
|
|
|
|
|
|
|
11,000 feet of material at a standard cost of $6.00 per foot
2Materials used
3Labor cost
Problem 10-16 (45 minutes)
1. a.
-
Actual Quantity of Inputs, at Actual Price
Actual Quantity of Inputs, at Standard Price
Standard Quantity Allowed for Output, at Standard Price
(AQ × AP)
(AQ × SP)
(SQ × SP)
25,000 pounds × $2.95 per pound
25,000 pounds × $2.50 per pound
20,000 pounds* × $2.50 per pound
= $73,750
= $62,500
= $50,000
Price Variance,
$11,250 U
19,800 pounds × $2.50 per pound
= $49,500
Quantity Variance, $500 F
*5,000 ingots × 4.0 pounds per ingot = 20,000 pounds
Alternatively:
Materials Price Variance = AQ (AP – SP)
25,000 pounds ($2.95 per pound – $2.50 per pound) = $11,250 U
Materials Quantity Variance = SP (AQ – SQ)
$2.50 per pound (19,800 pounds – 20,000 pounds) = $500 F
Problem 10-16 (continued)
b.
-
Actual Hours of Input, at the Actual Rate
Actual Hours of Input, at the Standard Rate
Standard Hours Allowed for Output, at the Standard Rate
(AH × AR)
(AH × SR)
(SH × SR)
3,600 hours × $8.70 per hour
3,600 hours × $9.00 per hour
3,000 hours* × $9.00 per hour
= $31,320
= $32,400
= $27,000
Rate Variance, $1,080 F
Efficiency Variance, $5,400 U
Total Variance, $4,320 U
*5,000 ingots × 0.6 hour per ingot = 3,000 hours
Alternatively:
Labor Rate Variance = AH (AR – SR)
3,600 hours ($8.70 per hour – $9.00 per hour) = $1,080 F
Labor Efficiency Variance = SR (AH – SH)
$9.00 per hour (3,600 hours – 3,000 hours) = $5,400 U
Problem 10-16 (continued)
c.
-
Actual Hours of Input, at the Actual Rate
Actual Hours of Input, at the Standard Rate
Standard Hours Allowed for Output, at the Standard Rate
(AH × AR)
(AH × SR)
(SH × SR)
$4,320
1,800 hours × $2.00 per hour
1,500 hours* × $2.00 per hour
= $3,600
= $3,000
Spending Variance, $720 U
Efficiency Variance, $600 U
Total Variance, $1,320 U
*5,000 ingots × 0.3 hours per ingot = 1,500 hours
Alternatively:
Variable Overhead Spending Variance = AH (AR – SR)
1,800 hours ($2.40 per hour* – $2.00 per hour) = $720 U
*$4,320 ÷ 1,800 hours = $2.40 per hour
Variable Overhead Efficiency Variance = SR (AH – SH)
$2.00 per hour (1,800 hours – 1,500 hours) = $600 U
Problem 10-16 (continued)
2. Summary of variances:
-
Material price variance
$11,250
U
Material quantity variance
500
F
Labor rate variance
1,080
F
Labor efficiency variance
5,400
U
Variable overhead spending variance
720
U
Variable overhead efficiency variance
600
U
Net variance
$16,390
U
The net unfavorable variance of $16,390 for the month caused the plant’s variable cost of goods sold to increase from the budgeted level of $80,000 to $96,390:
-
Budgeted cost of goods sold at $16 per ingot
$80,000
Add the net unfavorable variance (as above)
16,390
Actual cost of goods sold
$96,390
This $16,390 net unfavorable variance also accounts for the difference between the budgeted net operating income and the actual net loss for the month.
-
Budgeted net operating income
$15,000
Deduct the net unfavorable variance added to cost of goods sold for the month
16,390
Net operating loss
$(1,390)
3. The two most significant variances are the materials price variance and the labor efficiency variance. Possible causes of the variances include:
-
Materials Price Variance:
Outdated standards, uneconomical quantity purchased, higher quality materials, high-cost method of transport.
Labor Efficiency Variance:
Poorly trained workers, poor quality materials, faulty equipment, work interruptions, inaccurate standards, insufficient demand.
Problem 10-17 (45 minutes)
1. The standard quantity of plates allowed for tests performed during the month would be:
-
Smears
2,700
Blood tests
900
Total
3,600
Plates per test
× 3
Standard quantity allowed
10,800
The variance analysis for plates would be:
-
Actual Quantity of Inputs, at Actual Price
Actual Quantity of Inputs, at Standard Price
Standard Quantity Allowed for Output, at Standard Price
(AQ × AP)
(AQ × SP)
(SQ × SP)
$38,400
16,000 plates × $2.50 per plate
10,800 plates × $2.50 per plate
= $40,000
= $27,000
Price Variance,
$1,600 F
14,000 plates × $2.50 per plate
= $35,000
Quantity Variance, $8,000 U
Alternative Solution:
Materials Price Variance = AQ (AP – SP)
16,000 plates ($2.40 per plate* – $2.50 per plate) = $1,600 F
*$38,400 ÷ 16,000 plates = $2.40 per plate.
Materials Quantity Variance = SP (AQ – SQ)
$2.50 per plate (14,000 plates – 10,800 plates) = $8,000 U
Problem 10-17 (continued)
Note that all of the price variance is due to the hospital’s 4% quantity discount. Also note that the $8,000 quantity variance for the month is equal to nearly 30% of the standard cost allowed for plates. This variance may be the result of using too many assistants in the lab.
2. a. The standard hours allowed for tests performed during the month would be:
-
Smears: 0.3 hour per test × 2,700 tests
810
Blood tests: 0.6 hour per test × 900 tests
540
Total standard hours allowed
1,350
The variance analysis of labor would be:
-
Actual Hours of Input, at the Actual Rate
Actual Hours of Input, at the Standard Rate
Standard Hours Allowed for Output, at the Standard Rate
(AH × AR)
(AH × SR)
(SH × SR)
$18,450
1,800 hours × $12 per hour
1,350 hours × $12 per hour
= $21,600
= $16,200
Rate Variance, $3,150 F
Efficiency Variance, $5,400 U
Total Variance, $2,250 U
Alternative Solution:
Labor Rate Variance = AH (AR – SR)
1,800 hours ($10.25 per hour* – $12.00 per hour) = $3,150 F
*$18,450 ÷ 1,800 hours = $10.25 per hour
Labor Efficiency Variance = SR (AH – SH)
$12 per hour (1,800 hours – 1,350 hours) = $5,400 U
Problem 10-17 (continued)
b. The policy probably should not be continued. Although the hospital is saving $1.75 per hour by employing more assistants relative to the number of senior technicians than other hospitals, this savings is more than offset by other factors. Too much time is being taken in performing lab tests, as indicated by the large unfavorable labor efficiency variance. And, it seems likely that most (or all) of the hospital’s unfavorable quantity variance for plates is traceable to inadequate supervision of assistants in the lab.
3. The variable overhead variances follow:
-
Actual Hours of Input, at the Actual Rate
Actual Hours of Input, at the Standard Rate
Standard Hours Allowed for Output, at the Standard Rate
(AH × AR)
(AH × SR)
(SH × SR)
$11,700
1,800 hours × $6 per hour
1,350 hours × $6 per hour
= $10,800
= $8,100
Spending Variance, $900 U
Efficiency Variance, $2,700 U
Total Variance, $3,600 U
Alternative Solution:
Variable Overhead Spending Variance = AH (AR – SR)
1,800 hours ($6.50 per hour* – $6.00 per hour) = $900 U
*$11,700 ÷ 1,800 hours = $6.50 per hour
Variable Overhead Efficiency Variance = SR (AH – SH)
$6 per hour (1,800 hours – 1,350 hours) = $2,700 U
Yes, the two variances are related. Both are computed by comparing actual labor time to the standard hours allowed for the output of the period. Thus, if there is an unfavorable labor efficiency variance, there will also be an unfavorable variable overhead efficiency variance.
Problem 10-18 (60 minutes)
1. a.
-
Actual Quantity of Inputs, at Actual Price
Actual Quantity of Inputs, at Standard Price
Standard Quantity Allowed for Output, at Standard Price
(AQ × AP)
(AQ × SP)
(SQ × SP)
21,120 yards × $3.35 per yard
21,120 yards × $3.60 per yard
19,200 yards* × $3.60 per yard
= $70,752
= $76,032
= $69,120
Price Variance, $5,280 F
Quantity Variance, $6,912 U
Total Variance, $1,632 U
*4,800 units × 4.0 yards per unit = 19,200 yards
Alternatively:
Materials Price Variance = AQ (AP – SP)
21,120 yards ($3.35 per yard – $3.60 per yard) = $5,280 F
Materials Quantity Variance = SP (AQ – SQ)
$3.60 per yard (21,120 yards – 19,200 yards) = $6,912 U
-
b.
Raw Materials (21,120 yards @ $3.60 per yard)
76,032
Materials Price Variance (21,120 yards @ $0.25 per yard F)
5,280
Accounts Payable (21,120 yards @ $3.35 per yard)
70,752
Work in Process (19,200 yards @ $3.60 per yard)
69,120
Materials Quantity Variance (1,920 yards U @ $3.60 per yard)
6,912
Raw Materials (21,120 yards @ $3.60 per yard)
76,032
Problem 10-18 (continued)
2. a.
-
Actual Hours of Input, at the Actual Rate
Actual Hours of Input, at the Standard Rate
Standard Hours Allowed for Output, at the Standard Rate
(AH × AR)
(AH × SR)
(SH × SR)
6,720 hours* × $4.85 per hour
6,720 hours × $4.50 per hour
7,680 hours** × $4.50 per hour
= $32,592
= $30,240
= $34,560
Rate Variance, $2,352 U
Efficiency Variance, $4,320 F
Total Variance, $1,968 F
-
*
4,800 units × 1.4 hours per unit = 6,720 hours
**
4,800 units × 1.6 hours per unit = 7,680 hours
Alternatively:
Labor Rate Variance = AH (AR – SR)
6,720 hours ($4.85 per hour – $4.50 per hour) = $2,352 U
Labor Efficiency Variance = SR (AH – SH)
$4.50 per hour (6,720 hours – 7,680 hours) = $4,320 F
-
b.
Work in Process (7,680 hours @ $4.50 per hour)
34,560
Labor Rate Variance (6,720 hours @ $0.35 per hour U)
2,352
Labor Efficiency Variance (960 hours F @ $4.50 per hour)
4,320
Wages Payable (6,720 hours @ $4.85 per hour)
32,592
Problem 10-18 (continued)
3. |
Actual Hours of Input, at the Actual Rate |
|
Actual Hours of Input, at the Standard Rate |
|
Standard Hours Allowed for Output, at the Standard Rate |
||||||||||
|
(AH × AR) |
|
(AH × SR) |
|
(SH × SR) |
||||||||||
|
6,720 hours × $2.15 per hour |
|
6,720 hours × $1.80 per hour |
|
7,680 hours × $1.80 per hour |
||||||||||
|
= $14,448 |
|
= $12,096 |
|
= $13,824 |
||||||||||
|
|
|
|
|
|
|
|
|
|||||||
|
Spending Variance, $2,352 U |
Efficiency Variance, $1,728 F |
|
||||||||||||
|
Total Variance, $624 U
|
|
|||||||||||||
Alternatively:
Variable Overhead Spending Variance = AH (AR – SR)
6,720 hours ($2.15 per hour – $1.80 per hour) = $2,352 U
Variable Overhead Efficiency Variance = SR (AH – SH)
$1.80 per hour (6,720 hours – 7,680 hours) = $1,728 F
4. No. This total variance is made up of several quite large individual variances, some of which may warrant investigation. A summary of variances is given below:
-
Materials:
Price variance
$5,280
F
Quantity variance
6,912
U
$1,632
U
Labor:
Rate variance
2,352
U
Efficiency variance
4,320
F
1,968
F
Variable overhead:
Spending variance
2,352
U
Efficiency variance
1,728
F
624
U
Net unfavorable variance
$ 288
U
Problem 10-18 (continued)
5. The variances have many possible causes. Some of the more likely causes include:
Materials variances:
Favorable price variance: Good price, inaccurate standards, inferior quality materials, unusual discount due to quantity purchased, drop in market price.
Unfavorable quantity variance: Carelessness, poorly adjusted machines, unskilled workers, inferior quality materials, inaccurate standards.
Labor variances:
Unfavorable rate variance: Use of highly skilled workers, change in wage rates, inaccurate standards, overtime.
Favorable efficiency variance: Use of highly skilled workers, high-quality materials, new equipment, inaccurate standards.
Variable overhead variances:
Unfavorable spending variance: Increase in costs, inaccurate standards, waste, theft, spillage, purchases in uneconomical lots.
Favorable efficiency variance: Same as for labor efficiency variance.
Problem 10-19 (45 minutes)
1. a. In the solution below, the materials price variance is computed on the entire amount of materials purchased, whereas the materials quantity variance is computed only on the amount of materials used in production:
-
Actual Quantity of Inputs, at Actual Price
Actual Quantity of Inputs, at Standard Price
Standard Quantity Allowed for Output, at Standard Price
(AQ × AP)
(AQ × SP)
(SQ × SP)
$46,000
8,000 pounds × $6.00 per pound
4,500 pounds* × $6.00 per pound
= $48,000
= $27,000
Price Variance, $2,000 F
6,000 pounds × $6.00 per pound = $36,000
Quantity Variance, $9,000 U
*3,000 units × 1.5 pounds per unit = 4,500 pounds
Alternatively:
Materials Price Variance = AQ (AP – SP)
8,000 pounds ($5.75 per pound* – $6.00 per pound) = $2,000 F
*$46,000 ÷ 8,000 pounds = $5.75 per pound
Materials Quantity Variance = SP (AQ – SQ)
$6 per pound (6,000 pounds – 4,500 pounds) = $9,000 U
b. No, the contract should probably not be signed. Although the new supplier is offering the material at only $5.75 per pound, it does not seem to hold up well in production as shown by the large materials quantity variance. Moreover, the company still has 2,000 pounds of unused material in the warehouse; if these materials do as poorly in production as the 6,000 pounds already used, the total quantity variance on the 8,000 pounds of materials purchased will be very large.
Problem 10-19 (continued)
2. a.
-
Actual Hours of Input, at the Actual Rate
Actual Hours of Input, at the Standard Rate
Standard Hours Allowed for Output, at the Standard Rate
(AH × AR)
(AH × SR)
(SH × SR)
1,600 hours* × $12.50 per hour
1,600 hours × $12.00 per hour
1,800 hours** × $12.00 per hour
= $20,000
= $19,200
= $21,600
Rate Variance, $800 U
Efficiency Variance, $2,400 F
Total Variance, $1,600 F
-
*
10 workers × 160 hours per worker
= 1,600 hours
**
3,000 units × 0.6 hours per unit
= 1,800 hours
Alternatively:
Labor Rate Variance = AH (AR – SR)
1,600 hours ($12.50 per hour – $12.00 per hour) = $800 U
Labor Efficiency Variance = SR (AH – SH)
$12.00 per hour (1,600 hours – 1,800 hours) = $2,400 F
b. Yes, the new labor mix should probably be continued. Although it increases the average hourly labor cost from $12.00 to $12.50, thereby causing an $800 unfavorable labor rate variance, this is more than offset by greater efficiency of labor time. Notice that the labor efficiency variance is $2,400 favorable. Thus, the new labor mix reduces overall labor costs.
Problem 10-19 (continued)
3. |
Actual Hours of Input, at the Actual Rate |
|
Actual Hours of Input, at the Standard Rate |
|
Standard Hours Allowed for Output, at the Standard Rate |
||||||||||
|
(AH × AR) |
|
(AH × SR) |
|
(SH × SR) |
||||||||||
|
$3,600 |
|
1,600 hours × $2.50 per hour |
|
1,800 hours × $2.50 per hour |
||||||||||
|
|
|
= $4,000 |
|
= $4,500 |
||||||||||
|
|
|
|
|
|
|
|
|
|||||||
|
Spending Variance, $400 F |
Efficiency Variance, $500 F |
|
||||||||||||
|
Total Variance, $900 F |
|
|||||||||||||
Alternatively:
Variable Overhead Spending Variance = AH (AR – SR)
1,600 hours ($2.25 per hour* – $2.50 per hour) = $400 F
*$3,600 ÷ 1,600 hours = $2.25 per hour
Variable Overhead Efficiency Variance = SR (AH – SH)
$2.50 per hour (1,600 hours – 1,800 hours) = $500 F
Both the labor efficiency variance and the variable overhead efficiency variance are computed by comparing actual labor-hours to standard labor-hours. Thus, if the labor efficiency variance is favorable, then the variable overhead efficiency variance will be favorable as well.
Problem 10-20 (30 minutes)
1. a., b., and c.
-
Month
1
2
3
4
Throughput time in days:
Process time
0.6
0.5
0.5
0.4
Inspection time
0.7
0.7
0.4
0.3
Move time
0.5
0.5
0.4
0.5
Queue time
3.6
3.6
2.6
1.7
Total throughput time
5.4
5.3
3.9
2.9
-
Manufacturing cycle efficiency (MCE):
Process time ÷ Throughput time
11.1%
9.4%
12.8%
13.8%
Delivery cycle time in days:
Wait time
9.6
8.7
5.3
4.7
Total throughput time
5.4
5.3
3.9
2.9
Total delivery cycle time
15.0
14.0
9.2
7.6
2. The general trend is favorable in all of the performance measures except for total sales. On-time delivery is up, process time is down, inspection time is down, move time is basically unchanged, queue time is down, manufacturing cycle efficiency is up, and the delivery cycle time is down. Even though the company has improved its operations, it has not yet increased its sales. This may have happened because management attention has been focused on the factory—working to improve operations. However, it may be time now to exploit these improvements to go after more sales—perhaps by increased product promotion and better marketing strategies. It will ultimately be necessary to increase sales so as to translate the operational improvements into more profits.
Problem 10-20 (continued)
3. a. and b.
-
Month
5
6
Throughput time in days:
Process time
0.4
0.4
Inspection time
0.3
Move time
0.5
0.5
Queue time
Total throughput time
1.2
0.9
Manufacturing cycle efficiency (MCE):
Process time ÷ Throughput time
33.3%
44.4%
As a company pares away non-value-added activities, the manufacturing cycle efficiency improves. The goal, of course, is to have an efficiency of 100%. This will be achieved when all non-value-added activities have been eliminated and process time equals throughput time.
Problem 10-21 (45 minutes)
The answers below are not the only possible answers. Ingenious people can figure out many different ways of making performance look better even though it really isn’t. This is one of the reasons for a balanced scorecard. By having a number of different measures that ultimately are linked to overall financial goals, “gaming” the system is more difficult.
1. Speed-to-market can be improved by taking on less ambitious projects. Instead of working on major product innovations that require a great deal of time and effort, R&D may choose to work on small, incremental improvements in existing products. There is also a danger that in the rush to push products out the door, the products will be inadequately tested and developed.
2. Performance measures that are ratios or percentages present special dangers. A ratio can be increased either by increasing the numerator or by decreasing the denominator. Usually, the intention is to increase the numerator in the ratio, but a manager may react by decreasing the denominator instead. In this case (which actually happened), the managers pulled telephones out of the high-crime areas. This eliminated the problem for the managers, but was not what the CEO or the city officials had intended. They wanted the phones fixed, not eliminated.
3. In real life, the production manager simply added several weeks to the delivery cycle time. In other words, instead of promising to deliver an order in four weeks, the manager promised to deliver in six weeks. This increase in delivery cycle time did not, of course, please customers and drove some business away, but it dramatically improved the percentage of orders delivered on time.
Problem 10-21 (continued)
4. As stated above, ratios can be improved by changing either the numerator or the denominator. Managers who are under pressure to increase the revenue per employee may find it easier to eliminate employees than to increase revenues. Of course, eliminating employees may reduce total revenues and total profits, but the revenue per employee will increase as long as the percentage decline in revenues is less than the percentage cut in number of employees. Suppose, for example, that a manager is responsible for business units with a total of 1,000 employees, $120 million in revenues, and profits of $2 million. Further suppose that a manager can eliminate one of these business units that has 200 employees, revenues of $10 million, and profits of $1.2 million.
-
Before eliminating the business unit
After eliminating the business unit
Total revenue
$120,000,000
$110,000,000
Total employees
1,000
800
Revenue per employee
$120,000
$137,500
Total profits
$2,000,000
$800,000
As these examples illustrate, performance measures should be selected with a great deal of care and managers should avoid placing too much emphasis on any one performance measure.
Problem 10-22 (30 minutes)
1. |
Lanolin quantity standard: |
|
|
|
Required per 100-liter batch |
100 |
liters |
|
Loss from rejected batches (100 liters × 1/20) |
5 |
liters |
|
Total quantity per good batch |
105 |
liters |
|
|
|
|
|
Alcohol quantity standard: |
|
|
|
Required per 100-liter batch |
8.0 |
liters |
|
Loss from rejected batches (8 liters × 1/20) |
0.4 |
liters |
|
Total quantity per good batch |
8.4 |
liters |
|
|
|
|
|
Lilac powder quantity standard: |
|
|
|
Required per 100-liter batch |
200 |
grams |
|
Loss from rejected batches (200 grams × 1/20) |
10 |
grams |
|
Total quantity per good batch |
210 |
grams |
|
|
|
|
2. |
Direct labor quantity standard: |
|
|
|
Total hours per day |
8 |
hours |
|
Less lunch, rest breaks, and cleanup |
2 |
hours |
|
Productive time each day |
6 |
hours |
|
Time required per batch |
120 |
minutes |
|
Lunch, rest breaks, and cleanup (120 minutes ÷ 3 batches) |
40 |
minutes |
|
Total |
160 |
minutes |
|
Loss from rejected batches (160 minutes × 1/20) |
8 |
minutes |
|
Total time per good batch |
168 |
minutes |
Problem 10-22 (continued)
3. Standard cost card:
|
|
Standard Quantity or Time per Batch |
Standard Price or Rate |
Standard Cost per Batch |
||
|
Lanolin |
105 |
liters |
€16 |
per liter |
€1,680.00 |
|
Alcohol |
8.4 |
liters |
€2 |
per liter |
16.80 |
|
Lilac powder |
210 |
grams |
€1 |
per gram |
210.00 |
|
Direct labor |
168 |
minutes |
€0.20 |
per minute |
33.60 |
|
Total standard cost per good batch |
|
|
|
|
€1,940.40 |
Problem 10-23 (60 minutes)
1. Both companies view training as important; both companies need to leverage technology to succeed in the marketplace; and both companies are concerned with minimizing defects. There are numerous differences between the two companies. For example, Applied Pharmaceuticals is a product-focused company and Destination Resorts International (DRI) is a service-focused company. Applied Pharmaceuticals’ training resources are focused on their engineers because they hold the key to the success of the organization. DRI’s training resources are focused on their front-line employees because they hold the key to the success of their organization. Applied Pharmaceuticals’ technology investments are focused on supporting the innovation that is inherent in the product development side of the business. DRI’s technology investments are focused on supporting the day-to-day execution that is inherent in the customer interface side of the business. Applied Pharmaceuticals defines a defect from an internal manufacturing standpoint, while DRI defines a defect from an external customer interaction standpoint.
Problem 10-23 (continued)
2. Students’ answers may differ in some details from this solution.