What is forecast accuracy?
Forecast accuracy measures how close a forecast came to what actually happened. It is usually expressed as a percentage, where 100% is a perfect call.
It matters because decisions ride on the forecast. Hiring plans, spend commitments, and investor guidance are all set against it, so a forecast that is consistently off creates real downstream cost.
The formula.
Forecast accuracy = 100% minus the forecast error, where error is the absolute difference between forecast and actual divided by actual. This tool shows both the error and the resulting accuracy.
Using the absolute difference means over-forecasting and under-forecasting are treated the same. Both are misses, and both erode trust in the number.
A worked example.
A team forecasts 95,000 and actual comes in at 100,000. The error is 5,000 divided by 100,000, or 5%, so accuracy is 95%.
What is a good forecast accuracy?
90% and up is accurate enough to plan around confidently. Between 75 and 90% is workable but carries real planning risk, and below 75% means the forecast is off by more than a quarter, which is a process problem.
A forecast is only as good as the pipeline behind it. Reading accuracy next to pipeline coverage and forecast off a steadier demand base shows whether the inputs are stable enough to forecast from.
How to improve it.
Tighten stage probabilities and close dates, and confront the human factors, rep sandbagging on one side and happy-ears optimism on the other. Accuracy improves when the pipeline reflects reality, not hope.
A steadier flow of inbound demand makes forecasts easier, because the top of the funnel stops swinging.