Data mining techniques for optimizing inventories for electronic commerce

Key data mining principles that can play a pivotal role in an electronic commerce environment are explained and two case studies in which neural network-based data mining techniques were used for inventory optimization are highlighted.

Abstract

As part of their strategy for incorporating electronic commerce capabilities, many organizations are involved in the development of information systems that will establish effective linkages with their suppliers, customers, and other channel partners involved in transportation, distribution, warehousing and maintenance activities.These linkages have given birth to comprehensive data warehouses that integrate operational data with supplier, customer, channel partners and market information.Data mining techniques can now provide the technological leap needed to structure and prioritize information from these data warehouses to address specific end-user problems.Emerging data mining techniques permit the semi-automatic discovery of patterns, associations, changes, anomalies, rules, and statistically significant structures and events in data.Very significant business benefits have been attained through the integration of data mining techniques with current information systems aiding electronic commerce.This paper explains key data mining principles that can play a pivotal role in an electronic commerce environment.The paper also highlights two case studies in which neural network-based data mining techniques were used for inventory optimization.The results from the data mining prototype in a large medical distribution company provided the rationale for the strategy to reduce the total level of inventory by 50% (from a billion dollars to half a billion dollars) in the particular organization, while maintaining the same level of probability that a particular customer's demand will be satisfied.The second case study highlights the use of neural network based data mining techniques for forecasting hot metal temperatures in a steel mill blast furnace.