The fleet average is the least useful number you have.
Every fleet reports one. It moves a point a quarter and tells you nothing, because it is an average of people who were never the problem and a handful who are.
What coaching actually does
22 drivers over 90 days. Drag the months — only the drivers below 72 are coached, and only they move.
- Fleet average
- 72.0
- Below 72
- 7
- Drivers coached
- 7
- Untouched
- 15
7 of 22 drivers sit below 72. The fleet average of 72.0 is not the problem — the shape underneath it is.
Ranking on event counts ranks mileage
This is the mistake that kills a behaviour programme in month two. Sort the fleet by how many events each driver triggered and you have sorted it by who drove furthest.
Same drivers, same 90 days, two orderings. S. Rahman tops the raw list with 48 events — across 21,400 km, which works out at 2.58 per 1,000. W. Nasser triggered 38 in 8,400 km, which is 4.36. One of them needs a conversation.
Ranked by raw event count
What most systems show by default
- 1 S. Rahman Long haul · 21.4k km 48
- 2 P. Kumar Mixed · 15.8k km 45
- 3 Z. Ahmed Urban delivery · 10.2k km 38
- 4 W. Nasser Urban delivery · 8.4k km 38
- 5 A. Al-Harbi Long haul · 24.8k km 29 not actually
- 6 N. Siddiqui Urban delivery · 11.6k km 27 not actually
Ranked per 1,000 km
What Saqr scores on
- 1 W. Nasser Urban delivery · score 26 4.36
- 2 E. Kone Urban delivery · score 34 3.89 missed
- 3 Z. Ahmed Urban delivery · score 39 3.59
- 4 O. Adeyemi Urban delivery · score 48 3.09 missed
- 5 P. Kumar Mixed · score 49 3.00
- 6 S. Rahman Long haul · score 56 2.58
2 drivers in the left-hand list do not belong there. A. Al-Harbi and N. Siddiqui rank highly on raw counts because of how much they drive, not how they drive — normalised, they sit mid-pack. 2 who genuinely need coaching, E. Kone and O. Adeyemi, never appear on it at all. Run a programme off the left-hand list and you spend your credibility on the wrong people in the first fortnight.
What goes into it
Four components, published weights. A score nobody can reconstruct is a score drivers are right to distrust.
- Harsh braking Deceleration past a threshold that scales with speed, not a fixed g.
- ×1.0
- Harsh acceleration Weighted lower — it costs fuel more than it costs safety.
- ×0.8
- Cornering Lateral g, suppressed on roundabouts where the geometry forces it.
- ×0.8
- Speeding Against the posted limit, weighted highest: it decides how bad the other three are.
- ×1.6
Most events should never reach a manager
The in-cab warning does nearly all the work. By the time something reaches a coaching session it is a pattern, not an incident — and the driver has already seen every clip in it.
How the in-cab alert works- 01
In the cab
An audible warning at the moment it happens. Most events end here and never reach anyone's desk.
- 02
In the driver's app
Their own events, their own score, their own trend — visible to them before it is visible to a manager.
- 03
Self-review
The clip is theirs to watch. A driver who has already seen it does not need to be told about it.
- 04
A session, if needed
Only for a sustained pattern. Coaching everything trains people to ignore coaching.
- 05
Back to the score
The programme is judged on whether the tail moved, not on how many sessions were run.
The rest of the platform
Live tracking
Position, speed and ignition every ten seconds.
Routing and dispatch
Plan the day, send it to the driver's phone.
Asset and trailer tracking
Trailers, generators, plant and containers.
AI dashcam
Road and cabin, clipped to the event.
Incident centre
Footage, telemetry and witnesses in one file.
Maintenance
By odometer, engine hours or date.