Process Mining

May 24, 2018

Process Mining and Predictive Monitoring: an overview

Chiara Ghidini, Senior Research Scientist @ Fondazione Bruno Kessler

According to one of the reference courses on the topic, Process Mining is Data Science in Action: the “missing link between model-based process analysis and data-oriented analysis techniques”. Indeed it consists of a series of techniques that enable the (i) discovery, (ii) monitoring, and (iii) improvement of real processes (i.e., not assumed processes) leveraging the knowledge contained in today’s (information) systems and represented in the format of so-called event logs.
In this presentation I will provide an overview of the main components of process mining, namely: the automated process discovery from event logs, the checking of conformance (or deviations) of the process model and the event log, and the improvement of models based on the actual process executions contained in the event log. I will also illustrate in detail some of the work we carry out on predictive process monitoring, that is, the ability of foreseen the future unfolding of current process executions.

Slides

Taking Process Mining from a technical software solution to a full enterprise ready platform

Manuel Haug, Head of Product Management Core @ Celonis

Serving the largest companies in the world with a state of the art software is a challenge: it’s not just the solution of a calculation problem or the invention of a new algorithm but generating value on the customers data. Manuel Haug shares various experiences in facing this challenge. These include shifting minds and making people realize that enterprise software can be modern, easy to use and user centric, but also security and data regulations and necessary steps to develop a customer-specific value proposition.

Slides