Safe Driving Analytics
Quantify driving behavior and create coaching loops using speed, braking, acceleration, cornering and contextual risk.
What this capability solves
Safe Driving Analytics converts fragmented operational signals into an accountable digital workflow so teams can detect risk earlier, optimize resources and improve safety or productivity without losing human operational control.
Technology is implemented as an operating capability: architecture, integration, governance, assurance, people, procedures and measurable outcomes are designed together.
Capability model
Modular building blocks allow the scope to start with a focused pilot and expand into an enterprise operating model.
Driving Events
Speed, harsh acceleration/braking/cornering.
Context
Route, road segment, vehicle type and operating environment.
Driver Score
Risk-weighted and trend-based performance.
Coaching
Targeted feedback and improvement plans.
Policy
Vehicle/route-specific thresholds.
Management
Driver cohort and fleet risk analytics.
How the capability fits together
Final topology, control placement and deployment model are validated during discovery and detailed design.
Controls & governance
- Authorized and purpose-bound data collection
- Safety-first operational boundaries and human override
- Role-based access and asset ownership
- Data-quality and calibration controls
- Event/audit history and investigation evidence
- Cybersecurity for devices, edge and enterprise integration
Priority use cases
- Corporate safety
- Oil/mining transport
- Passenger fleet
- Delivery operations
Key deliverables
- Operational/process assessment
- Reference architecture
- Pilot design/configuration
- Integration and data map
- SOP / escalation model
- KPI baseline and scale roadmap
Integration considerations
- Telematics
- GNSS
- DMS
- HR/training
- Fleet platform
- BI
Phased delivery
Each phase ends with evidence, acceptance criteria and a decision gate before broader scale-out.