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Understanding Driver Performance: How to Compare Apples to Oranges

Updated: Dec 3, 2021

When we put pen to paper on the design of our flagship PedalCoach solution back in 2014, the primary focus was fairness. At that time, our goal was to create a level-playing field for drivers and organizations, removing everything outside of the driver’s control (e.g., truck make, model, load, terrain) through machine learning, providing drivers with a fair fuel target, and organizations with a fuel efficiency score that could be utilized across the entire fleet. From those humble beginnings, fairness has been embedded in the fabric of our designs, rippling through each and every decision we make and reverberating at the core of who we are. It is with this in mind that we shared Marco Alverà’s TED talk on “the surprising ingredient that makes business work better,” as a precursor to this post, focusing specifically on fairness, and it’s also why we are so excited to share how this mantra applies and extends to our Driver Performance Management (DPM) solution today.

Fleet management and operational teams have the ubiquitous and time-consuming task of assessing the apples and oranges within their fleets to truly understand how the organization might be performing, and this is before they can even consider coaching drivers. The types and responsibilities of fleets and drivers within an organization can vary widely, and with that variability, not only can targeted performance levels differ drastically, but the KPIs themselves can also be entirely different. Ignoring this variability and assessing an Over the Road (OTR) driver the same way you might a Local driver, for example, would be like trying to coach track and field athletes the same way, regardless of whether they compete in the shot put or the 100-meter dash. It’s with this in mind that our focus on fairness and refusal to accept a one-size-fits-all approach comes center-stage with the implementation of driver profiles in our DPM solution in order to truly provide a world-class solution to the industry.

Above: (Left) MyDrive report sent to drivers nightly after they wrap up for the day. (Center) LinkeDrive portal’s Company Score showcasing aggregate metrics, trending, and distributions. (Right) MyScore report automatically sent to drivers when the month wraps up, their month over month performance metrics, where things went well, and where focus is needed. Drivers will also be automatically coached weekly through our system based upon where the focus is needed!

At the most basic level, consider driver profiles as “performance definitions,” for specific driving types, such as: OTR, Regional, Local, Shuttle, etc. Within each one of these profiles exists what we statistically determine during implementation, combined with feedback from our customers, to be appropriate thresholds for these profiles among the variety of associated metrics. Let’s take for example one of the more common metrics that fleets assess: idle percent. Bottom line is, what might be considered appropriate for an OTR living out of the cab of the truck, may be drastically different for a Regional day-tripper. Seems simple enough, right? Expand that to the dozens of metrics that should be important in ensuring your business is operating effectively and competitively, and then further expand that to the variability amongst the array of driving types that exist in your organization today. Now, consider coaching drivers across that variability. Who do you focus on, what do you say, how do you even say it… and did you wait too long for it to be relevant? It’s easy to see how this can quickly become very complicated as well as daunting to operationalize effectively. Therein lies the challenge, as well as an opportunity to improve and grow your organization.

Initially, we mentioned fairness as being embedded in the fabric of our designs, rippling through each and every decision we make and reverberating at the core of who we are. It is important then to share that driver profiles aren’t simply a “definition” in our DPM solution, but that it is fundamental and deeply rooted in our DPM framework, influencing every aspect of our solution to not only ensure fairness when assessing driver performance through our reporting infrastructure, but also extending to driver coaching. Yes, even LinkeDrive’s patent-pending coaching, leveraging Natural Language Generation (NLG), focuses on fairness and is tied to driver profiles. “Getting it right” with how you coach, what you say, and who you say it to is critically important to get the best engagement, and then in turn the best performance. You simply have to ask yourself, going back to the track and field example, would they be going to the nationals if everyone was coached the same regardless of whether they competed in the shot put or the 100m dash? It’s safe to say it would be a short season. The fact of the matter is, our ethos hasn’t changed from our inception, and we will continue to provide fairness, equity, and satisfaction in every solution and to every customer, no matter the playing field.


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