Variance Analysis
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Variance analysis is the process of comparing actual results to planned or expected values to understand the reasons for differences.
Definition
Variance analysis is an analytical process that compares actual performance to planned, budgeted, or expected values, then investigates the causes of significant differences. Variance analysis answers "Did we hit the target?" and more importantly "Why or why not?" Analysis breaks total variance into components (volume variance, price variance, efficiency variance, etc.) to pinpoint specific causes. This enables targeted action—addressing the actual drivers of deviation rather than guessing at solutions.
Examples
Monthly production costs exceeded budget by $50,000. Variance analysis decomposed this into: material price variance (+$15K from commodity increases), labor efficiency variance (+$25K from new product learning curve), volume variance (+$10K from higher demand). Each component led to different responses.
Key Points
- Compares actual to planned/expected performance
- Decomposes total variance into specific components
- Identifies root causes of deviation
- Enables targeted rather than generic responses
Common Misconceptions
All variance is bad. Favorable variance (better than planned) deserves investigation too. Understanding why results exceeded expectations enables replicating success. Variance analysis is about understanding, not just problem-finding.
Variance analysis is just financial. While commonly applied to budgets, variance analysis applies to any measurable target—quality, delivery, productivity, safety. The principle of comparing actual to expected and understanding why applies universally.