Creating business value with process mining

Badakhshan, Peyman; Wurm, Bastian ; Grisold, Thomas; Geyer-Klingeberg, Jerome; Mendling, Jan und Vom Brocke, Jan (Oktober 2022): Creating business value with process mining. In: Journal of Strategic Information Systems, Bd. 31, Nr. 4, 101745

Abstract

Information systems research has a long-standing interest in how organizations gain value through information technology. In this article, we investigate a business process intelligence (BPI) technology that is receiving increasing interest in research and practice: process mining. Process mining uses digital trace data to visualize and measure the performance of business processes in order to inform managerial actions. While process mining has received tremendous uptake in practice, it is unknown how organizations use it to generate business value. We present the results of a multiple case study with key stakeholders from eight internationally operating companies. We identify key features of process mining-data & connectivity, process visualization, and process analytics-and show how they translate into a set of affordances that enable value creation. Specifically, process mining affords (1) perceiving end-to-end process visualizations and performance indicators, (2) sense-making of process-related information, (3) data-driven decision making, and (4) implementing interventions. Value is realized, in turn, in the form of process efficiency, monetary gains, and non-monetary gains, such as customer satisfaction. Our findings have implications for the discourse on IT value creation as we show how process mining constitutes a new class of BI&A technology, that enables behavioral visibility and allows organizations to make evidence-based decisions about their business processes.

• Dokumententyp: Zeitschriftenartikel
• Keywords: Process Mining; Big Data Analytics; Business Intelligence; Business Value; Multiple Case Study
• Fakultät: Betriebswirtschaft > Institut für Digitales Management und Neue Medien ; Betriebswirtschaft > Institut für Digitales Management und Neue Medien > Process and Algorithmic Management
• Themengebiete: 300 Sozialwissenschaften > 330 Wirtschaft
• ISSN: 0963-8687
• Sprache: Englisch