THE USE OF DATA ANALYTICS IN DECISION-MAKING IN MID-SIZED COMPANIES

Abstract

This study explores the role of data analytics in enhancing decision-making processes in mid-sized companies, with a focus on financial management. In today’s data-rich business environment, organizations generate large volumes of financial and operational data that can support more accurate and timely decisions when properly analyzed. Data analytics helps transform raw data into meaningful insights, allowing managers to improve forecasting, reduce uncertainty, and optimize performance.

The research is based on a qualitative analysis of existing literature and theoretical frameworks. The findings indicate that companies adopting data-driven decision-making achieve better financial results, higher efficiency, and improved competitiveness. Data analytics also enables real-time monitoring and supports transparency and continuous improvement in financial operations.

However, mid-sized companies face several challenges, including limited financial resources, lack of analytical expertise, and insufficient data integration. Despite these constraints, they benefit from greater flexibility and access to affordable analytical tools. The study concludes that gradual adoption of data analytics can significantly improve financial decision-making and long-term business performance in mid-sized companies.