WAPE vs. MAPE — why we prefer WAPE
MAPE (mean absolute percentage error) treats every period equally, so a big miss in a big quarter looks the same as a tiny miss in a tiny month. WAPE weights by actual volume, so a $1M miss in a $10M quarter matters 100x more than a $10K miss in a $100K month. That's what the CFO wants to see.
Bias is the diagnosis, WAPE is the symptom
High WAPE with low bias is normal deal variance — the process is fine, the outcomes are noisy. High WAPE with high bias means the categories are broken (or reps are sandbagging / hallucinating). Fix bias first — usually by tightening what qualifies as Commit vs. Best Case.
What to do at each accuracy band
Rough playbook:
- • ≥90% accuracy (WAPE ≤10%): protect the process, spend cycles on next-quarter pipeline.
- • 80–90% (WAPE 10–20%): tighten exit criteria on late-stage deals.
- • 70–80% (WAPE 20–30%): audit the last 10 slipped deals — is it discovery, decision process, or economic pressure?
- • <70%: forecast is not usable for finance. Rebuild categories and inspection cadence.
FAQ
Why 4 periods and not more?
Four is the minimum to spot a trend (single miss vs. pattern). Once you have 8+ periods, look at rolling 4-quarter WAPE — it smooths out one-off outliers.
Should I separate new business from renewals?
Yes, always. They have different forecastability. Blending them makes both look worse.
How is this different from pipeline coverage?
Coverage is a leading indicator (do we have enough?). Accuracy is a lagging indicator (did we get it right?). Both matter.
What causes a persistent positive bias?
Usually one of three: happy-ears reps, categories defined too loosely, or manager pressure to commit deals that aren't ready.
Can I use this on rep-level forecasts?
Yes, but with more skepticism — rep-level noise is huge. Only trust the number after 6+ quarters of data.
How this calculator is built
Independently maintained
Written by Sam Doshi and the RevenueLab editorial team. We don't sell the data feeds this tool is built on.
Sourced from primary data
Benchmarks come from public AdSense / Stripe / IRS disclosures and reader-submitted data — never third-party "$X per view" claims. Full methodology.
Last reviewed
July 2026. We re-check every figure on the platform on a rolling quarterly cycle.
Editorial standards
See our editorial policy and disclaimer. Results are estimates, not advice.