The Role of Data-Driven Business Intelligence in Decision-Making and Business Performance: A Systematic Literature Review - Dea Okviar Egano Napitupulu; Yuni Wulandari; Aprizal Haris Sinaga (Sean Institute, 2026)
The growth of the digital economy has increased organizations’ need for data-driven decision-making, in which Business Intelligence (BI) serves as a mechanism for processing data into relevant information. Although research on BI continues to evolve, the relationship between BI, decision-making, and business performance still shows varying findings and limitations in conceptual integration. This study aims to synthesize the scientific literature on the role of data-driven BI in decision-making and business performance, as well as to identify patterns of relationships and research gaps. The method used is a Systematic Literature Review, following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. The data were obtained from reputable scientific databases through a selection process based on inclusion and exclusion criteria, resulting in 48 articles that were analyzed using thematic synthesis and conceptual analysis. The results indicate that BI is consistently associated with improvements in the quality and speed of decision-making. The impact of BI on business performance is generally indirect and mediated by variables such as decision quality and analytical capabilities. In addition, it was found that contextual factors, including a data-driven culture and technology-organizational fit, also influence the effectiveness of BI. The study’s conclusions confirm that the role of BI in an organization is best understood as a capability that supports the decision-making process, rather than as a direct determinant of business performance. This study contributes an integrated conceptual framework and recommendations for the development of more comprehensive empirical research.