Running a Forecast
Once the forecast hierarchy is determined, click "Run Forecast" to commence the forecasting process.
Upon opening the popup, the latest hierarchy and settings from last forecast run are applied. These settings may be modified as follows:
- Aggregation Type: Select either top-down or middle out to select the type of aggregate forecasting process. See below to understand how the different options produce a forecast.
- Bucket Type: Select monthly or weekly buckets - we recommend choosing a single bucketing method consistently.
- The forecast levels included in the hierarchy are presented. If a level is removed or change, the selections will in turn change.
- If top down is selected as the aggregation type, only one level is allowed to be selected as the forecast level.
- If middle-out is selected, two levels are selected as the forecast levels.
Forecast settings are shared for both manual forecast analysis and automated forecast analysis. Automated forecast uses the latest saved forecast settings (used during last manual run).
If an incorrect selection is made, an error will be displayed and the forecast will not be able to be executed. In the example below, a second level is required to fulfill the requirements of the Middle-Out aggregation type.
Running a Forecast
Once the options are selected, click "Run Forecast" to commence the forecasting process.
The process runs the statistical forecasts, drives the forecasts down to the base (PCL) entity level, sums up forecasts at each level of the hierarchy, calculates sales dollars and average sales prices as well as calculates performance metrics.
Summary of Top-Down vs Middle-Out
If Top-Down is selected, the forecast at an upper level of the hierarchy will superimposes the shape of the aggregate forecast down to the item by the weighted distribution of the items history within the context of the top level. For example if an item makes up 20% of the overall history of the customer, the items forecast will be 20% of the overall customer forecast. Please note that the image below is from an earlier version of DemandCaster.
The Middle-Out approach is the best of both worlds since the overall shape of the aggregate forecast is combined with the shape and trend of the item level forecast. Though the middle-out approach takes longer to process since it is running twice the number of forecasts, we recommend it in most instances. Please note that the image below is from an earlier version of DemandCaster.
The time required to generate the forecast is dependent on numerous factors including the number of customers, levels, and items being forecasted.
Please note that the forecast UI only presents the forecast results and the measures related to forecast. Any overrides to the forecast values will be performed in the Demand Planning section.