Over the last decade, companies have invested heavily in telematics. And with good reason, as telematics helps in numerous ways when it comes to fleet management – route planning, logistics management, driver communications, reduced fuel usage, improved productivity, better maintenance etc. But it’s brought with it an overwhelming amount of telematics data. “Can’t see the forest for the trees” or “information overload” are common struggles that companies face.

To make matters worse, it’s actually compromising fleet risk management and driver safety.

If it could be tapped into, this data could be useful throughout all areas of fleet management – including risk management and driver safety. The answers are in the data. But the volume of data is making the answers too hard to find.

Why Is There So Much Telematics Data?

From black box telematics, forward-facing dashcams, and complete video footage surrounding the vehicle, to online driver training, license check systems and beyond – fleet managers have to somehow sift through and make sense of it all.

Larger fleets often have a number of different telematics solutions, camera systems and fleet management information providers. These offer the same, or similar, telematics data but in different formats and with differing interpretations – making the task of logging into, using and understanding separate systems time-consuming and inefficient.

To make matters more challenging, one system only provides a singular view of the risks within the fleet operations at any one time. This creates an additional, tedious task of aggregating telematics data into a reporting structure, commonly an Excel spreadsheet.

Given all this, you can see how companies and organizations operating fleets now face the problem of “what do we do with all this data? How can we best manage, interpret and implement practices based around this ocean of information?”

And once they finally gain control of their data, how can they see the true level of fleet risk within their operations?

Problems Surrounding Too Much Data Will Only Increase with Time

Vehicles today have about 40 microprocessors and dozens of sensors that collect telematics and driver behavior data. This data can be analyzed in real-time to keep the vehicle’s performance, efficiency and safety in check. While these enhancements work to improve the way we travel, they also pose many challenges when it comes to the future of data aggregation and analysis.

As more of these connected vehicles hit the market, we’ll soon be seeing 25GB of data produced each hour by each vehicle. That’s the same amount of data in 6,000 music tracks or 10,000 emails – every hour.

For example, if a van is traveling 56 hours per week, it could be generating 56 x 25 = 1,400GB (or 1.4 TB) of data within seven days. That’s the equivalent of streaming about 300 HD movies on Netflix.

The Value of Telematics Data Merits the Need for a Solution

The data gathered via telematics is without a doubt a great resource. Businesses can look into each component individually to see how a specific risk aspect is performing. It offers valuable insight, from checking speeding reports to ensuring employees remain focused while driving via in-vehicle camera systems.

But managing this telematics data across a fleet of several hundred or thousands of vehicles and drivers becomes an overwhelming task. The information overload provides more data, but not always more insight. Fleet managers are often compromised in their role by the very systems that were designed to help them.

Imagine a full risk management system that brings in other non-telematics data, like a driver’s training history (or lack of), violations, license status updates and more. Aggregating data like this with telematics data would give a broader and more comprehensive view of the fleet’s risk profile and potential issues in driver safety.

To learn more about how you can leverage our solutions at SambaSafety to get more out of your telematics data, fill out our form to schedule a demo with one of our data insight experts below.