When a fleet is evaluating whether to implement online driver training, I’ll occasionally be asked: “How do you know if the driver actually completed the course?”
It might seem like a logical question since a fleet might be looking to augment or move away from in-classroom training where they know they can get a headcount and document driver attendance. Online means trusting the driver to do the courses. And, for some fleets, they might think online training will open a can of worms where drivers don’t actually go through the courses or have someone else take the courses instead.
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Lack of trust
Asking “how can you be sure Driver A took the course?" tells me the fleet doesn’t trust its drivers. When discussing the prospect of delivering training remotely to maximize the convenience and effectiveness of the programs, the questioner jumps to the assumption that if they weren't being watched then drivers en masse would get someone else to do it for them (often suggesting their kids as co-conspirators). Several questions immediately spring to mind in response:
- Why do you assume they won’t do it themselves? Why don't you trust them? Is it normal for your drivers to cheat like that?
- Do you regularly have drivers getting others to do their work for them? If so, how do you know they’re actually driving the truck?
- If you can’t trust them to take an online course, why are you letting them drive that expensive truck filled with expensive cargo?
- Do you have a lot of cheaters and dishonest people working at your company? If so, shouldn’t you focus on solving that problem?
Considering how to make the most of new programs is certainly fine, but if the base assumption is that drivers are going to cheat, it leads to other decisions that make things much worse.
The solution creates more problems
When fleets assume that they can’t trust their drivers to do online courses, they typically explore a few ways to prevent misuse.
Some fleets make drivers check a box to acknowledge they are who they say they are. That never works. Anyone who’s going to cheat won’t have a problem checking a box (if they even bother to read it).
Sometimes they make drivers do the courses at the terminal, on a public PC (where office staff can watch over them and ensure they do it). That’s not much better, since it defeats the purpose of online learning (access anywhere, anytime) and treats drivers like children who need constant supervision.
Even for fleets that don’t go to those extremes, the lack of trust can limit the effectiveness of the program. Rather than letting drivers proceed through the content at their own pace, fleets that don't trust often implement what’s known as “navigation lockdown,” forcing drivers to listen to all the narration and click every link before moving on. That removes another benefit of online learning—flexibility to customize the learning path—minimizing the effectiveness and irritating drivers when they have to sit through things they don’t really need. It also sends a clear message that the company has no faith in its ability to self-regulate.
Those things can be irritants that hamper the program, but it's the long-term impact of that lack of trust that's most damaging. If the company demonstrates a lack of trust in their training programs, they're likely demonstrating it elsewhere.
The result? Good people don’t stick around a company that treats them like children instead of trusting them to do their jobs. The people who do stick around will see their performance drop over time as they feel less and less valued. Not exactly a recipe for success.
A better approach
There is a more effective and positive way to approach the situation, creating a much better outcome over time.
Going back to the original question: “How do you know who did the coursework?” The answer is that you don’t know with absolute certainty who went through the training. However, if you implement online training the right way, that won’t be a problem. And, it’s not that hard.
First, position training properly—drivers need to see it as an investment in their future and a way to help them do their jobs better and not as “corrective action”—something that implies a chore or punishment. If it’s an investment in them, then they’re more likely to buy-in. Make training a positive and they’ll be interested.
Next, training needs to be scheduled in a way that doesn’t add to their stress. Just be careful; if too much is assigned with too short a deadline, it doesn’t work. Heavy assignments give them one more thing to worry about finishing, as well as taking away their opportunity to think about the content and consider how to integrate it into their work. Lighten the load, extend the schedule, and better results will come.
Third, follow up after drivers complete the course and discuss it with them. That discussion gives them a chance to interact with the content in a different way (talking about it), so it helps ingrain the material and make it part of their normal workflow.
To be clear, I’m not suggesting fleets should blindly trust their drivers and leave it at that. “Trust but verify” applies, so it’s important to find ways to prevent cheating while also minimizing the intrusions or babysitting for the honest people. The steps above do that—positioning it as something that's valuable for them, giving them ample time to embrace and complete it, and discussing it afterward to (gently) confirm they did it.
For the most part, drivers have to be honest people who are trusted to do their jobs. They’re hauling valuable cargo and tasked with driving across a city or across the country, dealing with unknowns all along the way. If that’s the foundation of the relationship, and online training is rolled out in a way that reflects that trust, then there are rarely issues with people cheating.
Mark Murrell is co-founder of CarriersEdge, a provider of online driver training for the trucking industry, and co-creator of Best Fleets to Drive For, an annual evaluation of the best workplaces in the North American trucking industry produced in partnership with the Truckload Carriers Association.
