History demonstrates that it is not easy for physical and hardware product companies to adapt to the software business. We saw how many mobile phone manufacturers, such as Nokia, failed to compete with Google and Apple on mobile platforms. We are now seeing the same situation in the automobile industry, as carmakers struggle to become more software and data oriented.
I have rented top-brand European cars. They are nice looking cars, and their engine and physical parts work smoothly. But when you look at their software and especially the user experience, it is not such a smooth experience anymore.
Navigation is hard to get right
If we take, for example, the navigation system, it is nice that it’s integrated into the car’s own display, and is easier to use than a mobile phone when you drive. But when you compare its functions to Google Maps, they are not nearly on the same level. It is hard to find an address especially if you mistype only one letter), adjust your route manually or download up-to-date traffic jam and delay information.
Sometimes the driving instructions are outdated, when e.g some roads are blocked or rerouted due to construction. Sometimes they are slow to give instructions when you must make several turns and lane changes quickly.
The navigation system is just one small example of something that should be quite easy to handle. But it also demonstrates clearly that you need enough computer science competence to not only create these services, but make them very easy to use. Things that sound very simple – like correcting a misspelled address – are not so easy if the company doesn’t have strong competence in software and user experience.
Car manufacturers have tried to build and acquire that competence to make better software and utilize data better. For example, back in 2015, a consortium of German car manufacturers acquired Nokia’s Here map business. The problem is that owning a map software company doesn’t mean you understand how to make the best use of it when your roots and experience lie in building and assembling mechanical parts.
Carmakers can use much more data
That said, it’s worth remembering the auto industry is still at the very early stage of its software/data journey. Soon we will see much more serious efforts by carmakers to utilize data to improve the user experience and enable autonomous cars. We’ll also see rapid development of AI for use in vehicles.
Cars already collect a lot of data – in fact, most cars also have APIs to port data to external systems. Among other things, this means that carmakers no longer have to compete just with other carmakers, but also with software companies and platforms. For example, many user-oriented functions for cars can be implemented in a mobile phone app or the user’s own cloud.
It is also possible to combine car data with data from other systems. For example, a service could combine a car’s data with external public data (weather, road and traffic information and historical data from other similar cars) and driver’s data (sleep data, tiredness, stress level) and build much more personal services to support drivers. These applications are also better for safety and driver experience.
However, in practice, car manufacturers are wary of sharing data with or relying on third parties when it comes to data. Several car manufacturers have hesitated to cooperate with Google and Apple, because they’re worried those companies could acquire too much of their data and thus too much control in cars. This is a very real possibility, so they probably have good reasons to be skeptical. At the same time, Google Maps has become such an ubiquitous gold standard for navigation that drivers inevitably compare the car’s navigation system to it, and carmakers are struggling to offer a good user experience at that level on their own.
User-held data relevant to carmakers
At the same time, drivers may also not be too keen for their cars to share data externally. Privacy is increasingly important now, and cars can collect a lot of sensitive data. Most people would hesitate to use cars that share that data with third parties – it could reveal in accurate detail, for example, when and where you drive, and whether other people were in the car with you.
This is even more controversial when governments get involved. Some years ago Finland planned to introduce a new car tax model that would have been based on tracking cars, keeping tabs on how much and where they are driven. The government reversed its plans under political pressure, but it illustrates how authorities are also interested in using car data.
Naturally, user-held data models are becoming relevant for the car industry as well. User-held models would combine data from the car and the user’s other devices and sensors, whilst also protecting privacy and preventing Internet data giants from getting more control of drivers and car companies.
This could create a plethora of inniovative data use cases for cars. For example, user data on health, tiredness, stress and weather could be combined with car data to significantly improve safety and the overall driving experience. The car could recommend you to avoid driving if you are too tired and haven’t slept properly. Or it could recommend another route, if you are more tired than normal. Or if your tiredness and stress levels get too high, the car can recommend you to pull over and take a break.
These are just simple examples, but they demonstrate how the combination of car data with other data sources becomes very powerful.
Interestingly, the motorsports sector is already at the leading edge on this. Motorsports is very data oriented nowadays – for example, the teams of F1 and the world rally series collect a lot of data from their cars and use it to prepare for thousands of different scenarios. But they are also in a much earlier phase to utilize data from drivers and combine it with the technical and external data. Motorsports is often a test bed for future car technology, and it could serve the same role for software and data utilization.
In any case, it’s clear the car industry needs to get better at utilizing data and making better software. At the moment, the sector is having a hard time competing with big data companies, so it should find its own unique way to become better.
An important part of this is finding ways to better combine and utilize data from multiple sources, and also offer better privacy. Cars have been traditionally a symbol of freedom. Car companies must find a way to offer a top-level user experience and better safety and privacy in their software and data services.