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A fleet manager running 12 trucks reads that top-performing fleets hit 94% PM compliance, checks their own number at 81%, and concludes they have a discipline problem. A fleet manager running 48 trucks reads the same benchmark, checks the same number, and reaches the same conclusion. Only one of them is probably right, and it is not the one with 12 trucks.
The benchmarks themselves are not the issue. They are well established and broadly correct. What almost no benchmark article mentions is that the operational path to hitting a given number, and the meaning of falling short of it, changes substantially depending on how many trucks are generating the data. A truck preventive maintenance program at 12 trucks and one at 48 face genuinely different obstacles to reaching the same target, and treating them as the same problem leads small fleets to misdiagnose what is actually going wrong.
The first and most underappreciated difference is arithmetic. A 10-truck fleet running PM-A and PM-B services generates a relatively small number of scheduled service events in any given quarter. A 50-truck fleet generates five times as many. When you express performance as a percentage, the fleet with fewer events sees far more dramatic swings from the same absolute number of misses.
One truck that runs past its PM-B window because a load ran long moves a 10-truck fleet's compliance rate by a visible margin. The identical miss on a 50-truck fleet barely registers in the quarterly number. This means a small fleet's compliance percentage is a noisier signal than a large fleet's, and reading one quarter's figure as a verdict on program quality produces false alarms in both directions. A 10-truck fleet at 78% one quarter and 96% the next has not transformed its maintenance program. It has had two different quarters with a small handful of events each.
The practical implication is that small fleets should be reading these metrics as trends across three or four quarters rather than as quarterly report cards, and should probably track absolute misses (how many service windows did we actually blow) alongside the percentage, because the raw count is a more stable signal at that scale than the ratio is. The fleet maintenance program performance article covers what these metrics measure and why they matter. What this article adds is that the same number carries different confidence depending on how many events produced it.
The second difference is where the work sits. At 50 trucks, maintenance coordination generates enough volume that someone typically owns it as a defined responsibility, whether that is a dedicated coordinator, a shop manager, or a coordination program handling it externally. At 10 trucks, the volume rarely justifies a dedicated role, so the work lands on whoever has capacity, usually a dispatcher already managing loads, drivers, and customer calls.
That distinction matters because the failure mode is different. A 50-truck fleet missing its PM targets usually has a process problem: the tracking system is inadequate, the shop network cannot absorb the volume, or the scheduling logic is broken. A 10-truck fleet missing the same targets usually has an attention problem: the tracking exists, someone knows the truck is due, and the service window passed because three more urgent things happened that week. Those two situations look identical in the compliance percentage and require completely different fixes.
This is why generic advice to "improve your PM tracking" frequently fails at small fleets. The tracking is often fine. What is missing is anyone whose actual job is to act on it when a service window approaches and the truck is 600 miles from home. The fleet PM tracking article covers the execution mechanics of that problem in detail, and the execution gap is consistently larger at small fleets than the knowledge gap is.
The third difference shows up in cost benchmarks rather than compliance ones, and it is the one small fleets have the least control over independently.
A 50-truck fleet approaching a shop or a parts supplier brings enough annual volume to make pre-negotiated pricing worth the supplier's administrative effort. A 10-truck fleet approaching the same shop brings a fraction of that volume, and frequently gets quoted closer to walk-in rates as a result. When both fleets are then measured against the same cost-per-mile benchmark, the small fleet is being held to a target that partly reflects purchasing power it does not have.
This is not a discipline gap and it does not respond to better internal process. A 10-truck fleet can run flawless PM scheduling and still sit above the cost-per-mile benchmark simply because every part and every labor hour costs it more than it costs the larger fleet it is being compared against. The coordination cost article covers how network-level pricing works, and the relevant point here is that aggregated volume is the mechanism by which a small fleet accesses rates its own volume would not command.
If your fleet sits in the 10 to 20 truck range and your cost-per-mile number has stayed stubbornly above benchmark despite genuinely solid maintenance discipline, purchasing power is worth ruling in or out before you go looking for a process failure that may not exist. A coordinated nationwide truck preventive maintenance program aggregates volume across many fleets, which is what allows a 12-truck operation to buy at rates its own annual spend would never justify on its own.
Given all three of the above, the most useful adjustment a small fleet can make is not chasing the headline percentage harder. It is changing which numbers get attention.
Absolute miss count is more stable than compliance percentage at small volumes, so tracking how many service windows were actually blown in a quarter gives a cleaner read on whether things are getting better or worse. Time-to-schedule, meaning how long between a service window being identified as approaching and an appointment actually being booked, isolates the attention problem that most commonly drives small fleet misses, and it is a number a dispatcher can act on directly. And per-unit cost tracking matters more at small scale than fleet-average cost per mile, because with only 10 or 12 trucks, a single problem unit distorts the fleet average enough to make the aggregate number nearly meaningless as a management signal.
None of this means small fleets should hold themselves to lower standards. The 94% compliance target is achievable at 10 trucks, and the fleets that hit it see the same breakdown frequency benefits that larger fleets do. It means the route there runs through different obstacles, and diagnosing a purchasing-power problem as a discipline problem, or a noisy quarterly percentage as a program failure, sends a fleet manager chasing fixes for things that were never broken.
The benchmarks are not wrong. They are just incomplete without the context of what produces them. A fleet manager who understands why their 14-truck operation sits where it does on each metric is in a much better position than one comparing themselves to an industry average built largely from the performance of fleets several times their size.
The fleet maintenance plans page covers how coordination works across different fleet sizes, including what changes at the smaller end where dedicated internal coordination is not realistic. If you want to look at where your specific fleet sits on these metrics and whether the gaps are discipline, attention, or purchasing power, reach out through the contact page with your fleet profile and recent maintenance history. Sorting out which of the three is driving your numbers is a much more productive conversation than benchmarking against an average.
This article draws on the following sources:
