Abstract: Systems and methods of monitoring a demand forecasting process are described. In accordance with a demand forecasting monitoring method, a measure of forecast error variability is computed at each period of a selected time frame, and an indicator of forecast bias is computed at a given period within the selected time frame based on forecast error consistency over periods of the selected time frame prior to the given period. A computer program for implementing the demand forecasting monitoring method is described. A system for monitoring a demand forecasting process that includes a graphical user interface configured to display a measure of standard deviation of percent forecast error at each period of a selected time frame also is described.

Abstract: Systems and methods of monitoring a demand forecasting process are described. In accordance with a demand forecasting monitoring method, a measure of forecast error variability is computed at each period of a selected time frame, and an indicator of forecast bias is computed at a given period within the selected time frame based on forecast error consistency over periods of the selected time frame prior to the given period. A computer program for implementing the demand forecasting monitoring method is described. A system for monitoring a demand forecasting process that includes a graphical user interface configured to display a measure of standard deviation of percent forecast error at each period of a selected time frame also is described.

Abstract: A development environment for supply chain management decision support systems. A framework is provided for the automatic generation of a supply chain model based upon input data concerning product demand and the parts and products that flow through activity centers such as factories, hubs, depots and the like. Parts source nodes, internal demand nodes, and terminal demand nodes are interconnected using an interactive symbolic visual interface that provides for the interconnection of nodes representing the activity centers to create a supply network scenario within the model. The supply network scenario may include more than one supply chain with each product having a unique supply chain. For each scenario, the statistical characteristics of part and product flow through the supply chain nodes is calculated within the model.

Abstract: An integrated reliability and financial planning system. The system uses contemporary and historical information on product warranty events, shipments and installed base to determine expected events over time. Based upon the expected event rate and warranty structure, the warranty cost for a product is predicted over the warranty life of the product. The resources required for service and support of the product are determined, and accruals and de-accruals for warranty expenses are planned for automatically, The system also provides for the examination of alternative scenarios to determine the impact of warranty structural changes and event rate changes.