A Systematic Review of the Benefits and Challenges of Data Analytics in Organizational Decision Making

Abstract

Data analytics has been relied heavily in organizational decision-making, which allows accuracy, timeliness, and data-driven processes in a wide range of industries. These factors are influential as the figure and complexity of data are on the rise, along with problems like authentication, integration, and organizational resistance. The current study seeks to systematically review the benefits and challenges of data analytics on decision-making in different sectors using the PRISMA guidelines. A total of 32 articles published from 2020 until 2024 were identified through this review from reputable databases, including Scopus, Web of Science, IEEE Xplore, ProQuest, and Emerald Insight. These insights underscore the power of data analytics in driving change, enabling more accurate, faster, and aligned decision-making with organizational objectives. Challenges remain though, including the availability of broken data systems, hindrance due to a non-standardized norm across the whole sector, and resistance in places where data literacy is low or cultures resist data-driven practices. To mitigate the challenges, this review offers organizations practical recommendations for management. Companies that successfully incorporate analytics into their overall business strategies and create an organization-wide value for data and insights will be able to leverage analytics more effectively to enhance efficiency, encourage innovative growth, and navigate future disruptions. However, tackling these challenges is more than just optimizing performance—it is about future-proofing organizations in a world increasingly defined by data.