In 1913, the Ford Motor Company was at the forefront of car manufacture. Designing the reasonably-priced Model T to appeal to the masses and employing division of labour & moblised assembly lines in the factory made Ford the largest automobile factory in the world at that time. In 2007, the

Ford have been at the forefront of top-down big data analytics from the get-go. In our interview with Ford’s Chief Data Scientist Mike Cavaretta last year, he alluded to the opening of a research centre, to propel Ford’s big data research to dizzying new heights. Now, this plan has come to

The 2015 Consumer Electronics Show at Las Vegas saw automaker Ford reveal its ‘Smart Mobility Plan and 25 Global Experiments’ designed as a move to change mobility worldwide. “Even as we showcase connected cars and share our plans for autonomous vehicles, we are here at CES with a higher purpose,”

2014 Has been a massive year for Big Data, as it transitioned from an emerging and exciting technology to a somewhat overused buzzword for any application of data science. This was reflected earlier in the year by Gartner’s always insightful ‘hype cycle‘, where we saw the term drop off the ‘Peak of

“Some people worry that artificial intelligence will make us feel inferior, but then, anybody in his right mind should have an inferiority complex every time he looks at a flower.” There has been a lot of media attention on Artificial Intelligence this week, with leading influencers taking various positions on

Success stories of how data-driven practices can revitalise businesses are rife today, but there are few as compelling as the story of Ford. In 2006, the legendary car manufacturers were in trouble; they closed the year with a $12.6 billion loss, the largest in the company’s history. As we reported

Using Big Data, Ford builds better cars. Car sensors, interactions within the company and the customers themselves are all generating Data that Ford can use in order to build better cars. The Leader of the data science department, Michael Cavaretta, interviewed with GigaOm’s Structure Show podcast in order to explain