Analysis and Prediction of Delivery Lead Time and Operational Delays Using Supply Chain Analytics

This study examines the key factors influencing delivery lead time and operational delays in supply chain systems using a data driven approach. In today’s competitive business environment, timely delivery has become essential for maintaining customer satisfaction and operational efficiency. The research focuses on important operational factors such as transportation efficiency, inventory availability, supplier performance, warehouse operations and order processing time. A quantitative research design was used, and primary data was collected through a structured questionnaire from 104 respondents with knowledge of supply chain operations. Secondary data from industry reports and academic studies was also used to support the analysis. Statistical techniques including descriptive analysis, correlation, regression and Random Forest modelling were applied to identify relationships and key predictors of delivery delays. The results show that transportation efficiency and inventory availability have the strongest impact on delivery lead time. Warehouse operations and order processing have a moderate effect, while supplier performance shows limited influence in this study. The findings also highlight the importance of supply chain analytics in improving decision making and enabling predictive insights. The study contributes by combining analytical and predictive approaches and provides practical suggestions for improving delivery performance. It emphasizes the need for data driven strategies, better logistics planning and efficient inventory management to reduce delays and improve overall supply chain efficiency.