[8] LOGISTICS KPI ANALYSIS AND COST FORECASTING: A STUDY ON DHANAM INDUSTRIES, COIMBATORE

CrossRef DOI: https://doi.org/10.56815/ijmrr. v5.si1.2026.69-79

Authors

  • Dr. N. Prem Anand Professor, Department of MBA Sri Ramakrishna College of Arts & Science, Coimbatore, India
  • Ms. K. Aadhavan Student, Department of MBA Sri Ramakrishna College of Arts & Science, Coimbatore, India.

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https://doi.org/10.56815/ijmrr.%20v5.si1.2026.69-79

Abstract

The study on Logistics KPI Analysis and Cost Forecasting at Dhanam Industries, Coimbatore, investigates the effectiveness of predictive
analytics in optimizing transportation costs, improving delivery performance, and enhancing operational efficiency. It examines key
logistics performance indicators such as transportation cost, fuel cost, shipment volume, route efficiency, and delivery performance that align operational activities with the company's strategic cost management objectives. Through a detailed analysis of 12 months of historical logistics data (July 2023 - June 2024) comprising approximately 200 shipments, the study applies statistical forecasting models including Holt-Winters Exponential Smoothing and SARIMA to predict future logistics costs. Key findings focus on identifying seasonal cost patterns, route-wise cost disparities, and the strong correlation between shipment volume and transportation expenses. The research proposes actionable strategies including dynamic route optimization, preventive maintenance programs, and digital dashboard implementation to drive cost efficiency and foster a data-driven logistics culture at Dhanam Industries

Keywords:

Logistics KPI, cost forecasting, transportation management, SARIMA, Holt- Winters, fuel cost analysis, route optimization, predictive analytics, Dhanam Industries

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