How to calculate Sales Forecast Accuracy

Formula

Forecast accuracy = 100 − (|actual − forecast| ÷ actual × 100)

SQL query

This example assumes: forecasts(period, forecast_amount), actuals(period, actual_amount). It is written in PostgreSQL syntax; date functions differ slightly in MySQL, BigQuery and SQLite, and your column names will differ from these.

SELECT f.period,
       f.forecast_amount,
       a.actual_amount,
       100 - ABS(a.actual_amount - f.forecast_amount) * 100.0
             / NULLIF(a.actual_amount, 0) AS accuracy_pct
FROM forecasts f
JOIN actuals a USING (period)
ORDER BY f.period;

Common mistakes that make Sales Forecast Accuracy wrong

• Use the forecast as it stood at the start of the period, not a revised one.
• Over- and under-forecasts cancel out in a simple average; also track the signed error.
• A very small actual makes the percentage error huge; show absolute amounts too.

Ask for Sales Forecast Accuracy in plain English

Instead of writing the query yourself, you can type the question. SchemaChat turns it into SQL against your connected database or uploaded file, runs it, and shows the SQL and the figures it used so you can check the answer before you share it. It does not replace your judgement about the definition: check that the query matches the formula your business uses.

• How accurate was our forecast each quarter this year?
• Do we tend to over- or under-forecast?