The assault on reality seems incessant. One way it starts is with decisions being made based on survey results. Survey data is one of the most dangerous weapons wielded in the misinformation war. It’s like calling in the heavy artillery. The bigger the survey, the statisticians will try to convince you, the more accurate the information.
If you look at surveys where so-called independent parties “surveyed fleet owners” you will likely get different conclusions than if you use data culled from “surveying drivers” or “surveying customers.” Why is that? Can they all be right?
The problems start with asking someone their opinion about a topic rather than getting hard data. Opinions are just what you feel about a topic, and they often are less than accurate. It’s why “eye witness” testimony is often questioned in legal fights, and why camera footage is so valuable.
In a past life as an engineering manager, I had a group of engineers whose role was to make data happen. Data about fuel economy, about noise levels, about service life, about duty cycles, etc. A fleet owner might mention to an OEM executive that they were disappointed in the performance of a truck model. That complaint would wind up in my group to “figure it out and fix it.”
Like a scene from a CSI television show, we had to start with understanding how the truck actually was being used. We pulled the build paperwork on the truck, we visited the fleet and installed data loggers that logged all the vehicle’s operational parameters over a week or two of operation in microscopic time spans. Where possible, we observed the fleet in operation, talked to drivers, took photos, did all the investigatory research of a detective.
It often turned out the we could clearly identify the root causes of a performance issue, and just as often, it started with the fleet not fully understanding their own trucks or operations. Assumptions were being made that were not supported by data. One example was a fleet buying aerodynamic trucks but running excessively long trailer gaps, essentially eliminating the benefit of the tractor configuration. Other situations included running very high resistance tires, excessive idle times from long waits at warehouses, high out-of-route miles for parking or fueling, or drivers using excessive braking and rapid accelerations, etc.
That awkward discussion with the fleet to go through how they used their own trucks was frequently left to an OEM executive or someone in marketing and sales skilled in the art of fleet sales diplomacy. But not always. Sometimes my group was volunteered to be the pointed end of the stick, or rather the sacrificial lambs lead to slaughter, if a fleet owner was particularly opinionated.
Fleet owners have some stereotypical traits shared by many successful company leaders — they believe they are right. Their experience got them where they are. They often have to make judgment calls in the absence of complete, perfect information. They’ve been around for years, and still are in business, so many of those judgment calls have been more correct than not. That leadership position often means they are somewhat less connected to first-hand current experience, and they may rely more and more on past experiences to guide their current decision making.
A great example of this is from J.B. Hunt in the 2016 study of their own operations, 660 Minutes: How Improving Driver Efficiency Increases Capacity, where they were challenging assumptions that drivers were actually rolling 11 hours a day when in actuality the time they spent driving was impacted by a variety of things like detention time, inefficiencies, prep time, etc. More recent fleet information has been documenting lost time looking for parking compiled by ATRI and reports by Geotab from telematics data on actual daily route lengths.
One of the great legal qualifiers in all stock market performance company press releases is “past performance is no guarantee of future results.” The author of one study from Leeds University said about that disclaimer that the disclaimer “…tells investors that past performance does not ‘guarantee’ future results, it would seem that they still believe that there is a relationship between the two, if not a 100% correlation. This is in fact wrong, as there is no relationship at all between past performance and future performance.” The same is very true, I feel, about predicting truck performance.
An example is fuel economy. Since 2009 fuel economy for new model, aerodynamic OEM offerings has doubled from around 6 MPG to 12 MPG in some cases. Average fleet fuel economy also is starting to reflect the fact that those older trucks are leaving the market with national averages now over 7 MPG.
A frequent assumption I see is that all heavy-duty trucks go long distances (600+ miles per day) and all are running heavy at near 80,000 lbs. Yet when you look at telematics data, like the Geotab information, or survey data like in ATRI’s Analysis of the Operational Cost of Trucks, you see more than 50% of trucks run less than 500 miles per day. Other weigh-in-motion data that actually measures truck weights on real highways shows that typical weights were well below that 80,000 lbs. level, and averages are in the 65,000 lbs. range.
The assumptions often are wrong, but I think that stems from the need to be optimistic about business metrics. A fleet really wants all its loads to be 80,000 lbs., and all its distances to exceed 600 miles per day. Logic and reason don’t always apply to business opinions.
In other examples, the assumptions are part of vested interest campaigns to influence opinions. Label that as you wish — hype, propaganda, marketing, branding, advertising or whatever — I prefer to call it intentional misinformation.
When OEMs misinform fleets about new products, it is very short sighted as fleets can quickly see for themselves what the weight of the truck is, what the range is, what the fuel economy is.
When fleets deceive themselves by relying on opinions rather than measured data, it’s a self-inflicted wound. The availability of hard data off today’s trucks is phenomenal — telematics, load boards, load tracking, weigh-in-motion, camera systems, etc. There really is no excuse for self-inflicted misinformation. The growth in AI tools will make decisions based on misinformation even harder to rationalize.
I question why survey data is being used when real, measured data is so readily available. Survey data seems only useful to measure how out of touch opinion is with reality.
Fact-based decision making is the future of efficient fleet operations. Challenging assumptions and past experience need to be part of every analysis. The pace of technological change in the last decade has been tremendous and promises to accelerate for the trucking industry. We are in a transition in fleet operations like the difference between 1930s trucking and 1980s trucking, compressed down to a single decade.
Fleet leaders always need to trust their judgment, but they also need to base that judgment on readily available, real-world data. Leaders need to challenge the misinformation machines and have their teams do their homework.
