Critical success factors for change management in business process management

The purpose of this study is to determine the influence of project critical success factors (CSFs) on change management in the context of business process management (BPM). Despite widespread interest in BPM, the existing literature is insufficient in addressing the antecedents that contribute to change management in business process projects.

Key factors of change management success in BPM projects were initially identified in a systematic literature review (SLR) and were used as antecedents of change management through a structural equation modeling (SEM) with 464 business project stakeholders. Next, a neural network analysis allowed the key factors to be ranked non-linearly. Finally, a latent class analysis (LCA) was performed to determine the sample's heterogeneous groups based on their project management characteristics.

Project management, top management support and technological competencies were the main CSFs identified as having positive effects on change management. The most important factor is project management, followed by top management support, which plays a crucial mediating role in enabling change management. Although relevant, technological competencies were secondary in the study. Regarding project management CSF, four heterogeneous classes of individuals were determined.

Although this study provides an opportunity to observe CSFs, it does not address the need to analyze the phenomenon in different classifications of projects, regarding maturity, complexity, project management approach and other aspects that differentiate projects in a meaningful way.

The study allows practitioners to understand the critical factors underlying change management and take necessary actions to manage it, recognizing that individuals have heterogeneous profiles regarding project management.

This study pioneeringly discusses the CSFs of change management BPM projects to enable successful change management, ranking the main factors and mapping heterogeneous profiles.