Business Process Management: Integrated Data Perspective. A Framework and Research Agenda

Business Process Management (BPM) is confronted with rapidly growing data flows of various types. One established way to address the complexity caused by structured log flows produced by Information Systems (IS) is Process Mining (PM). However, in this approach, unstructured natural language data generated by humans remains uncovered. With the significant advances in Natural Language Processing (NLP), we observe the attention of BPM research and practice shifting towards this type of data. In the study, building on the Task Technology Fit Theory and Contingency Theory, we derive a framework that addresses relevant future research questions in the context of integrated process data perspective, including structured logs and unstructured natural language. The proposed framework considers traditional BPM logics and highlights BPM as a sociotechnical discipline