How do you calculate forecast accuracy attainment rate?

Divide the number of SKUs meeting the accuracy target by the total SKUs in the portfolio, then multiply by 100. With 8 of 250 SKUs at target, the attainment rate is 3.2%.

What is a good forecast accuracy attainment rate?

It depends on your threshold, but mature planning organizations expect a large majority of A-class SKUs to clear their accuracy bar. An attainment of 3.2% against a 95% target signals the threshold is too strict, the models are weak, or both.

What does the gap to target mean?

It is the difference between your current attainment rate and your goal. Here, 3.2% attainment against a 95% target leaves a 91.8-point gap, meaning almost the entire portfolio needs improvement to reach the standard.

Why measure SKUs at target instead of overall MAPE?

Blended MAPE hides distribution. A few high-volume items can make average accuracy look fine while most SKUs are poorly forecast. Counting how many clear a threshold exposes that spread and points to where planner effort should go.

Should the target rate be the same for all SKUs?

No. Fast-moving A items warrant a high target while intermittent-demand C items may never be forecastable to the same standard. Segment the portfolio and run this calculation per class for a fair picture.

Attainment rate vs forecast bias: what is the difference?

Attainment rate is a pass/fail count against an accuracy threshold. Bias measures whether you systematically over- or under-forecast. You can have high attainment with low bias, or hit target on average while being consistently biased on individual items.

S&OP, Demand Planning & Forecasting calculator

Forecast Accuracy Improvement Value Calculator

This calculator measures the share of your SKU portfolio that currently meets a forecast accuracy target and how far that share sits below where you want it. Demand planners and S&OP leaders use it to size the improvement opportunity before investing in better models or planner time. Rather than reporting a single blended MAPE, it forces a portfolio view: how many items are actually good enough versus the goal. The gap in points is the headline that drives your accuracy roadmap.

What this calculator does

Estimate forecast accuracy improvement value 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 improvement value 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 percentage of SKUs at or above the accuracy target and the point gap between that attainment rate and your desired target rate.

Formula used

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

Inputs explained

SKUs meeting the accuracy target:
Total SKUs in the forecast portfolio:
Target forecast accuracy attainment rate:

How to use the result

Use it in monthly forecast review to track how much of the portfolio is meeting accuracy standards and to quantify the distance to a stretch goal.
It counts SKUs pass or fail against a threshold and says nothing about how far below target the failing items are, so a portfolio can improve in MAPE without moving this rate at all.

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 attainment rate? Divide the number of SKUs meeting the accuracy target by the total SKUs in the portfolio, then multiply by 100. With 8 of 250 SKUs at target, the attainment rate is 3.2%.
What is a good forecast accuracy attainment rate? It depends on your threshold, but mature planning organizations expect a large majority of A-class SKUs to clear their accuracy bar. An attainment of 3.2% against a 95% target signals the threshold is too strict, the models are weak, or both.
What does the gap to target mean? It is the difference between your current attainment rate and your goal. Here, 3.2% attainment against a 95% target leaves a 91.8-point gap, meaning almost the entire portfolio needs improvement to reach the standard.
Why measure SKUs at target instead of overall MAPE? Blended MAPE hides distribution. A few high-volume items can make average accuracy look fine while most SKUs are poorly forecast. Counting how many clear a threshold exposes that spread and points to where planner effort should go.
Should the target rate be the same for all SKUs? No. Fast-moving A items warrant a high target while intermittent-demand C items may never be forecastable to the same standard. Segment the portfolio and run this calculation per class for a fair picture.

Last reviewed 2026-05-12.