Abstract:

This paper aims to clarify the concept of data-driven organizations by synthesizing diverse definitions and conceptualizations in the literature and proposing a unified conceptual framework grounded in technology, culture, management, and human capability. A theoretical literature review is conducted using a structured search in the Web of Science database, applying strict inclusion criteria: (1) open access; (2) English language; (3) Business & Management category; (4) published since 2014. After filtering and PRISMA-style screening, eight key publications were selected for in-depth interpretive analysis. The analysis reveals four interdependent dimensions critical for becoming data-driven: (1) cultural transformation; (2) technological infrastructure; (3) managerial practices; (4) human capabilities. Cultural change emerges as the most fundamental driver, enabling effective knowledge sharing, experimentation, and trust in data. Technological systems (e.g. cloud, analytics, IoT) provide infrastructure, but their value depends on alignment with organizational strategy. Managerial roles must interpret and embed insights into business models, while human skills (both analytical and interpretative) bridge data and decision-making. Multiple configurations of these dimensions may yield successful outcomes depending on context. This study contributes by integrating fragmented definitions of data-driven organizations. It highlights that data-driven transformation is not primarily a technological challenge, but a holistic organizational shift.