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Variance Analysis: A Comprehensive Guide

2025-07-07

Variance Analysis: A Comprehensive Guide

In business, even small deviations from the plan can have a big impact. Understanding why performance differs from expectations is key to staying in control. That’s where variance analysis comes in as a fundamental tool in management accounting that compares planned financial outcomes with actual results.

Variance analysis helps organisations gain actionable insights into operational efficiency, cost control, and strategic decision-making. In this guide, we'll explore its principles, applications and calculations to empower businesses in optimising financial health.

What Is Variance Analysis?

Variance analysis examines deviations between budgeted and actual figures across revenue, costs or operational metrics. It is used to transform raw data into actionable intelligence by categorising variances as favourable (actual performance better than expected) or unfavourable (worse than expected). For instance, if raw material costs exceed projections due to supplier price hikes, this unfavourable variance prompts supply chain reviews.

If we go beyond problem identification, we'll see that it drives continuous improvement by highlighting efficiency gaps and validating forecasting models.

The Role of Variance Analysis in Performance Management 

Most businesses perform variance analysis on a periodic basis: monthly, quarterly or annually. This is done in enough detail to allow managers to understand what's happening to the business while not overburdening staff. However, by the time the information is produced, it is already out of date. 

Using a software solution helps businesses meet the demands of decision makers in a more timely way. Real-time, detailed variance analysis is now possible with technology solutions, and the right solution should enable finance to do more than simply present the numbers to the board. 

Mercur's performance management platform automates variance tracking, linking discrepancies to specific departments or activities for accountability. This granular visibility helps managers:

  • Identify inefficiencies (e.g., production delays inflating labour costs)

  • Reward outperformance (e.g., sales teams exceeding targets)

  • Refine future budgets using historical variance patterns

For dynamic performance optimisation, explore Mercur’s performance management solutions, which transform variance data into strategic adjustments.

Types of Variances 

Variance comes to life when applied to real-world business scenarios. Examining specific cases allows organisations to see how differences between planned and actual results reveal important insights. 

This is the reason businesses need to understand the different types of analysis, which shed light on a specific aspect of an organisation's financial performance. Breaking them down into categories means businesses can pinpoint exactly where results deviate from expectations and why. The foundation for meaningful budget variance analysis and improved decision-making is knowing the types of variances. 

Purchase Variance Analysis

Also known as purchase price variance (PPV), it deals with the difference between the actual price for goods and the standard or budgeted price. It helps businesses to measure procurement efficiency and understand cost discrepancies in purchasing. Businesses can also use it to identify areas for improvement in procurement. Let's see this with an example:
Suppose a company budgeted to purchase 1,000 units of a component at a standard price of £8 per unit. However, due to market fluctuations, the actual price paid was £9 per unit.

We calculate using the following formula:

PPV=(Actual Price−Standard Price)×Quantity Purchased
PPV = (£9 − £8) × 1,000 = £1 × 1,000 = £1,000 (unfavourable)

This means the company spent £1,000 more than expected on purchasing these components, resulting in an unfavourable purchase price variance. A favourable PPV occurs if bulk negotiations reduce per-unit costs below budget. So, let's say the same company managed a successful negotiation, where the actual price paid was only £7.50 per unit.

PPV = (£7.50 − £8.00) × 1,000 = (−£0.50) × 1,000 = −£500 (favourable)

This means the company spent £500 less than expected on purchasing these components, resulting in a favourable purchase price variance.

Sales Variance Analysis

The sales variance analysis examines the difference between the budgeted or forecasted sales and the actual sales. It's used to understand the reasons for the discrepancy and find ways to improve them. 

Let's see how this works if we use an example. Suppose a company budgeted to sell 4,000 units of a product at a standard price of £25 per unit. In reality, the company sold 4,500 units at an actual price of £23 per unit.

Sales Volume Variance=(Actual Units Sold−Budgeted Units)×Standard Price (4,500−4,000)×£25=500×£25=£12,500 (favourable)

Sales Price Variance=(Actual Price−Standard Price)×Actual Units Sold                                                        (£23−£25)×4,500=(−£2)×4,500=−£9,000 (unfavourable)

The company sold 500 more units than expected, resulting in a £12,500 favourable volume variance. However, the lower selling price of £23 instead of £25 caused a £9,000 unfavourable price variance. Overall, the net effect on revenue is a £3,500 favourable variance.

Overhead Variance Analysis

This process is used by businesses to understand whether they manage their resources well. It's also used for pricing products or services and controlling costs. 

For instance, a company budgets £30,000 for overhead costs in a given month, which includes expenses such as utilities, rent and maintenance. At the end of the month, the actual overhead costs total £33,500.

Overhead Variance=Actual Overhead−Budgeted Overhead
Overhead Variance = £33,500 − £30,000 = £3,500 (unfavourable)

The company spent £3,500 more on overhead than planned. This unfavourable variance might prompt management to investigate causes such as unexpected repairs, higher utility bills or inefficient resource use. It requires taking corrective actions to control overhead costs in future periods.

How about if the actual overhead costs come to £27,000?

Overhead Variance = £27,000 − £30,000 = −£3,000 (favourable)

In this case, the company spent £3,000 less than expected on overhead costs. This could be a result of energy-saving initiatives, negotiated lower rent or efficient maintenance scheduling. It reflects effective cost control.

Material Variance Analysis

The formula used in this analysis will help those businesses that wish to find out where they are using more materials than they actually need. It's a way for businesses to decide whether they should look for a new material supplier or continue with the existing one. Excessive usage variance may indicate wasteful production practices.

For example, a bakery sets a standard cost for flour at £0.80 per kilogram and expects to use 1,000 kg for the month. During the month, the bakery actually purchases 1,100 kg of flour but manages to pay only £0.75 per kilogram. The actual quantity of flour used is 950 kg, which is less than the standard quantity expected.

Material Price Variance=(Actual Price−Standard Price)×Actual Quantity                                                    (£0.75−£0.80)×1,100=(−£0.05)×1,100=−£55 (favourable)

Material Usage Variance=(Actual Quantity Used−Standard Quantity)×Standard Price (950−1,000)×£0.80=(−50)×£0.80=−£40 (favourable)

The bakery saved £55 by purchasing flour at a lower price than expected and saved £40 by using less flour than the standard allowance. Both variances are favourable, indicating effective cost control in purchasing and usage.

Now, let's see an unfavourable scenario. A furniture manufacturer sets a standard cost for wood at £12 per board foot and expects to use 5,000 board feet for production. However, during the month, the manufacturer purchases 5,200 board feet at £13 per board foot. The actual quantity of wood used is 5,300 board feet, exceeding the standard quantity.

(£13−£12)×5,200=£1×5,200=£5,200 (unfavourable)

(5,300−5,000)×£12=300×£12=£3,600 (unfavourable)

The manufacturer incurred £5,200 extra cost due to paying a higher price for wood and £3,600 more due to using more wood than planned. Both variances are unfavourable, signalling issues in procurement pricing and production efficiency.

Labour Variance Analysis

The formulas below are used to assess workforce cost-efficiency. So, for instance, a company sets a standard labour rate of £15 per hour and expects 1,200 hours to complete a job. However, the actual labour rate paid is £14 per hour, and the actual hours worked are 1,100.

Labor Rate Variance=(Actual Rate−Standard Rate)×Actual Hours

(£14−£15)×1,100=(−£1)×1,100=−£1,100(favourable)

Labor Efficiency Variance=(Actual Hours−Standard Hours)×Standard Rate

(1,100−1,200)×£15=(−100)×£15=−£1,500(favourable)

The company paid £1,100 less per hour than expected and used 100 fewer hours than budgeted, saving £1,500 in labour time. Both variances are favourable, indicating efficient labour cost management and productivity.

Unfavourable efficiency variance often points to training gaps or outdated workflows. So, if a manufacturing firm budgets a standard labour rate of £20 per hour and expects 800 hours for production. In reality, the actual labour rate is £22 per hour, and the actual hours worked are 900.

(£22−£20)×900=£2×900=£1,800(unfavourable)

(900−800)×£20=100×£20=£2,000(unfavourable)

This means that the company paid £1,800 more due to a higher wage rate and spent 100 extra hours, costing an additional £2,000. 

Efficiency Variance Analysis

Measures resource productivity beyond labour, like machine output per hour. Let's say a furniture manufacturer budgets to produce 1,000 chairs in a month. The standard cost to produce each chair is £50. Based on production plans, the standard output expected by this point in the month is 1,000 chairs. However, the actual output achieved is 1,100 chairs.

Efficiency Variance = (Actual Output − Standard Output) × Standard Cost per Unit

(1,100 − 1,000) × £50 = 100 × £50 = £5,000 (favourable)

The manufacturer produced 100 more chairs than planned at the standard cost per unit, resulting in a £5,000 favourable efficiency variance. This indicates better-than-expected productivity, as more output was achieved without increasing the standard cost per unit. Such a variance suggests effective use of resources and operational efficiency.

If the actual output had been less than the standard output, the variance would be unfavourable, signalling inefficiencies or production issues needing attention.

 

 

 

How To Automate Variance Analysis with Mercur

Mercur Business Control can become your organisation's primary tool for analysis and meets all your requirements for fixed and flexible reports, and dynamic analysis. 

Mercur Solutions has developed and delivered advanced and high-quality solutions for planning, reporting and analysis for over 40 years. Its corporate performance management and business intelligence software can support different technical environments and very diverse requirements for customers across the globe. 

 

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