Companies are now challenged with a unique set of obstacles, including transportation issues, distant work, shortages due to unanticipated increased demand, and so on, in addition to escalating consumer expectations, lack of visibility, and operational complexity.
FREMONT, CA: How can businesses ensure that their supply chain is running smoothly? For many suppliers, distributors, manufacturers, and retailers, this is an open question. Businesses are questioning how to make their supply chain less vulnerable to disruption in the face of change in supply chain market dynamics, changing ways of working, and increasingly fluctuating demand. Many well-known and emergent supply chain difficulties can be solved with machine learning.
Every component of the supply chain, including procurement, production, inventory management, warehousing, shipping, and customer support, can benefit from machine learning and AI. Take a closer look at the key issues in the supply chain and how machine learning can overcome them.
Key Challenges in The Supply Chain
Machine Learning (ML) can help businesses enhance supply chain management and make it more resilient to disruptions. Uncertainty, fragility, and a lack of transparency plague the global supply chain market. Only one out of ten organizations can remain ahead of their supply chain challenges. Companies are now challenged with a unique set of obstacles, including transportation issues, distant work, shortages due to unanticipated increased demand, and so on, in addition to escalating consumer expectations, lack of visibility, and operational complexity.
The sector witnessed the shift of the traditional linear supply chain into Digital Supply Networks (DSNs) in recent years. COVID-19 has hastened this transition, forcing businesses to reconsider their global supply chain strategy in light of the new reality. Traditional, linear supply chains may be transformed into connected, intelligent, scalable, and configurable digital supply networks with the use of technologies like IoT, artificial intelligence, and machine learning.
Benefits of ML
ML adds unparalleled value to supply chain operations, ranging from cost savings and risk reduction to improved supply chain forecasts, faster delivery, better customer service, and others. The most significant benefits of ML, according to research, will be in giving supply chain experts more substantial insights into how supply chain performance may be improved, as well as identifying anomalies in logistics expenses and performance before they occur. ML is also revealing where automation can provide the most significant scale benefits.