← All use cases
AI USE CASE
Field service scheduling optimisation
Auto-build technician schedules that maximise jobs-per-day while honouring SLAs.
What it is
An optimisation model builds daily routes and assignments factoring in skills, parts on the van, traffic and SLAs. Field teams complete 15–25% more jobs per day and customer SLA compliance climbs above 95%.
Data you need
Job history, technician skills, parts inventory, location data.
Required systems
- erp
- project management
Why it works
- Build trust with dispatchers in a 30-day shadow run
- Constrain re-optimisation to morning briefing
How this goes wrong
- Dispatchers ignore optimised plans and revert to spreadsheets
- Live re-optimisation creates job churn
When NOT to do this
Don't deploy if your team is under 10 technicians, manual scheduling stays cheaper.
Vendors to consider
This use case is part of a larger Data & AI catalog built from 50+ enterprise transformation programs. Take the free diagnostic to see how it ranks against your specific context.