Design of a process mining alignment method for building big data analytics capabilities

Lukas Pfahlsberger, Jan Mendling, Andreas Eckhardt

Publication: Chapter in book/Conference proceedingContribution to conference proceedings

34 Downloads (Pure)

Abstract

Process mining is a big data analytics technique that supports business process management in an evidence-based way. Nowadays, companies struggle to build the required capabilities that lift process mining beyond technical proof-of-concept implementations. As research on process mining is largely limited to algorithm design and project management recommendations, current research does not understand well how process mining and complementary resources and capabilities can be aligned. By understanding those interrelations, companies learn to leverage their organizational potential during the execution of process mining more effectively and efficiently. In this paper, we address this research gap by using the design science research approach to develop a process mining alignment method. Our method supports companies mapping their individual technical requirements of process mining to their underlying organizational resources. We evaluate our method through a series of interviews with IT consultants.
Original languageEnglish
Title of host publicationProceedings of the 54th Annual Hawaii International Conference on System Sciences, HICSS 2021
EditorsTung X. Bui
PublisherIEEE Computer Society
Pages5666-5675
Number of pages10
ISBN (Electronic)9780998133140
DOIs
Publication statusPublished - 2021
Event54th Annual Hawaii International Conference on System Sciences, HICSS 2021 - Virtual, Online
Duration: 4 Jan 20218 Jan 2021

Publication series

NameProceedings of the Annual Hawaii International Conference on System Sciences
Volume2020-January
ISSN (Print)1530-1605

Conference

Conference54th Annual Hawaii International Conference on System Sciences, HICSS 2021
CityVirtual, Online
Period4/01/218/01/21

Bibliographical note

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