Built-in Automated Cleanup in Services Forecasting Processes

The existing Services Forecasting processes are designed to ensure your forecast data stays accurate and reliable. This topic describes the built-in cleanup steps automatically performed by the process that generates forecast data. For more information about the available scheduled processes in Services Forecasting, see Services Forecasting Scheduled Processes.

In addition to generating raw services forecast data for all eligible records, the run services forecast process performs the following cleanup steps during every scheduled or on-demand run:

• Automatically deletes existing raw services forecast data for projects, opportunities, and accounts that have been deleted. The deletion occurs in batches based on the size defined in the Forecast Factor Batch Size field on the active services forecast setup record.
• Automatically deletes existing raw services forecast data for opportunities converted to projects. The job does not perform this cleanup step if the Disable Opportunity Forecast Cleanup checkbox on the active services forecast setup record is selected.
• Automatically deletes existing raw services forecast data for projects that are either deactivated, no longer included in forecasting, or both. This only happens if the Delete Inactive or Excluded Project Data field is selected on the active services forecast setup record.

This process automatically handles a large portion of your data maintenance. However, several of the cleanup steps depend directly on your specific Services Forecasting setup. You can adapt these cleanup operations to your business needs using specific configuration options. For more information about the fields on the services forecast setup record that enable you to control these operations, see Services Forecast Setup Fields.

The process that updates the Services Forecast Live dataset aligns with these cleanup changes to ensure the dataset contains your most up-to-date forecast data. This process guarantees that forecast data that no longer exists is no longer represented in the dataset. For more information about how to schedule this process or run it on demand, see Scheduling the Process to Update the Services Forecast Live Dataset and Updating the Services Forecast Live Dataset On Demand.

Note:

Before verifying that stale forecast data has been deleted, ensure the scheduled process that generates raw forecast data has run at least once after the records are modified or deleted. If you do not want to wait for the next scheduled run, you can perform an on-demand run to remove the stale forecast data immediately. For more information about how to perform an on-demand run, see Generating Services Forecast Data for All Records On Demand. For more information about how to schedule the process, see Scheduling the Process to Generate Services Forecast Data.