8:45 – 10:15
Presenters: Chiara Ghidini & Chiara Di Francescomarino, Fondazione Bruno Kessler, Italy
Predictive process monitoring is a branch of process mining that aims at predicting at runtime and as early as possible the future development of ongoing cases of a process given their uncompleted traces. This lecture aims at (i) offering an introduction on Predictive Process Monitoring, including an overview of the existing families of approaches and typical encodings; (ii) introducing one of the existing Predictive Process Monitoring tools.
10:45 – 11:30
Presenter: Andrea Burattin, Technical University of Denmark
Streaming process mining refers to the set of techniques and tools which have the goal of processing a stream of events (as opposed to a finite event log). The goal of these module is to understand what is streaming process mining, why it is relevant and how it can be performed. Some general techniques will be presented.
11:30 – 12:15
Presenter: Felix Mannhardt, Process Analytics Group, Eindhoven University of Technology, The Netherlands
Responsible data science aims for responsibility to be built, by design, into management, analysis, and algorithmic decision-making techniques based on data to prevent harm. Process mining may also lead to harm. Participants learn about state of the art in Responsible Process Mining, which aims to systematically address issues from the perspectives of Fairness, Accuracy, Confidentiality, and Transparency (FACT).
14:00 – 15:30
Presenter: Dr Lars Reinkemeyer, VP Customer Transformation, Celonis SE
This sessions’ focus is on industry experience and operational best practices: 1. Siemens’ journey from leveraging Process Mining for Process Discovery to intelligent Process Execution. 2. The importance of balancing between data discovery and operational action. 3. Best practices in respect to business value realisation including a future outlook.
16:00 – 17:30
Presenters: Niels Martin, Research Group Business Informatics, Hasselt University, Belgium & Nils Wittig, Chief Experience Officer at KMS Vertrieb und Services AG, Germany
Healthcare is a promising domain for process mining given the significant societal value that can be generated by supporting data-driven process improvement. In this lecture, you will be introduced to process mining in healthcare. First, the particularities of healthcare processes will be introduced, as well as ongoing research. Afterwards, we will take a deep dive into a real-life case study of process mining in healthcare. To end the lecture, some open challenges will be discussed.
19:00 – 00:00
SkyLounge, Templergraben 55, 52062 Aachen