# Variance Analysis in Budgeting & Accounting

## What is variance analysis?

Variance analysis is a technique used in accounting and financial management to compare actual results against forecasted results. It involves analyzing the differences between the resulting figures in order to identify the reasons for any variances, and take corrective action if necessary.

By conducting variance analysis, business can identify areas of success and focus on any potential improvements.

## Variance analysis formula

The formula for variance analysis can vary depending on the specific application, but a general formula for calculating variance is:

Variance = Actual Amount – Budgeted Amount

• Actual amount: the actual amount of a particular item, such as revenue or expenses, for a given period of time.
• Budgeted amount: the amount that was expected or planned for that same item for the same period of time.

The variance can be positive, indicating that the actual amount exceeded the budgeted amount, or negative, indicating that the actual amount fell short of the budgeted amount. A large positive or negative variance can be a sign that there may be issues that need to be addressed in order to improve financial performance.

In addition to this basic formula, there are many variations and specific formulas used for variance analysis in different fields and industries, such as manufacturing, healthcare, and project management.

## The role of variance analysis in budgeting

As discussed, variance analysis involves comparing actuals against expected results and analyzing the differences. The differences can be positive or negative, and they can be expressed as either favorable or unfavorable variances.

Favorable variances are those that result in better-than-expected financial performance, while unfavorable variances result in worse-than-expected performance. By comparing the variances, businesses can see the causes of the differences and take corrective actions to address any problems or capitalize on any opportunities.

## Why is variance analysis useful in budgeting?

### 1. It helps to monitor and evaluate financial performance

By comparing actual results to budgeted results, businesses can quickly identify areas where they are over or underperforming.

### 2. It can identify the causes of variances

Variance analysis enables businesses to identify the reasons for the differences between actual and budgeted results. This information is essential for developing corrective actions that can improve financial performance.

### 3. Business can evaluate the effectiveness of budgeting

By analyzing variances, businesses can evaluate how accurate their budgeting process is and make improvements if necessary.

### 4. Business can make informed decisions

By understanding the causes of variances, businesses can make informed decisions about resource allocation and prioritize areas where corrective actions are needed.

## What are the types of variances

There are several types of variance analysis.

### 1. Cost variance analysis

This type of variance analysis is used to identify the difference between the actual cost in producing a product or delivering a service and the expected cost. It is useful for identifying areas of inefficiency or cost overruns.

#### Cost variance analysis formula

CV = Earned Value (EV) – Actual Cost (AC)

• Earned value (EV) represents the budgeted cost of the work that has been completed up to the point of analysis, as determined by the project’s performance measurement baseline (PMB).
• Actual cost (AC) represents the actual cost incurred by the project up to the point of analysis.

If the resulting CV is a positive number, it means that the project is under budget. Conversely, if the CV is negative, it means that the project is over budget. A CV of zero means that the project is exactly on budget.

### 2. Revenue variance analysis

This type of variance analysis is used to identify the difference between actual revenue and expected revenue. It is useful for identifying areas where sales are falling short of expectations or where pricing strategies may need to be adjusted.

#### Revenue variance analysis formula

Revenue Variance = Actual Revenue – Expected Revenue

• Actual revenue: The revenue that a company has actually earned during a particular period.
• Expected revenue: The revenue that a company was forecasted or budgeted to earn during the same period.

If the revenue variance is positive, it means that the company has earned more revenue than expected. If the variance is negative, it means that the company has earned less revenue than expected.

### 3. Volume variance analysis

This type of variance analysis is used to identify the difference between actual sales volume and expected sales volume. It is useful for identifying areas where sales are falling short of expectations or where capacity utilization is not optimal.

#### Volume variance analysis formula

Volume Variance = (Actual Quantity – Budgeted Quantity) x Budgeted Price

• Actual quantity: The actual number of units sold or produced during a period.
• Budgeted quantity: The number of units that were planned to be sold or produced during a period.
• Budgeted price: The expected price per unit for the budgeted quantity.

The volume variance can be calculated for different elements of the business, such as sales or production, and can be used to determine the factors that caused the variance. If the volume variance is positive, it means that the actual quantity sold or produced exceeded the budgeted quantity, and if it is negative, it means that the actual quantity was lower than the budgeted quantity.

### 4. Material variance analysis

This type of variance analysis is used to identify the difference between the actual cost of materials used in production and the expected cost. It is useful for identifying areas where waste or inefficiency is occurring in the use of materials.

#### Material variance analysis formula

Material Cost Variance = (Actual Quantity of Material Used x Actual Cost of Material) – (Standard Quantity of Material Allowed x Standard Cost of Material)

• Actual quantity of material used: the total amount of materials actually used in production.
• Actual cost of material: the actual cost incurred to purchase the materials used in production.
• Standard quantity of material allowed: the amount of material that should have been used based on the standard set by the company.
• Standard cost of material: the standard cost of materials established by the company.

The material cost variance can be further broken down into two components:

A. Material price variance

The difference between the actual cost of materials purchased and the standard cost of materials that should have been paid.

Material Price Variance = (Actual Quantity of Material Used x (Actual Price – Standard Price))

B. Material usage variance

The difference between the actual amount of materials used and the standard amount of materials that should have been used.

Material Usage Variance = (Standard Price x (Actual Quantity of Material Used – Standard Quantity of Material Allowed))

### 5. Labor variance analysis

This type of variance analysis is used to identify the difference between the actual labor cost incurred and the expected cost. It is useful for identifying areas where labor inefficiencies or productivity issues may be occurring.

#### Labor variance analysis formula

Labor Variance = (Actual Hours Worked x Actual Rate) – (Standard Hours Allowed x Standard Rate)

• Actual hours worked: The total number of hours worked by employees during a specific period.
• Actual rate: The actual rate per hour paid to employees during the same period.
• Standard hours allowed: The standard number of hours allowed for completing a specific job or task.
• Standard rate: The standard rate per hour paid to employees for completing the same job or task.

By comparing the actual labor cost with the standard labor cost, managers can identify whether labor costs are higher or lower than expected. If the actual labor cost is higher than the standard labor cost, it indicates that the labor cost was not efficiently managed, and corrective actions need to be taken to reduce the cost. On the other hand, if the actual labor cost is lower than the standard labor cost, it indicates that the labor was managed efficiently, and the company can take steps to maintain or improve the current performance.

### 6. Overhead variance analysis

This type of variance analysis is used to identify the difference between the actual overhead cost incurred and the expected cost. It is useful for identifying areas where overhead costs are higher than expected, such as in utilities or rent.

#### Overhead variance analysis formula

Overhead Variance = Actual Overhead Costs – Budgeted/Standard Overhead Costs

• Actual overhead costs: The actual expenses incurred by a business during a particular period. These costs include all the indirect expenses associated with the production process, such as rent, utilities, depreciation, and indirect labor costs.
• Budgeted/standard overhead costs: The estimated or predetermined costs that a business expects to incur during a particular period. These costs are calculated based on various factors such as historical data, industry benchmarks, and production levels.

By comparing the actual overhead costs with the budgeted or standard overhead costs, businesses can identify the reasons for the variance and take corrective actions to control their overhead expenses.

## Problems with variance analysis

There are some potential problems that can arise when using variance analysis, including:

### Incomplete or inaccurate data

Variance analysis requires accurate and complete data in order to be effective. If the data used in the analysis is incomplete or inaccurate, the results will not be reliable or meaningful.

### Overreliance on averages

Averages can be useful for summarizing large amounts of data, but they can also be misleading if there is a lot of variation within the data. In some cases, it may be more useful to look at the distribution of the data or to use other statistical measures to gain a better understanding of the variability.

### Failure to consider all factors

Variance analysis typically focuses on financial data, but there may be nonfinancial factors that are also contributing to the variance. For example, changes in market conditions, customer preferences, or production processes may all have an impact on the results, but may not be reflected in the financial data.

### Inappropriate benchmarking

Variance analysis often involves comparing actual results to some kind of industry benchmark or standard. However, if the benchmark is inappropriate or unrealistic, the results may be misleading. It is important to carefully select the appropriate industry benchmarks and to adjust them as needed based on changes in the business environment.

### Failure to consider causality

Variance analysis can identify differences between actual and expected results, but it does not necessarily explain why those differences exist. It is important to dig deeper and identify the underlying causes in order to develop effective strategies for improvement.

## Example of Variance Analysis

Imagine a company that budgeted \$100,000 for sales revenue in a particular quarter but only achieved \$90,000 in actual sales revenue. The variance is -\$10,000, which indicates that the actual performance is worse than the planned performance.

The company can perform a variance analysis to identify the reasons for the variance. Possible reasons may include lower than expected sales volume, lower selling prices, or higher costs of goods sold. By identifying the cause of the variance, the company can take corrective action, such as adjusting sales strategies or reducing costs, to improve future performance.

## Using financial forecasting tools for financial analysis

Variance analysis is just one aspect of tracking and assessing your business’ financial performance and objectives. A financial forecasting tool can be an excellent companion for financial analysis as they help businesses make informed decisions based on accurate predictions of future financial performance.

The Brixx financial forecasting tool can ensure that variance analysis, alongside other financial components, are tracked and reported on with ease – simply needing a few data entries to be entered throughout the software. Sign up today for a trial.