Fleet managers today can access a vast amount of data, but unfortunately, most of this data is either unused or underused. This results in missed opportunities to improve operations and reduce costs.
The organizations that are successful in using the data for actionable insights see significant benefits such as reduced fuel costs, lower maintenance expenses, increased productivity, and improved driver safety.
Why raw data isn’t the same as insight?
Telematics provided us with real-time information about the exact location, speed, and engine status of each vehicle. This was one of the first advancements. The second, and more impactful one, was using this data to make decisions that help minimize costs and risks.
Many fleets are in this gap between the two advancements. They receive lots of data points but aren’t able to connect a specific metric to a related management decision. We share with you below the seven KPIs that you can track as a system and that can tell you exactly where you are unnecessarily spending money.
1. Cost Per Mile (CPM).
The cost per mile is the most critical number in the finance department, and it should be your most important number too. To calculate this, add up all your fixed costs like depreciation, insurance, and financing. Then add to that all your variable costs like fuel, tires, and maintenance labor. Divide that by all the miles you drove. The average marginal cost of operating a commercial vehicle hit a record high of $2.251 per mile in 2023 (American Transportation Research Institute). That gives you something to measure against, but your CPM is worthless if it’s an average. Your CPM needs to be tracked at the vehicle level. A vehicle running at $3.10 per mile is either due for disposal or needs an immediate maintenance review. You won’t know which until you isolate it.
The cost per mile is usually a dirty number. When it goes up, it’s rarely because of one thing. Rather, it’s an amalgamation of a dozen little issues. Tracking the cost per mile at the vehicle level allows you to identify trends across the RFM cycle. For example, if you get three months out of a tire’s predicted replacement date and the tire is already ruined, you have a maintenance issue. If that tire routinely goes on your top-performing vehicles, that is a routing and maintenance issue.
2. Unscheduled downtime vs. scheduled maintenance ratio.
A properly managed fleet will expect about 80% of vehicle downtime to be “planned” – that is, taken up by scheduled preventive maintenance, inspections, and regulatory checks. If you’re experiencing more than 20% of total downtime due to breakdowns, your preventive maintenance program is not working as it should.
This ratio is also one of the most reliable measurements of operational maturity. Unscheduled downtime will nearly always cost you more than scheduled work because of emergency labor, rush order parts, towing, and the downstream costs of a late delivery. A truck that comes in for a $300 PM service every 15,000 miles is vastly cheaper to run than a machine that misses it and breaks down by the side of the road at 22,000 miles.
Tracking the split of your downtime over time will also tell you if your predictive diagnostics tools are anything other than a burden on the P&L. If you buy engine data monitoring and none of the key engine failure breakdown numbers improve, that’s how you’ll know it also.
3. Fuel efficiency and idle time.
Fuel is often the most expensive variable cost in fleet operations, and much of it is used when vehicles are simply sitting idle. Idle time, meaning the engine is running but the vehicle isn’t moving, is low-hanging fruit because the waste is completely avoidable and within direct control of the driver and dispatch.
The trick is to measure idle hours independently of driving hours. Once they are combined, the figure gets lost in the overall fuel spend and you can’t see who is doing what. Separate the number out by driver and by vehicle, and you’ll start to notice trends pretty quickly. A driver who idles 2.5 hours per shift on a diesel is using a lot of extra fuel that, when multiplied over the span of a year, can easily reach into the thousands of dollars.
Driver training specifically on the subject of idling is well worth the investment. We have coached fleets to reduce idle time by 20-30% in one quarter. The reason the idle time came down wasn’t because the drivers were deliberately idling too much but that, for the first time, they were being shown the data.
4. Asset utilization rate.
Asset utilization reveals the amount of time your vehicles are in use as opposed to being parked in a yard or depot somewhere. If a fleet’s utilization falls below 65-70%, it is almost certain that there are vehicles not contributing revenue but still adding costs.
People sometimes refer to these as “ghost assets”. They are fully paid for via insurance direct costs, depreciation, and regular maintenance checks, but they typically sit unused most of the time. In some fleets, ghost assets can make up as much as 15-20% of total asset count, and that loss is unseen unless specific measurements are taken to reveal it.
The response here isn’t always to sell them. Sometimes low utilization points to a scheduling issue, a geographic misalignment between asset location and where it’s needed, or to having chosen a vehicle type best suited to the work as it was three contracts ago. Determining what the problem at your fleet is and how to address it successfully becomes a matter of guesswork without accurate data on utilization at the individual unit level.
This is the point where trying to keep tabs on everything via spreadsheet becomes completely impossible. The number of variables quickly becomes overwhelming, the data is constantly changing, and the metrics are too dependent on each other to manipulate them by hand. Today’s fleet management solutions can aggregate real-time telematics data and present it in a way that allows you to identify a ghost asset in a matter of seconds rather than a quarter.
5. Driver behavior metrics.
Driver behavior scores are calculated based on telematics data related to harsh braking events, rapid acceleration, aggressive cornering, and speeding. For the most part, fleet managers view these scores as a safety metric, but the reality is that the cost-based behavior connection has a stronger impact.
Poor driver behavior scores correlate directly with fuel cost escalations. Roughly, aggressive acceleration and braking on a diesel vehicle can use up 15-25% more fuel over the same route driven with a smoother style. The same behaviors also accelerate brake wear, tire wear, and transmission stress, pushing maintenance costs up and pulling asset lifespan down.
The insurance connection is becoming more direct over time. Carriers are increasingly requesting telematics data as part of renewal discussions, and fleets that can demonstrate consistent improvements in driver safety scorecards are in a better position to negotiate. A sustained 10% reduction in incident rates translates to a measurable conversation at renewal – not a hypothetical one.
Coaching programs tied to driver behavior scores work best when drivers can see their own data. Gamification approaches, where drivers can track their scores against their own history or against anonymized peers, consistently outperform top-down reporting in changing actual behavior.
6. Maintenance compliance rate.
Ensuring preventive maintenance (PM) tasks are completed on time is not just an operational matter. It’s actually a financial issue too because when you eventually want to sell or trade your assets, higher PM compliance rates lead to better resale values. Resale values are higher for well-maintained vehicles. Differences can be clearly seen, for instance, in auto leases when the leasing company gets to sell the vehicle returned from lease.
Beyond maintenance avoiding breakdowns, overhauls, or even having to retire an asset early because overhaul costs exceed the residual value, are all hidden revenues. To measure PM compliance, you can track the number of PMs completed on time versus their scheduled date. Target a PM compliance rate of 95% or higher. For below 90%, chances are that the shop in general is already overburdened or individual assignments are falling through the cracks.
7. Route adherence and on-time delivery (OTD).
Route adherence is a measure of how closely the actual paths taken by vehicles match the planned routes. On-time delivery (OTD) rate is the percentage of jobs or deliveries that are completed within the committed window of time. Both metrics combined show if your optimization actually functions in reality or simply on spreadsheets.
Sometimes, route deviations don’t have anything to do with drivers. If the software planning the optimal route doesn’t have all the required data or if restrictions impede the optimal route in the real world, that’s not a driver issue. Tracking route-level data over time can pinpoint recurring route deviation issues that can indicate a need for adjustments in planning.
One driver constantly deviating at the same intersection is a driver coaching issue. Every driver deviating where every other driver has the exact same problem is a planning or mapping issue. The only difference is whether you’re measuring route-level data.
Building a single source of truth.
If you are tracking seven key performance indicators (KPIs) or metrics around your fleet, but the data for each metric lives in disparate systems, it’s highly unlikely you are using that data to maximum effect. This is how it typically works today: You rely on finance to give you your cost per mile (CPM) number from the enterprise’s financial management or corporate performance management (CPM) system, while the safety team manages driver behavior data in the safety and compliance system, and operations might be in charge of deriving maintenance compliance from the fleet management system. However, you’re not likely getting the full, most current, and relevant data from each of those systems.
Your goal should be to make all that data dynamically available along with the other four metrics I’ve mentioned – and likely many others – in a single dashboard that can be accessed by any relevant manager within the typical fleet organization. In this case, you’re always getting the most up-to-date analysis on the performance of your assets, operations, and drivers. No more waiting until the end of the month to discover that your cost per mile is too high.
Finance, fleet, and safety working from the same data removes the internal friction that can slow decisions down while adding value to the enterprise. And, it provides the best business case possible for the purchase of additional technology – since the technology, in this case, pays for itself, with the proper deployment, through increased uptime and availability on the capital asset. The fleets that manage their assets best today and for the future are the ones who are the best informed.
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