We simulated {{resultSettings.numReps}} days of dispatch operations during this {{resultSettings.hours}}-hour shift {{resultSettings.exoFactors}}. Here are your results on how each {{textStrings.operator.toLowerCase()}} and team spent their time at work, including a breakdown by task(s) and {{textStrings.fleet.toLowerCase()}}(s). In the next tabs, you should find results on errors and delays in performance.
{{ textStrings.operator }} Workload
Utilization (% busyness) represents workload. When an operator spends too much of their shift below 30% or too much time above 70% utilization, research has shown that they begin to underperform.
Most of the time, {{ resultSettings.busyTimePerOp }}. Continue below here to see what is contributing to your operators' busyness.
Breakdown of Time by Task per Team
{{ resultSettings.busyTimePerTask }}
Breakdown of Time by By {{ textStrings.fleets }} per Team
{{ resultSettings.busyTimePerFleet }}
Failed Task Analysis
Missed Tasks
Incomplete Tasks
Failed Tasks and Not Caught
Failed Tasks and Caught
{{ textStrings.operator }} Team
Task Name
Cnt
Avg
SD
Cnt
Avg
SD
Cnt
Avg
SD
Cnt
Avg
SD
{{ textStrings.operator }} Wait Time
Breakdown of Time by By Tasks Per Team
{{ resultSettings.waitTimePerTask }}
Breakdown of Time by By {{ textStrings.fleets }} Per Team
{{ resultSettings.waitTimePerFleet }}
Raw results of workload per day across all tasks over ten-minute intervals of each {{textStrings.operator}}'s shift.
Human error (failed tasks) by type per day, including a summary file across all days simulated.