How do I compare forecast vs actual with iDBQuery?
Ask iDBQuery 'How did actuals compare to our forecast each month this year, and where were we most off?' It aligns forecast to actuals period by period, returns the accuracy and gaps as a chart, and cites every figure back to its source rows.
Forecast-vs-actual analysis measures how close your predictions came to reality, so you can trust, and improve, your forecasting. iDBQuery lines up the two series and quantifies the miss without a manual spreadsheet.
- You'd ask iDBQuery: 'Compare forecast to actual revenue by month this year, show the error in value and percent, and flag the months we missed by the most.'
- It joins your forecast table to actuals, computes the variance and a forecast-accuracy figure, and returns a chart plus a table.
- Each figure is cited to its source rows, so 'we were 12% under forecast in May' traces to both the forecast and the actuals.
The value is in learning where forecasts break down. Ask 'Which product line do we forecast worst?' or 'Do we consistently over-forecast Q4?' and iDBQuery keeps the thread, exposing systematic bias. Because forecasts often live in a planning file and actuals in the ledger or a warehouse, the one live model joins them with no ETL, and the semantic layer keeps the revenue definition consistent so you are comparing like with like. Save a live report that updates as actuals land, and let the Analyst agent flag where the forecast is drifting from reality and by how much, citing the rows. This closes the loop with sales and demand forecasting, variance analysis, and budget-vs-actual.
Updated 2026-06-22