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Written by Minh Cao

The automotive industry is undergoing rapid transformation. A shift in market requirements is taking place, customer expectations and demands are growing, and environmental concerns are increasing.

In an attempt to evolve and adapt, the industry is moving towards more interconnected ride-sharing, car-sharing and autonomous driving. As a result, cars have become more than a method for getting from A to B. Today, they are mobile hubs of data, generating and processing quantities of information that were unforeseeable even a few years ago.

The value of this data is tremendous. In fact, according to the report published by McKinsey & Company, the value of vehicle-generated data is estimated to be USD 450 to 750 billion by 2030.


Vehicle-generated data is currently managed by OEMs, which have exclusive control over it. Every vehicle model has its requirements for accessing the data, but only OEMs have the decoding tables to extract the necessary information.

After being collected and stored on a centralised server, data is assigned in brand-based data silos. From centralised silos, data is sent to aggregators such as Lovego or Otonomo, who then monetise it and connect with various service providers.

The justification for this locked-in data approach is historic and related to safety, pledging that limiting access to data will secure cars from attacks. Certainly, this approach was secure 20 years ago, but recent attacks like the notorious Jeep case shows that security for connected cars is no longer granted.


The current approach is counterproductive for all participants in the automotive network and prevents development of a new economy around connected vehicles. Deliberately giving access to a restrained amount of data infringes not only end users’ data access rights, but also blocks the development of new use cases and services.

On the EU level, this issue is already recognised. Initiatives like GAIA-X, for hosting community data, with clear fundamental requirements in terms of privacy (GDPR) and transparency, are trying to avoid monopolistic positions, data silo states and fragmented ecosystems. However, these efforts, at least for now, remain on a quiet, philosophical stage rather than on a concrete development level.

Yes, the EU is great in setting up groups for defending values and standards, but the gap for reaching the services of the ‘hyperscalers’ (Amazon, Google, Microsoft, etc.) seems to be impossible to fill until industrialists risk investing in their infrastructures — the entire industry needs to play the double agent game until the regulation or the market decides on the dominating model.


The EU sees the danger of this and has therefore already started to encourage the industry to adapt new business models. But in the meantime, the usual approach remains. Companies such as Otonomo or Wejo are solving the data silo issue for OEMs by playing the role of data aggregator. They buy data from OEMs to clean, reformat and compute, and then monetise that data to the corresponding use cases. This is a consequent business: Otonomo has a public valuation of USD 1.4 million, while Wejo would be estimated at USD 2 million if it decides to go public. Nevertheless, this business frame looks fragile, since it’s very much dependent on the OEM’s data rates and their goodwill to cooperate with those companies.

It’s no surprise that the major industry players are already engaged in data consortium initiatives like Catena-X that …should enable a secure and cross-company wide data exchange of all participants of the automotive value chain”. But often in those good sense movements lies a danger of too many highly influential players lobbying for their interest, ending up with weak engagements and reduced trust from all members.

From a scaling point of view, a car will produce over three terabytes of raw data per day, most of which is not relevant. What counts are the interactions of different types of data, mixed with context, data analysis algorithms and patterns for predictive maintenance, which requires the storage of, and controlled access to, huge numbers of data lakes. Knowing that almost all vehicles will be connected, the amount of data to manage with this “top down” approach is totally unrealistic in terms of bandwidth, storage and analytical computing.

All this doesn’t look like a future-proof realistic approach neither for the industry nor for kicking off an ecosystem that requires agility and cross-vertical data exchange (e.g. energy, insurance and government).

The fact is that with such an approach, OEMs are missing out on a range of services for connecting with brands. On the other hand, service providers, such as insurance companies, are constrained by the number of people and vehicles they can serve. This data silo syndrome leads players to develop their own platform, consuming integration efforts for every new service — and general costs and efforts are not improving the end user experience in terms of interoperability and service offering.

These issues have led OEMs to start investigating opportunities for data sharing and new ways to monetise the data and generate additional revenue streams. During 2019 and 2020, we witnessed an increase in the sharing of collected data with third parties and penning deals with both data aggregators and marketplaces.

Still, OEMs remain cautious, one of the main reasons for that being handling data privacy concerns. They are aware that any leaks or issues will lead to negative effects on the reliability and reputation of their brands. And this is where digital disruptors and innovative startups can help OEMs, service providers and drivers to share vehicle-generated data and create new business models, services and products in a privacy-compliant manner.

Stay tuned…

To find out more, read about RIDDLE&CODE’s approach to mobility or feel free to contact us directly.
Originally published at https://www.riddleandcode.com.




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