Variance analysis

Variance analysis takes the gap between what actually happened and what was planned, actual - budget (or actual - forecast), and asks why it exists. On its own, a single "revenue was $200k under budget" number says little; variance analysis breaks that figure down into components such as price variance, volume variance, and mix variance so a finance team can tell whether the miss came from selling less, selling cheaper, or selling a different mix of products.

This goes a step further than a plain budget vs. actual report, which just shows the two numbers side by side. Variance analysis adds the explanatory layer: it attributes the difference to specific drivers, often expressed as both a dollar amount and a percentage of budget, and flags which variances are favorable versus unfavorable.

It matters because it turns a scorecard into a diagnostic tool. FP&A teams use recurring variance analysis, typically monthly, to catch problems early, hold budget owners accountable, and refine the assumptions feeding the next rolling forecast. A common pitfall is treating every variance as equally meaningful: small variances on volatile, low-materiality line items get the same scrutiny as large ones on core revenue lines, wasting review time that should go toward genuine root cause analysis.