Business partner collaboration and buy analysis

Abstract

The present invention provides a method, system and computer program product for implementing an automated inventory replenishment process between a manufacturer and a business partner. In one embodiment of the invention, a method is provided comprising the business partner purchasing and maintaining an inventory of goods from the manufacturer, and the manufacturer providing price protection to the business partner for the purchasing of the goods. This embodiment further comprises managing said inventory by using an automated process that takes into account said price protection for the purchasing of the goods.

What is claimed is: 
     
         1 . A method of forecasting sales comprising:
 inputting historical sales data to a forecasting engine;   processing the input historical sales data by applying an outlier detection and correction procedure to the input historical sales data to eliminate specified one-time sales events;   feeding the processed input historical sales data to a long-term trending procedure and to a short-term trending procedure;   using the long-term trending procedure to detect a long-term trend based on repetitive sales patterns;   using the short-term trending procedure to detect a short-term trend based on a selected time horizon; and   combining the long-term trend and the short term trend to produce a point sales forecast for a future time period.   
     
     
         2 . The method according to  claim 1 , further comprising inputting into the forecasting engine product transition data comprising predecessor-successor relationship among parts. 
     
     
         3 . The method according to  claim 1 , wherein the processing the input historical sales data includes using robust regression to process the historical data to detect and correct for the outliers. 
     
     
         4 . The method according to  claim 1 , wherein the using the long-term trending procedure includes, said long-term trending procedure discounting the historical data based on recency and seasonality. 
     
     
         5 . The method according to  claim 4 , wherein the using the long-term trending procedure further includes adjusting said discounting through control parameter, and updating said control parameters based on historical forecast accuracy. 
     
     
         6 . The method according to  claim 1 , wherein the using the short-term trending procedure includes using an auto-regression forecasting model to extrapolate future sales from an evolution of defined sales data. 
     
     
         7 . A system for forecasting sales comprising:
 one or more hardware processing units configured for:   inputting historical sales data to a forecasting engine;   processing the input historical sales data by applying an outlier detection and correction procedure to the input historical sales data to eliminate specified one-time sales events;   feeding the processed input historical sales data to a long-term trending procedure and to a short-term trending procedure;   using the long-term trending procedure to detect a long-term trend based on repetitive sales patterns;   using the short-term trending procedure to detect a short-term trend based on a selected time horizon; and   combining the long-term trend and the short term trend to produce a point sales forecast for a future time period.   
     
     
         8 . The system according to  claim 7 , wherein said one or more hardware processing units is further configured for inputting into the forecasting engine product transition data comprising predecessor-successor relationship among parts. 
     
     
         9 . The system according to  claim 7 , wherein the processing the input historical sales data includes using robust regression to process the historical data to detect and correct for the outliers. 
     
     
         10 . The system according to  claim 7 , wherein the using the long-term trending procedure includes, said long-term trending procedure discounting the historical data based on recency and seasonality. 
     
     
         11 . The system according to  claim 10 , wherein the using the long-term trending procedure further includes adjusting said discounting through control parameter, and updating said control parameters based on historical forecast accuracy. 
     
     
         12 . The system according to  claim 11 , wherein the using the short-term trending procedure includes using an auto-regression forecasting model to extrapolate future sales from an evolution of defined sales data. 
     
     
         13 . An article of manufacture comprising:
 at least one computer usable device having computer readable program code logic tangibly embodied therein to execute machine instructions in one or more processing units for forecasting sales, said computer readable program code logic, when executing, performing the following:   receiving historical sales data in a forecasting engine;   processing the historical sales data by applying an outlier detection and correction procedure to the input historical sales data to eliminate specified one-time sales events;   feeding the processed historical sales data to a long-term trending procedure and to a short-term trending procedure;   using the long-term trending procedure to detect a long-term trend based on repetitive sales patterns;   using the short-term trending procedure to detect a short-term trend based on a selected time horizon; and   combining the long-term trend and the short term trend to produce a point sales forecast for a future time period.   
     
     
         14 . The article of manufacture according to  claim 13 , wherein the receiving historical sales data includes receiving in the forecasting engine product transition data comprising predecessor-successor relationship among parts. 
     
     
         15 . The article of manufacture according to  claim 13 , wherein the processing the historical sales data includes using robust regression to process the historical data to detect and correct for the outliers. 
     
     
         16 . The article of manufacture according to  claim 13 , wherein the using the long-term trending procedure includes, said long-term trending procedure discounting the historical data based on recency and seasonality. 
     
     
         17 . The article of manufacture according to  claim 16 , wherein the using the long-term trending procedure further includes adjusting said discounting through control parameter, and updating said control parameters based on historical forecast accuracy. 
     
     
         18 . The article of manufacture according to  claim 13 , wherein the using the short-term trending procedure includes using an auto-regression forecasting model to extrapolate future sales from an evolution of defined sales data.