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Industry AI

Fleet Fuel and Driver Behaviour Analysis

Telematics generates enormous amounts of data and little insight. What actually correlates with fuel use, and how to use it without alienating drivers.

Updated 2 min readBy SpiderHunts Technologies

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Quick answer — TL;DR

Raw telematics scores rank drivers on routes of different difficulty, which is unfair and ignored. Adjusting for load, route, weather and vehicle before comparing produces figures drivers accept - and that is what makes the analysis change anything.

Data without insight

Telematics systems record speed, acceleration, braking, idling, fuel and location continuously. Most fleets use a fraction of it, typically a vendor's driver score that nobody fully trusts.

The distrust is usually justified. A score comparing a driver on urban multi-drop work against one on trunk routes is comparing different jobs, and drivers know it.

Adjust before you compare

The analysis that produces change is one that accounts for what each driver was actually doing.

  • Load weight, which drives fuel consumption directly
  • Route type - urban stop-start against motorway
  • Gradient along the route, which varies enormously by region
  • Weather, particularly wind and temperature
  • Vehicle and its age and specification
  • Traffic conditions at the time

Once these are accounted for, the remaining variation is closer to genuine driving difference. That is a fair basis for comparison and, importantly, one drivers will accept as fair.

What actually correlates with fuel use

FactorTypical influence
Excessive idlingDirect, easily measured, easily reduced
Harsh accelerationSignificant, and coachable
Speed on motorwaySubstantial at the top of the range
Anticipation and coastingReal but harder to measure well
Route choiceOften larger than driving style
Vehicle maintenanceTyre pressure and servicing matter more than expected

The last two rows are worth noting because they are not driver behaviour at all. Fleets sometimes run extensive driver coaching programmes while routing and maintenance offer larger, easier gains.

Use it for coaching, not league tables

Published rankings produce gaming and resentment. Drivers learn what the score measures and optimise for it, sometimes in ways that make actual driving worse.

Individual, specific and private feedback works better: this trip had 40 minutes of idling against 12 on comparable trips, here is where. That is actionable in a way a score out of a hundred is not.

Where incentives are used, base them on improvement against a driver's own history rather than on ranking. That rewards everyone who improves rather than only those on the easiest routes.

Be straight about monitoring

Telematics involves monitoring employees, which carries legal obligations and a real effect on trust. Both are better handled openly.

Tell drivers what is collected, what it is used for, and what it will not be used for. Involve them in designing how it is used. Fleets that impose monitoring silently get resistance and data manipulation; those that are transparent generally get cooperation.

A driver score that ignores the route is a score of the route.

FAQ

Frequently asked questions

The questions readers ask us after this guide.

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How much fuel saving is realistic?

It varies by fleet, current practice and route mix. Establish your own baseline and measure - published figures rarely transfer.

Is telematics monitoring legal?

Generally yes with appropriate notice, purpose limitation and an assessment, but obligations vary by jurisdiction. Take advice before deploying.

Do we need load data?

It substantially improves the analysis. Without it, comparisons between drivers carrying different weights are unreliable.

Should driver scores be shared?

Individually and privately, yes. Public league tables tend to produce gaming rather than improvement.

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