Abstract: A system and method are presented for processing demand data for a set of resources in a technology platform. A method is provided that includes collecting demand profiles for the set of resources; reformatting each demand profile into a cumulative demand plot; calculating a distance metric for each pair of cumulative demand plots based on an area between the pair of cumulative demand plots; clustering the resources into a set of clusters based on calculated distance metrics; and generating a characterization for each of the clusters to facilitate management or control of the technology platform.

Abstract: A system and method are presented for optimizing choices of control parameters.

Abstract: A system, method and program product for cluster-based forecasting of intermittent demand. A computer system is disclosed for forecasting intermittent demand, having a data management system that provides access to historical demand data for a plurality of items; and a forecast system that generates a distribution of lead time demand predictions for a selected item having intermittent demand, and wherein the forecast system includes program code for performing the steps of: identifying a cluster from historical demand data, wherein the cluster includes items having an aggregated demand that defines a cluster driver; detecting if an association exists between historical demand data of a selected item and the cluster driver; and if the association is detected, utilizing the historical demand data of the selected item and the historical demand data to generate a distribution of lead time demand predictions.

Abstract: A system and method for forecasting intermittent demand. The forecasting technique utilizes sample reuse techniques to build a distribution of predicted cumulative lead time demand values that can be analyzed using statistical methods, be used as input for an inventory control system, be used as input for a sales planning system, etc.