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.
Recommended Citation
Eggers, Julia; Hein, Andreas; Böhm, Markus; and Krcmar, Helmut, "Leveraging Big Data for M&A: Towards Designing Process Mining Analyses for Process Assessment in IT Due Diligence" (2023). PACIS 2023 Proceedings. 45.
https://aisel.aisnet.org/pacis2023/45
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Comments
Paper Number 1250; Track AI; Complete Paper