How do you calculate forecast accuracy?

Divide the number of forecast periods that landed within tolerance by the total periods evaluated, then multiply by 100. With 8 hits out of 250 periods that is 8 / 250 x 100 = 3.2%.

What is a good forecast accuracy rate?

For finished-goods families, 70-85% within a reasonable tolerance is typical; fast-moving stable items can exceed 90%. The 3.2% in our example is far below any usable target and signals a broken tolerance or model.

What is the difference between forecast accuracy and MAPE?

This calculator scores a hit/miss count against a tolerance, while MAPE averages the percentage error magnitude across periods. Use both: accuracy tells you how often you are close, MAPE tells you how far off you are when you miss.

Why is my forecast accuracy gap to target so large?

The gap is your rate minus target; here 3.2% - 95% = -91.8 points (shown as 91.8 points of shortfall). A gap that large usually means the tolerance band is too tight or the count is only capturing exact hits.

What tolerance should I use for a forecast hit?

Set tolerance to the plus or minus percentage of actual demand a period can deviate and still count as accurate, commonly plus or minus 10-20% for volatile SKUs. Keep it constant so month-to-month comparisons stay valid.

How often should forecast accuracy be measured?

Measure it every planning cycle, usually monthly, at the lag your supply chain actually reacts to (e.g. lag-1 or lag-3) so the score reflects the forecast decisions that drove real orders.

S&OP, Demand Planning & Forecasting calculator

Forecast Accuracy Calculator

Forecast accuracy measures how often your demand forecast lands within an agreed tolerance band of actual sales. Demand planners and S&OP leads track it by SKU, family, and location to judge whether the forecast is trustworthy enough to drive inventory, capacity, and supplier commitments. A low accuracy rate quietly inflates safety stock, triggers expedites, and erodes fill rate, so it is one of the first numbers reviewed in every monthly S&OP cycle. Measuring it consistently also lets you compare planner performance, statistical models, and consensus overrides on a level footing.

What this calculator does

Estimate forecast accuracy for sandop, demand planning and forecasting using production-ready inputs so teams can track KPI performance and decide whether corrective action is needed.
Use it when forecast accuracy in s and op, demand planning and forecasting needs a clean rate and gap-to-target you can put on a tier board.
It computes the share of evaluated forecast periods that fell within tolerance and the gap in points to your target rate.

Formula used

Forecast accuracy rate = forecast accuracy count ÷ total forecast accuracy population × 100
Forecast accuracy gap to target = forecast accuracy rate - target forecast accuracy rate

Inputs explained

Forecast periods hit within tolerance:
Total forecast periods evaluated:
Target forecast accuracy rate:

How to use the result

Use it in the monthly S&OP demand review to score forecast quality by SKU, product family, or planner before locking the consensus plan.
A single hit-rate hides magnitude of error and directional bias, so pair it with MAPE and forecast bias before drawing conclusions.

Current U.S. benchmarks

The producer price index for steel mill products stands at 348.53 (BLS, May 2026), up 6.7% from a year earlier. Quotes priced off last quarter's material cost miss this move.
The U.S. has 3,569 primary metal manufacturing establishments employing about 354,911 workers (Census County Business Patterns, 2023).

Common questions

How do you calculate forecast accuracy? Divide the number of forecast periods that landed within tolerance by the total periods evaluated, then multiply by 100. With 8 hits out of 250 periods that is 8 / 250 x 100 = 3.2%.
What is a good forecast accuracy rate? For finished-goods families, 70-85% within a reasonable tolerance is typical; fast-moving stable items can exceed 90%. The 3.2% in our example is far below any usable target and signals a broken tolerance or model.
What is the difference between forecast accuracy and MAPE? This calculator scores a hit/miss count against a tolerance, while MAPE averages the percentage error magnitude across periods. Use both: accuracy tells you how often you are close, MAPE tells you how far off you are when you miss.
Why is my forecast accuracy gap to target so large? The gap is your rate minus target; here 3.2% - 95% = -91.8 points (shown as 91.8 points of shortfall). A gap that large usually means the tolerance band is too tight or the count is only capturing exact hits.
What tolerance should I use for a forecast hit? Set tolerance to the plus or minus percentage of actual demand a period can deviate and still count as accurate, commonly plus or minus 10-20% for volatile SKUs. Keep it constant so month-to-month comparisons stay valid.

Last reviewed 2026-05-12.