Using big data to increase the efficiency of business processes in the digital economy of Ukraine

Abstract

This study explores the transformative role of big data tools in enhancing business efficiency within Ukraine's digital economy. Using a cross-sectional design, data were collected from 200 managers and experts across diverse industries through a semi-structured questionnaire. The analysis encompassed descriptive statistics, reliability testing, exploratory factor analysis (EFA), regression analysis, and cluster analysis to examine the adoption of predictive analytics, business intelligence, and process automation. Results highlight process automation as the most significant efficiency driver, followed by predictive analytics and business intelligence, enabling streamlined workflows, faster decision-making, and reduced operational costs. Cluster analysis identified three distinct groups of organizations: high adopters achieving notable efficiency gains, moderate adopters facing substantial barriers, and low adopters with targeted benefits but limited efficiency gains. Barriers such as skill shortages, infrastructure gaps, and organizational resistance were prominent among moderate adopters, underscoring the need for targeted interventions. Larger organizations and those led by experienced managers demonstrated greater efficiency, highlighting the importance of resources and leadership in digital transformation. The study emphasizes the need for investment in infrastructure, workforce development, and tailored support for SMEs to unlock the full potential of big data. Future research should focus on longitudinal impacts, sector-specific challenges, and integrating emerging technologies such as AI and IoT. These findings provide actionable insights for policymakers and organizations to foster a data-driven, competitive, and inclusive digital economy in Ukraine.