Algorithm owners hold the keys to exploiting UBI revenue streams

Key areas of the value chain

Embedded and aftermarket sensor data will benefit third parties but only if they fight for their share of the value chain, says Roger C. Lanctot, director, automotive connected mobility at Strategy Analytics. These include insurance companies, independent repair shops, dealerships and auto clubs. “The chief beneficiaries will all benefit equally and only marginally. This is a tiny market niche that is rapidly being marginalised by car companies building connectivity into their vehicles. These third parties have come together in Europe to fight hard for access to vehicle data in view of the eCall mandate and GDPR etc. but it’s a tough battle.”

Third party collaboration might be the best solution for those who benefit most from sensor data, including roadside assistance providers and dealerships. They may even choose to opt in for a data share set up, says Robert Gruszczynski, OBD communication expert with Volkswagen US. “I have spoken to a number of these groups over the years and they all would buy in to some sort of reasonable scheme.”

The big problem car manufacturers and third parties are currently facing is that consumer interest and demand in data is still low, says Lanctot. “Consumers simply aren’t that worried about or interested in sharing their data with third parties – even including the companies that make their cars,” he says.

Creating a high resolution image of the risk

Both our experts agree investment is the first key step to understanding how to combine sensor data from hardware such as LiDAR, radar and cameras to create a holistic picture of the driving and vehicle environment. Practically, this requires subsidising the data collection and delivery platform, says Lanctot. All of this new data will also need to be stored. “The more data that is required for a given application: a) will increase cost substantially; b) will require large amounts of (automotive grade) storage. While there has been a great advance in solid-state storage devices, the price does increase heavily with size,” says Gruszczynski.

Only Tesla has successfully fulfilled this requirement, with HERE, Mobileye and Intel trying to replicate what the brand have already created. The task is not an easy one. “It’s difficult and expensive and requires at least some consumer participation/cooperation,” says Lanctot. “Only Tesla has delivered a value proposition that has convinced consumers to participate in the programme.”

For other car manufacturers, only time will tell how they will overcome the many challenges associated with data collection and sharing. The main problem they face is how to aggregate data from different sources using multiple algorithms and equipment, says Lanctot. Mobileye’s consortium with BMW and Intel is an attempt at overcoming these barriers, he says.

Identifying the variances in data sets

Data sets should in theory remain the same regardless of transmission device, says Gruszczynski but there is one snag. “As always, the standardized OBD data is always available, manufacturer-defined data may not be.” There lies the conundrum – without a standard for telematics services, carmakers, insurance companies and third parties are all collecting data in different ways in a locked down system which is not only inefficient but slow too. This is giving the advantage to Bluetooth mobile systems that work together with third party apps as an open network, sharing data across multiple systems. It’s not only more intuitive but shares the cost, rather than replicating it, which is what is occurring in the telematics arena.

There is a growing need for a collaborative data standard that enables the sets to be usable across multiple algorithms and systems. This is an area where early adopters such as the autonomous specialist Mobileye are reaping the rewards.

“Mobileye has an advantage because it processes its own data with its own algorithm,” says Lanctot. “Competitors will either have raw data with differing elements or processed data which may be completely unusable.” Therefore, companies that are thinking in an intuitive way using smart data have the advantage when it applies to data organisation, processing and sharing. “The options are Mobileye/with Mobileye algorithm or raw data – with pre-aggregation clean-up/preparation,” explains Lanctot. “Mobileye will have a big advantage – hence the $15Bn (£11Bn) price tag.”


Leave a comment

Your email address will not be published. Required fields are marked *