Key takeaways
- AT&T reported saving $10M a year in route and fuel optimization with models that aligned local technician skills with local jobs while minimizing mileage.
- AT&T described a fleet of 7,000 trucks, where the mix of service requests changed every day.
- Models predict job duration and travel time and rank technicians on skill fit and distance, so fewer trucks cross town for a job.
- The platform runs in four deployment options: on-premises, air-gapped, private cloud and cloud.
Every extra mile is fuel, time and a later appointment
Your fuel bill is set one assignment at a time. When the nearest qualified technician is not the one sent, the truck drives farther, the customer waits longer, and the next job slips.
The best match is hard to see by hand. Technicians have different skills, start from different places and finish jobs at different speeds, and the day's requests change after the plan is made. Fixed rules help with the simple cases, but they break on the daily mix of installs, repairs and outages that a large territory produces.