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Forecast Accuracy

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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:

1MAPE = (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

  1. Navigate to Analyze → Forecast Accuracy
  2. 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

Permissions & Roles

Viewing forecast accuracy requires standard user permissions. All accuracy metrics are scoped to your organization.