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Wil van der Aalst is a full professor of Information Systems at the Technische Universiteit Eindhoven (TU/e). He is also the Academic Supervisor of the International Laboratory of Process-Aware Information Systems of the National Research University, Higher School of Economics in Moscow. He also just happens to be the world’s most cited European computer scientist with an H-index of more than 104 according to Google Scholar.
Since 2003 van der Aalst has had a part-time appointment at Queensland University of Technology (QUT). His research interests include workflow management, process mining, Petri nets, business process management, process modeling, and process analysis.
The best known and most productive BPM researcher in the world, van der Aalst has published more than 160 journal papers, 17 books (as author or editor), 300 refereed conference/workshop publications, and 50 book chapters.
He is also editor/member of the editorial board of several journals, including Computing, Distributed and Parallel Databases, Software and Systems Modeling, the International Journal of Business Process Integration and Management, among others, and is known as the Godfather of Process Mining.
In 2012, van der Aalst received the degree of doctor honoris causa from Hasselt University. In 2013, he was appointed as Distinguished University Professor of TU/e and is also a member of the Royal Holland Society of Sciences and Humanities (Koninklijke Hollandsche Maatschappij der Wetenschappen) and the Academy of Europe (Academia Europaea).
What are the major trends and changes you see in today’s software development world?
The emergence of “Big Data” and the central role of the “data scientist” in the future of engineering will have a huge impact on software development. The challenge is to turn today’s torrents of event data into valuable insights related to performance and compliance. Recently, process mining emerged as a new scientific discipline on the interface between behavioral models and event data. The two most prominent process mining tasks are process discovery, learning a process model from example behavior recorded in an event log, and conformance checking, diagnosing and quantifying discrepancies between observed behavior and modeled behavior. Process mining results can be used to identify and understand bottlenecks, inefficiencies, deviations, and risks.
Are there any significant new ideas in this field in the last 2-3 years or are they just repetitions and further development of already known methods?
This is an exciting time and many new things are happening concurrently. Too many people claim that there is nothing new while at the same time they cannot keep up with developments. The availability of large amounts of data combined with “mobility”, “cloud”, and “social” is creating a nexus of forces that will change our understanding of computing, processes, and software.
What’s your opinion on using agile/lean in the context of outsourcing? How does it work?
The ongoing trend is that software needs to be produced faster and there is no time for careful design cycles. Instead of fighting this, we should accept this and use the feedback from systems in the field to understand why software performs good or bad and adapt while the system is running. This will make outsourcing trickier because it cannot be automated and there should be no confusion about the goals and desirable functionality.
What can you say about Russia as an outsourcing destination? What sort of companies could benefit from choosing Russia, and why?
I’m in the fortunate position that I’m at the same time a Distinguished University Professor at Eindhoven University of Technology in the Netherlands, the Academic Supervisor of the International Laboratory of Process-Aware Information Systems of HSE in Moscow, and a part-time professor at Queensland University of Technology in Australia. Hence, I can see the differences in culture and technical skills. These differences make it important to formulate clear specifications and measurable targets. This also holds for Russia even though in many respects we share a common background.
What government actions would you consider to be most beneficial for a national software industry (in any country)? Which changes in the regulations seem most necessary to you today?
As an academic, I consider proper training and good technical skills as most important. Substantial investments in good universities that are research driven and at the same time provide excellent teaching are needed. I regret to see that salaries for PhDs, postdoc, and professors are too low in Russia. This way one will not attract and keep the best people. Of course these investments should result in measurable results, e.g., citations of research papers and spin-off companies. The software industry would immediately benefit from this as many studies show.
What are the general trends you see in the Russian software industry as compared to other countries?
There seem to be an emphasis on traditional software development in the Russian software industry. I would appreciate seeing more emphasis on the analysis of running systems and the alignment between real-life processes and the information systems. This is why I mentioned process mining as an important topic. I’m confident that there will be a transition from classical software development to analytics also in the Russian software industry.
Why did you decide to participate in the CEE-SECR 2013? What are your personal expectations for the conference?
I was invited to give a keynote address on Process Mining by the organizers. As the Academic Supervisor of the International Laboratory of Process-Aware Information Systems at HSE I’m also very interested in extending relations between the Netherlands and Russia. In particular I hope to meet software companies working on business process management and business process intelligence. Therefore, I’m eager to make new contacts and locate the really innovative software companies in the region.
What would you like our readers to take away from this interview?
Process mining is on the interface between process model analysis and data-oriented analysis and can be used to answer a variety of performance and compliance-related questions. It is very different from mainstream data mining and machine learning approaches focusing on classification, clustering, regression, and pattern/rule mining. None of these approaches tries to discover end-to-end processes. Moreover, issues like conformance are not considered at the process level. If you are interested, see the YouTube movie or visit our PAIS lab in Moscow!