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Ford Opens Silicon Valley Lab to Mine Big Data | Wall Street Journal

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Ford Motor Co. CEO Alan Mulally, left, and chairman William Ford.

Ford officially opened its new Silicon Valley lab on Monday to help the company better tap into tech innovation. Part of the lab’s mission will be to look at how technologies like big data can leverage technologies embedded in cars to make better business decisions, from marketing campaigns to vehicle safety features.

“It’s amazing how much data is out there,” Bill Ford Jr., chairman of the company, said during event Monday night at the Computer History Museum in Mountain View, Calif. “The question is how do we put it in a form that’s usable?” That’s one of the many questions the Silicon Valley lab will work to answer.

Currently, Ford collects and aggregates data from the 4 million vehicles that use in-car sensing and remote app management software to create a virtuous cycle of information. The data allows Ford engineers to glean information on a range of issues, from how drivers are using their vehicles, to the driving environment, to electromagnetic forces affecting the vehicle, and feedback on other road conditions that could help them improve the quality, safety, fuel economy and emissions of the vehicle, according to Paul Mascarenas, chief technical officer of Ford Research and Innovation. “Improving quality is about building a database and really understanding how many people are using their vehicles and making better choices and better decisions,” he told CIO Journal.

Read full story at http://blogs.wsj.com/drivers-seat/2012/06/20/ford-opens-silicon-val...

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Comment by Vincent Granville on June 22, 2012 at 10:04am

There are many interesting statistical problems related to cars

  • reducing car accidents
  • statistical litigation (accidents - assessing dollar amount due to car defects)
  • provide traffic alarms, best route to follow for commuters
  • crowd analytics to tell drivers where police traps are located
  • inventory management
  • optimization of supply chain
  • market research: which car will customers want next year? which features? how to better detect and target car purchasers?
  • pricing optimization (how much should a car be sold for)
  • cross-selling (sell car insurance, warranty, and other product mix)
  • optimize advertising campaigns, develop sales attribution models
  • financial and tax engineering to increase profit for car manufacturers
  • optimize car performance / safety / price / pollution factors simultaneously

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