Realizing the Value of Big Data: Q&A with Bryon Cook, Vice President Data & Analytics for Lytx

Capitalizing on Your Investment
Aug 28/2018 Published by: Lytx Lytx Telematics

Bryon Cook oversees Lytx’s data operations, which includes data gathered on more than 45 billion miles driven. This data covers a range of vehicle types – from Class 8 vehicles to transit to light duty trucks – driven in various conditions and settings, for virtually all industry segments within commercial transportation.

He took time to answer some questions about what it takes to realize the value of all the data Lytx gathers from event recorders.

What is actionable data?

The vast majority of the world’s data has been generated in the past few years as the result of the explosion of smart phones, social media, and sensors in everything from Fitbits on your wrist to accelerometers in your vehicle. All that data — big data — is passive, but actionable data – the translation of data into knowledge and knowledge into insights – has an active role in a fleet’s success.

What is the biggest benefit of actionable data for fleets?

Actionable data is used to solve and address problems. In fleets, actionable data can solve problems in four major buckets:

  • Safety: How can we make the vehicle and the driver safer?
  • Efficiency: How can we maximize time and fuel efficiency with each route?
  • Maintenance: What can we proactively do to keep our vehicles on the road?
  • Compliance: Are the vehicle and the driver meeting compliance rules and regulations?

At Lytx, our approach to data analytics is always to start with the end in mind. Without focus and intent, data is just a dormant asset. Our core focus is that first bucket of safety, but each of these buckets overlaps a bit.

How are the most successful fleets using their data?

Those fleets making the best use of their data have partnered with analytics providers like Lytx to collect, aggregate, integrate, and transform data into actionable insights. Insights can only surface when relationships between data attributes are identified. For example, from our database of 45+ billion miles driven, we know that summer driving actually leads to more collisions than in winter. Then we’ve narrowed the population to those that will benefit from coaching the most.

Fleet managers should start with the end in mind – and be clear about the problem they’re trying to solve. Are they trying to predict the future, like identifying drivers in their fleet most likely to have a collision? Or do they want to measure performance by looking backward and using data to diagnose problems?

How do you turn Actionable Data into Insights?

Data needs to be translated into knowledge…this means using data to identify attributes or groups relevant to the problem a fleet’s trying to solve. If it’s collisions, then data should be used to identify all the attributes of the collision group: time of day, location, likelihood of road congestion, rate of speed, and so on. Then identify correlative properties – what do these groups have in common? For example, the likelihood of being involved in a collision is highly correlative to drivers who don’t wear seat belts.
When you identify these correlative groups, you can build insights that power effective coaching programs to directly address the behavior.

Lytx does this heavy lifting with our team of data scientists, and we’re constantly uncovering new relationships between data points that inform more precise and insightful coaching. The net result is a highly effective coaching effort to help avoid collisions before they occur.

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