Variance analysis is found by determining the difference between what was budgeted and what actually occurred. Additionally, when variances are added together, we get a better picture of how well a company is measuring its performance against expected metrics. It’s also important to be mindful that each metric is measured to determine what the actual cost is versus the industry’s standard cost.

Whether it’s materials, labor, electricity, or another metric, if the actual cost is lower than the standard cost for the same quantity of materials, it would be a favorable price variance. However, if the number of materials was more than the standard quantity, it would be considered an unfavorable variance. Examining variance allows us to analyze the price and quantity of the variable being analyzed. Always keep in mind that unusual or significant variances should be investigated to see why such anomalies exist.

It’s important to distinguish between variances and the types of inputs. When it comes to materials, labor, and similar variable overhead, variances to be analyzed are for price and quantity/efficiency. When it comes to fixed overhead, analysis looks at variances in budget and volume.

One way to conduct variance analysis is through the Column Method. The following example illustrates this:

A business produces widgets. The following assumptions are made:

• 6,000 widgets are produced in a month
• Direct labor hours are used as the basis to allocate overhead costs to products
• Denominator level of activity is 8,060 hours, resulting in $48,360 in fixed overhead expenses budgeted.

Other cost assumptions include:

Direct Costs

Labor: 2.6 hours/widget @ $14 per hour

Materials: 10 pieces/widget @ $1/widget

Overhead

Variable: 2.6 hours/widget @ $8/hour

Fixed: 1.3 hours /widget @ $12/hour

However, the business saw the following costs for the month’s production:

Variable overhead manufacturing costs: $34,000

Fixed overhead manufacturing costs: $50,000

Both of the following are Direct Costs:

Material: 50,000 items bought @ $0.96/widget

Labor: 8,000 hours totaling $128,000

Materials Variance

Real Quantity x Real Price = 50,000 pieces x $0.96 per widget = $48,000

Real Quantity x Industry Price = 50,000 pieces x $1 per widget = $50,000

Standard Quantity x Industry Price = 36,000 pieces x $1 per widget = $36,000

Price Variance = $50,000 – $48,000 = $2,000

Quantity Variance = $50,000 – $36,000 = $14,000

When we find the difference between these two amounts, there’s an unfavorable variance of $12,000. Additionally, it’s worth looking at why there were 50,000 pieces used versus the standardized 36,000 pieces. It could be due to defective materials, problematic machinery, etc.

Labor Variance

Real Hours x Real Rate = 8,000 hours x $16 per hour = $128,000

Real Hours x Industry Rate = 8,000 x $14 per hour = $112,000

Standard Hours x Industry Rate = 7,800 x $14 hour = $109,200

Rate Variance = $112,000 – $128,000 = -$16,000

Efficiency Variance = $109,200 – $112,000 = -$2,800

Based on this calculation, there’s a total unfavorable variance of -$18,800. Management should look at why labor costs are higher than the standard and why production took more supplies than the industry standard.

While this is not all-encompassing, it does show the importance of understanding the nuances of calculating variances and how it’s essential to understanding a business’ (in)efficiency.