Formalizing the operational perspective in BPM: an ontology-based approach for tool integration

Purpose This study aims to formalize the operational perspective in business process management (BPM) by developing an ontology-based approach to integrating passive resources, mainly operational equipment, into process modeling and execution. The research addresses the current gap in BPM techniques for comprehensively modeling and tracking passive resources essential to real-world processes and manual tasks. Design/methodology/approach The study employs the design science research methodology (DSRM) (Peffers et al., 2007) to create an artifact that addresses the identified problem. For this, we develop a meta-model and ontology for the operational perspective following established ontology creation guidelines (Noy, 2001). Based on a systematic literature review, we identify existing approaches and gaps to create a prototypical implementation based on the ontology using resource description framework (RDF) to showcase the practical application in a craft business context. Findings This research presents a novel ontology-based framework that formalizes the operational perspective in process management, specifically focusing on the role of passive resources. The developed meta-model and ontology facilitate the structured integration of operational equipment into BPM, improving transparency, resource allocation and process execution. A prototypical implementation using IoT technologies showcases the framework’s feasibility in supporting passive resource management within craft business contexts, including tool allocation and real-time process adaptation. Originality/value This research bridges a critical gap between BPM and asset management, offering a foundational framework for integrating passive resources into process management. The ontology-based approach facilitates the explicit modeling of operational equipment and materials, paving the way for enhanced BPMN extensions. Future research directions include expanding the ontology’s scope, developing AI-driven resource allocation and investigating applications in human-centric and knowledge-intensive processes. This work underscores the significance of incorporating operational equipment management within BPM to achieve greater process efficiency and adaptability.