What is reference module in SAP SCM-FRE - Forecasting and Replenishment?

SAP Term: reference module

• Component: SCM-FRE

• Component Name: Forecasting and Replenishment

• Description: Data retention level in a reference assignment. A reference module contains all product/location combinations references where the consumption data is necessary for the calculation of the historical time series data in SAP SAP F&R. A reference module consists of a header data record with details on the entire reference module and data records for each assigned reference. The artificial history for a new product is always formed for one reference module.

Smart SAP Assistant

• Key Concepts: 
  Reference module is a component of the SAP SCM-FRE Forecasting and Replenishment module. It is used to create a reference forecast for a product or product group. This reference forecast is then used as a basis for creating a more accurate forecast. The reference module also allows users to compare the actual sales data with the reference forecast to identify any discrepancies. 
  
  How to use it: 
  To use the reference module, users must first create a reference forecast for the product or product group. This can be done by entering the historical sales data into the system and then using the forecasting algorithms to generate a reference forecast. Once the reference forecast is created, users can then compare it with the actual sales data to identify any discrepancies. 
  
  Tips & Tricks: 
  When creating a reference forecast, it is important to ensure that the historical sales data is accurate and up-to-date. Additionally, users should also consider any external factors that may affect the accuracy of the forecast, such as changes in market conditions or customer preferences. 
  
  Related Information: 
  The SAP SCM-FRE Forecasting and Replenishment module also includes other components such as demand planning, inventory optimization, and replenishment planning. These components can be used in conjunction with the reference module to create more accurate forecasts and optimize inventory levels.