A team of students from the Master’s programme in Information Engineering and Computer Science took part in the international ‘Business Process Intelligence Challenge 2019’ competition. They received the BPI Challenge Award in the ‘Student’ category for their compliance analysis of a procurement process.
The ‘Business Process Intelligence (BPI) Challenge’ has been held annually since 2011. This international competition in the field of process mining was launched by three Dutch technical universities. The aim is for students, researchers and companies to analyse a real-world dataset in an original and insightful way. Process mining is a method of process analysis – or business process analysis – used to visualise, analyse and optimise business processes on the basis of digital traces. It is already being used in a wide variety of areas, such as production and logistics chains, automation and IoT applications. The importance of this field is growing steadily, which is why an international conference on the subject, the International Conference on Process Mining (ICPM), was held for the first time this year.
A total of nine prizes were awarded at the conference, two of which were part of the BPI Challenge, with the categories ‘Student’ and ‘Non-Student’. The competition entries were assessed by a jury comprising professors from several renowned universities and organisations both in Germany and abroad. The jury was chaired by Professor Dr Boudewijn van Dongen from Eindhoven University of Technology.
The students Mounisha Juluru (Vijayawada, India), Vincent Meyer zu Wickern (Harsewinkel, Germany), Anshu Roy (Bangalore, India), Viet-Hung Vu (Ho Chi Minh City, Vietnam) and Thi-Thu-Hang Nguyen (Hanoi, Vietnam), from the Master’s programme in Information Engineering and Computer Science under the supervision of Professor Dr Timo Kahl, Professor of Business Informatics at Rhein-Waal University of Applied Sciences, have now emerged as the winning team in the ‘Student’ category of the BPI Challenge. For their competition entry, they carried out a compliance analysis of a procurement process. In doing so, they categorised the datasets according to relevant criteria and subsequently produced a detailed business process map. Taking the generated process models into account, a predictive process mining solution was ultimately developed to forecast irregular order items at an early stage and to analyse the factors influencing these irregular purchases.
The jury justified its decision by stating that the development of the process models was particularly well thought out, as not only were the given categories examined, but a clustering approach was also developed to further divide the provided dataset in a meaningful way. Furthermore, in developing a predictive process mining solution, not only was a classification system in the form of a decision tree created, but a precise link between the technology developed and the business context was also demonstrated on the basis of a detailed analysis of the individual components.
“We are delighted to receive this award. It is wonderful to see that our commitment and the work of our students are gaining international recognition,” said Professor Kahl, commenting on the award. And project leader Meyer zu Wickern added: “The task was a real challenge for us. The fact that we emerged as the winners of the competition with our solution makes us particularly proud. But it also shows us that we have made absolutely the right choice with our degree programme.”
