PERFORMANCE EVALUATION OF INVENTORY MANAGEMENT SYSTEMS IN SMES USING DATA ANALYTICS

Abstract

Efficient inventory management is critical for the competitiveness of small and medium-sized enterprises (SMEs), yet many continue to rely on traditional practices that lack real-time visibility and analytical decision support. This study evaluates the performance of inventory management systems in SMEs through the application of data analytics techniques. Key inventory performance indicators including stock accuracy, stockout frequency, lead time variability, order fulfilment rate, and carrying cost were analysed using descriptive analytics, trend analysis, and predictive modelling. Results demonstrate that data analytics improves forecasting accuracy, reduces excess inventory, enhances replenishment planning, and significantly minimises stockouts. The findings indicate that integrating data-driven insights with existing inventory processes enables SMEs to achieve cost-efficient, responsive, and agile inventory systems. Overall, the study highlights the transformative role of data analytics in strengthening SME operational performance and supporting informed decision-making.