Forecast Accuracy
Forecast accuracy measures how well your forecasts match actual demand.
Accuracy Metrics
MAPE (Mean Absolute Percentage Error)
Average percentage error across all forecasts:
MAPE = (1/n) × Σ|Actual - Forecast| / Actual × 100
Bias
Measures whether forecasts are consistently over or under:
- Positive Bias: Over-forecasting
- Negative Bias: Under-forecasting
- Zero Bias: Balanced forecasting
Hit Rate
Percentage of forecasts within acceptable tolerance:
- Within 10%: Forecasts within 10% of actual
- Within 20%: Forecasts within 20% of actual
- Within 50%: Forecasts within 50% of actual
Viewing Forecast Accuracy
- Navigate to Analyze → Forecast Accuracy
- Select:
- Forecast Scenario: Scenario to analyze
- Time Period: Date range
- Products: Products to analyze
- Channels: Channels to analyze
Accuracy Analysis
View accuracy by:
- Product: Accuracy per product
- Channel: Accuracy per channel
- Location: Accuracy per location
- Time Period: Accuracy over time
Improving Accuracy
Use accuracy insights to improve forecasts:
- Identify Patterns: Find products/channels with poor accuracy
- Adjust Models: Modify forecast model parameters
- Apply Events: Ensure events are properly applied
- Review Assumptions: Review and update assumptions
Related Pages
Permissions & Roles
Viewing forecast accuracy requires standard user permissions. All accuracy metrics are scoped to your organization.
