Forecast Override Analysis - Advanced
The Forecast Override Analysis - Advanced dashboard is designed to provide information about SKU streams that have forecast adjustments. You can compare the Forecast Performance of the SKU streams using KPIs that are calculated with and without forecast adjustments at different levels, such as Segment, Location, Part Type, and Forecast Methods with adjustments and without adjustments applied.
This dashboard can help you answer business questions such as:
• What is the count and % of under and over forecasted SKU Streams?
• What are the top-most over or under forecasted Locations or Part Types?
• Which Forecast Method or Parameter contributed to over and under forecasting?
• What is the comparison of overall trend of demand and forecast?
• What is the Forecast Method trend that depicts the type of demand pattern?
• What is the trend of Planner overrides on the Forecast Adjustment?
The widgets on the Forecasting Override Analysis - Advanced dashboard are separated into these mini-dashboards:
Mini-Dashboard | Description |
|---|---|
Forecast Override Error Analysis Summary | Information to help you analyze the following: • The number of SKU-Streams that have forecast adjustments in production • The number of those SKU Streams that are over or under forecasted depending upon tracking signal for lead time, and for those over or under forecasted SKU-Streams, how many have better tracking signal for lead time when their forecast adjustments were excluded • Forecast Accuracy for lead time with or without forecast adjustments. |
Information to help you understand the forecast error by showing the tracking signal trend and accuracy trend over time of the forecast with and without forecast adjustments | |
Information to help you review the trend of Total Demand, Total Raw Forecast, and Total Forecast (including adjustments). You can also see what is the forecast method trend for SKU-Streams with forecast adjustments, and what percentage of total forecast is the adjustment. | |
Information to help you analyze over forecast, under forecast and forecast accuracy for location, part type and forecast methods |