Process mining is a field of analytics that uses machine learning and other innovative data analytics methods to a) detect, b) monitor and c) optimize the processes based on data generated from process logs. The outcome of process mining is normally:
- a process visualization and the highlighting of bottlenecks;
- finding out the cause-effect relationships for the successes and failures of processes;
- real-time tracking of the processes and calculation of the probability of success;
- recommendations (whether step A, B or C should be taken to guarantee the highest probability of success).
STACC, in cooperation with the University of Tartu, offers process mining service for providing industrial companies with the tools for improving their work processes. It’s also worth emphasizing that Marlon Dumas, the head of STACC’s process mining area, is one of the most recognized scholars of the world in this field.
