The Role of Data Quality Dimensions in Enhancing Life Cycle Costing and Data-Driven Decision Making for Public Sector Asset Management

The transition toward data-driven decision-making has become increasingly important for modern Asset Management (AM) within the public sector, particularly in supporting effective Life Cycle Costing (LCC) and long-term asset investment decisions. Despite significant government initiatives to strengthen asset management practices in Malaysia, the implementation of LCC remains constrained by challenges associated with the quality and availability of asset information. This study aims to identify and prioritize the Data Quality Dimensions (DQD) that are most critical for supporting LCC and data-driven decision-making within Malaysian public sector asset management. A mixed-methods approach was adopted comprising a quantitative survey of experienced asset management practitioners and qualitative validation through five institutional building case studies. Data were analysed using the Relative Importance Index (RII) to determine the relative significance of Data Quality Dimensions and operational data quality challenges. The findings reveal that all Data Quality Dimensions are important for effective asset management; however, Accuracy, Reliability, and Availability emerged as the most critical dimensions for supporting LCC applications. The study further identified data recording problems, fragmented information systems, and limited access to historical asset information as key barriers affecting data quality and lifecycle-based decision-making. The institutional case studies validated these findings by demonstrating how deficiencies in data quality directly influence the reliability of lifecycle cost analyses and asset management decisions. This study contributes to the growing body of knowledge on asset information management by extending the application of the Wang and Strong Data Quality Framework to the context of public sector asset management and Life Cycle Costing. The proposed D-LCC Governance Framework provides practical guidance for improving data quality, strengthening information governance, and enhancing data-driven decision-making capabilities within public sector organizations.

Asset Management; Data Quality Dimensions; Life Cycle Costing; Data-Driven Decision Making

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