What are the most common mistakes when conducting variance analysis?

1 Using the wrong budget

One of the first steps in variance analysis is to select the appropriate budget to compare with the actual results. However, sometimes the budget may be outdated, unrealistic, or based on inaccurate assumptions. This can lead to large and irrelevant variances that do not reflect the true performance of the business. To avoid this mistake, you should update your budget regularly, use flexible budgets that adjust for changes in activity levels, and base your budget on reliable data and reasonable expectations.

2 Ignoring the interdependence of variances

Another common mistake is to analyze each variance in isolation, without considering the impact of other variances on the same or related items. For example, a favorable sales volume variance may be offset by an unfavorable sales price variance, or a favorable direct material price variance may be caused by a lower quality of material that leads to an unfavorable direct material efficiency variance. To avoid this mistake, you should look at the net effect of all the variances on the income statement, and investigate the root causes and interrelationships of the variances.

4 Using variance analysis as a substitute for strategic planning

A fourth common mistake is to rely too much on variance analysis as the main source of feedback and decision making, and neglect the strategic planning and control process. Variance analysis can provide useful information about the past performance and the current situation, but it cannot replace the need for setting goals, developing strategies, and monitoring progress. To avoid this mistake, you should use variance analysis as a complement to strategic planning, and align your budget and variances with your long-term vision and objectives.

5 Communicating variance analysis poorly

A fifth common mistake is to communicate the results of variance analysis poorly, either by using too much jargon, presenting too many details, or failing to explain the implications and actions. This can lead to confusion, misunderstanding, or resistance among the stakeholders, such as senior management, investors, customers, or employees. To avoid this mistake, you should communicate the results of variance analysis clearly, concisely, and effectively, using simple language, charts, and tables, and highlighting the key messages, recommendations, and follow-ups.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?