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Arrival Windows with Provider-Based Capacity

Learn how to set up arrival windows with automatic capacity calculation in FieldCamp.

Updated over a month ago

Provider-based capacity uses intelligent algorithms to determine how many jobs fit in each time window based on service duration, travel time, and team availability.

What you'll learn:

  • How provider-based capacity works

  • Configuration steps and settings

  • Smart calculation examples

  • Setup and optimization tips


What is Provider-Based Capacity?

Provider-based capacity automatically calculates how many jobs can fit within each arrival window. The system considers service duration, travel time between jobs, and team availability to optimize your schedule.

Example: For a 2-hour window with 45-minute services, the system calculates how many jobs are possible based on travel time and technician availability.


How It Works

The Smart Calculation Engine

The system automatically factors in five key elements when determining capacity.

  1. Service Duration - How long each job takes to complete

  2. Travel Time - Driving time between customer location

  3. Team Availability - Number of technicians workin

  4. Buffer Time - Extra time for delays or setu

  5. Geographic Distribution - How spread out customers are

Real-Time Optimization

As customers book appointments, the system continuously adjusts. Capacity updates dynamically with each booking. Routes optimize for minimal travel time. Team assignments balance automatically. Available slots reflect real-time capacity.


Configuration Steps

Step 1: Set Up Arrival Windows

Navigate to Service Area Settings and select your configuration.

Choose your window length between 1-4 hours. Set how often new slots start (15, 30, or 60 minutes). Select "Arrival Windows" as your scheduling format. Choose "Provider-Based" for capacity mode.

Step 2: Configure Service Parameters

Define the key timing elements for accurate capacity calculation.

Service Duration - Average time to complete each service
Travel Buffer - Additional percentage for travel between jobs
Setup Time - Minutes needed for equipment preparation

Step 3: Assign Your Team

Connect team members to service areas for capacity calculation.

Assign technicians to specific service areas. Set individual working schedules. Configure any skill requirements or specializations.


Calculation Examples

Example 1: HVAC Maintenance

Service Configuration:

  • Service Duration: 45 minutes

  • Average Travel Time: 15 minutes

  • Setup Time: 10 minutes

  • Window Length: 2 hours (120 minutes)

  • Available Team: 1 technician

Calculation Process:

Total time per job equals 45 + 15 + 10 = 70 minutes. With a 120-minute window, the system calculates 120 ÷ 70 = 1.7, rounding down to 1 job.

Result: System shows 1 available slot for the 9:00 AM - 11:00 AM window.

Example 2: Home Cleaning Service

Service Configuration:

  • Service Duration: 90 minutes

  • Average Travel Time: 20 minutes

  • Setup Time: 5 minutes

  • Window Length: 4 hours (240 minutes)

  • Available Team: 2 cleaners

Calculation Process:

Total time per job equals 90 + 20 + 5 = 115 minutes. Each cleaner can complete 240 ÷ 115 = 2.08, rounding to 2 jobs. With 2 team members, total capacity is 4 jobs.

Result: System shows 4 available slots for the 8:00 AM - 12:00 PM window.


Setup Walkthrough

Basic Configuration

Start in Service Area settings to define your coverage zone. Choose your area type and set boundaries. Select "Arrival Windows" as your scheduling format. Choose "Provider-Based" for automatic capacity calculation.

Service Parameters

Enter your average service duration in minutes. Set a travel buffer percentage (10-25% recommended). Add setup or breakdown time if needed. Save your configuration to activate.

Team Setup

Assign team members to each service area. Configure individual working schedules. Set skill levels if certain services need specific technicians. Review and confirm all assignments.

Testing and Optimization

Run test bookings to verify capacity calculations. Monitor how actual times compare to predictions. Adjust parameters based on real-world performance. Fine-tune settings for optimal efficiency.


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