Toward dataflow-centric process management of data-rich processes

Purpose This study aims to analyze the end-to-end management of complex processes by focusing on process efficiency, data utilization and automation potential to optimize value addition and business outcomes. It addresses an environment in which traditional workflow-centric process optimization is challenged by trends that significantly increase the amount of data in service and service delivery processes. Design/methodology/approach The approach involves analyzing process management in the insurance field by combining scoping reviews, qualitative semistructured interviews and data stream mapping. Findings The key findings indicate that the effective management of complex processes end-to-end requires a paradigm shift from a workflow-centric approach to dataflow-centric process management to achieve end-to-end effectiveness and efficiency. A dataflow-centric approach shows a better potential for data quality for process decision points, which would support decision-point automation. The downstream impacts of data quality and automation capability on downstream processes are highlighted as significant considerations. The importance of addressing data quality among the process effectiveness metrics is highlighted. Originality/value Originality involves a proposal for approaching a data-centric model that bridges the gap between workflow-centric process management and the complex data-intensive demands of modern service delivery processes. This is an environment with increasing amounts of data in service and service delivery processes.