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. A method includes collecting demand sequences, wherein each demand sequence is associated with a resource managed by a technology platform; processing a demand sequence for a selected resource to calculate an optimized control parameter (CP) value set adapted to manage an automated process within the technology platform, wherein calculating the optimized CP value set for the selected resource includes processing the demand sequence to generate a collection of bootstrapped demand sequences; and processing the bootstrapped demand sequences with a performance prediction process that models the automated process to calculate the optimized CP value set to achieve a best performance metric.

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

Abstract: A system and method for controlling an automated process based on a time series of count data. The approach includes characterizing an observed time series of counts by modeling the underlying dynamics that give rise to the observed data, including evaluating the time series with a driver estimation process, wherein the driver estimation process identifies a model by an iterative process that includes: providing a probability model; and utilizing a combined MCMC and EM algorithm to determine a set of model parameters for the time series; outputting an estimated sequence of driver values based on the identified model; outputting a series of statistically plausible future counts, and controlling the automated process based on the estimated sequence of driver values.

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

Abstract: A system and method are provided for detecting a significant change in the character of a time series collected from a technology platform. A system is disclosed that includes a memory; and a processor coupled to the memory and configured to process time series data for a set of resources according to a method that includes: collecting time series data associated with resources in a technology platform; analyzing each of a plurality of time series to determine whether a regime change occurred, and in response to a detected regime change in a time series, truncating the time series to generate a revised time series; and utilizing the revised time series to facilitate management or control the technology platform.

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, method and program product for analyzing demand data from an inventory database. A inventory demand analysis system is described having: a system for accessing an inventory database of item data, wherein the item data includes a historical demand for items characterized with intermittent demand; a demand pattern association system that analyzes the historical demand to calculate a set of coincidence probabilities for pairs of items in the inventory database; and a graphical representation system for generating a visual representation of a demand structure of the inventory database based on the set of coincidence probabilities.

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.