The automotive industry is definitely going through a transformation. While a significant type of transformation is towards EVs, automation, and digitization also are opening another paradigm of transformation. And that digitization opens the doors to building data and analytics-driven cars of the future. Cars that address pain points beyond getting from point A to point B. And that is why I really loved that in Inma Martinez’s book “The Future of The Automotive Industry: The Disruptive Forces of AI, Data, Analytics and Digitization”, part II of the book is titled ” From Transportation to Solving People’s Problems.”

The author presents some fine postulates. But some of those postulates already hold and have been considered by leading automakers. For example, many of us spend considerable time in our cars and love them to the point where we see them as second homes. So, the digitization aspects and the use of data suggested in the book will provide more creature comforts. They will definitely help address the needs of higher in Maslow’s hierarchy. However, the title of the section of the book opened my thought process on solving more fundamental problems related to transportation. Or problems people may encounter while they are on the road.

Car manufacturers have consistently tried to make the experience of being in the car comfortable. That comfort tends to be a bit higher in the hierarchy of needs. While navigation systems were a step towards addressing a foundational need, smartphones’ introduction and rapid technological advancement made that feature moot.

Automation currently helps us do something we should not be doing while driving: multitask safely. Voice assistants are an attempt in that direction. But let us explore an example of how data and analytics in future smart cars can help address our problems.

Consider a fundamental problem of costly repairs.

We talk about predictive maintenance in the industrial context. But when it comes to our cars, the automation, at least from the driver’s perspective, stops at proactive (like a reminder that maintenance is due in 30 days). Nowadays, Most cars have computers and sensors that can capture various data.

Imagine if your car app notifies a customer that the vibrations in a belt in the engine are off, and they should look into that. This is much more proactive than the “check engine” light that occurs only after something malfunctions. Based on the data captured and leveraging an algorithm, you can sell a service that will perform the predictive maintenance analysis on the data captured.

The difference between getting something fixed early on and after it breaks may mean hundreds of Dollars. Considering that a significant population in the U.S. lives paycheck to paycheck, a subscription service like this addresses a fundamental pain point and can be a good revenue generator.

It can also take a significant pain point away from the used car experience. While CarFax is essentially BI (A report of a car’s history), you can offer AI-enabled services for your brand of cars (that are equipped), that can help provide the historical internal parts performance data. There may be some legal aspects that may need to be addressed, though.

We have used automation extensively to make cars comfortable. Semi-self-driving features address another foundational pain point of driving in heavy traffic. But there is so much potential to move from leveraging BI on the data captured by sensors in the car to leveraging AI on that data. And obviously, addressing those foundational problems also means tremendous monetization opportunities.