Business analytics has revolutionized strategic management by enabling organizations to harness vast datasets to improve decision-making, enhance agility, and gain a competitive edge. This narrative literature review synthesizes peer-reviewed studies, focusing on organizational capabilities and managerial practices that underpin data-driven decision-making processes. Drawing from high-impact journals in management and information systems, the analysis reveals how analytics capabilities—spanning data infrastructure, analytical skills, and cultural alignment—mediate the translation of raw data into strategic outcomes. Key patterns demonstrate consistent positive linkages to firm performance through process optimization and innovation. At the same time, managerial practices emerge as critical bridges that interpret algorithmic insights and align them with organizational goals. Five interconnected research streams are identified: analytics capabilities linked to performance, data-driven strategic decision processes, organizational technology adoption, managerial dynamics in analytics-enabled environments, and analytics as a driver of innovation and competitive advantage. A conceptual synthesis model illustrates these relationships, showing pathways from capabilities through managerial practices to strategic advantages. Despite advances, tensions persist between technological determinism and a human-centric interpretation, with unresolved challenges in governance and the maturation of capabilities. This review advances the field by integrating diverse theoretical perspectives and highlighting avenues for deeper exploration of sustainable analytics-driven strategies in volatile markets.
The rapid proliferation of big data and advanced analytics has fundamentally altered how organizations develop analytical capabilities, execute strategic decisions, and undergo structural transformation. This integrative review synthesizes peer-reviewed studies published to map the evolving landscape of data-driven organizations in management research. By classifying extant work into thematic domains, the review traces the progression from foundational analytical competencies to their integration within strategic processes and, ultimately, to broader organizational change. Key insights reveal that analytical capabilities serve as critical enablers of data-informed decision-making, yet persistent tensions arise between algorithmic outputs and managerial intuition. Governance structures and cognitive shifts further mediate the translation of analytics into sustainable transformation. The study introduces the D3O Framework (Data-Driven Decision and Organizational Evolution Framework) as a novel synthesis architecture that organizes the literature into six interconnected layers, highlighting feedback mechanisms and inter-layer dynamics. This structured integration clarifies fragmented insights, underscores the shift from intuition-based to evidence-driven management, and offers a roadmap for future scholarship. The findings hold significant implications for theory and practice, emphasizing how organizations can harness analytics for competitive advantage while navigating human–data tensions.
Institute for Management, Business, and Accounting Studies