What is a good forecast accuracy? Why the headline number lies, what wMAPE really tells you, and the targets that actually move cash and service.
Ask five planners what counts as a good forecast and you will get five numbers. That is because accuracy only means something next to its context: which items, measured how, over what period, against what. A single percentage with none of that attached is a comfort blanket, not a measure.
A portfolio can post a respectable overall error while being badly wrong on the items that drive revenue and cash. Averages hide the misses, because the easy, high-volume items pull the number down and flatter the whole book. You do not run a business on the average item; you run it on the specific ones, which is why accuracy has to be read SKU by SKU.
wMAPE, weighted mean absolute percentage error, weights each item's error by its volume, so the products that matter most count most. It is a far more honest headline than a plain average because it stops a swarm of tiny, easy items from hiding big misses on the ones that count. Pair it with the per-SKU distribution and you finally see the truth.
Good varies by business, but for many mixed portfolios a weighted error in the low single digits overall, with a sensible median per SKU, is strong. The point is not to chase a vanity number; it is that even a 10 to 20% improvement in accuracy can cut inventory cost by several percent and shrink the safety stock you carry. Accuracy is not a scoreboard; it is cash and service.
A forecast number without its context is not a measure. It is a mood.
Picture your next S&OP meeting: one number on screen that nobody argues with. See it free, on your own data, in 45 minutes; and if it does not hold up, we part as friends.