The idea of adding electric vehicles to the fleet appeals to everyone. Less fuel, fewer emissions, easier access to restricted urban zones. But between the idea and the decision, there’s a step most companies skip: looking at their own data.
Every fleet is different. What works for an urban courier doesn’t work for a company distributing pharmaceuticals across a region. The only way to know if and where electric makes sense is to start from the numbers — the real ones, from your daily operations.
Here are the 5 key data points to analyze before any investment.
1. Average daily km per vehicle
It’s the simplest and most important data point. The real-world range of an electric van in 2026 sits between 150 and 300 km — but in practice, with full payload, hills, climate control and urban driving, expect 70-80% of the manufacturer’s stated range.
How to read it:
- Under 120 km/day → strong candidate for electric
- Between 120 and 200 km/day → possible, but requires case-by-case evaluation (especially available charging windows)
- Over 200 km/day → diesel remains more practical, unless routes include long, plannable stops
If you’re not measuring actual km per vehicle, you’re just guessing.
2. Route distribution: urban vs. interurban
An electric vehicle in urban environments is an efficiency machine. The electric motor performs better at low speeds, regenerative braking recovers energy at every stop, and per-km consumption drops dramatically compared to highway driving.
How to read it:
- Over 60% urban driving → the EV is in its element
- Predominantly highway routes → the advantage shrinks (constant speed = less regeneration, higher consumption due to aerodynamics)
GPS tracking data tells you exactly what the split looks like for every vehicle in your fleet. Without this data, you’re generalizing.
3. Idle patterns: when and where vehicles stop
Charging an electric vehicle isn’t as instant as filling up with diesel. It needs to be planned. And to plan it, you need to know when and where your vehicles sit idle.
What to look for:
- Overnight depot parking: the ideal case. If the vehicle returns every evening and sits for 10-14 hours, a 7-22 kW wallbox is enough for a full charge. Low cost, zero downtime.
- Predictable midday stops: if a vehicle regularly takes a 1-2 hour break at a fixed location, a fast charge can top up range.
- No fixed stops: the most challenging case. Without predictable charging windows, range becomes an operational constraint.
90% of distribution fleets fall into the first category. But without data, you don’t know that.
4. Operating costs per vehicle: the foundation for TCO calculation
Total Cost of Ownership (TCO) is the only comparison that matters. Not the list price, not fuel cost in isolation. TCO includes:
- Energy cost (fuel vs. electricity)
- Maintenance (an EV has 30-50% lower maintenance costs)
- Insurance (often similar, sometimes lower for EVs)
- Depreciation (caution: used EV residual values are still volatile)
- Ancillary costs (zone-access permits, reduced tolls, tax incentives)
To calculate the real TCO of switching a specific vehicle in your fleet to electric, you need actual current operating costs — not estimates. A telematics system that tracks consumption, maintenance and route data is the starting point.
How to read it:
- Calculate the total cost/km for each diesel vehicle
- Estimate the equivalent cost/km for an EV on the same route (dedicated calculators exist)
- If the delta is positive and payback is under 3 years → the investment makes sense
5. Driving style: whoever wastes most, gains most from switching
Driving style impacts diesel consumption by 15-25%. On an electric vehicle, the impact is even more pronounced because regenerative braking converts every deceleration into recovered energy.
A driver who brakes harshly and late in a diesel wastes fuel. The same driver in an EV wastes less, but still loses regenerative efficiency. A driver with smooth, anticipatory driving, on the other hand, can increase real-world range by 10-15%.
What to look for in the data:
- Efficiency scoring per driver (acceleration, braking, speed)
- Normalized consumption per route (same route, different drivers)
- Vehicles assigned to drivers with high scores are the best candidates for EV replacement: they’ll maximize the available range
The full picture: an example
Take a fleet of 12 vans for food distribution:
| Vehicle | Km/day | % urban | Depot idle time | Cost/km diesel | Driver score |
|---|---|---|---|---|---|
| V01 | 95 | 75% | 13h | €0.42 | High |
| V02 | 88 | 80% | 14h | €0.45 | Medium |
| V03 | 110 | 60% | 12h | €0.39 | High |
| V04 | 180 | 30% | 10h | €0.36 | Medium |
| V05 | 220 | 20% | 9h | €0.34 | Low |
V01, V02 and V03 have all indicators in their favor: short routes, high urban percentage, long charging windows, and at least two out of three have efficient drivers. They’re the first three to replace.
V04 is borderline: high mileage but sufficient depot parking. A deeper analysis is needed.
V05 is not a candidate — too many km, mostly interurban, short idle time.
Without these 5 data points, the decision would have been “buy 3 electric vans” (at random) or “wait” (forever). With the data, it’s “buy 3 electric vans — these three — and revisit V04 in 6 months when new models hit the market.”
Where to start
You don’t need a data analytics project to get these numbers. A telematics system with devices installed on vehicles collects them automatically, every day.
The most expensive thing isn’t the system. It’s making the wrong decision — buying the wrong electric van for the wrong route, or not buying one where it would have saved thousands of euros per year.
Data eliminates the risk. And the best time to start collecting it is before you need it.