Business Analytics for Sustainable Supply Chains: Inventory Optimization and Operational Efficiency in the Textile Industry

Abstract

The textile industry is increasingly adopting business analytics to improve supply chain visibility, inventory control, operational efficiency, and resource utilization. This study examines the role of business analytics in supporting sustainable supply chain management, with particular emphasis on inventory optimization and operational efficiency in the textile industry. The study adopted a descriptive research design using a mixed-method approach. Primary data were collected from respondents selected purposively from key supply chain functions, including managers and operational staff, while secondary data were obtained from operational inventory records and ERP/SAP-based information. Given the organization-specific and exploratory nature of the study, the sample was considered suitable for examining relationships among the selected variables. The analysis focused on business analytics usage, inventory visibility, inventory classification, inventory ageing, identification of slow-moving stock, and data-driven procurement decisions. Descriptive analysis of operational records showed that 94% of the total inventory was unrestricted stock, while the inventory ageing analysis revealed that 47.81% of inventory had remained in stock for more than 90 days, indicating the presence of substantial slow-moving inventory. The study also found that ABC classification and ageing analysis help identify critical and excess inventory categories and support better stock-control decisions. Statistical analysis indicated positive relationships between business analytics practices, inventory management, identification of ageing inventory, and operational efficiency. The findings suggest that the integration of analytics with inventory and procurement practices can improve stock visibility, reduce unnecessary inventory accumulation, strengthen resource utilization, and support resource-efficient and operationally sustainable supply chain practices. The study recommends greater use of real-time dashboards, ERP-integrated analytics, predictive tools, and periodic inventory-ageing reviews to strengthen data-driven and sustainable supply chain decision-making in textile organizations.