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