ML technology has enabled supply chain management organizations to efficiently monitor weather forecasts, traffic situations, and other relevant factors, giving them more control over their operations.
FREMONT, CA: Machine learning (ML) is one of the most popular applications of artificial intelligence (AI), which enables digital systems to learn from the available datasets and improve future experiences. ML technology brings significant potential into the supply chain sector, where the processes are affected by a multitude of variables, including unreliable area mapping, resource availability, vehicle breakdown, and weather conditions.
One of the challenges faced by the supply chain organizations is matching customer convenience with delivery timing. The effective incorporation of ML technology will not only enhance customer experience but will also transform the prospects of the logistics sector. It leverages AI algorithms to learn the patterns and draw predictive insights from the datasets, thus enabling the organizations to figure out the ideal delivery time. Organizations can leverage the capabilities of ML to keep track of the weather conditions, traffic situations, and other related factors which are likely to affect the delivery schedule.
Supply chain organizations might not have access to highly accurate maps with precisely listed addresses. Also, remote places do not offer internet connectivity, which makes it difficult for delivery personnel to locate isolated addresses. The inaccurate data not only hinders the supply chain management but also leads to friction between the organization and customers. In such cases, ML technology will enable organizations to leverage the historical delivery data and triangulate the approximate locations.
Robust ML systems will empower the field staff to make smart decisions based on ground conditions. Natural calamities can often lead to the rerouting of shipments via different routes and different warehouse locations. Often, political or national events might also hinder the delivery process due to unavailability of the delivery personnel. The advanced and predictive analytics capabilities offered by ML will enable supply chain managers to realize the best and worst-case scenarios and make decisions accordingly.
The success of AI and ML technology in the logistics sector presages the digitalization and automation of the supply chain ecosystem. Logistics organizations will increase their adoption of ML systems to achieve actionable insights and enhance their processes through efficient inventory planning, cost optimization, fraud elimination, risk reduction, and error-free delivery management.