explain-my-variance

P&L variance analysis decomposes material line movements into price, volume, mix, and one-time drivers grounded in specific journal entry IDs to explain why actuals differ from budget or prior periods.

Month-end variance analysis compares actuals against budget, prior period, and same period prior year, applying materiality filters to isolate significant swings and producing a narrative report explaining the largest movers.

Decomposing budget vs actual variances breaks down material changes into price, volume, mix, and one-time drivers tied to transaction sets, surfacing unexplained residuals explicitly rather than guessing causes.

Yes, variance analysis can produce a 3–5 paragraph narrative report highlighting the biggest P&L movers with driver attribution, providing a decision-ready story rather than only spreadsheet data.

Yes, running P&L variance analysis requires loading bookkeeping context alongside journal entries and any available budget file to compute materiality-filtered variances and attribute drivers accurately.

Unexplained residuals surface when P&L line movements cannot be substantiated by journal-backed drivers, ensuring variance analysis reports explicit residuals instead of quietly inventing causes for unsupported swings.