Subject: Information Management
Title: Enhancing Risk Management in ERP Project through Structured RAID-Log Analysis: A Mixed-Methods Approach to Continuous Learning and Governance
Abstract:
Introduction – This study explores how a structured analysis of RAID-logs can enhance risk management in ERP projects by supporting early risk detection, continuous learning, and as a result long-term organisational resilience.
Contribution – This study adopts a holistic perspective by combining quantitative and qualitative methods to address the underexplored long-term improvement of risk management practices in ERP implementations, shifting the focus from short-term mitigation to continuous learning through structured RAID-log analysis. It provides actionable insights for project managers by demonstrating how structured RAID-log analysis can improve early risk detection, support ongoing risk evaluation, and strengthen organisational resilience.
Methodology – This study employs an explanatory sequential mixed-methods design, combining quantitative analysis of RAID-log data with qualitative expert interviews to uncover patterns, validate findings, and provide a holistic understanding of how RAID-logs support risk management in ERP projects.
Results – The results reveal significant inconsistencies in how RAID-logs are used across ERP projects, with trends showing that effective RAID practices enable faster resolution, better risk response alignment, and offer potential for continuous learning when supported by standardized labelling and active monitoring.
Conclusions – This study has shown that RAID-logs contribute to a better understanding of risks and enhance their impact on project risk management by revealing escalation patterns between RAID elements, supporting proactive decision-making, and enabling continuous learning.
Further research – Future research should explore longitudinal studies, and the role of organisational culture, while expanding to large, multi-organisational datasets to better capture RAID-log dynamics and enhance their application through advanced methods like machine learning.
Key words: ERP implementation, risk management, continuous learning, RAID-log analysis, and process improvement.