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Process mining is often referred to as an X-ray of business processes. It helps identify gaps between expectations and reality. Specialized software connects to corporate systems for process management, customer service, corporate data storage, and accounting. It then retrieves so-called event logs and transforms this raw data into visual maps. These maps illustrate all the paths and deviations that processes actually take and help identify weaknesses. The development and optimization of approaches that enable these analyses are part of the research conducted by RNDr. Martin Macák, Ph.D., from the Department of Computer Systems and Communications at FI MU, who describes the details to us in this interview.

In the fall semester of 2025, you launched the "Process Mining" course for the first time at FI MU. What was your goal in creating it, and what did you want students to take away from it?

The primary goal was to enrich the existing practice-oriented graduate programs at our faculty with a new perspective on data analysis. Students should primarily acquire the ability to recognize in which situations process mining makes sense, while also understanding how such analysis can be effectively applied in practice. 

How would you explain in simple terms what makes process mining interesting and why it should also interest computer science students? 

In today’s world of complex organizational structures, intricate workflows and vast amounts of collected data, it is often difficult to identify “what is actually happening” and “where the real problem lies.” Process mining combines several areas of computer science, enabling the use of logged events to, for example, optimize organizational operations, speed up services, reduce costs, and minimize problems. Students can focus, for instance, on appropriate data acquisition and preprocessing, algorithm optimization, data analytics, or data visualization.

Can you give me an example of the data you’ve analyzed and what you discovered from it?

Currently, for example, it’s interesting to analyze software development processes. We’ve already analyzed processes in Git, processes in Jira, and also programmers’ interactions with AI tools. Our techniques have allowed us to gain insight into how individuals or teams work during development and to identify opportunities to improve those processes.

Looking back on the first run of your new course, what pleased or surprised you most about the students’ reactions? Was there anything that you’d like to adjust for future semesters?

With new courses, it usually takes a few years for them to reach a stable and sustainable state. Although I put maximum effort into the preparation, I expected that several unexpected problems and complications would arise during the semester that could negatively impact the students’ experience of the course. Of course, a few problems and complications did arise, but I was very pleased with the positive feedback from students at the end of the semester. They enjoyed the course, found it useful, and reportedly didn’t even feel that it was being taught for the first time. 

In the future, I plan to implement several improvements to the lectures while also focusing on the course’s scalability so that it is accessible to a larger number of students.

What are the prerequisites for taking your course?

I strive to design the course so that it is accessible to students from various study programs at our faculty. I would definitely recommend that students have completed at least the first two years of their bachelor’s program so that they do not struggle with the course material, which combines theoretical computer science, data analytics, and the practical implementation of a group project. The course is primarily intended for first-year master’s students, but skilled third-year bachelor’s students can also handle it, and it may open doors for them to pursue a bachelor’s thesis in this field.

Is there anything that makes your course unique?

When I compare our course with similar courses at other universities, I would say that this course stands out for its practical focus, which effectively complements the theoretical foundations. We owe this to our collaboration with SAP, which provides us with access to the modern process mining tool SAP Signavio Process Intelligence, where students can complete their final project. Many SAP employees have also been involved in the course through practical presentations or by providing feedback to students.

What are the weaknesses of existing processes, and specifically, what are you “improving” through your process mining research?

Typically, it’s a combination of the human factor and poorly designed processes, where people aren’t clear on how they should or can proceed in different situations. Whether we’re looking at internal company processes or customer interaction with a product, the weaknesses are often similar.

First, everyone may perform a given process somewhat “in their own way.” People also often look for “shortcuts” to simplify or speed up the execution of individual tasks. Non-standard situations also arise that require an urgent response or improvisation. In some cases, this may even involve malicious activity that creates cybersecurity risks.

Our research therefore focuses on developing techniques capable of analyzing how processes actually function even under such complex conditions and helping to identify opportunities for improvement.

You spent six months working in Estonia. What was the main goal of this stay, and what did you bring back from your time in Estonia to your work at FI MU?

I traveled to the University of Tartu as part of the cybersecurity project called “Cyber-security Excellence Hub in Estonia and South Moravia” (CHESS). The aim of our joint research was a process-oriented approach to addressing security risks in the field of car sharing. I collaborated there with the InfoSec group, but I also got to know the process mining group that operates at the university. This visit provided me with many opportunities to network and share ideas and experiences not only in research but also in teaching.

How did your Estonian experience influence the new course or how you think about process mining today?

I was fortunate that their Process Mining course was being taught at the university that very semester, so it nicely expanded the perspective I had gained previously during my Ph.D. internship in Aachen from their Process Mining course. As with any creative process, it’s important to know “how others do it” so that you can draw inspiration and then bring your own approach to the result. Part of the course’s initial success certainly lies in this opportunity to travel to Estonia.

What do you personally enjoy about process mining? And what’s the easiest way to get started in this field at the FI MU?

What I really enjoy about process mining is that it can reveal from data how things work in reality, not just “on paper.” Precisely because we can identify various problems in processes, it can have a very practical and useful impact.

The easiest way to get started is to enroll in the new course PA231 Process Mining. Students can also join the PV226 Lab Seminar – Lasaris, where they’ll get a closer look at the research conducted by our Laboratory of Software Architectures and Information Systems.

Are there other activities students can get involved in, such as seminars, theses, research collaborations, or through the Association of Industrial Partners?

There are two ways to get involved. For students interested in research collaboration, we currently have two active projects, and more will be launched next year. At the same time, we have several thesis projects underway where we are addressing process mining for various companies.

In the future, we would like to offer students some process mining internships and projects in collaboration with SAP, but for now, this is still a distant goal that we are currently working hard to achieve.

Last year, FI MU joined the SAP University Alliances. What does this mean specifically for the faculty, and what opportunities does it open up for teachers and students?

The SAP University Alliances program connects more than 2,800 educational institutions worldwide. As part of this partnership, we gain, for example, free access to the SAP Learning Hub platform, which offers a wide range of educational materials for both faculty and students. This platform enables the development of practical skills in modern SAP technologies and also offers the opportunity to earn selected certifications.

The partnership also includes a connection to a center that provides hosting for the necessary software we can use in teaching—in our case, SAP Signavio Process Intelligence.

Thank you for the interview, and I wish you success in the further development of the course and your research.

Author: Marta Vrlová, Office for External Relations and Partnerships at FI MU

Photo: Martin Macák