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April 5, 2017

Imagining a digital twin for your connected car

The concept of digital twins is catching up fast. In simple words, a digital twin is a unique living model of a physical object that is continuously updated with real time data that can be leveraged in many ways in the entire product development lifecycle. This capability of creating a 1 to 1 model for analyzing behavioral consumption patterns has been successfully accomplished in the online marketplaces. In the industrial domain, digital twins are being created for jet engines, turbines, locomotives and are used for anomaly detection, predictive analytics and also performance optimization. 

The concept of digital twins is in its infancy and the implications are extraordinary when combined with the power of industrial digital platforms such as PREDIX, MindSphere.'d like to borrow the concept of digital twin and apply it in the context of a connected car. To imagine a digital twin for the connected car, let's start with a few defining questions

  • What are the most commonly used features? How frequently are they used? How does feature usage change over time? 
  • Does driving behavior, environmental factors such as traffic, weather, and purpose of commute impact feature usage? 
  • Is there perceived value in the features? What is the linkage between perceived value and subscriptions?
  • How often do customers listen to the service recommendations? Are the recommendations relevant, timely and impactful?
  • Are there regional, demographic similarities among customers in feature usage? Any seasonal variations that can be derived from usage?
  • How often the driving assistance features are used in the vehicle for instance Forward Collision Warning, Blind Spot Detection?
  • Are there driving behavioral patterns that can be inferred based on time, day, destination, weather, traffic conditions?
  • What is the correlation between customer demographics, and driving behavior and feature usage? Are there patterns that can be deduced?
  • Can historical analysis of features be used to determine purchase behavior and thereby influence services buy as well?
  • How can the customer behavioral analysis through the pre-purchase phase be correlated to the connected services that they consume?

You can continue down this road to ask questions that help improve the business, product, customer experience and operations. When the digital twin of a connected vehicle is coupled with a virtual customer the impact is manifold. The customer DNA is richer through multitude of interactions in their digital lifestyle. I have captured this in a graphical model below that highlights the benefits of creating digital twins, analyzing them and also doing an aggregate analysis

The connected vehicle digital twin can be created by instrumenting the software with the right kind of probes so that behavioral data is captured and continuously updates the virtual vehicle. The instrumentation is tricky since it has be performed without compromising the system performance. The digital twin is an important concept that is useful to understand overall vehicle, its performance and also the connected features. Think about it as your digital avatar that predicts your behavior and provides the right information when you need it, where you need and also recommends what you expect to the producers of the product/service. The explosion in connectivity has closed the distance between the producer and consumer, the digital twin will amplify this effect and a truly personalized product or service from concept to delivery will happen in the future

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