The Challenge
Six depots. Two telematics vendors. One TMS. Three views of the same vehicle.
De Rooy's data was already there — in the telematics, in the route plan, in the dispatcher's notebook. The fuel team saw consumption patterns the planning team never saw. The dispatcher saw delays the maintenance team needed to know about.
Each system was good at its own job; none was capable of telling the operation that the diesel anomaly on truck 37 was related to the brake-wear pattern that had been quietly trending all week.
The Approach
Don't build a new dashboard. Improve the one the dispatcher already lives in.
Three phases, each anchored in a depot manager's acceptance of the result.
Data unification
Two telematics vendors and the TMS unified into one canonical fleet event stream. The operation no longer chooses which truth to act on.
Behaviour modelling
Driver scoring anchored in measurable, defendable signals: fuel burn against load, harsh-event patterns, route adherence. Coaching that doesn't feel like surveillance.
Workflow integration
The intelligence lives inside the dispatcher's existing screen — not a parallel system. Adoption was measured in dispatcher behaviour, not user counts.
Continuous tuning
Quarterly model reviews with depot leads, with thresholds tuned to the operation's seasonal pattern rather than a vendor schedule.
What We Built
Telematics ingestion layer
Real-time ingestion from two telematics vendors and the existing TMS into a single canonical fleet event stream — without forcing the operation to consolidate vendors or rip out what already worked.
Driver behaviour scoring
A driver behaviour model anchored in fuel burn, harsh-event signatures, and route adherence. Coaching conversations now start from data the driver also sees — not from a number on a manager's screen.
Live dispatcher dashboard
A dispatcher view that surfaces ETA risk, fuel anomalies, and route deviations as they happen — embedded inside the dispatch workflow rather than living in a separate tab no one opens.
Depot-level rollout
Phased rollout across six depots with a calibration cycle at each. Adoption was measured in dispatcher confidence and driver acceptance — not in user counts.
The Results
Numbers the operation can act on, in the moment they happen.
- 9% reduction in fleet-wide fuel consumption within twelve months of go-live.
- 18% improvement in on-time delivery accuracy across the long-haul lanes.
- 6 depots running on the unified platform with consistent KPIs.
- €1.4M estimated annual operational savings attributed to the unified intelligence layer.
In Their Words
“What I appreciate most is that Qubiz didn't replace anything. They made what we already had finally work together. My dispatchers were the ones who told me the new system was worth keeping.”
Pieter de Rooy — Operations Director, De Rooy
Frequently asked questions
01Did De Rooy have to replace its existing systems?
No. Qubiz unified two telematics vendors and the existing TMS into one canonical fleet event stream without forcing the operation to consolidate vendors or rip out what already worked.
02How is driver behaviour scored fairly?
Scoring is anchored in measurable, defendable signals — fuel burn against load, harsh-event patterns and route adherence — and drivers see the same data, so coaching starts from shared facts rather than surveillance.
03Why embed the intelligence in the existing dashboard?
Because adoption depends on it. The intelligence lives inside the dispatcher's existing screen rather than a parallel system, so it's used in the moment decisions are made — adoption was measured in dispatcher behaviour, not user counts.
04What results did it deliver?
Within twelve months: a 9% reduction in fleet-wide fuel consumption, an 18% improvement in on-time delivery accuracy, six depots on a unified platform, and an estimated €1.4M in annual operational savings.
