Original equipment manufacturers (OEMs) are increasingly turning to predictable, recurrent
digital services to reveal new revenue streams. Let’s take a look at three business models and how digital learning can help reduce time to solve issues and while increasing revenue.
Model 1: Remote Diagnostics as a ServiceI have worked with a leading oil and gas OEM in Houston that had a vision
Model 2: Performance Benchmarking as a Service
I have worked with an OEM that benchmarked the health of the assets deployed, and depending upon their condition, offered additional value-added services, such as finding a buyer for assets past their performance. Performance Benchamarking as a Service is still at the infant stage and we expect this trend to rapidly accelerate in the coming years.
Model 3: Extreme Pricing Personalization
In the automotive industry, Progressive Insurance created an offering around bartering machine data (mileage, braking, turns, acceleration) from cars. This data is used as an example for driving habits and was provided in return for discounted insurance prices. Progressive agreed to install a device in the car that would tap into the machine data generated, which would then infer driving habits. The data was used to create risk profiles that informed pricing models unique to the individual, as opposed to being a part of a generic segment.
These examples illustrate how the additional information gleaned from deep learning provides new perspectives on myriad situations, offering new levels of business insights. Deep learning is the new frontier for business to truly begin understanding how to mitigate risk and find new pools of revenue.