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Design of a Process Mining Alignment Method for Building Big Data Analytics Capabilities

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dc.contributor.author Pfahlsberger, Lukas
dc.contributor.author Mendling, Jan
dc.contributor.author Eckhardt, Andreas
dc.date.accessioned 2020-12-24T20:11:05Z
dc.date.available 2020-12-24T20:11:05Z
dc.date.issued 2021-01-05
dc.identifier.isbn 978-0-9981331-4-0
dc.identifier.uri http://hdl.handle.net/10125/71308
dc.description.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.
dc.format.extent 10 pages
dc.language.iso English
dc.relation.ispartof Proceedings of the 54th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Business Intelligence, Business Analytics and Big Data: Innovation, Deployment, and Management
dc.subject big data analytics capability
dc.subject process-mining alignment
dc.subject process-orientation
dc.subject resourced-based view
dc.title Design of a Process Mining Alignment Method for Building Big Data Analytics Capabilities
dc.identifier.doi 10.24251/HICSS.2021.688
prism.startingpage 5666
Appears in Collections: Business Intelligence, Business Analytics and Big Data: Innovation, Deployment, and Management


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