How an AI-Applied Supply Chain Enables Efficiency

Today's supply chains are laden with inefficiencies, as most companies rely on antiquated practices to oversee and manage how goods get from place to place. The supply chain is delicate -- even one disruption among suppliers, buyers, and logistics providers can have a trickle-down effect that causes waste, time loss, and increased carbon emissions. With the supply chain still managed manually, logistics managers are operating under intense pressure, with the sheer amount of data about material supply, demand, and transportation routes overwhelming. Even with machine learning providing managers with intelligent analysis, logistics managers can only react so quickly to the thousands of changes along a single supply chain. As managers are overburdened, their slow reactions to real-time problems and disruptions cause the supply chain inefficiencies that create higher costs, waste, and even greater environmental impact.