Due to the increased use of information systems by organizations to support process execution, detailed information on the implementation of business processes is being recorded. This fact enables using process mining projects as a powerful tool for improving performance. Process Mining is a relative young research discipline that sits between data science on the one hand and process modelling and analysis on the other hand. Process mining allows gaining knowledge of the organization’s actual business processes by extracting data from existing information systems mediums such as event logs, transaction logs etc.
The purpose of this presentation is to demonstrate how a process for conducting process mining projects was designed, developed and applied in some organizational units.

The process was implemented through nine research steps, inspired by the V-model, where elements on the right-hand side aim to answer questions presented in steps on the left-hand side. In the first two steps, the research problem and the research objectives were defined. A literature review was performed in step 3. In the fourth step, requirements for the process were identified and implemented. In step 5, a running example was carried out to test the process. Verification and validation of the process were performed in step 6 and step 7. Step 8 covered the discussion of results. The last step concludes the research, including checking if the research problem was solved.

Organizations seeking for performance improvement can now benefit of a process that explicitly states which process mining tools, techniques and algorithms to be used in process mining projects.