You build a scheduling policy in Field Service by attaching work rules and service objectives to a Scheduling Policy record, then weighting the objectives to match your priorities. Most teams clone a standard policy and adjust rather than start empty.
- Open or clone a policy
From the Scheduling Policies tab, open a standard policy like Customer First, or clone it so you keep the original intact. Give the clone a clear name that signals what it optimizes for.
- Attach work rules
On the policy, add the work rules that must hold true, such as Match Skills, Match Territory, and Service Resource Availability. Keep the set lean so you do not accidentally rule out every candidate.
- Add and weight service objectives
Add objectives like Minimize Travel, ASAP, or Resource Priority, then set a weight on each to rank their importance. Higher weights pull schedules toward that goal relative to the others.
- Test, tune, and roll out
Run a sample optimization or use Get Candidates in the dispatcher console under the new policy. Review the Gantt, adjust one weight at a time, then make the policy available to dispatchers and automated jobs.
Pass-or-fail filters that drop any resource who cannot do the job, covering skills, territory, time, and availability.
Weighted goals that score qualified candidates so the engine can pick the best one for the appointment.
A number per objective that sets its relative importance; raising it biases the schedule toward that objective.
The policy field on scheduling actions, the dispatcher console, Appointment Booking, and optimization jobs that decides which policy runs.
- Too many strict work rules can leave the engine with no eligible resource, so the appointment stays unscheduled.
- Objectives with near-identical weights blur priorities and make the engine's choices hard to predict.
- Automated jobs and the dispatcher console can run different policies, so confirm which policy a given action actually uses.
- A policy only reflects its inputs; wrong skills, operating hours, or resource priorities produce poor schedules even with good weights.