Introduction to Six Sigma

Six Sigma is usually related to the magic number of 3.4 defects per million opportunities. People often view Six Sigma as yet another rigorous statistical quality control mechanism.

Pioneered at Motorola in the mid-1980s, Six Sigma was initially targeted to quantify the defects occurred during manufacturing processes, and to reduce those defects to a very small level. Motorola claimed to have saved several million dollars. Another very popular success was at GE. Six Sigma contributed over US $ 300 million to GE's 1997 operating income.

Today Six Sigma is delivering business excellence, higher customer satisfaction, and superior profits by dramatically improving every process in an enterprise from financial to operational to production. Six Sigma has become a darling of a wide spectrum of industries, from health care to insurance to telecommunications to software.

What is Six Sigma?

It is important to recall that every customer always values consistent and predicable services and/or products with near zero defects. Therefore they experience the variation and not the mean. Mean is their expectation or our target.

If we can measure process variations that cause defects i.e. unacceptable deviation from the mean or target, we can work towards systematically managing the variation to eliminate defects.

Six Sigma is a methodology focused on creating breakthrough improvements by managing variation and reducing defects in processes across the enterprise.

Sigma is a Greek symbol represented by "σ".

Why do we call Six Sigma as Six Sigma and not Four or Five Sigma or Eight Alpha (another Greek symbol)? Sigma is a statistical term that measures process deviation from process mean or target. Mean is also referred as average in common language. The figure of six was arrived statistically by looking at the current average maturity of most business enterprises. We would like to revise this figure to 8 or may be 9 provided the world becomes a more orderly and predictable (even with increasing entropy or chaos) place to live!

We have a detailed discussion on keywords "breakthrough improvement" and "variation" apart from the "methodology" in later sections.

Example

Let us take an example to bring a breakthrough improvement in our current understanding of the concept of Six Sigma. This requires us to have basic knowledge of statistics. We have a detailed discussion on required statistical concepts later.

Consider a pizza delivery shop that guarantees the order delivery with 30 minutes from the time of accepting an order. In the event of a delivery time miss, the customer is refunded 100% money. The management took a target (read mean) of delivering every pizza order within 15 minutes and aligned its processes to meet this goal.

If we collect data of delivery times over a large number of the delivery made by the pizza shop and make a frequency distribution graph, we discover that it resembles a "bell shaped curve". A frequency distribution graph is constructed from the frequency table; a frequency table lists different time intervals (called classes) like 0 to 2 minute, 2 to 4 minutes, to 14 to 16 minutes to 28 to 30 minutes and the count of the deliveries made in each interval. The mean is found to be 16 minutes and standard deviation (measure of deviation or dispersion in data i.e. σ) is found as 2.5 minutes. A graph drawn from the data of over 5000 deliveries made is given below. Note, this not a real graph and is used only for illustration purposes.

This bell shape curved is called "normal distribution" in statistical terms. In real life, a lot of frequency distributions follow normal distribution, as is the case in the pizza delivery times. Natural variations cause such a distribution or deviation. One of the characteristics of this distribution is that 68% of area (i.e. the data points) falls within the area of -1σ and +1σ on either side of the mean. Similarly, 2σ on either side will cover approximately 95.5% area. 3σ on either side from mean covers almost 99.7% area. A more peaked curve (e.g. more and more deliveries were made on target) indicates lower variation or more mature and capable process. Whereas a flatter bell curve indicates higher variation or less mature or capable process.

After this statistical detour let us come back to our pizza example. If the pizza shop delivers 68% of pizza orders in time, we call it a "One Sigma shop". Similarly, if the pizza shop makes 95.5% deliveries on time, we call it a "Two Sigma shop". In our example, data suggests that it is almost a "Three Sigma shop".

We should now be able to appreciate why management took a delivery time target of 15 minutes and not 30 minutes. Imagine what would have happened with a 30 minutes delivery time target!

The "delivery time" is a critical-to-quality parameter from the customer perspective and has a significant impact on profits. In addition, it is an entry barrier for the competition. Such a parameter is called a CTQ and its definition in context of our pizza shop is given below:

CTQ Name: Timely Pizza delivery
CTQ Measure: Time in Minutes
CTQ Specification: Delivery with 30 minutes from the order acceptance time

Now we can easily define a defect:

Defect: Delivery that takes longer than 30 minutes
Unit: Order
Opportunity: 1 per order i.e. only "1" defect can occur in "1" order

Technical Note: This discussion on the example did not include 1.5σ process shift during the above analysis. The concept is discussed later. The Six Sigma conversion graph including a 1.5σ shift in process is given below:

This graph is on a logarithmic scale. Notice the increasing rate of improvement. For example, 1 sigma to 3 sigma is only 10 times improvement; 3 sigma to 4 sigma is a big 10 times improvement; whereas 5 sigma to 6 sigma is a whooping 1825 times change. That is why we are talking about breakthrough improvements in a journey to Six Sigma.

How does Six Sigma work?

The driving force behind any Six Sigma project comes from its primary focus - "bringing breakthrough improvements in a systematic manner by managing variation and reducing defects". This requires us to ask tougher questions, raise the bar significantly, and force people to think out of the box and to be innovative. The objective is to stretch, stretch mentally and not physically. To make this journey successful there is a methodology(s) to support Six Sigma implementations.

There are 2 potential scenarios - (a) there is already an existing process(s) that is working "reasonably" well and (b) there is no process at all. A bad process is as good as no process.

Scenario (a) focuses on significant process improvements and requires use of DMAIC:

1. Define process goals in terms of key critical parameters (i.e. critical to quality or critical to production) on the basis of customer requirements or Voice Of Customer (VOC)
2. Measure the current process performance in context of goals
3. Analyze the current scenario in terms of causes of variations and defects
4. Improve the process by systematically reducing variation and eliminating defects
5. Control future performance of the process

Scenario (b) focuses on process design using Design For Six Sigma (DFSS) approach. DFSS typically requires IDOV:

1. Identify process goals in terms of critical parameters, industry & competitor benchmarks, VOC
2. Design involves enumeration of potential solutions and selection of the best
3. Optimize performance by using advanced statistical modeling and simulation techniques and design refinements
4. Validate that design works in accordance to the process goals

Note, sometimes a DMAIC project may turn into a DFSS project because the process in question requires complete re-design to bring about the desired degree of improvement. Such a discovery usually occurs during improvement phase of DMAIC.

In addition to the methodology, what counts in this journey is being smart and innovative

Variance Analysis

Variance Analysis

A variance is the difference between an actual result and an expected result. The process by which the total difference between standard and actual results is analysed is known as variance analysis. When actual results are better than the expected results, we have a favourable variance (F). If, on the other hand, actual results are worse than expected results, we have an adverse (A).

I will use this example throughout this Exercise: Standard cost of Product A $ Materials (5kgs x $10 per kg) 50 Labour (4hrs x $5 per hr) 20 Variable o/hds (4 hrs x $2 per hr) 8 Fixed o/hds (4 hrs x $6 per hr) 24 102 Budgeted results Production: 1,200 units Sales: 1,000 units Selling price: $150 per unit ACTUAL Results Production: 1,000 units Sales: 900 units Materials: 4,850 kgs, $46,075 Labour: 4,200 hrs, $21,210 Variable o/hds: $9,450 Fixed o/hds: $25,000 Selling price: $140 per unit

1. Variable cost variances

Direct material variances

The direct material total variance is the difference between what the output actually cost and what it should have cost, in terms of material.

From the example above the material total variance is given by:

	$
1,000 units should have cost (x $50)	50,000
But did cost	46,075
Direct material total variance	3, 925 (F)

It can be divided into two sub-variances

The direct material price variance

This is the difference between what the actual quantity of material used did cost and what it should have cost.

	$
4,850 kgs should have cost (x $10)	48,500
But did cost	46,075
Direct material price variance	2,425 (F)

The direct material usage variance

This is the difference between how much material should have been used for the number of units actually produced and how much material was used, valued at standard cost

1,000 units should have used (x 5 kgs)	5,000 kgs
But did use	4,850 kgs
Variance in kgs	150 kgs (F)
Valued at standard cost per kg	x $10
Direct material usage variance in $	$1,500 (F)

The direct material price variance is calculated on material purchases in the period if closing stocks of raw materials are valued at standard cost or material used if closing stocks of raw materials are valued at actual cost (FIFO).

Direct labour total variance

The direct labour total variance is the difference between what the output should have cost and what it did cost, in terms of labour.

	$
1,000 units should have cost (x $20)	20,000
But did cost	21,210
Direct material price variance	1,210 (A)

Direct labour rate variance

This is the difference between what the actual number of hours worked should have cost and what it did cost.

4200hrs should have cost (4200hrs x $5)	$21000
But did cost	$21210
Direct labour rate variance	$210(A)

The direct labour efficiency variance

The is the difference between how many hours should have been worked for the number of units actually produced and how many hours were worked, valued at the standard rate per hour.

	$
1,000 units should have taken (x 4 hrs)	4,000 hrs
But did take	4,200 hrs
Variance in hrs	200 hrs
Valued at standard rate per hour	x $5
Direct labour efficiency variance	$1,000 (A)

When idle time occurs the efficiency variance is based on hours actually worked (not hours paid for) and an idle time variance (hours of idle time x standard rate per hour) is calculated.

2. Variable production overhead total variances

The variable production overhead total variance is the difference between what the output should have cost and what it did cost, in terms of variable production overhead.

	$
1,000 units should have cost (x $8)	8,000
But did cost	9,450
Variable production o/hd expenditure variance	1,450 (A)

The variable production overhead expenditure variance

This is the difference between what the variable production overhead did cost and what it should have cost

	$
4,200 hrs should have cost (x $2)	8,400
But did cost	9,450
Variable production o/hd expenditure variance	1,050 (A)

The variable production overhead efficiency variance

This is the same as the direct labour efficiency variance in hours, valued at the variable production overhead rate per hour.

Labour efficiency variance in hours	200 hrs (A)
Valued @ standard rate per hour	x $2
Variable production o/hd efficiency variance	$400 (A)

3. Fixed production overhead variances

The total fixed production variance is an attempt to explain the under- or over-absorbed fixed production overhead.

Remember that overhead absorption rate =	Budgeted fixed production overhead
	Budgeted level of activity

If either the numerator or the denominator or both are incorrect then we will have under- or over-absorbed production overhead.

• If actual expenditure ± budgeted expenditure (numerator incorrect) » expenditure variance
• If actual production / hours of activity » budgeted production / hours of activity (denominator incorrect) » volume variance.
• The workforce may have been working at a more or less efficient rate than standard to produce a given output » volume efficiency variance (similar to the variable production overhead efficiency variance).
• Regardless of the level of efficiency, the total number of hours worked could have been more or less than was originally budgeted (employees may have worked a lot of overtime or there may have been a strike and so actual hours worked were less than budgeted) » volume capacity variance.

4. The fixed production overhead variances are calculated as follows:

Fixed production overhead variance

This is the difference between fixed production overhead incurred and fixed production overhead absorbed (= the under- or over-absorbed fixed production overhead)

	$
Overhead incurred	25,000
Overhead absorbed (1,000 units x $24)	24,000
Overhead variance	1,000 (A)

Fixed production overhead expenditure variance

This is the difference between the budgeted fixed production overhead expenditure and actual fixed production overhead expenditure

	$
Budgeted overhead (1,200 x $24)	28,800
Actual overhead	25,000
Expenditure variance	3,800 (F)

Fixed production overhead volume variance

This is the difference between actual and budgeted production volume multiplied by the standard absorption rate per unit.

	$
Actual production at std rate (1,000 x $24)	24,000
Budgeted production at std rate (1,200 x $24)	28,800
	4,800 (A)

Fixed production overhead volume efficiency variance

This is the difference between the number of hours that actual production should have taken, and the number of hours actually worked (usually the labour efficiency variance), multiplied by the standard absorption rate per hour.

Labour efficiency variance in hours	200 hrs (A)
Valued @ standard rate per hour	x $6
Volume efficiency variance	$1,200 (A)

Fixed production overhead volume capacity variance

This is the difference between budgeted hours of work and the actual hours worked, multiplied by the standard absorption rate per hour

Budgeted hours (1,200 x 4)	4,800 hrs
Actual hours	4,200 hrs
Variance in hrs	600 hrs (A)
x standard rate per hour	x $6
	$3,600 (A)

KEY. The fixed overhead volume capacity variance is unlike the other variances in that an excess of actual hours over budgeted hours results in a favourable variance and not an adverse variance as it does when considering labour efficiency, variable overhead efficiency and fixed overhead volume efficiency. Working more hours than budgeted produces an over absorption of fixed overheads, which is a favourable variance.

Sales variances

5. Selling price variance

The selling price variance is a measure of the effect on expected profit of a different selling price to standard selling price. It is calculated as the difference between what the sales revenue should have been for the actual quantity sold, and what it was.

	$
Revenue from 900 units should have been (x $150)	135,000
But was (x $140)	126,000
Selling price variance	9,000 (A)

Sales volume variance

The sales volume variance is the difference between the actual units sold and the budgeted quantity, valued at the standard profit per unit. In other words it measures the increase or decrease in standard profit as a result of the sales volume being higher or lower than budgeted.

Budgeted sales volume	1,000 units
Actual sales volume	900 units
Variance in units	100 units (A)
x standard margin per unit (x $ (150 – 102) )	x $48
Sales volume variance	$4,800 (A)

KEY. Don’t forget to value the sales volume variance at standard contribution marginal costing is in use.

Operating Statement

Operating statements

The most common presentation of the reconciliation between budgeted and actual profit is as follows.

                                                 $              $

Budgeted profit before sales and admin costs                                                                                        X

Sales variances          - price                                X

                                      - volume                                                                                            X

                                                                                                                                                                                         X

Actual sales minus standard cost of sales                                                                                                   X

Cost variances                                                                                         $              $

(F)                                 (A)

Material price                                                                                          X

Material usage etc                                                               __                         X

                                                                                                         X                            X                                  X

Sales and administration costs                                                                                 X

Actual profit                                                                                                                                                        X

Variances in a standard marginal costing system

• No fixed overhead volume variance
• Sales volume variances are valued at standard contribution margin (not standard profit margin)

Reasons, interdependence and significance

6. Reasons for variances

Material price

• (F) – unforseen discounts received, greater care taken in purchasing, change in material standard
• (A)– price increase, careless purchasing, change in material standard.

Material usage

• (F) – material used of higher quality than standard, more effective use made of material
• (A) – defective material, excessive waste, theft, stricter quality control

Labour rate

• (F) – use of workers at rate of pay lower than standard
• (A) – wage rate increase

Idle time

• Machine breakdown, non-availability of material, illness

Labour efficiency

• (F) – output produced more quickly than expected because of work motivation, better quality of equipment or materials
• (A) – lost time in excess of standard allowed, output lower than standard set because of deliberate restriction, lack of training, sub-standard material used.

Overhead expenditure

• (F) – savings in cost incurred, more economical use of services.
• (A) – increase in cost of services used, excessive use of services, change in type of services used

Overhead volume

• (F) – production greater than budgeted
• (A) – production less than budgeted

7. Interdependence between variances

The cause of one (adverse) variance may be wholly or partly explained by the cause of another (favourable) variance.

• Material price or material usage and labour efficiency
• Labour rate and material usage
• Sales price and sales volume

8. The significance of variances

The decision as to whether or not a variance is so significant that it should be investigated should take a number of factors into account.

• The type of standard being used
• Interdependence between variances
• Controllability
• Materiality

9. Materials mix and yield variances

The materials usage variance can be subdivided into a materials mix variance and a materials yield variance if the proportion of materials in a mix is changeable and controllable.

The mix variance indicates the effect on costs of changing the mix of material inputs.

The yield variance indicates the effect on costs of material inputs yielding more or less than expected.

Standard input to produce 1 unit of product X:

		$
Material A	20 kgs x $10	200
Material B	30 kgs x $5	150
		350

In period 3, 13 units of product X were produced from 250 kgs of material A and 350 kgs of material B.

Solution 1: individual prices per kg as variance valuation cases

Mix Variance

                                                                                                                                      Kgs

Standard mix of actual use:      A: 2/5 x (250+350)   240

                                                                            B: 3/5 x (250+350)    360

                                                                                                                                      600

                                                                                                                                      ===

                                                                            A                                   B

Mix should have been                           240 kgs                         360 kgs

But was                                             250 kgs              350 kgs

Mix variance in kgs              10 kgs (A)              10 kgs (F)

x standard cost per kg                          x $10                                        x $5

Mix variance in $                             $100 (A)                              $50 (F)

                                                                        =====                       ===

                                       50 (A)

Total mix variance in quantity is always zero.

Yield variance

                                                                                                                   A                                   B

13 units of product X should have used       260 kgs             390 kgs

but actual input in standard mix was                   240 kgs              360 kgs

Yield variance in kgs                                                                           20 kgs (F) 30 kgs (F)

x standard cost per kg                                                                x $10                              x $5

                                                                                                          $200 (F)                        $150 (F)

                                                                                                         =====                           =====

                                                                                                                                      $350 (F)

                                                                                                                                      ====

Solution 2: budgeted weighted average price per unit of input as variance valuation base.

Therefore, Budgeted weighted average price =$350/50 = $7 per kg

•                 Mix variance

A                                   B

13 units of product X should have used     260 kgs               390 kgs

but did use                                                                                       250 kgs                        350 kgs

Usage variance in kgs                                                                          10 kgs (F)         40 kgs (F)

x individual price per kg – budgeted

weighted average price per kg

$ (10 – 7)                                                                              x $3

$ (5 – 7)                                                                                                    ____                             x ($2)

                                                                                                                   $30 (F)                                   $80 (A)

                                                                                                                   ===                                         ===

                                                                                                                                      $50 (A)

                                                                                                                                      ===

•                 Yield variance

A                                   B

Usage variance in kgs                                                                   10 kg (F)                      40 kg (F)

x budgeted weighted average

Price per kg                                                                                   x $7           x $7

                                                                                                          $70 (F)                        $ 280 (F)

                                                                                                          ===           ====

                                                                                                                            $350 (F)

                                                                                                                            ====

10. Sales mix and quantity variances

The sales volume variance can be subdivided into a mix variance if the proportions of products sold are controllable.

Sales mix variance

This variance indicates the effect on profit of changing the mix of actual sales from the standard mix.

It can be calculated in one of two ways.

• The difference between the actual total quantity sold in the standard mix and the actual quantities sold, valued at the standard margin per unit.
• The difference between actual sales and budgeted sales, valued at (standard profit per unit – budgeted weighted average profit per unit)

Sales quantity variance

This variance indicates the effect on profit of selling a different total quantity from the budgeted total quantity.

It can be calculated in one of two ways.

• The difference between actual sales volume in the standard mix and budgeted sales valued at the standard margin per unit.
• The difference between actual sales volume and budgeted sales valued at the budgeted weighted average profit per unit.

KEY. With all variance calculations, from the most basic (such as variable cost variances) to the more complex (such as mix and yield / mix and quantity variances), it is vital that you do not simply learn formulae. You must understand what your calculations are supposed are supposed to show.

VARIANCES ANALYSIS PRACTICE QUESTIONS

Question 1

Standard Cost for Product RBT

	£
Materials (10kg x £8 per kg)	80
Labour (5hrs x £6 per hr) ¬	30
Variable O/Hds (5hrs x £8 per hr)	40
Fixed O/Hds (5hrs x £9 per hr)	45
	195

Budgeted Results
Production	10000 units
Sales	7500 units
Selling Price	£300 per unit

Actual Results
Production	8000 units
Sales	6000 units
Materials	85000 kg Cost £700000
Labour	36000 hrs Cost £330900
Variable O/Hds	£400000
Fixed O/Hds	£500000
Selling Price	£260 per unit

Calculate

1. Material total variance
2. Material price variance
3. Material usage variance
4. Labour total variance
5. Labour rate variance
6. Labour efficiency variance
7. Variable overhead total variance and all sub- variances
8. Fixed Production overhead total Variance and all sub-variances
9. Selling price variance
10. Sales volume variance

Question 2

Standard Cost for Product TUH
	£
Materials (10kg x £8 per kg)	80
Labour (5hrs x £6 per hr) ¬	30
Variable O/Hds (5hrs x £8 per hr)	40
Fixed O/Hds (5hrs x £9 per hr)	45
	195

Budgeted Results
Production	11000 units
Sales	7500 units
Selling Price	£300 per unit

Actual Results
Production	9000 units
Sales	7000 units
Materials	85000 kg Cost £700000
Labour	36000 hrs Cost £330900
Variable O/Hds	£410000
Fixed O/Hds	£520000
Selling Price	£260 per unit

Calculate

1. Material total variance
2. Material price variance
3. Material usage variance
4. Labour total variance
5. Labour rate variance
6. Labour efficiency variance
7. Variable overhead total variance and all sub- variances
8. Fixed Production overhead total Variance and all sub-variances
9. Selling price variance
10. Sales volume variance

Question 3

Standard Cost for Product TD
	£
Materials (10kg x £5 per kg)	50
Labour (5hrs x £6 per hr) ¬	30
Variable O/Hds (5hrs x £8 per hr)	40
Fixed O/Hds (5hrs x £9 per hr)	45
	165

Budgeted Results
Production	8000 units
Sales	7500 units
Selling Price	£300 per unit

Actual Results
Production	11000 units
Sales	10000 units
Materials	85000 kg Cost £700000
Labour	36000 hrs Cost £330900
Variable O/Hds	£400000
Fixed O/Hds	£500000
Selling Price	£320 per unit

Calculate

1. Material total variance
2. Material price variance
3. Material usage variance
4. Labour total variance
5. Labour rate variance
6. Labour efficiency variance
7. Variable overhead total variance and all sub- variances
8. Fixed Production overhead total Variance and all sub-variances
9. Selling price variance
10. Sales volume variance

Question 4

Standard Cost for Product WXYZ
	£
Materials (4kg x £8 per kg)	32
Labour (5hrs x £10 per hr) ¬	50
Variable O/Hds (5hrs x £8 per hr)	40
Fixed O/Hds (5hrs x £6 per hr)	30
	152

Budgeted Results
Production	10000 units
Sales	7500 units
Selling Price	£300 per unit

Actual Results
Production	8000 units
Sales	6000 units
Materials	85000 kg Cost £700000
Labour	36000 hrs Cost £330900
Variable O/Hds	£400000
Fixed O/Hds	£500000
Selling Price	£260 per unit

Calculate

1. Material total variance
2. Material price variance
3. Material usage variance
4. Labour total variance
5. Labour rate variance
6. Labour efficiency variance
7. Variable overhead total variance and all sub- variances
8. Fixed Production overhead total Variance and all sub-variances
9. Selling price variance
10. Sales volume variance

Question 5

Standard Cost for Product RTY
	£
Materials (10kg x £8 per kg)	80
Labour (5hrs x £6 per hr) ¬	30
Variable O/Hds (5hrs x £8 per hr)	40
Fixed O/Hds (5hrs x £9 per hr)	45
	195

Budgeted Results
Production	13000 units
Sales	10000 units
Selling Price	£300 per unit

Actual Results
Production	12000 units
Sales	9000 units
Materials	90000 kg Cost £750000
Labour	40000 hrs Cost £350000
Variable O/Hds	£500000
Fixed O/Hds	£600000
Selling Price	£350 per unit

Calculate

1. Material total variance
2. Material price variance
3. Material usage variance
4. Labour total variance
5. Labour rate variance
6. Labour efficiency variance
7. Variable overhead total variance and all sub- variances
8. Fixed Production overhead total Variance and all sub-variances
9. Selling price variance
10. Sales volume variance

Question 6

Standard Cost for Product RED
	£
Materials (10kg x £7 per kg)	70
Labour (5hrs x £6 per hr) ¬	30
Variable O/Hds (5hrs x £8 per hr)	40
Fixed O/Hds (5hrs x £9 per hr)	45
	185

Budgeted Results
Production	10500 units
Sales	7800 units
Selling Price	£310 per unit

Actual Results
Production	8500 units
Sales	6200 units
Materials	87000 kg Cost £700000
Labour	36000 hrs Cost £330900
Variable O/Hds	£400000
Fixed O/Hds	£550000
Selling Price	£270 per unit

Calculate

1. Material total variance
2. Material price variance
3. Material usage variance
4. Labour total variance
5. Labour rate variance
6. Labour efficiency variance
7. Variable overhead total variance and all sub- variances
8. Fixed Production overhead total Variance and all sub-variances
9. Selling price variance
10. Sales volume variance

Question 7

Standard Cost for Product BUZZ
	£
Materials (3kg x £8 per kg)	24
Labour (5hrs x £10 per hr) ¬	50
Variable O/Hds (5hrs x £9 per hr)	45
Fixed O/Hds (5hrs x £10 per hr)	50
	169

Budgeted Results
Production	10000 units
Sales	7500 units
Selling Price	£300 per unit

Actual Results
Production	8000 units
Sales	6000 units
Materials	85000 kg Cost £700000
Labour	36000 hrs Cost £330900
Variable O/Hds	£400000
Fixed O/Hds	£500000
Selling Price	£260 per unit

Calculate

1. Material total variance
2. Material price variance
3. Material usage variance
4. Labour total variance
5. Labour rate variance
6. Labour efficiency variance
7. Variable overhead total variance and all sub- variances
8. Fixed Production overhead total Variance and all sub-variances
9. Selling price variance
10. Sales volume variance

Question 8

Standard Cost for Product RST
	£
Materials (10kg x £20per kg)	200
Labour (5hrs x £16 per hr) ¬	80
Variable O/Hds (5hrs x £8 per hr)	40
Fixed O/Hds (5hrs x £9 per hr)	45
	365

Budgeted Results
Production	1000 units
Sales	7500 units
Selling Price	£800 per unit

Actual Results
Production	8000 units
Sales	6000 units
Materials	85000 kg Cost £700000
Labour	36000 hrs Cost £330900
Variable O/Hds	£400000
Fixed O/Hds	£500000
Selling Price	£260 per unit

Calculate

1. Material total variance
2. Material price variance
3. Material usage variance
4. Labour total variance
5. Labour rate variance
6. Labour efficiency variance
7. Variable overhead total variance and all sub- variances
8. Fixed Production overhead total Variance and all sub-variances
9. Selling price variance
10. Sales volume variance

Question 9

Standard Cost for Product FGT
	£
Materials (10kg x £8 per kg)	80
Labour (5hrs x £6 per hr) ¬	30
Variable O/Hds (5hrs x £8 per hr)	40
Fixed O/Hds (5hrs x £9 per hr)	45
	195

Budgeted Results
Production	10000 units
Sales	7500 units
Selling Price	£300 per unit

Actual Results
Production	13000 units
Sales	6000 units
Materials	85000 kg Cost £700000
Labour	36000 hrs Cost £330900
Variable O/Hds	£400000
Fixed O/Hds	£500000
Selling Price	£260 per unit

Calculate

1. Material total variance
2. Material price variance
3. Material usage variance
4. Labour total variance
5. Labour rate variance
6. Labour efficiency variance
7. Variable overhead total variance and all sub- variances
8. Fixed Production overhead total Variance and all sub-variances
9. Selling price variance
10. Sales volume variance

Question 10

Standard Cost for Product White Diamond
	£
Materials (7kg x £9 per kg)	63
Labour (6hrs x £9 per hr) ¬	54
Variable O/Hds (6hrs x £6 per hr)	36
Fixed O/Hds (6hrs x £7 per hr)	42
	195

Budgeted Results
Production	12500 units
Sales	8500 units
Selling Price	£500 per unit

Actual Results
Production	15000 units
Sales	8000 units
Materials	8750 kg Cost £85000
Labour	5200hrs Cost £52900
Variable O/Hds	£25500
Fixed O/Hds	£84000
Selling Price	£600 per unit

1. Material total variance
2. Material price variance
3. Material usage variance
4. Labour total variance
5. Labour rate variance
6. Labour efficiency variance
7. Variable overhead total variance and all sub- variances
8. Fixed Production overhead total Variance and all sub-variances
9. Selling price variance
10. Sales volume variance