Free Tool · 1 free use per week
Score your forecast accuracy with MAPE, WAPE, and Bias analysis. Best-in-class weekly MAPE is ±3%.
Last verified: March 2026
Enter your actual vs. forecast volumes for each period. MAPE (Mean Absolute Percentage Error) gives equal weight to each period. WAPE (Weighted Absolute Percentage Error) weights by volume — better for operations with variable demand. Bias reveals systematic over- or under-forecasting.
#
ACTUAL
FORECAST
W1
W2
W3
W4
MAPE Score0.0% — Excellent
ExcellentGoodAcceptablePoor
Industry Context
Good MAPE5-10%
Bias Target+/-5%
Volume-WeightedWAPE
Typical HorizonWeekly
Key:MAPE at 0% is best-in-class (<3%). Your forecasting operation is well-calibrated. Watch for bias drift — you're currently under-forecasting (risking service level breaches) by 0.0%.
Benchmark: Weekly Forecast Accuracy
W1
98.4%
W2
97.5%
W3
97.7%
W4
99.2%
W5
95%
W6
99.2%
W7
98.5%
W8
98.3%
The 8 Forecast Killers
#1Training window too long — irrelevant historical patterns
#2Training window too short — insufficient data
#3Unexcluded anomalies — outages contaminating models
#4Wrong algorithm for pattern type
#5AHT forecast neglected — volume accurate, staffing wrong
#6Interval distribution mismatch — daily right, half-hour wrong
#7Channel blending errors — chat/email mixed with voice
#8Special event overlay failures — holidays, campaigns missed
