Bridging the Data Gap in Driver Training

Fleets may have all the latest technology on their trucks and many modern systems to assist with safety, but when it comes to driver training, very few have changed their processes in the past decades.

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We live in a world defined by data. Everywhere you look, you see stories about how artificial intelligence (AI), machine learning, algorithms and real-time analytics are used.

In the past few years, the march of technology has entered the trucking industry, with a sudden influx of vendors offering products powered by big data and machine learning. Enterprise content management (ECM) systems, electronic logging devices (ELDs), trailer sensors and a variety of other Internet of Things (IoT) devices collect a lot of data, and the prevalence of good mobile service makes it easy for that data to be saved to the cloud.

As a result, there’s a lot of information being compiled and a variety of ways to parse, analyze and act on the insights being revealed by that data. In the battle to improve safety and operating efficiency, the trucking industry has powerful weapons.

That is, except for one area of business – driver training. Instead, most fleets are continuing to use the same tools as they did 20 years (or longer) ago to track training information. Fleets may have all the latest technology on their trucks and many modern systems to assist with safety, but when it comes to driver training, very few have changed their processes in the past decades.

Driver training today

Today’s driver training departments regularly use a range of different tools to deliver content (classroom, online, simulators), but the tracking of that activity still routinely relies on paper. For example:

  • Drivers attend a training session or safety meeting with a sign-in sheet to prove they were there
  • In-cab trainers use a paper checklist to itemize the skills demonstrated during the road test
  • Drivers sign acknowledgements to confirm they completed assigned activities

All of these are then commonly stored in a “driver file” in a physical filing cabinet somewhere in the terminal.

In some cases, attendance at meetings and completion of simulator sessions are saved in an Excel file, but that’s uncommon. That said, the file is often kept on one specific PC, so it’s not much different from a paper file in a physical cabinet. 

This kind of activity tracking has many deficiencies.

Problems with paper

The problem with paper is that it’s fragile, unreliable and easy to lose. It can’t easily be shared, unless it’s copied or scanned (which is also rare), so you need to have the physical item to get the value out of it. If there are multiple terminals, then paper files could be spread across the country with no easy way to consolidate them.

All of those are weaknesses of paper-based tracking, but there’s another huge gap that really highlights how antiquated this approach is – it doesn’t support continuous training improvement.

With paper files or Excel documents, you can’t look at the driver training program as a whole and see what is working or what needs to improve. You can’t correlate training activities to on-road performance because there’s effectively no actionable data being collected on the training.

In other areas of the business, fleets are collecting data to see which drivers have the best fuel efficiency, speed management, lane keeping, braking habits and more. They can combine different data points to create risk profiles for drivers, allowing them to focus trainer efforts where it can be most effective. They can see where all their equipment is at any given time and analyze patterns to improve efficiency. 

Against all that, tracking training activity with a stack of papers is like bringing a knife to a gunfight.

Digging into training data

There are ways to capture that data in online systems and use it to help improve the driver development program and overall risk profile of the fleet. Here are some ways to start using those tools to capture more training data online and make good use of it afterwards.

Standardized testing. For classroom events like orientation or quarterly meetings, have a standardized online test at the end to validate that the learning objectives were met. The test doesn’t have to be long, but it does need to test the material covered during the session. The most successful ones require people to look up answers in their driver handbooks or reference guides, providing some extra engagement. There are some immediate benefits to doing this:

  • It shows you the comprehension level from the session and who may need more help
  • It lets you measure how well you’re delivering the content (if everyone gets the same questions wrong, maybe the content needs revisiting)
  • If you have multiple instructors delivering the content (and all students take the same online test), it makes it easy to see which instructors are most effective in their delivery.

Tracking of classroom and practical activities. Classroom and practical training can be tracked online as well, so students can be tied to events that are then tied to specific instructors. With even basic registration management, you can easily quantify which drivers are most diligent about attending and which aren’t. Much like the standardized tests, you can also track results by instructor to see who’s having the best effect on students.

With registration data online, you never need to worry about losing it. Some additional benefits:

  • It puts all training related activities in one place – classroom, practical and online are all part of the same driver profile, removing the need to hunt down files from multiple sources.
  • It lets you more easily see what the training program looks like from the driver’s perspective. When data is captured in different systems, it’s hard to get a real picture of what drivers are actually doing. When it’s all in one place, fewer things get missed.

Those are two simple ways to get started. More data to analyze, more insights into program effectiveness and more ability to tie that into performance data from other systems paints an even clearer picture of what’s happening in the fleet.

Other parts of the fleet and even other safety functions have benefitted greatly from online systems that track and analyze data continuously. Driver training doesn’t have to be left out of that. It’s time to bridge the data gap in driver training.