Business Intelligence and the Development of Data-Driven Decision-Making in the Public Sector
Keywords:
Business intelligence, Data-driven decision-making, Public sector, Digital governance, Data analyticsAbstract
Objective: This study aims to systematically examine the role of business intelligence in enhancing data-driven decision-making within public organizations, focusing on its components, processes, and outcomes in the context of smart governance.
Methods and Materials: This research employed a qualitative systematic review design. Data were collected through a targeted search in major academic databases including Scopus, Web of Science, and ScienceDirect. From an initial pool of 60 studies, 12 articles were selected based on relevance and quality criteria. The data were analyzed using Nvivo 14 through open, axial, and selective coding. The analysis continued until theoretical saturation was achieved, leading to the identification of conceptual patterns and relationships.
Findings: The qualitative analysis revealed three main themes: (1) Business intelligence infrastructures in the public sector, including data integration, data quality, and IT infrastructure; (2) Data-driven decision-making processes in public organizations, encompassing intelligent decision models, data-oriented culture, and institutional accountability; and (3) Outcomes and public values of business intelligence, including organizational efficiency, transparency, innovation, and public trust. The results emphasized that the success of data-driven decision-making depends on the synergy between technology, human capability, and organizational culture.
Conclusion: The study concludes that business intelligence serves as a strategic enabler of data-driven governance. Its effective implementation in the public sector requires integrated data infrastructures, a data-driven organizational culture, and transparent ethical frameworks. Employing business intelligence enhances efficiency, accountability, and citizens’ trust in governmental institutions.
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