Hello everyone,
I'm trying to understand the recommendation logic used by FSL when displaying candidates in the Gantt.
In my scenario, three technicians are returned as candidates for the same Service Appointment. All of them receive the same grade (100/100), but FSL recommends Technician C instead of Technician A.
What I've already validated:
• Same Skills and Skill Levels
• Same Service Territory
• Same Operating Hours
• Same Efficiency settings
• Same Work Rules
• Same Scheduling Policy
• Same Resource Availability
• Same Grade (100/100)
The only difference I've identified so far is their starting location. However, Technician A is actually closer to the Service Appointment than Technician C. Additionally, Technician A's last known location is also closer to the activity.
As shown in the screenshot, all three resources have a score of 100/100, but the system recommends Technician C.
My questions are:
1. When multiple candidates have the same grade, what tie-breaker logic does FSL use?
2. Does the Candidate List use factors that are not reflected in the displayed grade?
3. Could travel calculations, optimization settings, resource priority, or another hidden factor influence the recommended candidate?
Any guidance on where to investigate would be appreciated.
Thank you.
I would check:
- all service objectives and weights in the scheduling policy
- whether Resource Priority or Preferred Resource is active
- actual travel time used by the scheduler, not only map distance
- geocoding on the Service Appointment and resource locations
- whether last known location is actually used for scheduling
- whether the visible 100/100 score is rounded
- whether the result changes with a simplified test policy using only availability, skills, territory and minimize travel.