Variance analysis made simple, with a full worked example
A variance is the gap between what a cost should have been and what it actually was, split so you can see why. Here are the material and labour variances worked through Alma Roasters, with every figure reconciled so you can check the arithmetic yourself.
Variance analysis compares what a cost should have been, the standard, against what it actually was, and splits the difference into its causes. For a material, that split is price and usage; for labour, it is rate and efficiency. The point is not the number itself but the story it tells: a single total variance says something went wrong, while the split tells you what, which is the difference between knowing your costs overran and knowing why.
Standards and variances trip up more ACCA MA students than almost any other topic, usually because the formulas get memorised without the meaning. So we will work the whole thing through Alma Roasters, where Mateo Reyes has just closed a month and wants to know why his costs came in over plan.
The standard cost card
Before the month began, Mateo set a standard for what one bag of roasted coffee should cost in materials and labour:
| Per bag | Standard | Cost |
|---|---|---|
| Direct materials (green beans) | 0.3 kg at £8.00 / kg | £2.40 |
| Direct labour | 0.1 hours at £12.00 / hour | £1.20 |
During the month, Mateo actually produced 2,000 bags. Here is what really happened:
| Actual results (2,000 bags) | |
|---|---|
| Green beans used | 640 kg, costing £4,992 |
| Labour worked | 210 hours, costing £2,646 |
Two quick figures to pull out before we start, because the variance formulas need them. The actual price of the beans was £4,992 ÷ 640 = £7.80 per kg. The actual labour rate was £2,646 ÷ 210 = £12.60 per hour.
Materials: the standard for what was actually made
The golden rule of variances is that you compare against the standard for the output you actually achieved, not the output you planned. Mateo made 2,000 bags, so the standard allows 2,000 × 0.3 kg = 600 kg of beans, at a standard cost of 2,000 × £2.40 = £4,800. He actually spent £4,992, so the total materials variance is £4,800 − £4,992 = £192 adverse. Now we split it.
Material price variance
The price variance asks: for the beans we actually bought, did we pay more or less per kilo than standard? Take the difference in price and apply it to the actual quantity:
Price variance = (standard price − actual price) × actual quantity = (£8.00 − £7.80) × 640 kg = £0.20 × 640 = £128 favourable.
Favourable, because the beans came in 20p a kilo cheaper than standard. Mateo found a good lot at auction.
Material usage variance
The usage variance asks: did we use more or fewer kilos than we should have for what we made, valued at the standard price? The standard allowed 600 kg; he used 640 kg:
Usage variance = (standard quantity for actual output − actual quantity) × standard price = (600 − 640) × £8.00 = −40 × £8.00 = £320 adverse.
Adverse, because he used 40 kg more than the standard allowed. And here is the story the split reveals: the cheaper beans came with a lower yield, more chaff and waste in the roast, so the £128 Mateo saved on price cost him £320 in extra usage. A single total variance of £192 adverse would have hidden that completely.
The two parts must add back to the total: £128 favourable + £320 adverse = £192 adverse. They reconcile, so the working holds.
Labour: the same idea, different names
Labour works exactly like materials, with rate in place of price and efficiency in place of usage. Mateo made 2,000 bags, so the standard allows 2,000 × 0.1 = 200 hours at a standard cost of 2,000 × £1.20 = £2,400. He actually spent £2,646 on 210 hours, so the total labour variance is £2,400 − £2,646 = £246 adverse.
Labour rate variance
Rate variance = (standard rate − actual rate) × actual hours = (£12.00 − £12.60) × 210 = −£0.60 × 210 = £126 adverse.
Adverse, because Mateo paid 60p an hour above standard. He brought in a temp over a busy weekend at a premium rate.
Labour efficiency variance
Efficiency variance = (standard hours for actual output − actual hours) × standard rate = (200 − 210) × £12.00 = −10 × £12.00 = £120 adverse.
Adverse, because the work took 10 hours longer than the standard allowed. The temp was new and slower on the roaster, which is often how a rate variance and an efficiency variance turn out to be two halves of the same decision. Check the reconciliation: £126 adverse + £120 adverse = £246 adverse. Correct.
What the numbers tell Mateo
Pulled together, the month looks like this:
| Variance | Amount | What happened |
|---|---|---|
| Material price | £128 F | Cheaper beans bought |
| Material usage | £320 A | Lower yield, more waste |
| Labour rate | £126 A | Premium temp rate |
| Labour efficiency | £120 A | Temp slower on the roaster |
This is why variance analysis matters, and why MA keeps testing it. Mateo does not just learn that he overspent by £438 on the two costs combined. He learns that a decision to buy cheaper beans backfired through waste, and that covering a busy weekend with a premium temp cost him twice, once on rate and once on speed. Those are decisions he can change next month, which is the whole purpose of the exercise. Before you can build the standard cost card in the first place, you need to be able to split fixed and variable costs, which is exactly what the high-low method does.
Frequently asked questions
What is the difference between a price variance and a usage variance?
The price variance measures whether you paid more or less per unit of material than standard, calculated on the quantity you actually bought. The usage variance measures whether you used more or less material than the standard allowed for your output, valued at the standard price. Price is about the rate you paid; usage is about how much you consumed.
Why do you use standard hours for actual output, not budgeted output?
Because a variance should compare like with like. If you made more or fewer units than planned, the budget is no longer a fair benchmark. Flexing the standard to the output you actually achieved isolates genuine efficiency and price effects from the simple fact that volume changed.
What does adverse and favourable mean in variance analysis?
Favourable means the actual result was better for profit than the standard, usually a lower cost or a higher price. Adverse means it was worse, usually a higher cost. Adverse variances are not always bad decisions and favourable ones are not always good, which is why the causes matter more than the labels.
Do material price and usage variances always add up to the total?
Yes, and checking that they do is the fastest way to catch an error. The price variance plus the usage variance must equal the total material variance. If they do not reconcile, you have used the wrong quantity or price somewhere in one of the two calculations.