Demand driver recommendations

While configuring aggregation and filling methods for demand drivers, a general guideline is to assign mean aggregation for both boolean and continuous data types. To fill a missing value, use zero filling for boolean data while mean filling is suitable for continuous data.

Note that the choice of aggregation and filling method configuration depends on the data characteristics and assumptions about missing values. Here is an example.

Demand Planning recommends adjusting the demand driver configuration to best suit your dataset needs. The demand driver configuration will impact the forecast accuracy.

On the AWS Supply Chain web application, under Demand planning, Overview, you will view the impact scores associated with demand drivers, aggregated at the demand plan level. These impact scores measure the relative influence of demand drivers on forecast. A low impact score does not indicate that the demand driver has a minimal effect on forecast values. Instead, it suggests that its influence on forecast value is comparatively lower than the other demand drivers. When the impact score is zero under certain circumstances, it should be interpreted as the demand driver has no impact on the forecast values. Demand Planning recommends revisiting the aggregation and filling method configuration applied to that particular demand driver.