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#DCR Process Mining

DCR Process Intelligence Portal

DCR Whiteboard makes it possible to mark activities for Process Intelligence. Under Options a Process Intelligence can be selected as outlined below:

When you mark an activity as an Process Intelligence activity, it can be monitored during execution and business intelligence data about the activity can be provided. The following information is available for each activity execution:

  1. Duration since the activity was enabled – median, standard deviation and details
  2. Duration since the activity was enabled and pending – median, standard deviation and details
  3. Number of times the activity was executed in total
  4. Duration since the instance was created – median, standard deviation and details

These numbers enables business managers and employees to investigate and analyze work behavior, and identify possible improvements.

Image an activity that typically takes 24 hours to execute from enabled and pending. However, 30% af these activities takes 7 days to execute. Identify the specific process instances and analyze the data to find possible reasons why 30% of the executions takes substantially more time.

A sketch of the future Graph Insight is outlined below:

In the top the user selects a period to analyze.

36 instances are found, from where 2 are non-compliant!

Investigang the different activities marked in the Process Intelligence panel above, we can see how many times eaech activity is executed and how many executions was non-compliant. Clicking any activity will display median duration from enabledness or enabledness and pending of the activity.

“Pay out” is executed 30 times, of which 2 are non-compliant. Clicking “2” will display the id of the particular instances that can be viewed in the DCR Swimlane editor.

Related Release notes

Release 6.3

  • Faster and smoother looking DCR portal
  • Making it easier for modellers - Use drag-n-drop to nest activity

Related Videos

DCR Process Intelligence

Related Articles

DisCoveR: Accurate & Efficient Discovery of Declarative Process Models

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