Tracking and tracing systems have become basic services for most logistics companies and are particularly essential for the shipping and logistics industry. Dynamic logistics management today need constant supervision and management of continuously-changing supply chains that motivate the necessity of goods-centric logistics monitoring and tracking, which guarantees a chance to improve transparency and control of a company’s multiple logistical activities. However, operational inefficiencies due to the conventional monitoring system for the supply chain management can also result in sales loss, higher cost, poor customer service–and eventually lower profits. Based on research literature, this paper aims to provide a novel approach for tracking and tracing shipment in a logistics organisation by implementing deep natural language processing concepts. The study aims to allow the stakeholders to think in new ways in their organisation and helping them to have a powerful influence on tracking and tracing to make the best decision possible at the right time. The proposed method is compared based on the accuracy of identifying the query, and results are significantly acceptable. This study is of related interest to researchers, academicians, and practitioners.

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