Fleet fuel over-consumption: how to detect it from data you already have

Fuel is typically the largest single cost line of a road-freight carrier — and the one with the least visibility. The good news: you don't need to install anything to get that visibility. A data sensor beats a tank sensor: the evidence is already sitting in your fuel-card statements and odometer records.

The method, in four steps

1. Set a norm per vehicle class. Every vehicle class has an expected consumption corridor (public baselines: a loaded 40 t long-haul set typically runs ~30–33 l/100 km — see our benchmark article). Adjust for your reality: route profile, typical payload, winter operations. Where manufacturer or telemetry data exists, use it — the norm must be defensible, not optimistic.

2. Compute actuals per vehicle, monthly. Litres from the fuel-card export ÷ kilometres from the odometer or tachograph = l/100 km, per vehicle, per month. This is deliberately vehicle-level: consumption analysis needs no driver names, and processing none keeps the analysis clean legally and fair operationally.

3. Look at deviations, not absolutes. A vehicle 2 % over its norm is noise. The signal is a vehicle consistently and materially above the norm of its own class — especially when its siblings on similar work are not.

4. Explain before you conclude. Most deviations have benign operational causes, and they should be checked in this order: payload changes (+3 t ≈ +1.5–3 l/100 km), route or customer mix, winter share and idling, tyre condition and pressure, vehicle age and recent maintenance. What remains after honest explanation — an unexplained residual deviation — is what deserves verification: inspect the vehicle, review the refuelling process, reconcile card transactions against routes. A deviation is a reason to verify, never a verdict about a person.

Doing it in a spreadsheet — and where that breaks

For a handful of trucks, four columns do the job: month, vehicle, litres, km. Add a norm column and a deviation formula, and you have a working control.

It breaks at scale: 20+ vehicles × 12 months × mixed refuelling sources produce format chaos (every card provider exports differently), odometer gaps, partial months, and vehicles that switch duties mid-year. That's the point where carriers either give up — or automate the comparison.

The 60-second version

Our free check runs step 1–3 for one vehicle class in about a minute: enter the class, monthly kilometres and monthly fuel spend, and you get an A–F grade plus a euro estimate of the gap against a calibrated norm. No file upload, no signup, nothing stored, EU processing — and a human reviews conclusions before anything becomes a recommendation.

→ Run the free fleet fuel check

If the grade points at a real gap, the next step is a free human-delivered audit of 12 months of your fuel-card data (vehicle-level only — we ask you to remove driver columns before sending). You get a written findings memo and a short call; what you do with it is your decision.

LKW Control is operated by Engineers-incubator s.r.o., Horná 67, 974 01 Banská Bystrica, Slovakia. Contact: hello@euhub-ai.com. This article is analytical guidance, not tax or legal advice.