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August 20, 2014

Automakers Embrace Predictive Analytics to Boost Sales

The use of predictive analytics to discern consumer preferences is expanding to car dealerships where manufacturers led by Ford Motor Co. are trying to convince local dealers that big data can help them reduce the number of days cars sit unsold on their lots.

While some dealers are resisting new analytical tools like Ford’s Smart Inventory Management System rolled out in 2009, industry analysts recently told the publication Automotive News that predictive analytics could help save dealerships $100 or more on each car sold.

One reason Ford and big data specialists like IBM are pushing predictive analytics is that the auto industry produces a lot of information suitable for number crunching. The amount of data will only increase as upstarts like Tesla Motors fine-tune their customer loyalty programs that rely heavily on consumer data.

The Tesla sales model in which its cars are sold in “showrooms” rather than auto dealerships poses a small but growing threat to the traditional automotive supply chain. Whether traditional auto dealerships move to embrace predictive analytics the way Tesla has leveraged applied analytics remains to be seen.

For now, Ford appears to be leading the pack of established automakers seeking to leverage analytics to boost sales. Others are using big data technologies for other applications. For instance, Toyota Motor Corp. launched a big data effort last year that so far is limited to collecting traffic and other data gathered by 700,000 Toyota vehicles. Toyota hopes to eventually sell the data.

Elsewhere, the delivery service DHL Express launched a pilot project in 2011 designed to track the driving patterns of its delivery trucks in Singapore

Ford has traditionally been the most “data-driven” of the major U.S. car manufacturers and was one of the first to embrace big data as a way to improve is operations and better gauge customer preferences.

“We recognize that the volumes of data we generate internally — from our business operations and also from our vehicle research activities as well as the universe of data that our customers live in and that exists on the Internet — all of those things are huge opportunities for us that will likely require some new specialized techniques or platforms to manage,” Ford’s big data analytics leader John Ginder told the web site ZDNet in 2012.

“Our research organization is experimenting with Hadoop and we’re trying to combine all of these various data sources that we have access to,” Ginder added.

Still, some outspoken and—some would say, hidebound–managers of local car dealerships continue to resist disruptive technologies like predictive analytics. One commercial sales manager of a Ford dealership in Michigan recently told Automotive News that he had been managing his inventory for 16 years, “and I know what I want in my parking lot. They don’t.”

Elsewhere, General Motors is combining big data analytics and geographic information systems to model dealership performance, then pushing that capability out to its dealers. According to GM’s analytics manager Bruce Wong, the carmaker is combining the technologies to find out where customers live, who is buying GM vehicles and how far they live from dealerships.

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