Predictive Analytics for Inbound Logistics: Optimizing Lead Times and Vendor Reliability - Gupta, Vikas; Patro, Ravindra Kumar; Sharma, Aditya Kumar (International Journal of Supply Chain Management, 2025)
Lead time variability has significant impact on supply chain management (SCM) and is a critical factor that affects operational efficiency, cost management, and logistical aspects of a business. This coupled with vendor reliability is the key to quality assurance, waste reduction and cost rationalization. This article delves into the manner in which variations in lead time impact two important aspects of supply chain performance, lead time optimization and vendor management. The focus is on application of predictive analytics in this respect. The article underscores the strong potential that predictive analysis has in addressing the key threats and opportunities faced by modern supply chains. The key contribution of this research is addition to the pool of literature that covers the relatively less widely discussed areas - inbound logistics and the application of sophisticated modern technologies towards improvement of  supply chain visibility for enhancing efficiency of supply chain management. The article establishes that predictive analytics can be effectively used to facilitate data-driven decision-making in supplier management thus making decisions more proactive than reactive which significantly improves supply chain resilience.