Intelligent information technology for business process model quality and error volume assessment

In the Business Process Management domain, business process modeling is the key technique used to bridge the gap between Information Technology and Management domains, by introducing graphical diagrams understandable by both technical and business stakeholders.Nowadays BPMN (Business Process Model and Notation) models are the most widely-used workflow mapping diagrams, used to document, analyze, improve, and automate organizational activities.Therefore, business process models must be of high quality as ones of the most valuable artifacts for organizational and information systems design and development.This study considers the application of intelligence theory by introducing and using predicates to assess the business process modeling rules fulfillment by BPMN elements.The proposed intelligent information technology assumes BPMN model processing, detection of incorrect elements that violate modeling rules, impact assessment of different element types, quality and error volume measurement, as well as the textual explanations generation for the detected incorrect BPMN elements.The experiments with the large set of business process models are performed, obtained results are analyzed and discussed, conclusions are drawn and the further research is formulated.