Data mining challenges in the automotive domain

Abstract

Automotive companies, such as Ford Motor Company, have no shortage of large databases with abundant opportunities for cost reduction and revenue enhancement. The Data Mining Group at Ford has worked in the areas of Quality, Customer Satisfaction and Warranty Analytics for close to ten years. In this time, we have developed a number of methods for building systems to help the business. One area of particular success has been in warranty analysis. While traditional hazard analysis has been applied at Ford for a number of years, we have used techniques from other industries (e.g. retail), as well as text mining to view warranty analytics in a new way. However, our success has been tempered by serious challenges particularly in the areas of data understanding, computing meaningful aggregations and implementation. Case studies from the automobile industry (warranty, quality, forecasting, etc.) as well as from other industries will be used.