In the second of a two-part series, Andrew Tolve explores the Big Data opportunity – and why so few automakers have capitalized on it.
Automakers and consumers alike have much to gain from Big Data. In part I of this series, we delineated the various opportunities and use cases that Big Data offers automakers, and they ranged from faster response times and product improvements to partnering with outside organizations to access new revenue streams.
Cisco recently calculated that the value of Big Data for OEMs will approach $300 per vehicle per year, with much of that value coming from lower warranty costs and improved app design. In the same analysis, Cisco concluded that Big Data will help drivers save upward of $500 a year thanks to better navigation and smarter routing.
Three hundred dollars per vehicle per year could make a sizable impact on an OEM’s bottom line, particularly in a stagnant market such as the current one. And yet, despite these promising numbers, few automakers have managed to monetize the Big Data opportunity to date.
Consider General Motors, a proven telematics leader and owner of one of the biggest data sets in the industry. GM declined to be interviewed for this story, but the company has stated previously that it’s already using OnStar’s data repository to learn more about its customers.
Sounds promising. Then again, in July, Tim Nixon, GM’s executive director, CTO and applications delivery, told Digital Trends that GM’s high priority with Big Data was “demystifying the check engine light” – in other words, telling people what’s actually going on when the check engine light illuminates.
This is no doubt valuable for the customer, but it’s also decidedly small data (helping a customer on the individual level) rather than Big Data (combining tens of thousands of check engine lights to spot a trend quickly and respond to it before a recall is necessary).
This is not to pick on GM. It’s just using one company – a connectivity pioneer – to illustrate that a gap exists between what people are saying about Big Data potential and what auto OEMs are actually doing. “Comparing the amount of discussions around Big Data and the opportunity enabled by it, the actual degree of monetization is still extremely low,” says Robert Kempf, vice president at Symphony Teleca.
Big Data, big challenges
Part of the problem is technical. In order to gather data today, carmakers generally wait for drivers to bring their cars in for service, at which point technicians can access data through the onboard diagnostic system. But drivers don’t bring their cars in for service all that often – the dutiful ones every 10,000 miles – which means that analyzing data from all cars on the road in a continuous and proactive fashion is a challenge.
With the emergence of fully connected cars, over-the-air software and configuration management allows carmakers full access to data from the vehicle anywhere, anytime, making the transfer easier and more feasible. But until connected cars represent the majority of cars on the road, Big Data collection will remain episodic.
“As it relates to OEMs, the first thing we have to do is introduce the connected car,” says Henry Bzeih, head of telematics and infotainment at Kia Motors America. “That’s step one. Step two is to achieve critical mass with those connected cars, at which point we can ask what we can do with Big Data.”
Another challenge is that preparing for the processing of Big Data requires significant investment long before new revenue streams and cost savings start to kick in.
(For more on this, see No easy road to get to M2M’s ‘rosy future’)
Storage is one challenge. There are loads of data warehouse and analytics companies out there – Teradata, IBM and Aster Data, to name a few. But they come with a price. “It’s not only expensive to store [Big Data], it’s prohibitively expensive to deliver to store,” says Alex Varshavsky, founder and CEO of Talksum.
Automakers can elect to store and analyze data in-house, as well, but the expertise to do this differs from what OEMs have historically built up internally. Thus, carmakers must either invest in outside insights, management and storage capabilities, or in building up those new capabilities internally.
“Historically, automakers didn’t have that many technical resources around data and almost none in the wireless space,” says Scott McCormick, president of the Connected Vehicle Trade Association (CVTA) and industry adviser to the U.S. Secretary of Transportation. “Knowing how electronic control units worked in the car was a huge leap. Big Data is thus new territory for them.”
Privacy and safety
A final consideration is safety and privacy. In 2011, GM changed the terms and conditions for OnStar, giving itself the permission to continue collecting data about customers after OnStar subscriptions ended. The terms also said that GM could share details of a car’s usage with other companies, whether or not a subscription was active.
An uproar ensued led by U.S. Senator Charles Schumer, who asked, in a letter, the Federal Trade Commission to investigate. Within several weeks, GM backed down, leaving many automakers wary of Big Data in the process. “We never really use privacy information,” Bzeih says. “We look at trends, that’s what Big Data is: trends.”
Safety is of equal concern. “To store any data, you have to have a mechanism to bring it in and use it,” McCormick says. “Once you have that mechanism, you’ve created a gateway that others can corrupt.” This presents potential concerns about competitors stealing information, according to McCormick. “If you’re an automaker, you don’t want a competitor to be able to find out diagnostic information off a car and run comparative ads and compete,” he says.
It also creates concerns about terrorists or hackers doing something more sinister. Consider a study from the University of Washington and the University of California-San Diego, in which researchers were able to hack into messages that tire-pressure sensors send to the car and, thus, confuse the car into thinking it had a flat.
“In theory, you could reprogram the car while it is parked, then initiate the program with a transmitter by the freeway,” team co-leader Tadayoshi Kohno said in an interview with Vanity Fair. “The car drives by, you call the transmitter with your smartphone, it sends the initiation code – bang! The car locks up at 70 miles per hour. You’ve crashed their car without touching it.”
(For more on data security, see Telematics and data security.)
The road forward
With these challenges in mind, it’s understandable why automakers have assumed a cautious posture with Big Data. All the experts interviewed for this story agreed that all automakers will be leveraging the Big Data opportunity by 2020. Between now and then, however, the road forward seems unclear.
One of the best ways forward is to start simple, our experts suggest. “When looking at data in the car, forget the universe of data,” McCormick says. “Let’s talk basics about what you could do, where you could go, what value you could add, and what’s the best way to get the specific data that will enable that. Drill down into it rather than starting with this massive cloud of data that you’re overwhelmed by.”
It might also be a good idea to use third-party services to help isolate the key data opportunities, services like IBM’s Data Warehouse Optimization, for instance.
The value of partnerships
Partnerships are also key. Automakers have historically made pretty crummy partners with each other, given their reluctance to show their cards on anything proprietary, especially something as personal as their data. “We gather a bunch of OEMs together, and everyone becomes defensive and close to the chest,” Bzeih says. “It’s a competitive industry, and everyone is in the business to make a brand better and achieve sales targets. So there’s a lot of jockeying for position.”
“It’s just reality,” Varshavsky says. “They all go in their own direction, and they can’t slow down to make sure everyone else follows.”
At the same time, Bzeih points out that automakers are likely to end up using Big Data sets that closely resemble each other. “What is unique about Ford or Kia from a data perspective?” he asks. “When it comes to raw data, we’re almost the same. We’re dealing with a standard set of messages, reading messages off of the CAN bus, collecting vehicle mileage. Those are standard in every car.”
Partnership on a general level could, therefore, help expedite the process for everyone. “Everyone’s saying, ‘Let’s meet and talk,’ but I don’t see anything concrete yet in which those collaborations are actually happening,” Bzeih says. “That’s the next step, to build these strong partnerships that will allow customers to benefit from Big Data.”
Andrew Tolve is a regular contributor to TU.
For all the latest telematics trends, check out Telematics Japan/China 2013 on Oct. 8-10 in Tokyo, Telematics Munich 2013 on Nov. 11-12 in Munich, Germany, Telematics for Fleet Management USA 2013 on Nov. 20-21 in Atlanta, Georgia, Content and Apps for Automotive USA 2013 on Dec. 11-12 in San Francisco, Consumer Telematics Show 2014 on Jan. 6, 2014, in Las Vegas.
For exclusive telematics business analysis and insight, check out TU’s reports: Telematics Connectivity Strategies Report 2013, The Automotive HMI Report 2013, Insurance Telematics Report 2013 and Fleet & Asset Management Report 2012.