Process Mining as enabler of RPA Automation adoption

What is process mining?

Process mining provides the fact-based insights into the processes based on the data stored in the corporate its Systems.

The following is an example of an Invoice process where we can see the difference between the expected process as designed on the left and actual process being used on the right recreated from the system data.

The process insights can be leveraged to plan for right Automatable process with better ROI, monitor the impact of change in-line with business expectation and other related broader business goals.

How does process mining works?

The process mining requires three pieces of data for mining of any defined process.

Case Id: This is the key identification of the process that is defined and logged in the system of records. For example, if we are trying the mine the invoice process, the case id could be Invoice ID.

Activity Id: These are various activities rendered for a given case ID. For example, in the given Invoice process, it could be invoice creation, review and approvals.

Timestamp: The timestamps associated for each of the activity associated to a Case ID.

The following diagram provides logical flow of these ID’s are captured from event logs stored in the system of records and helps in creating actual process models.

Why process models?

Process models are created through process mining activity and depict the flow of actual process being used by the stakeholders in the organization.

Following are some of the benefits of Process models

  • Process Insight: Provides E2E comprehensive view of the Actual process and how it is different from the expected or intended behaviour
  • Process review: the stakeholders use models to structure discussions;
  • Process Documentation: processes are documented for instructing people or certification purposes (cf. ISO 9000 quality management);
  • Process Verification: process models are analysed to find errors in systems or procedures (e.g., potential deadlocks);
  • Performance analysis: techniques like simulation can be used to understand the factors influencing response times, service levels, etc.;
  • Process simulation: models enable end users to “play out” different scenarios and thus provide feedback to the designer;

How process mining helps in RPA Adoption?

The process models created out of mining activity offers wealth of information as articulated above. The following are important from RPA Automation adoption perspective:

  1. Identify the most frequently used processes suitable for RPA Automation with higher ROI
  2. Identify the bottlenecks and helps in streamlining the process before pushing for RPA Automation
  3. Provides better documentation mined from the actual usage for RPA implementation
  4. Mining also helps in monitoring the process to assess the impact of Automation and process change
  5. Helps baseline the current performance metrics of the current process before Automation so that ROI post implementation can be clearly measured.

What are the leading Process mining products?

Some of the leading Process mining solutions are Celonis ( and UiPath Process mining (

Key takeaways

  • Process mining certainly accelerates the adoption of RPA with its compelling benefits
  • Process mining helps in smart RPA implementation by identifying the right process with higher potential for ROI
  • Process insights helps in identifying the bottlenecks and streamlining the process before implementing the RPA Automation.