AUTOMATED IDENTIFICATION OF ANOMALOUS CONDITIONS IN SUPPLY CHAIN PROCESSES

A product supply chain may be viewed not just as a series of discrete, unrelated shipment transactions, but as a “process” (or pipeline) that can be subject to statistical process control. The present invention is directed to novel systems and methods for collecting data concerning one or more aspects of a supply chain, for performing statistical analysis on the collected data to facilitate the identification of anomalies or inefficiencies in the process, and for communicating the results of such statistical analysis to those responsible for the supply chain so that remedial measures may be taken, if appropriate. Among other things, a method for analyzing a supply chain process is disclosed that involves automatically determining whether a plurality of data points, each representing at least one determined value of at least one monitored aspect of a supply chain, match a pattern indicative of an anomalous condition in the supply chain process.