Spare-parts demand forecasting is a service forecasting use case, and Salesforce explicitly requires a different data-processing model from the standard sales-oriented Advanced Account Forecasting implementation.
Salesforce documents that service revenue and spare-parts demand forecasts require organizations to create custom forecast fact objects together with Data Processing Engine templates and jobs. Those DPE definitions can then be invoked through custom flows to generate the required forecasts.
This distinction is technically important because the underlying forecast inputs differ from conventional sales forecasting. UC needs to derive expected spare-parts demand from signals such as defective-part Cases and requests or Orders originating through distribution partners. The custom fact structure defines the service-specific forecast grain and measures, while the custom DPE logic retrieves, filters, transforms, aggregates, and writes those service signals into the forecast facts.
Salesforce explicitly notes that the default Advanced Account Forecast Fact objects and DPE templates supplied for sales use cases do not work for service use cases. Therefore, the Product Category forecasting prebuilt asset is not sufficient for this requirement.
A custom fact table alone would provide storage but not the processing logic necessary to generate the forecasts.
Study Guide references/topics: Configure and Build — Service Revenue and Spare Parts Demand Forecasting; Custom Forecast Fact Objects; Custom DPE Definitions; Advanced Account Forecasting.
