A sales forecast is only useful if you know how wrong it usually is. Order 500 units on a forecast that is typically 30% high and you carry dead stock through the festive season; order on one that is typically 20% low and you stock out on Dhanteras. This calculator measures forecast accuracy for any period — absolute error, percentage error, MAPE across multiple periods, and bias (do you consistently over- or under-forecast?) — so you can set safety stock and staffing with numbers instead of nerves.
The metrics
| Metric | Formula | Reading |
|---|---|---|
| Forecast error | Actual − Forecast | Positive: you under-forecast; negative: you over-forecast |
| Absolute % error (APE) | |Actual − Forecast| ÷ Actual × 100 | Error relative to what really happened |
| Forecast accuracy | 100% − APE | 85% means you were within 15% |
| MAPE | Mean of APE across periods | The typical miss over a season |
| Bias | Mean of (Actual − Forecast) ÷ Actual | Direction of systematic error |
Forecast ₹8,00,000, actual ₹9,20,000 → error +₹1,20,000, APE 13%, accuracy 87%. Across six months with APEs of 8, 13, 22, 5, 11 and 17%, MAPE is 12.7%.
How to use the calculator
- Enter forecast and actual for one period, or paste up to 24 periods (months, weeks, or festive windows) in the table.
- Read accuracy, APE and error for each period, then MAPE and bias for the set.
- Segment by product line or channel — accuracy for online orders often differs from the counter.
- Use MAPE to size safety stock: at 13% MAPE on 500 units, keeping ~65 extra units covers a typical miss.
- Recheck after each quarter; forecasting improves fastest when errors are reviewed monthly.
Forecast bias: the number the tool also gives you
Bias = (Forecast − Actual) ÷ Actual × 100. Positive means you forecast high, negative means you forecast low. Forecast ₹10,00,000 against actual ₹8,80,000 and the bias is +13.6% — you planned for 14% more demand than arrived, and that difference is sitting in your stockroom. The calculator shows bias beside accuracy on every calculation, and flags it once it passes 15% in either direction.
Why bias matters more than accuracy
Two shops both have 15% MAPE. One misses randomly in both directions; the other always forecasts 15% high because the owner "plans for growth". The first needs safety stock; the second needs to cut forecasts by 15% — and is quietly tying up cash in inventory every month. The bias line separates the two. Use the inventory turnover calculator to see the cash cost of chronic over-forecasting.
Better forecasts for small businesses
- Start from last year, adjust for growth: the revenue growth rate gives the trend; the CAGR calculator the longer view.
- Separate base and festive demand: Diwali, Eid, wedding season and back-to-school need their own forecasts — the eight-week plan in Festive season 2026 checklist walks through it.
- Account for known shocks: price changes after the GST rationalisation, a competitor's opening, a bank-strike week, quick-commerce entry in your area.
- Forecast in units, then rupees: price changes distort rupee comparisons.
- Track the pipeline for B2B: the marketing funnel calculator turns leads into an expected-orders forecast.
Using accuracy in planning
- Purchasing: order quantity = forecast + safety stock based on MAPE and lead time.
- Staffing: schedule to the forecast, keep on-call staff for the upper error band.
- Cash: a forecast that is 20% high overstates cash inflow; plan working capital on the lower bound, especially around GST and payroll dates on the GST calendar.
- Targets: set sales targets from the forecast, then measure budget variance against actuals.
Related tools
- Budget variance calculator — planned vs actual for costs and revenue.
- Revenue growth rate — the trend feeding next period's forecast.
- Inventory turnover — the cost of forecasting high.
- Marketing funnel — pipeline-based forecasting for B2B.
- Capacity utilization — can you deliver the forecast?