When most people think of Machine Learning in automotive, it’s in relation to how it can help in plant operations – predictive maintenance, diagnostic predictions, process optimization, etc. Effective use of Machine Learning at plants can significantly save costs, improve quality and minimize downtime. All positive things!
Automakers are in the midst of an amazing opportunity to transform themselves. As exponential technologies are changing the way we move today and especially in the future, automakers are looking at new business models and services to help move people and goods in more novel and different ways. Machine Learning can play an important role in how this shapes out. These new service offerings OEMs are piloting are new areas of play for them, so guidance from Machine Learning on the market opportunity and target audience (e.g., which generation or generations) can guide them in employing the right business model for the right area.
For example, cities are very unique and differ in significant ways around the world with some common threads as well. A service that works well in one city might fail in another. These data-driven insights can truly hone the investment and market strategy as well as the scaling of these services. Competition is fierce and to the extent that Machine Learning can minimize “trial and error” pilots that most OEMs are currently conducting in favor of fewer but primed-for-success innovation projects, it can be truly transformational.
On the other hand, enterprise support functions such as human resources can also gain significant new capabilities powered by Machine Learning. The war on talent is real and predictive models can help automakers in hiring, predicting employee attrition and employee benefit personalization that can all aid in attracting and retaining the right kind of talent for delivering on these new needs.
As the Automotive industry moves from a 100-year-old traditional product industry to redefine itself in this era of mobility services and as companies and society as a whole collect more and more data, how to synthesize and utilize that in real-time will be key to success. Those that can figure out how to truly leverage Machine Learning will put themselves in a position to drive how future automotive services ecosystems will deliver value to the consumers. Fasten your seat belts!