Fleet Management and the Cost of Decarbonisation: How European Operations Should Sequence the Transition

The sequencing problem

Most European fleet decarbonisation plans start with vehicles. A replacement schedule, a charging infrastructure plan, a capital request, and a timeline that stretches across several budget cycles.

That plan is necessary and it is the wrong thing to do first, for a reason that has nothing to do with technology. A vehicle replacement programme consumes capital immediately and produces reportable reductions slowly, because the reductions arrive vehicle by vehicle as the schedule advances. Meanwhile the operation continues running the same number of kilometres, a portion of which is avoidable.

Reversing the order changes the economics. Reducing kilometres for the same delivered volume produces an immediate reduction, requires no capital, and lowers the number of vehicles the eventual replacement programme has to cover. Every avoidable kilometre removed before the transition is a kilometre you never have to electrify.

That is a fleet management argument rather than a sustainability one, which is why it tends to sit outside the programme that owns decarbonisation.

Also Read: Which CSRD Scope 3 Path Fits Your Operation? A Decision Framework for European Logistics Leaders

How much of your current emissions is avoidable

Two measures locate it, and both are already in your operational data.

Empty running. Eurostat reports that 21.6 percent of distances travelled by road freight vehicles in the EU were performed by empty vehicles in 2024, rising to nearly 26 percent for national transport. Those kilometres consume fuel and produce emissions while carrying nothing.

Fill rate on loaded journeys. Chalmers University of Technology research indicates that optimised consolidation can raise vehicle fill rates from approximately 45 percent to approximately 74 percent. A journey running at half capacity produces close to the same emissions as the same journey running full.

Read together, they describe a meaningful share of current road freight emissions attributable to capacity that carried nothing or carried little. Not all of it is addressable, since directional imbalance and service requirements make some empty running structural, but the addressable portion is the cheapest abatement available to any fleet and it is available now.

The cost structure explains why this rarely gets prioritised. ATRI’s cost data, which is US-based and used here for composition rather than for European cost levels, puts driver compensation at roughly 44 percent of operating cost, equipment at roughly 28 percent, and fuel at roughly 21 percent. Fuel is the only line that falls when kilometres fall, so a distance reduction shows up as a modest cost saving and a substantial emissions saving. Programmes justified on cost alone therefore undervalue it, and programmes justified on emissions alone rarely look at it because it is not a vehicle initiative.

Sequencing in three phases

Phase one: eliminate avoidable distance

No capital, immediate effect, and it shrinks the scope of everything that follows.

Four levers, in order of typical size. Consolidation, so fewer journeys carry the same volume. Backhaul matching, so return legs carry load. Multi-drop density improvement through better clustering. And elimination of repeat journeys caused by failed deliveries, which are emissions produced for no delivered output at all.

The measurement to establish first is kilometres per delivered unit, by route type. That is the metric this phase moves, and it is also the metric that makes phase three defensible, because it tells you how many vehicles you actually need rather than how many you currently run.

The planning gap this addresses is documented. McKinsey has found that static planning models can leave as much as 60 percent of operating hours either understaffed or overstaffed, and the same static approach produces the empty and underfilled journeys above.

Phase two: match vehicle to duty cycle

Before replacing anything, establish which routes suit which vehicle type. This is analysis rather than procurement, and it determines whether phase three succeeds.

Electric vehicles perform best on predictable, moderate-distance, return-to-base duty cycles with depot charging. They perform worst on long, variable, unpredictable routes where range and charging availability become planning constraints. Urban access schemes complicate this further, since low emission and zero emission zones across European cities make vehicle eligibility route-specific rather than fleet-wide.

The output of this phase is a route-to-vehicle-type map, which tells you which portion of your fleet is a candidate for replacement now, which is a candidate later, and which is not a candidate at all with current technology. Buying before doing this produces vehicles assigned to routes they cannot serve, which is the most expensive failure mode in the whole transition.

Also Read: Electrification and Route Constraints: What European Fleets Need to Model Before They Buy

Phase three: replace where the duty cycle fits

Now the capital programme, scoped by the map from phase two and sized by the reduced kilometre base from phase one.

Two things change when the sequence runs this way. The vehicle count is lower, because avoidable distance was removed first, so the capital request is smaller for the same delivered volume. And the assignment risk is lower, because vehicles are purchased against duty cycles they were matched to rather than against a replacement schedule.

Charging infrastructure follows the same logic. Depot charging capacity should be sized against the routes assigned to electric vehicles rather than against the fleet, which is a materially different number.

Where reporting scope sits now

The regulatory driver deserves a caveat, because it has changed.

CSRD brought granular Scope 3 reporting into view for a large population of European companies, and that population has since narrowed. The European Commission’s Omnibus package is expected to remove around 80 percent of companies from CSRD scope while reducing administrative costs by approximately 4.4 billion euros annually. Separately, EFRAG found that nearly 89 percent of surveyed companies rated the effort of implementing ESRS as enacted in 2023 as high or very high, with the revised draft cutting mandatory datapoints by 61 percent.

Two implications. Establish whether you remain in scope before building a programme around the requirement, since the answer has changed for many mid-market operations. And note that enterprise customer requirements frequently outlast regulatory ones: a company outside CSRD scope may still face Scope 3 data requests from customers who are inside it, which is a commercial driver rather than a compliance one and does not disappear with the regulation.

That distinction matters for how the programme is justified internally. A compliance-driven programme is vulnerable to scope changes. A programme justified on kilometres removed, cost reduced, and customer data requests satisfied is not.

Also Read: Scope 3 Transport Emissions: The Hidden Cost of AI Carbon Tracking Across European Multi-Carrier Networks

Also Read: Fleet Management and Utilization: How AI Architecture Improves Capacity, Cost, and Performance in 2026

What this means for fleet management specifically

Three practices sit with the fleet function rather than with sustainability, and all three affect the outcome more than the vehicle choice does.

Measure kilometres per delivered unit, not total kilometres. Total kilometres falls when volume falls, which tells you nothing. Kilometres per unit isolates efficiency from demand and is the only measure that shows phase one working.

Report emissions by route type rather than fleet-wide. A fleet-wide figure is a weighted average across urban, regional, and long-haul work with entirely different abatement options. Route-type reporting shows where reduction is available and where it is not.

Treat vehicle eligibility as an allocation constraint. Once a mixed fleet exists, with different vehicles eligible for different zones and different duty cycles, allocation becomes a constraint problem rather than a scheduling one. A vehicle assigned to a route it cannot legally or practically serve produces an invalid plan, not a chargeable event.

Where Locus fits

Locus, the world’s first Decision-Intelligent, Agentic TMS, operates on the decisions that determine phase one and phase three feasibility: how much distance is run, how full vehicles are, and which vehicle serves which route.

Within DiSCO, the Dispatch agent plans and re-sequences against 250+ real-world constraints, which include vehicle type eligibility and access restrictions, the Capacity agent matches demand to available capacity and identifies consolidation opportunities, and the Carrier agent allocates across owned and contracted resources. For a mixed electric and conventional fleet, that constraint set is what prevents a vehicle being assigned to a route it cannot complete.

Locus has been recognized by Gartner for seven consecutive years, featured in the 2026 Hype Cycle for Supply Chain Execution and Logistics Technologies, named a Leader in TMS by QKS Group (SPARK Matrix), and ranked #1 in Route Planning on G2’s 2026 Best Software Awards. In October 2025, Ingka Investments, the investment arm of Ingka Group, the world’s largest IKEA retailer, acquired Locus. Locus continues to operate independently, with 800M+ miles eliminated and 17M+ kg of CO2 avoided across its deployments.

Two deployments show phase one operating at scale. A global FMCG leader running distribution across ten countries eliminated 12,000+ trips each month through demand-matched capacity and fuller loads, alongside 15 percent less distance travelled, with the case noting that route optimisation lowered fuel cost and carbon emissions together while protecting thin distributor margins.

A global lottery operator running a field-service network across 25 or more jurisdictions cut drive distance and time by 15 percent and fuel spend by 18 percent through skill-matched assignment and live re-optimisation, with the same workforce covering more cases. Neither deployment required a single vehicle purchase.

Also Read: CSRD Scope 3 Transportation: How AI-Powered Route Optimisation Closes the Emissions Data Gap

The analysis to run before the next capital request

Calculate kilometres per delivered unit by route type, then estimate what it would be with your empty running at the achievable share and your fill rate at the achievable level.

The difference is the vehicle count your replacement programme does not need to cover. In most operations it is large enough to change the capital request materially, and it is available before any procurement decision is made.

That number is also the strongest internal argument for sequencing this way, because it converts a sustainability programme into a smaller capital programme, which is a different conversation with finance.