Variance analysis compares actual performance with a standard or budget. Calculating a variance is only the first step. Good management accounting explains why it occurred, how related variances interact, who can investigate it and whether corrective action will improve the business.
Basic variance interpretation rule
Under the convention used in this lesson:
- Favourable (F): actual profit is higher, or actual cost is lower, than the flexed standard.
- Adverse (A): actual profit is lower, or actual cost is higher, than the flexed standard.
Always compare actual cost with the standard cost allowed for the actual output. Comparing actual cost with an original static budget can confuse an output-volume difference with an efficiency or price problem.
Direct material variances
Material price variance = Actual quantity × (Standard price − Actual price)
Material usage variance = Standard price × (Standard quantity for actual output − Actual quantity)
Worked material variance example
Standard material for 1,000 units is 2 kg per unit at $5 per kg. Actual usage is 2,100 kg at $4.80 per kg.
- Standard quantity = 1,000 × 2 kg = 2,000 kg
- Price variance = 2,100 × ($5.00 − $4.80) = $420 F
- Usage variance = $5.00 × (2,000 − 2,100) = $500 A
- Net material cost variance = $420 F − $500 A = $80 A
The lower purchase price did not create an overall saving because the business used 100 kg more than allowed. A likely explanation is that cheaper material was lower quality, although handling, machine settings, training, product design or an unrealistic standard could also be responsible.
Direct labour variances
Labour rate variance = Actual hours × (Standard rate − Actual rate)
Labour efficiency variance = Standard rate × (Standard hours for actual output − Actual hours)
A favourable rate variance can be connected to an adverse efficiency variance when less-experienced employees receive a lower wage but take longer. The reverse can occur when skilled employees earn a higher rate yet complete work faster with fewer errors.
Other causes include overtime premiums, staff shortages, learning curves, machine downtime, poor scheduling, weak supervision, defective materials and changes in production methods. See the detailed lesson on direct labour cost variances.
Variable overhead variances
When variable overhead is absorbed using labour or machine hours, the two common components are:
- Expenditure variance: the difference between the standard variable overhead rate and the actual rate for the hours worked.
- Efficiency variance: the overhead effect of using more or fewer activity hours than the standard allowed.
The efficiency variance often mirrors the underlying labour- or machine-efficiency issue. Managers should avoid investigating the same operational cause twice as if it were two unrelated problems.
Fixed overhead variances
- Expenditure variance: budgeted fixed overhead minus actual fixed overhead.
- Volume variance: absorbed fixed overhead minus budgeted fixed overhead.
The volume variance arises because actual production differs from budgeted production. Depending on the system, it may be analysed into capacity and efficiency components, and sometimes a calendar component. Review overhead cost variances.
Sales variances
A sales price variance and a sales volume variance should be interpreted together. A price reduction may create an adverse price variance but increase demand enough to produce a favourable volume variance. A premium price can create the opposite combination.
Market growth, competitor action, product mix, sales incentives, service quality, stock availability and economic conditions may all contribute. See sales variance analysis.
Important relationships between variances
| Variance pattern | Possible relationship | Evidence to check |
|---|---|---|
| Material price F + usage A | Lower-grade material may create waste or defects. | Supplier, rejection, scrap and rework records |
| Labour rate A + efficiency F | More-skilled employees may work faster. | Skill mix, hours, quality and throughput |
| Sales price A + volume F | A discount may have increased demand. | Contribution, customer mix and campaign data |
| Labour efficiency A + variable overhead efficiency A | Both may result from excess activity hours. | Downtime, scheduling and machine logs |
| Fixed overhead volume A | Output was below the budgeted level. | Demand, capacity, shutdown and inventory data |
Controllable versus uncontrollable causes
Responsibility should follow influence, not simply the department name attached to a report. Purchasing may negotiate material prices, but production decisions may determine emergency order quantities. Production may control usage, but material quality or product design may be the real cause. External inflation or regulation may be outside a manager’s control.
Joint investigation is often more useful than assigning blame to one person.
Planning and operational variances
An adverse total variance may occur because the original standard became unrealistic after a major market change. Separating a planning variance from an operational variance helps distinguish forecasting error from execution performance. Standards should not be revised merely to hide poor performance, but they should remain relevant and attainable.
When should a variance be investigated?
Materiality is important, but a small variance may still signal fraud, safety risk, customer harm or a recurring process failure. Consider:
- absolute value and percentage size;
- whether it repeats or is part of a trend;
- the cost and likely benefit of investigation;
- controllability and speed of response;
- impact on quality, customers and future periods; and
- whether favourable and adverse variances offset each other.
Frequently asked questions
Is every favourable variance good?
No. Lower spending can reduce quality, capacity, employee development or future sales.
Why must variances be flexed for actual output?
It separates the effect of producing a different volume from price, rate and efficiency performance.
Who is responsible for a material usage variance?
Production often influences usage, but purchasing quality, engineering design, maintenance and standards can also contribute.
Can one cause create several variances?
Yes. Machine downtime can affect labour efficiency, variable overhead efficiency, output volume and sales availability.
What is the purpose of variance analysis?
To support learning, control and better decisions—not merely to calculate differences or assign blame.
Continue learning: begin with the full variance analysis overview and use the Management Accounting learning path.
- Materiality. Small variations in a single period are bound to occur and are unlikely to be significant. Obtaining and ‘explanation ‘is likely to be time-consuming and irritating from the manager concerned. The explanation will offer be ‘chance ‘which is not, in any case,
Particularly helpful. For such variations further investigation is not worthwhile. - Controllable. Controllable must also influence the decision whether to investigate further. If there is general worldwide price increase in the price increase in the price of an important raw material there is nothing that can be done internally to control the effect of this. If a central decision is made to award all examples a 10% increase in salary, staff costs in division A will increase by this amount and variance is not controllable by division A’s manager. Uncontrollable
Variances call for a change in the plan’ not an investigation into past. - Variance tread. If, say, an efficiency variance is RS. 1,000 adverse in month 1, the obvious conclusion is that the process is out of control and that corrective action must be taken. This may be correct but what if the same variance is Rs. 1,000adverse every month? The trend indicates that the process is in control and the standard has been wrongly set. Suppose, though, that the same variance is consistently Rs.1,000 advise for each of the first six months of the year but that production has steadily fallen form 100 units in month 1 to 65 units by month6.The variance trend in absolute terms is constant, but relative to the number of units produced, efficiency has tot steadily worse.
Variance analysis is a mend of assessing performance, but it is only a method of signaling to management areas of possible weakness where control action might be necessary. It does not provide a ready-made diagnosis of faults, nor does it provide management with a reedy made indication of what action needs to be taken. It merely highlights items for possible investigation.
Individual variances should not be looked at in isolation. As an obvious example, favorable sales price variance is likely to be accompanied by an adverse sales volume variance: the increase in price has caused a fall in demand. We now know in addition that set of variances should be scrutinized for a number of successive periods if their full significance is to be appreciated.
Here are some of the signals that may be extracted form variance trend information,
- Materials price variances may be favorable for a few months, then shift to adverse variances from the next few months and so on. This could indicate that process are seasonal and perhaps stock could be built up it cheap seasons.
- Regular, perhaps fairly slight, increase in adverse rice variances usually indicates the working of general inflation. If desired allowance could be made for general inflation when flexing the budget.
- Rapidly large increases in adverse price variances may suggest a scudded scarcity of a resource.
- Gradually improving labour efficiency variances may signal the existences of a learning curve , or the success of a productivity bonus scheme. In either case opportunities should be sought to encourage the trend.
- Worsening trends in machine running expenses may show up that equipment is deteriorating and will soon need repair or even replacement.
Here is an example,
- Material price and usage—if cheaper materials are purchased in order to obtain a favorable price variance, materials wastage might be higher and an adverse usage variance will occur. If the cheaper material is more difficult to handle, there might be an adverse labour efficiency variance too. If more expensive material is purchased, however the price variance will be adverse but the usage variance might favorable.
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