What a Vehicle Actually Costs

Fleet decisions are usually made on purchase price or monthly finance. Neither predicts what the vehicle will cost over its life.

The components

Acquisition: purchase or finance, less residual value at disposal.

Fuel or energy, over the holding period.

Maintenance and repair, scheduled and unscheduled.

Tyres.

Insurance and tax.

Downtime, which is the cost of the work not done while the vehicle is off the road.

The last one is real and is omitted from almost every fleet calculation, because nobody owns the number.

Assembling it from your own data

Per vehicle, per year, from the systems you already have.

Fuel from the cards, reconciled against consumption.

Maintenance from the workshop or the supplier invoices.

Downtime from the maintenance records, counted in days.

Residual from actual disposal proceeds rather than a book figure.

A spreadsheet, an afternoon, and it is the first time most fleets have seen the number.

What it reveals

That the cheapest vehicle to buy is frequently not the cheapest to run, which is the whole point of the exercise.

That maintenance cost rises sharply after a threshold, which varies by type and is the replacement signal.

That one model in the fleet costs materially more than another doing the same work, which is a purchasing decision waiting to be made.

And that downtime dominates for vehicles doing revenue work, which changes the argument for holding a spare.

Using it for replacement

Plot annual cost per vehicle against age or distance.

The curve flattens then rises. The rise is the replacement point, and it is specific to your work and your models.

Which is more reliable than a fixed replacement policy, and frequently later for some vehicles and much earlier for others.

Telematics contributes the usage and condition data that makes the curve real rather than modelled.

What to be careful with

Averaging across vehicle types, which produces a number describing nothing.

Ignoring the tail: a few vehicles with very high repair costs distort a mean and are themselves the finding.

Treating residual value as certain, which it is not, particularly with electric vehicles where the market is still moving.

The measure

Cost per mile or per operating hour, per vehicle, per year.

Trended, because the direction matters more than the level.

And compared across models doing the same work, which is the comparison that informs the next purchase.

Use actual disposal proceeds

Not a book figure.

Residual value is the largest single uncertainty in the calculation and the one most often taken from an accounting policy rather than from what vehicles actually sold for.

Record realised proceeds against forecast, every disposal.

After a few years you have a residual curve for your own models, which is worth more than any published table.

Reproduce the workflow

For another way to make this requirement testable, consult project time tracking for operational costs. Reproduce the case with real roles, codes, failures and recovery steps.