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Real-time Insights on Driving Patterns from Big Data – The Next Frontier for Competitive Advantage for Automakers

Getting real-time insights on driving patterns could disrupt how automotive manufacturers compete, build, market and offer cars in the next decade and beyond. Note that I didn’t use the word “sell” which I think is fast becoming the old way of doing business – “pushing” products to consumers i.e “build it and they will come” strategy will simply not work as consumerization takes hold

A recent report from Center for Automotive Research, pegged industry revenues from car sales alone to be over $564 billion in 2010. Given the size of this automotive market and the rapidly rising trends in consumerization, getting insights on driving patterns become even more important. Consumers already want cars that can be personalized and customized in real-time based on his/her own driving preferences and desired driving experiences.

Give the above viewpoints, the question then centers around what types of data should automotive manufacturers collect for analysis, how to extract relevant insights from real-time analytics and what benefits they accrue. More importantly, what would be the value created for the consumer – the buyer?

To answer these, I present, below, a core set of multi-dimensional (driver, vehicle, environmental) data that should be collected to provide actionable insights into driving patterns and to establish a basis for new segmentation opportunities, real-time recommendations and predictions. Correlating driver’s driving habits and profile with vehicle performance and environmental data will provide deep insights and open up opportunities to create new value propositions that benefit the driver, the automaker and the environment.

  1. Anonymous driver profile
  2. Start events
  3. Driving/Cruising speed
  4. Miles driven per trip
  5. Stop events
  6. Location
  7. Routes taken
  8. Traffic data on routes taken
  9. Road conditions
  10. Weather (Seasonality, Unexpected)
  11. Fuel consumption rate
  12. Emissions count

Now to get a sense of how this is a Big Data Problem, just consider the following deduction (using data from the Federal Highway Statistics Department).

There are 255 million car owners who drive an average of 40 miles per day. If the minimum amount of data collected (includes all the dimensions in the above list) is 1kB (1,024 bytes) per mile driven, we now have 10.2 billion bytes of data per day!.  If you happen to be one of the “Big Three” US automakers to hold a large market share, interesting insights can be extracted from this large data volume and variety, using advanced real-time analytics.

For automakers, three key benefits accrue, among others, from these real-time insights:

  • Dynamic adjustment of vehicle performance to provide desired driving experience
  • Identify new class of drivers (segments) with unique driving patterns
  • Design new capabilities & innovations in advance of customer expectations and experiences

For the driver, the value of real-time feedback on his/her driving patterns can have a profound impact on his/her loyalty to the automaker. Other potential benefits include:

  • Recommending driving habits to provide desired experiences
  • Predicting part failure in advance
  • Increasing average miles driven per gallon
  • Reducing cost of maintenance with less wear & tear
  • Lesser emissions
  • Lower fuel consumption
  • Increased safety in driving

In conclusion, analyzing driving patterns in real-time can unveil new stream of innovation opportunities for the automaker and compelling benefits for the driver and buyer thus providing a new basis for competitive advantage.

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