A scoping review of the role of data analytics in management decision planning and analysis

This scoping review investigates the critical role of data analytics in enhancing management decision-making, analysis, and modeling across various industries, with a particular focus on healthcare and business sectors. Based on approximately 112–140 peer-reviewed empirical studies, the review consolidates evidence demonstrating how data analytics shifts traditional intuition-based approaches toward more precise, evidence-driven strategies. Advanced technologies such as machine learning, artificial intelligence, as well as predictive, diagnostic, and prescriptive analytics, enable organizations to extract actionable insights from complex datasets, thereby supporting improved strategic planning, risk assessment, forecasting, inventory management, sales prediction, consumer behavior analysis, and resource allocation. Empirical results indicate significant benefits, with analytics tool adoption rates reaching as high as 78%, and operational efficiency improvements of around 35%. Additionally, many organizations report a competitive advantage of approximately 22%. Organizations with advanced analytics capabilities tend to achieve better performance outcomes, including increased profitability, improved decision quality, greater agility in responding to market trends, and proactive risk management. However, several challenges remain that can impede effective implementation and decision quality. Major barriers include data quality issues such as inaccuracies and incompleteness, the increasing volume and complexity of data that surpass traditional system capacities, shortages of skilled analytics personnel, organizational resistance to adopting a data-driven culture, siloed organizational structures, and concerns related to data privacy and security. Organizations that address these challenges through strong data governance, cross-departmental collaboration, analytics training, and cultural change initiatives are more likely to realize sustained operational efficiencies and competitive advantages. Ultimately, this review emphasizes that data analytics is essential for making accurate, timely, and strategic management decisions across diverse fields, while underscoring the importance of targeted efforts to overcome barriers and unlock its full transformative potential. Keywords: data analytics, quantitative methods, decision-making, and strategic management