Pharmaceutical Supply Chain Management

Abstract

Supply chain management (SCM) refers to the coordination and oversight of all activities involved in the production, procurement, transformation, and delivery of goods or services from the point of origin to the point of consumption. It encompasses the planning, execution, and control of various processes involved in the flow of materials, information, and finances across the entire supply chain. In this paper, the authors have done a detailed analysis of the pharmaceutical dataset and predicted useful metrics that can be used in the shipping industry. This paper aims to demonstrate the application of machine learning models on the prediction of shipping mode. The model is trained on various features of the pharmaceutical supply chain dataset such as unit price, first-line designation, and delivery dates. Data cleaning and feature engineering were done and multiple models were trained. Out of the models tested, XGboost was found to give the best results for the prediction of weight, shipment modes and delivery date. Key Words: Supply chain management, Machine Learning models, Shipping Industry, XG Boost