task-mining
2022.10
false
  • Release notes
  • Getting started
  • Setup and configuration
  • Unassisted Task Mining
    • Introduction
    • Project management
    • Installing the recorder
      • Running the ML pipeline
      • Opening a project
      • Viewing tasks
      • Viewing traces
    • Best practices
  • Additional resources
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Task Mining
Automation CloudAutomation Cloud Public SectorAutomation Suite
Last updated Oct 17, 2024

Opening a project

Follow these steps to open a project.

  1. Go to the Task Mining Home Portal.

  2. Select the project you want to view.

Study overview

The study overview gives you a summary of the analysis.

  • Tasks - number of repetitive tasks identified by the machine learning model.
  • Actions captured - number of actions (click, type, etc.) captured in the dataset.
  • Total time captured - number of hours of recording.
  • Users - number of users that have recorded their daily activities in this project.
  • Total number of applications used - number of users that have recorded their daily activities in this project.



Detailed metrics

Scroll down, to find the list of repetitive tasks and the detailed metrics for each task:

  • Task name - default is Task + number. The task name can be edited.
  • Total time - total time the users spent performing this task.
  • Users - number of users who have performed this task repetitively.
  • Traces - number of times this task has happened in the dataset. One trace is one iteration of this task done by one user.
  • Steps, in Median - number of steps in the most representative trace for this task - indicating the complexity of the task.
  • Actions, in Median - number of actions (click, type, etc.) in the most representative trace for this task - indicating the complexity of the task.
  • Execution time, Median - execution time of the most representative trace for this task - indicating the complexity of the task.
  • Used apps - number of apps used to perform this task.

    Note: The tasks are ranked based on these tasks' automation potential, considering various factors, including repeatability and complexity. However, we strongly recommend that users review the tasks and prioritize them for automation based on their own criteria.

Task grouping

Analysis executions produce grouped tasks in the analysis results table. Task groups are defined by the Task Mining model combining similar tasks found in a dataset as it is challenging to understand exactly the right start and end steps for a task and the middle steps. A group of tasks can be expanded to show task alternatives or collapsed to show only the representative task.

  • A task is selected by default by Task Mining as a representative, but this can be changed by selecting a subtask and set it as representative.



  • A subtask can also be transferred to another Task if it is now properly assigned to the current Task. To do this, you can select the subtask, and by selecting the return arrow, you can select the Task to which the subtask is transferred.



  • Study overview
  • Detailed metrics
  • Task grouping

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