It’s all about the process

The world and the industry has changed radically in recent years. Of course, evolutions and revolutions have become commonplace in modern economies. This time, however, is different. It is not the products and services that are changing, it is the way in which they are delivered to the customer that is totally different.

The guest lecture is part of the BPM course in Master of Management and the speaker is Jan Mendling, professor at the Wirtschaftsuniversität Wien and thought leader in the area of Business Process Management.

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The future of conformance checking: identifying challenges and opportunities

On the 8 and 9th of February 2018, we gathered with an international group of process mining researchers to discuss the many challenges in the field of conformance checking. The event was organized by the Flemish Scientific Research Community on Process Mining (htpps://www.srcprocessmining.org), a community that is led by our research group, together with KULeuven and UGent. The brainstorm session was attended by researchers from the Polytechnic University of Catalonia, the Pontifical Catholic University of Chile,  RWTH Aachen University, the Technical University of Eindhoven and the Wirtschaftsuniversität Wien.

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bupaR: Business Process Analysis with R

Organizations are nowadays storing huge amounts of data related to various business processes. Process mining provides different methods and techniques to analyze and improve these processes. This allows companies to gain a competitive advantage. Process mining initiated with the discovery of work-flow models from event data. However, over the past 20 years, the process mining field has evolved  into a broad and diverse research discipline.

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Why should we trust your algorithm?

There is no doubt about the current role of Machine Learning in the fascinating world of Business Intelligence. Predicting whether a customer will be loyal to the company or not, understanding customers’ behavior or anticipating market fluctuations are typical examples on which Machine Learning may be pivotal. Unfortunately, most successful Machine Learning algorithms like Random Forests, Neural Networks or Support Vector Machines do not provide any mechanism to explain how they arrived at a particular conclusion and behave like a “black box”. This means that they are neither transparent  nor interpretable. We could understand transparency as the algorithm’s ability to explain its reasoning mechanism, while interpretability refers to the algorithm’s ability to explain the semantics behind the problem domain.

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From relational database to valuable event logs for process mining – A procedure

The huge potential of process mining applications is -luckily- already discovered in a variety of business settings. In industry, more and more companies are learning about its potential value. In meanwhile, academic researchers continue their quest to the best algorithm, the most meaningful metrics, the most understandable visualisations, etcetera. Whatever ‘best’, ‘meaningful’, and ‘understandable’ may be… These are food for thought and discussion on their own. But I’d like to address a different mini-research-topic-on-its-own: the event log.

An implicit assumption in process mining (both research and applications), is the existence of an event log.

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How to select activities for your process model – Some BPMN guidelines

doubting_activtieis

Should everything that happens within your company be represented as an activity?

The picture above shows a list of possible actions that might be going on in an organization. As a process modeler, would you include all of them as activities in your diagram? Or do you think some are too detailed or rather not detailed enough to be considered an activity? Maybe you even argue that some of them are not relevant enough to figure in a process at all…

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