The massive recall of Firestone Tires in the autumn of 2000, particularly those on Ford Explorer SUVs, produced a major financial impact on both Firestone (including its parent Bridgestone) and Ford Motor Company. The sweeping recall occurred as tire blowouts and related vehicle rollovers were reported at alarming rates. The tread on certain brands and sizes of Firestone tires had a tendency to separate—particularly if the tires were under-inflated, driven at high speeds in hot climates, or carrying a heavy load. The result has been numerous lawsuits filed against both Bridgestone/Firestone and Ford Motor Co.
The burning question is why didn’t Ford and/or Firestone discover the problem earlier? One reason was that Ford “lack[ed] a database it could use to determine whether incident reports on one type or brand of tire represented a deviation from those of other tires on Ford vehicles.” 1 As a result, Ford did not identify the problem until the public relations damage was severe and then only after organizing a team to pore over the documentation on hand in the offices of Firestone. If a database of information related to tire problems had been available, standard data mining techniques likely would have detected the information much earlier. In this chapter, we will explore the advantages of database management systems and related analysis tools that can improve the decision support required for timely decision making.
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