Average operation time widget (Dock Scheduler)

Updated 1 month ago by Katarzyna

Who can use this function?

This function is available to users of the Trans.eu Platform and Dock Scheduler with access to the Schedules module.

Learn more about the Dashboard and widgets module.

Basic information about the widget

Add Average operation time to your Dashboard to constantly verify operation times (loading and unloading) in your warehouses.

Dock Scheduler - average operation time widget:

  • belongs to widgets from the Schedules category,
  • presents data based on all successfully completed bookings,
  • presents data for all warehouses,
  • presents historical data, the average time is calculated based on the last 30 days,
  • you can add it to the Dashboard only once.

Widget navigation

The main elements of the widget are:

  1. Charts of average operation times for the 5 warehouses with the highest number of operations.

The chart consists of 4 parts:

  1. Name of the warehouse (e.g. Magazyn Bemowo).
  2. A bar with information about the average time between the arrival and departure of a vehicle from a given warehouse (e.g. 100 minutes)
  3. The part of the chart marked blue that informs about the average operation time - loading, unloading (e.g. 50 minutes)
  4. A yellow, dashed line that indicates the default operation time in this warehouse (e.g. 60 minutes)

How to analyze data

Tooltips that appear on each chart when you hover over it with the mouse cursor will be useful in data analysis.

Analyzing the data for the example Prague Furniture warehouse, you can observe that the average stay time of vehicles in this warehouse is 72 minutes, the average operation time is 41 minutes, while the default operation time is set to 20 minutes.

With this data, the warehouse manager can determine whether the average operation time and the time between arrival and departure are close to the assumed default time.

In this case, it turns out that in almost all warehouses, operations-related tasks take longer than expected. You can investigate whether this situation is related to technical problems, low efficiency among employees, insufficient processes or other factors.

Data analysis can help identify areas to improve efficiency, optimize processes and increase the quality of warehouse operation.

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