AWS Supply Chain Demand Planning announces Demand Driver-Based Forecasting
AWS Supply Chain now allows demand planners to input factors (demand drivers) that could influence forecasted demand. Demand Driver Based Forecasting is an adaptive approach that enables machine learning models to capture influence factors that improve forecast accuracy.
AWS Supply Chain now allows demand planners to input factors (demand drivers) that could influence forecasted demand. Demand Driver Based Forecasting is an adaptive approach that enables machine learning models to capture influence factors that improve forecast accuracy.
Demand planners can now input historical and/or future demand drivers such as price changes and promotional events directly into the AWS Supply Chain Data Lake. Demand Planning manages data at any level of granularity (by date or products) and allows users to configure reasonable defaults for partial data in the demand drivers. The machine learning algorithms refine the demand forecast by correlating historical trends with these demand drivers.
AWS Supply Chain measures the relative influence of demand drivers on forecast with an impact score. These impact scores are displayed on the user interface so demand planners can easily interpret whether a demand driver has a comparatively higher or lower impact on the forecast. This enables improved demand forecasting and better decision-making.
This feature is available to customers at no additional cost and is available in US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney) and Europe (Frankfurt). Please visit AWS Supply Chain to learn more and get started.