Employing Business Intelligence As a Tool for Decision-Making

by Curt Hall, Senior Consultant, Cutter Consortium

The other morning, over coffee, I was talking with several folks about the predicament that the big US automotive manufacturers General Motors and Ford now find themselves in. Simply put, GM and Ford are in trouble because sales of their SUVs, pickups, and other large vehicles have declined considerably. Some defined it as a forecasting problem. Others said it was faulty data analysis, and asked me why Ford and GM's BI folks failed to predict the shift in consumer sentiment to smaller, more gas economical cars. Actually I have received this comment (sarcastically) from several friends giving me a hard time, knowing that I'm "into BI."

But who's to say that GM and Ford's analysts failed to predict the shift in consumer sentiment to smaller vehicles? All the data was there for the taking, including years of almost continuously rising oil prices coupled with little or no prospect of the trend abating because of the ever increasing turmoil in the Middle East. History was there, too. The same thing happened in the eighties when the American auto manufacturers basically ceded the small car market to the Japanese car makers. Throw into this equation the development of new hybrid automotive technology by competitors Honda and Toyota, and the prospect that consumers might shift to more economical vehicles seems like not that tough of a prediction to make. Surely GM and Ford analysts were crunching the data.

I believe that the dilemma that GM and Ford now find themselves in has little to do with prediction or forecasting or any other kind of analyses. In fact, I bet both companies' analysts correctly (fore)saw the writing on the wall. Instead, it comes down to strategy and adaptation. Both GM and Ford have relied on sales of larger vehicles to drive profits (because such vehicles tend to generate the most profit per unit) for so long that both companies -- for whatever reasons -- were simply unable to adapt their business strategies to meet new consumer demands caused by a hyper-dynamic world. Maybe management wanted to, but the companies were simply too inflexible to implement the necessary changes. Or maybe they were so involved with trying to meet their short-term quarterly needs (compounded by huge employee pension/health insurance needs, etc.) that they could not focus on the future. Or maybe the "old way" of doing things was simply too entrenched for anyone to really believe that the market could actually change so much.

I'm sure that someday someone from GM or Ford or another insider will write a revealing book on the subject. But until this happens, who can really answer the big "why" with any certainty? In the meantime, companies in every industry should heed this lesson. Cutting-edge forecasting and prediction algorithms can provide valuable decision-making input. And flexible infrastructure can help organizations adapt in response to dynamic business environments. But when it comes to strategic decision making, in the end, technology is no substitute for leaders who possess the vision or foresight to recognize that a sea of change in their industry is approaching like a tidal wave, and who have the wherewithal to ram home a new strategy in response. BI -- like all technologies -- is just another tool to assist them.

-- Curt Hall, Senior Consultant, Cutter Consortium