Big Data Analytics in Organizational Process Management: A Systematic Review of Methods, Challenges, and Cultural Impacts
DOI:
https://doi.org/10.5753/isys.2025.6593Keywords:
Big Data Analytics (BDA), management of organizational processes, decision-making, advanced digital technologies, corporate cultureAbstract
Context: The adoption of Big Data Analytics (BDA) in organizational process management has been consolidated as a transformative strategy for organizations. The use of tools and methods based on advanced digital technologies supports decision-making more efficiently. Such practices generate benefits by optimizing managerial processes, increasing productivity, and enhancing strategic decisions. Problem: However, BDA implementation faces challenges such as the integration of large data volumes, privacy, ethics, and the lack of advanced analytical skills. In this sense, companies must invest both in technological infrastructure and in cultural changes. Objective: This paper analyzes how BDA have been applied in organizational process management and how they guide decision-making in the business context. Method: We conducted a systematic literature review, analyzing 176 empirical and theoretical studies published between 2019 and 2024 across five major databases. Results: The findings reveal a set of widely adopted methods and tools, including machine learning, BI/ERP systems, IoT, dashboards, and data mining frameworks, while also identifying recurrent barriers such as system integration issues, lack of analytical skills, and resistance to data-driven practices. The review highlights consistent impacts on organizational culture, including increased transparency, agility, and emphasis on evidence-based decision-making. Conclusions: The study contributes to the field by consolidating current knowledge on BDA in organizational processes, exposing research gaps, and offering insights to guide future implementations and investigations. By mapping practices, challenges, and impacts, this work supports researchers and practitioners in effectively integrating BDA to foster innovation, operational efficiency, and a robust data-driven culture.
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