The future of connected transport: 5 main questions

The digitalization of the auto industry is already worldwide known. Since at least the 1990s, automakers have been using electronic Engine Control Modules to diagnose and repair cars. However, there is a significant difference between loading 200 kilobytes of service data every 15-20 thousand km and analyzing terabytes from thousands of machines daily. It is estimated that by 2030 one machine will generate about 10 TB of data daily, which is comparable to 520 million messages in the WhatsApp messenger (just imagine this huge array).

Frost&Sullivan conducted a study commissioned by Dell Technologies in July, which interviewed 17 IT executives from leading car companies in the world to find out how they see their prospects in the context of digitalization and what tasks they are preparing for.


1. What data should be collected?

Now you can observe the practice when all the data is collected to deal with them later. But the true value of the «Internet of things» is the «Analysis of things.»

Data in and of itself, out of context and application, is useless. Therefore, it will be necessary to determine what kind of data should be collected, and how to relate it to each other to expand the context and use it to solve specific problems in real conditions.

Otherwise, car manufacturers risk drowning in the ocean of data coming from connected devices, draining budgets for data storage and not benefiting.

2. How to collect and process data?

In answering this question, we do not avoid the topic of clouds. Moreover, the clouds are not only and not so much as choosing a place to store, but rather, as a model, a way to work with data. The boom of public clouds passed, and many companies managed to repatriate data from the clouds, according to IDC, 80% of the participants in the 2018 survey transferred their applications and data to their local storage. But local storage is not enough. The cloud market, including the public cloud segment, will continue to grow.

Secondly, you can not ignore the technology of artificial intelligence (AI) and machine learning. Of course, you will have to move away from traditional approaches to effectively operate on such a scale. However, this requires appropriate specialists. And now automakers are experiencing a shortage of professionals who are versed in the auto industry, as well as in the topics of clouds, AI, and big data. Also, even if you manage to find such specialists, their expertise is very expensive. Therefore, the optimal solution here is cooperation and close collaboration with IT companies that have both solutions and expertise for their implementation.

3. How to manage data on a large scale?

Managing data on the scale that is projected in the coming years requires new approaches. At Dell Technologies, it is believed that this may be a platform for working with data — a mobile-connected platform (connected mobility platform).

Already today, carmakers note that they do not have enough of their specialists who would have expertise in the fields of analyzing big data, clouds, peripherals, AI, machine learning, or the IT solutions they currently have. Therefore, they attract partners who would help to develop, implement and manage the entire data processing infrastructure.

4. How and what data to monetize?

It is necessary to create new types of services based on the data generated by the TS. The first thing that comes to mind is the operating experience as such. Automakers can use their data to improve the quality of repairs and increase the life of the car.

At the same time, there are many innovative applications, such as real-time accident prevention systems or theft warnings in case of opening the car door or turning on the ignition.

Increasing the amount of data expands the possibilities for design improvement. For example, if the data shows that rear doors on a four-door sedan model are rarely used, then the automaker may consider creating a two-door model.

5. How to protect data and earn the trust of users?

Finally, last but not least. Auto concerns must take care of protecting the data they collect. Users are willing to share their data if they consider it profitable and appropriate. They will not mind when it comes to transferring data to an insurance company to accrue discounts or connect to PAYD technology (pay-as-you-drive — “pay as you run”), which allows you to reduce the cost of the policy and simplify the resolution of contentious issues in case of an accident. However, they are unlikely to want to share the data that could adversely affect their driving history or increase the cost of the policy for them.

Further tightening of regulatory requirements for data protection can be predicted. Already in 2019, British Airways received a fine of 183 million pounds for violating the GDPR, or rather, for the «poor security», which affected hundreds of thousands of airline customers.

Auto concerns understand that they will have to pay special attention to the generation, storage, and transmission of data while demonstrating the transparency of their approaches.

Digitalization of the automotive industry opens up enormous opportunities, but it is unlikely that these opportunities will be realized without changing the existing approaches, without involving technology partners and limiting ourselves to our expertise.