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Component: SCM-APO-FCS
Component Name: Demand Planning
Description: One of three categories of models used for forecasting. The other two are time series models and judgmental models. The basic premise of a causal model is that the future sales of a particular product or service are closely associated with changes in some other variables. Therefore, once the nature of that association or relationship is quantified, information about the other variables can be used to develop a demand forecast. The causal model used in is multiple linear regression.
Key Concepts: Causal models are used in SAP SCM-APO-FCS Demand Planning to identify the factors that influence demand. These models use historical data to identify patterns and relationships between different variables, such as price, seasonality, and promotional activities. The model then uses these relationships to predict future demand. How to use it: To use a causal model in SAP SCM-APO-FCS Demand Planning, you must first define the variables that will be used in the model. This includes selecting the data sources, such as sales history or customer surveys, and defining the parameters for each variable. Once the variables have been defined, the model can be built using statistical methods such as regression analysis or time series analysis. The model can then be used to generate forecasts for future demand. Tips & Tricks: When building a causal model in SAP SCM-APO-FCS Demand Planning, it is important to ensure that the data used is accurate and up-to-date. Additionally, it is important to consider how changes in one variable may affect other variables in the model. For example, if a promotional activity is expected to increase demand for a product, it is important to consider how this may affect other products in the same category. Related Information: For more information on causal models in SAP SCM-APO-FCS Demand Planning, please refer to the official SAP documentation at https://help.sap.com/viewer/product/SCM_APO_FCS/7.5/en-US.