Actualités et agenda
Nos formations
Établissement
Matières
OPERATIONS MANAGEMENT
Responsable(s)
L.STUDER
Intervenant(s)
Léonard STUDER
Présentation
Prérequis
Basic statistical and computer skills (descriptive statistics + Excel).
• Basic knowledge of some business process modelling techniques like Business Process Model and Notation (BPMN) or Event-driven process chain (EPC).
• Data manipulation with python or R scripting are welcomed skills for process miners but not required for the course.
• Basic knowledge of some business process modelling techniques like Business Process Model and Notation (BPMN) or Event-driven process chain (EPC).
• Data manipulation with python or R scripting are welcomed skills for process miners but not required for the course.
Objectifs
At the end of the course, the student should be able to :
Optimise and improve corporate performance by managing and optimising company's business processes through process mining.
Optimise and improve corporate performance by managing and optimising company's business processes through process mining.
Présentation
As written by Prof W. van der Aalst: "Process mining is a bridge between data mining and business process modeling". With process mining, discovery of process maps, conformance of the real process with some model and enhancement of the real processes can be investigated. Concepts, algorithms and tools to support the process mining will be presented. Real-life logs will be analysed in tutored studies. Data quality conditions and constraints to carry on meaningful process mining analysis of real-life data will be given.
Modalités
Organisation
| Type | Amount of time | Comment | |
|---|---|---|---|
| Présentiel | |||
| Cours magistral | 16,00 | includes small tutored process mining analysis sessions | |
| Autoformation | |||
| Lecture du manuel de référence | 4,00 | reading some internet documents | |
| Travail personnel | |||
| Charge de travail personnel indicative | 30,00 | ||
| Overall student workload | 50,00 | ||
Évaluation
Analyze real-life process log data and answer MCQ questions to validate the findings
Ressources
Bibliographie
"Process Mining: Data Science in Action" by Wil M. P. van der Aalst, Springer Verlag, 2016, (ISBN 978-3-662-49851-4) - this is a reference book; this is NOT a must-read before the course ref. -
"The Added Value of Process Mining"(http://www.bptrends.com/the-added-value-of-process-mining/) -
"Novatica Special Issue on Process Mining" (http://www.ati.es/novatica/2014/ASA/NvS2014-Digital.pdf) -
"Why Process Mining is better than Excel for Process Analysis" (http://fluxicon.com/blog/2014/01/why-process-mining-is-better-than-excel-for-process-analysis/) -
"The Added Value of Process Mining"(http://www.bptrends.com/the-added-value-of-process-mining/) -
"Novatica Special Issue on Process Mining" (http://www.ati.es/novatica/2014/ASA/NvS2014-Digital.pdf) -
"Why Process Mining is better than Excel for Process Analysis" (http://fluxicon.com/blog/2014/01/why-process-mining-is-better-than-excel-for-process-analysis/) -