The world's fastest spatio-temporal platform
In 2016, McKinsey predicted an immense $750 billion market potential for the connected car industry, only to revise their predictions in 2021 warning the entire OEM industry that they have only scratched the surface in connected car data monetization.
Moreover, McKinsey pointed out that the most valuable companies like Alphabet and Meta are already generating record-high revenues from big data. So what is fundamentally wrong with connected car data monetization?
Why do connected car data fail at monetization?
As it turns out, two of the three main reasons rely on the data itself. McKinsey identified three main reasons for the slow progress of data monetization:
- the lack of end-to-end access to terabytes of per-car data generated daily
- the failure to deliver services from idea to vehicle integration at an extremely fast pace - within six weeks
- the focus on aftermarket services, as opposed to the monetization throughout the vehicle life cycle
The sheer nature of connected car data - the temporal and geographical interdependence - makes it technology-wise extremely challenging to handle, exploit, and generate value.
On top of this, OEMs can expect even lower margins due to the necessary investments in mastering EV technology and its peculiarities.
What is the solution?
The industry needs to build new services quickly and at a reasonable cost.
The only way to solve this is by leveraging tools that are free of GPS peculiarities, further enrich the data, have a flat learning curve, and most importantly; are fast. The main objective is to have as few data analysts as possible that can test as many hypotheses as possible in as little time as possible. That's the way to reach the currently unattainable six weeks idea-to-integration time frame.