Crew Schedule Statistic

Updated July 4, 2025

Understanding the Crew Schedule Job Statistics

The Crew Schedule Job Statistic dashboard is a powerful visual and data-driven tool designed to assist managers in overseeing workload distribution and financial performance across multiple client projects within a given timeframe. It integrates both numerical and visual elements to provide a comprehensive overview of scheduled and unscheduled jobs for a specific crew.

To access this, navigate to Business Intelligence → Schedule → Crew Schedule Statistic

At the top of the dashboard, four key metrics summarize the financial status of job scheduling:

  • Previously Scheduled:
    Reflects the total value of jobs that were scheduled in prior periods

  • Currently Scheduled:
    Represents the combined value of all jobs actively scheduled within the selected date range.

  • Scheduled for the Future:
    Represents the combined value of all the jobs that are scheduled for the future

  • Unscheduled:
    Represents the combined value of all the unscheduled jobs

 To filter the list by a specific date range, click the calendar icon and select either a preset timeframe or customize your date range.

To export the list in a CSV file, click the Download CSV button.

To refine the data for more targeted insights, click on the Job Statistic Filter and fill in the relevant fields based on your preferences, then click Go to apply the filters.


Note: 
- Clicking on the WO number will redirect you to the corresponding Workorder profile.
- Entries marked with a yellow triangle icon indicate that the scheduled amount exceeds the service total.

To the right of the table is a calendar-style visual:

  • Dates Across the Top:
    Represent the days of the selected timeframe

  • Green Blocks:
    Highlights the specific day(s) a job is scheduled. The length and continuity of the green blocks visually represent the scheduled duration of each job.

This section allows managers to instantly evaluate the spread and intensity of the crew’s workload. It highlights which days are busy, where potential bottlenecks may exist, and where there may be underutilized capacity.