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Leveraging Big Data for M&A: Towards Designing Process Mining Analyses for Process Assessment in IT Due Diligence

Autoren

Julia Eggers
Andreas Hein
Prof. Dr. rer. nat. Markus Böhm
Markus.Boehm@haw-landshut.de
Helmut Krcmar

Medien

Pacific Asia Conference on Information Systems (PACIS)

Veröffentlichungsjahr

2023

Band

2023

Seiten

45

Veröffentlichungsart

Konferenzbeitrag (peer reviewed)

Zitierung

Eggers, Julia; Hein, Andreas; Boehm, Markus; Krcmar, Helmut (2023): Leveraging Big Data for M&A: Towards Designing Process Mining Analyses for Process Assessment in IT Due Diligence. Pacific Asia Conference on Information Systems (PACIS) 2023, 45.

Peer Reviewed

Ja

Leveraging Big Data for M&A: Towards Designing Process Mining Analyses for Process Assessment in IT Due Diligence

Abstract

The success of mergers & acquisitions (M&A) depends on the buyer's adequate due diligence (DD) assessment of the target firm. Assessing the target's IT-enabled processes recently emerged as a novel information technology DD (IT DD) responsibility. However, it remains unclear how to operationalize and conduct the process assessment in IT DD. To address this challenge, we propose the big data analytics technology process mining (PM) and follow a design science research approach, based on literature and 12 interviews, to reveal and operationalize requirements for process assessment in IT DD, demonstrate PM to measure the operationalized requirements, and derive design principles and enabling factors to guide the design, implementation, and use of PM for process assessment in IT DD. Consequently, our study contributes to research on IT DD, M&A, and PM and provides practitioners with design knowledge and a prototypical PM artifact to leverage PM for process assessment in IT DD.