How to Do Variance Analysis From Start to Finish

Variance analysis is a financial management tool used to identify and explain differences between planned and actual financial results. It compares expected performance, often outlined in a budget, with what actually occurred over a specific period. This analysis provides insights into operational efficiencies and financial control. By examining these discrepancies, organizations can understand where and why performance deviated from targets, helping them make informed decisions and improve future planning.

Preparatory Steps for Variance Analysis

Setting clear and realistic standards is a foundational step for effective variance analysis. These standards serve as the baseline against which actual performance will be measured. For instance, a manufacturing company might establish a standard cost for materials, including a specific quantity and price per unit, or a standard time and rate for labor. Sales departments set standards for selling prices and expected sales volumes.

Standards are derived from various sources. Historical data provides a practical starting point, reflecting past operational performance. Engineering studies offer precise technical specifications for material usage or labor time. Market research helps establish realistic selling prices and sales volume expectations by analyzing consumer demand and competitor pricing.

There are two types of standards: ideal standards and attainable standards. Ideal standards represent the best possible performance under perfect conditions. Attainable standards are more realistic, allowing for normal inefficiencies, making them more practical for performance evaluation. Defining these standards precisely, including specific units, rates, and quantities, ensures accurate and meaningful analysis.

Calculating Key Variances

Material Variances

The material price variance measures the difference between the actual cost paid for materials and the standard cost. This variance highlights discrepancies from purchasing decisions or market fluctuations. It is calculated by subtracting the standard price from the actual price, then multiplying the result by the actual quantity of materials purchased. For example, if the standard material price was $10 per pound, but the actual price paid was $11 per pound for 2,000 pounds purchased, the variance would be ($11 – $10) 2,000 = $2,000 unfavorable.

The material quantity variance assesses the difference between the actual quantity of materials used and the standard quantity for the actual output. This variance indicates efficiency in material usage, often pointing to waste or spoilage. It is calculated by subtracting the standard quantity from the actual quantity and multiplying this difference by the standard price. For instance, if 1,000 units were produced, requiring a standard of 2 pounds per unit (2,000 pounds total), but 2,200 pounds were actually used, with a standard price of $10 per pound, the variance would be (2,200 – 2,000) $10 = $2,000 unfavorable.

Labor Variances

The labor rate variance identifies the difference between the actual hourly wage paid and the standard hourly wage. This variance can arise from using different skill levels of workers or unexpected changes in wage rates. It is calculated by taking the difference between the actual labor rate and the standard labor rate, then multiplying it by the actual hours worked. For example, if the standard labor rate was $20 per hour, but the actual rate paid was $19 per hour for 600 hours worked, the variance would be ($19 – $20) 600 = -$600, which is $600 favorable.

The labor efficiency variance measures the difference between the actual hours labor worked and the standard hours for the output achieved. This variance reflects workforce productivity, indicating whether more or less time was spent than planned. The calculation involves subtracting the standard hours from the actual hours and multiplying the result by the standard labor rate. If 1,000 units were produced, requiring a standard of 0.5 hours per unit (500 hours total), but 600 hours were actually worked with a standard rate of $20 per hour, the variance would be (600 – 500) $20 = $2,000 unfavorable.

Variable Overhead Variances

The variable overhead rate variance, also known as the variable overhead spending variance, measures the difference between the actual and standard variable overhead cost per unit of the activity base. This variance can be influenced by changes in the cost of indirect materials or utilities. It is calculated by subtracting the standard variable overhead rate from the actual variable overhead rate and multiplying by the actual hours of the activity base. If the standard variable overhead rate was $5 per direct labor hour, and $3,100 of variable overhead was incurred for 600 actual direct labor hours, the actual rate is $3,100 / 600 = $5.17 per hour. The variance would be ($5.17 – $5) 600 = $102 unfavorable (due to rounding).

The variable overhead efficiency variance determines the difference between the actual activity base hours and the standard activity base hours allowed for the actual output, multiplied by the standard variable overhead rate. This variance reflects the efficiency with which the activity base, often direct labor hours, was utilized. It is calculated by subtracting the standard hours allowed from the actual hours and multiplying the result by the standard variable overhead rate. If 1,000 units were produced, requiring a standard of 0.5 direct labor hours per unit (500 standard hours allowed), but 600 actual direct labor hours were used with a standard variable overhead rate of $5 per hour, the variance would be (600 – 500) $5 = $500 unfavorable.

Fixed Overhead Variances

The fixed overhead spending variance, sometimes called the budget variance, compares the actual fixed overhead costs incurred with the budgeted fixed overhead costs. This variance indicates whether more or less was spent on fixed overhead items like rent, insurance, or depreciation than planned. It is a straightforward comparison: actual fixed overhead minus budgeted fixed overhead. For example, if the budgeted fixed overhead was $10,000, but actual fixed overhead incurred was $10,500, the variance would be $10,500 – $10,000 = $500 unfavorable.

The fixed overhead volume variance, also known as the production volume variance, measures the difference between the budgeted fixed overhead and the fixed overhead applied to production based on standard hours allowed for actual output. It reflects the under- or over-absorption of fixed overhead. If budgeted fixed overhead was $10,000 for a budgeted production of 2,000 units (standard fixed overhead rate of $5 per unit), and actual production was 1,800 units, the fixed overhead applied would be 1,800 units $5/unit = $9,000. The variance would be $10,000 – $9,000 = $1,000 unfavorable.

Sales Variances

The sales price variance measures the difference between the actual selling price per unit and the standard selling price per unit, multiplied by the actual quantity sold. This variance indicates the impact of changes in selling prices on revenue. It is calculated as (Actual Selling Price – Standard Selling Price) Actual Quantity Sold. For instance, if the standard selling price was $50 per unit, but the actual selling price was $48 per unit, and 1,100 units were sold, the variance would be ($48 – $50) 1,100 = -$2,200, which is $2,200 unfavorable.

The sales volume variance measures the difference between the actual quantity of units sold and the standard (budgeted) quantity of units, multiplied by the standard contribution margin per unit. This variance reflects the impact of changes in sales volume on overall profitability. It is calculated as (Actual Sales Volume – Standard Sales Volume) Standard Contribution Margin Per Unit. If the standard sales volume was 1,200 units, but actual sales were 1,100 units, and the standard contribution margin per unit was $25, the variance would be (1,100 – 1,200) $25 = -$2,500, which is $2,500 unfavorable.

Interpreting Variance Results

After calculating variances, the next step involves understanding what these results signify. Variances are categorized as either “favorable” or “unfavorable.” A favorable variance indicates that actual results were better than the standard or budgeted amount, potentially leading to higher profits or lower costs. For example, a lower actual material price than budgeted would result in a favorable material price variance.

Conversely, an unfavorable variance means that actual results were worse than the standard, potentially leading to lower profits or higher costs. An example would be higher actual labor hours used than planned, resulting in an unfavorable labor efficiency variance. These labels simply denote a deviation from the standard, not necessarily a positive or negative outcome in all contexts.

Investigating the underlying causes of significant variances is crucial. A large unfavorable material price variance might be due to unexpected increases in raw material costs or a decision to purchase higher quality materials. An unfavorable labor efficiency variance could stem from less experienced workers, equipment breakdowns, or inefficient production processes. Understanding these root causes allows management to take corrective actions.

A variance alone does not provide the complete picture; context and further investigation are always necessary. For instance, a favorable material price variance achieved by purchasing lower-quality materials might lead to an unfavorable material quantity variance due to increased waste. Management must also consider materiality, which dictates when a variance is substantial enough to warrant detailed attention. Variances within an acceptable range, such as a deviation of less than 5% or a specific dollar amount threshold, might not require extensive investigation, allowing focus on more impactful deviations.

The Overall Variance Analysis Process

The variance analysis process begins with establishing clear and realistic standards. This involves setting precise benchmarks for costs, revenues, and operational efficiency.

The next step involves collecting actual data for the period under review. This includes gathering precise figures for actual costs incurred, such as material purchases and labor wages, as well as actual quantities produced and sold. Accurate and timely data collection is essential, typically sourced from accounting records, production logs, and sales reports.

Once both standards and actual data are available, calculating variances takes place. This involves applying specific formulas to determine the differences between actual and standard performance for various elements.

After calculations are complete, the process moves to analyzing and interpreting the results. This step involves reviewing the calculated variances, identifying whether they are favorable or unfavorable, and assessing their significance. Further investigation uncovers the underlying reasons for any substantial deviations.

The final step is reporting findings to relevant stakeholders. This involves communicating the results, identified causes, and potential corrective actions to management and other decision-makers. Effective reporting ensures insights gained are utilized to improve future planning, control costs, and enhance overall organizational performance.