Causal Analysis 
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 variable(s). Therefore, once the nature of that association or relationship is quantified, information about that other variable or variables can be used to develop a demand forecast. For example, you can gauge what price point you need to hit in order to reach a particular sales volume.
Note
Causal analysis cannot determine which independent variables are relevant. You decide which variables to examine based on the business process. Causal analysis however does give you information on how well a selected independent variable explains changes in the dependent variable.
The causal model used in Demand Planning (DP) is multiple linear regression (MLR). The following MLR methods are available in the Demand Planning: