Data Mining

Global Car Makers Join the Data Race

Drivers have long formed close relationships with their cars, whether banger or Bugatti. But if data scientists have their way, that bond will soon extend to the companies that make the cars, too.

In a bid to improve the kinds of things that many drivers care about, such as fuel economy and safety, the most enlightened car makers are pairing evermore in-car sensors with remote application management software to gather reams of data that will greatly enhance the relationship between driver and manufacturer.

The more information car makers gather, the better they can make the driving experience. The better the experience, the greater the chance of retaining the customer’s business. Ford’s design process has come a long way from ‘any colour you want as long as it’s black’. Consumer sentiment and driver behaviour are now starting to permeate the design process. Engineers working on the new Ford Escape SUV used social media sites to listen in on consumer conversations about the benefits of a manual liftgate versus a mechanised “power liftgate”, which opens automatically. Consumers seemed to prefer the latter and the engineers were able to implement the feature with a degree of confidence greater than any controlled focus group can provide.

While social sentiment is playing a growing role in the design of new vehicles, manufacturers can gather customer feedback on current models, too, identifying potential pain points and indeed anything that can help them get closer to the needs of customers. For example, as many makers of electric vehicles now understand, one of the biggest driver concerns is power, known in the trade as “range anxiety”. It’s an emotional response to a practical challenge, which is why the likes of Nissan and GM are looking at ways to help drivers monitor their vehicle batteries and remotely manage how they are charged.

Ford uses open source tools such as Hadoop to manage data as well as a range of other applications related to text- and data-mining. The company’s lab in Silicon Valley gathers information from over four million cars. All data is analysed in real-time, giving engineers valuable insight into a range of issues, and a broader view of how the car might respond in different conditions.

General Motors is also using Big Data to enhance product design, improve car performance and boost relationships with customers. GM collects information from its OnStar system to feed its analytics tools, with one benefit being the possible lowering of drivers’ insurance premiums, based on number of miles travelled. GM’s vision of the future is one supported by data, in which self-driving cars stop automatically at red lights, offer help with parking and alert drivers if they are too close to the car in front. Safety is a useful lever for marketers trying to build lifetime advocacy.

For car makers, it’s important that investment in analytics also delivers a bottom line return, chiefly through cost savings. The Indian conglomerate Tata is instrumenting all its trucks with GPS, sensors, and other telecoms equipment to help pinpoint not only the trucks’ position but also their general condition. Data-fuelled preventive maintenance, based on information from thousands of vehicles, is a Big Data challenge with huge potential gains. 

Meanwhile, data-driven marketing is also picking up speed in Germany, where many OEMs (Original Equipment Manufacturers) explore the potential for CRM that lies in their data, too. In order to better understand the customer, OEMs are breaking down data silos and enriching data pools with external information such as social media feeds, socio-geographic data or publicly available macroeconomic indicators. Their effort is rewarded with more accurate sales predictions, more efficient marketing campaigns and the ability to more proactively participate in the customer lifecycle through service reminders or cross- and upsell suggestions.

Hence, practically all of the data collected is useful for customer and manufacturer alike. But privacy watchers are concerned that connected cars are already encroaching into dangerous territory. One of Ford’s plug-in hybrid vehicles generates over 25 gigabytes of behavioural data every hour. Ford caused controversy at CES when an executive said the carmaker knew every time its customers were breaking the law. “The car must not become a data monster,” Volkswagen chairman Martin Winterkorn recently told a trade show audience in Germany. 

But the connected car seems here to stay. One projection has the market accounting for 90% of new vehicles by the end of the decade, from 10% today, quadrupling in value to $113bn. A key reason is safety. Connected cars are simply safer than traditional models. Black boxes are already standard in 85% of new cars, capturing vital information about the few seconds before and after a crash. The question for some motorists however, is who owns that data?

But connectivity also means that software updates can be issued, and that allows manufacturers to correct potentially dangerous defects. Last year, US authorities started an investigation into three battery fires resulting from high-speed accidents involving Tesla’s electric S car. Two of the incidents were caused by debris on the road that punctured the batteries and started a fire. Tesla responded by sending an update to thousands of vehicles that raised the default height of the cars' suspension at certain speeds. The move not only helped avoid a product recall, but also likely saved lives.

The future of the connected car lies in the value that consumers ascribe to closer relationships with car makers. The price of greater connectivity is greater volumes of data. If consumers want safer cars and greater functionality, the trade-off is possible third-party use of that data. There will be bumps in the road, but ultimately the market will decide where the lines are drawn.


Seshadri Rangarajan is CTO of Business Information Management at Capgemini India


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