Every automatic scheduling decision in Field Service, whether from the Schedule button, Get Candidates or optimization, is driven by a scheduling policy. Understanding the two halves of a policy is the fastest way to make scheduling behave the way your business expects.

Work rules: who can do the job

Work rules are hard filters. A resource that breaks a work rule is never offered. Common rules:

  • Match Territory: the resource is a member of the appointment's service territory.
  • Service Resource Availability: within working hours, without overlapping absences or other jobs.
  • Match Skills: the resource has the skills (and skill levels) the job requires.
  • Maximum Travel from Home: limits how far a resource travels from their home base.
  • Excluded and Required Resources: honour customer preferences such as "never send this technician" or "only this one".
  • Earliest Start Permitted and Due Date: keep the appointment inside its allowed window.

Service objectives: who should do the job

Among the resources that pass every rule, objectives score the options. Each objective has a weight:

  • ASAP: earlier slots score higher.
  • Minimize Travel: shorter drives score higher.
  • Minimize Overtime: avoids pushing technicians past normal hours.
  • Preferred Resource: favours the customer's preferred technician.
  • Resource Priority and Skill Level: favour certain resources or more experienced technicians.

Start from the standard policies

Field Service ships with policies such as Customer First, High Intensity, Soft Boundaries and Emergency. Clone the closest one and adjust it rather than starting from scratch, then test with real appointments and compare the candidates it produces against what an experienced dispatcher would choose.

Practical advice

  • Keep work rules strict and few. Every rule removes candidates, and too many leave nothing to schedule.
  • Change one weight at a time and retest. Objectives interact in ways that are hard to predict.
  • Use different policies for different situations, for example one for planned maintenance and one for emergencies.
  • Data quality beats tuning. Wrong home addresses, stale absences or missing skills will undermine any policy.