Enhancing Decision-Making in Technical Economics Through ERP-Based Data Analytics

Abstract

The integration of Enterprise Resource Planning (ERP) systems with data analytics has transformed decision-making processes within the field of technical economics. This study examines how ERP-based data analytics can enhance the accuracy, efficiency, and strategic quality of economic decisions in engineering and industrial environments. By combining real-time data collection, process automation, and predictive modeling, ERP platforms enable organizations to identify cost-saving opportunities, optimize resource allocation, and improve overall operational performance. The research employs a mixed-method approach, incorporating quantitative data from industrial case studies and qualitative insights from managerial interviews. The findings indicate that ERP-driven analytics significantly reduce decision latency, improve forecasting precision, and strengthen cross-departmental coordination. This paper concludes that integrating ERP-based data analytics into technical economic management fosters more adaptive, data-driven decision-making frameworks essential for sustainable industrial competitiveness.