But profits proved elusive last year. Ford lost almost $700 million in its most recent quarter (Q3 '01), after posting a gain of $888 million in the same quarter the year before. The ongoing tire-recall debacle is one factor, although Ford felt that pain the year before as well. Volume is strong thanks to zero-interest finance programs, but if profits are to rebound, it may require more than the right combination of cup holders and stereo components.

Companies across all industries are taking a broader look at the factors that influence profits, from activity-based costing to the geographic location of customers. At Ford, that means the software that serves as its "pricing engine" doesn't simply analyze the ramifications of different incentive programs; now it also links to production planning, distribution, marketing, and even financing databases in order to help Ford make smarter financing decisions. "We're pulling together all of the areas that touch revenue so that we can be more sophisticated about when to scale back production, when to work overtime, and when to change pricing and promotions," says Lloyd Hansen, vice president of revenue management.

A small but growing number of companies are following Ford's example. Fairchild Semiconductor International, for example, has launched a new initiative that synthesizes data from both internal sources (such as inventory) and external sources (such as market conditions) so that it can reprice 50,000 products as often as once a week, versus quarterly, and adjust production accordingly.

While these nascent efforts at Ford and Fairchild have yet to yield quantifiable results, recent research suggests there is much to be gained. AMR Research studied 35 companies that used a variety of "profit-optimizer" tools and found that they added as much as 6 percent to the bottom line within a year.

Most companies today are where Ford was two years ago: assessing a burgeoning taxonomy of tools that promise to wring more-profitable decisions out of disparate data. Forrester analyst Stacie McCullough Kilgore estimates that only between 1 percent and 5 percent of companies outside the hotel and airline industries (where finite capacity inspired yield-management software, the precursor to profit-optimization products), mostly in the manufacturing, financial services, and pharmaceutical sectors, are using such technology. One reason for the hesitation is that profit-optimizing projects are not quick hits. Success often requires investing in and integrating lots of software, a serious time and capital commitment. And most optimization tools tend to be specific to certain industries or pricing scenarios. ProfitLogic and KhiMetrics, for example, help retailers decide how to discount merchandise that won't move, but they don't answer the questions that companies with business customers face. Two-year-old Metreo has a business-to-business focus, but it's targeted primarily at manufacturers and distributors that deal with negotiated prices.

While much of the data needed to determine optimum prices resides in popular enterprisewide systems, Kilgore cautions that "vendors like SAP and Oracle maintain fixed pricing strategies like cost-plus or catalog, but they can't easily maintain dynamic forms or manage prices across channels." Nor can supply-chain management systems translate their capacity-planning forecasts into prices, she adds, and customer relationship management applications "are blind to changes in customer spending patterns." Many of these companies have profit-optimization applications in the works, but the programs won't be available for six months or so.