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

Lukas Pfahlsberger, Jan Mendling, Andreas Eckhardt

Publikation: Beitrag in Buch/KonferenzbandBeitrag in Konferenzband

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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.
OriginalspracheEnglisch
Titel des SammelwerksProceedings of the 54th Annual Hawaii International Conference on System Sciences, HICSS 2021
Herausgeber*innenTung X. Bui
VerlagIEEE Computer Society
Seiten5666-5675
Seitenumfang10
ISBN (elektronisch)9780998133140
DOIs
PublikationsstatusVeröffentlicht - 2021
Veranstaltung54th Annual Hawaii International Conference on System Sciences, HICSS 2021 - Virtual, Online
Dauer: 4 Jan. 20218 Jan. 2021

Publikationsreihe

ReiheProceedings of the Hawaii International Conference on System Sciences (HICSS)
Band2020-January

Konferenz

Konferenz54th Annual Hawaii International Conference on System Sciences, HICSS 2021
OrtVirtual, Online
Zeitraum4/01/218/01/21

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