Quotation Puchovsky, Matej, Di Ciccio, Claudio, Mendling, Jan. 2016. A Case Study on the Business Benefits of Automated Process Discovery. In Proceedings of the 6th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2016), Hrsg. Paolo Ceravolo, Christian Guetl, Stefanie Rinderle-Ma, 35-49. Graz, Austria: CEUR WS.


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Abstract

Automated process discovery represents the defining capability of process mining. By exploiting transactional data from information systems, it aims to extract valuable process knowledge. Through process mining, an important link between two disciplines – data mining and business process management – has been established. However, while methods of both data mining and process management are well- established in practice, the potential of process mining for evaluation of business operations has only been recently recognised outside academia. Our quantitative analysis of real-life event log data investigates both the performance and social dimensions of a selected core business process of an Austrian IT service company. It shows that organisations can substantially benefit from adopting automated process discovery methods to visualise, understand and evaluate their processes. This is of particular relevance in today’s world of data-driven decision making.

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Contribution to conference proceedings
Language English
Title A Case Study on the Business Benefits of Automated Process Discovery
Title of whole publication Proceedings of the 6th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2016)
Editor Paolo Ceravolo, Christian Guetl, Stefanie Rinderle-Ma
Page from 35
Page to 49
Location Graz, Austria
Publisher CEUR WS
Year 2016
URL http://ceur-ws.org/Vol-1757/paper3.pdf

Associations

People
Di Ciccio, Claudio (Details)
Mendling, Jan (Details)
External
Puchovsky, Matej (Vienna University of Economics and Business, Austria)
Organization
Applied Information Technology with Focus on IT in Organization (Details)
Research areas (Ă–STAT Classification 'Statistik Austria')
1105 Computer software (Details)
1108 Informatics (Details)
1109 Information and data processing (Details)
1122 Artificial intelligence (Details)
5306 Business data processing (Details)
5367 Management information systems (Details)
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