A STUDY ON OPTIMIZING FREIGHT COST USING DATA ANALYSIS

Abstract

This study explores how businesses use data analytics to optimize freight costs, a crucial aspect of supply chain management. The complexity of global trade and rising transportation costs have led to a growing interest in data analytics as a strategic tool for cost reduction and performance improvement. The study focuses on the use of analytics tools in freight management, data-driven decision-making, and the impact of digital transformation on cost reduction. Supply chain experts were surveyed to understand their experiences with tracking techniques, freight cost optimization, difficulties, and analytical tool investment. Results showed that software programs like SAP, Oracle Transportation Management, and Power BI are essential for increasing freight cost effectiveness. However, adoption obstacles like poor training, lack of visibility, and reliance on outdated cost-tracking techniques persist. The study suggests that companies must invest in sophisticated analytical solutions and personnel up skilling to improve decision-making skills. The study aims to offer organizations a data-driven perspective on freight cost management to optimize operations and enhance cost efficiency