Enabling Data-Driven Decision-Making in Smart Supply Chain Environments

Article from MHI Solutions Magazine

Advances in technology have made it easier for companies to amass extensive amounts of data about every aspect of their supply chain, in real-time. Using this technology in conjunction with artificial intelligence/machine learning (AI/ML) algorithms has resulted in supply chains that are “smart.” Smart implies that data and technology are leveraged to provide increased automation, situational awareness and advanced information about the potential supply chain disruptions. Consequently, supply chains that possess aspects of smart or intelligent technology can quickly adapt to shifting patterns in supply and demand.

A recent report by Gartner highlights some important trends with respect to supply chains of the future.Display footnote number:1 First, technology provides strategic advantage, so it is important for business owners to digitize their supply chains. Digitizing the supply chain means moving away from disconnected systems and manual processes for tracking and tracing products.Display footnote number:2 These actions limit the ability to respond with speed to shifting market demands, primarily due to the lack of real-time visibility to various aspects of the supply chain. Moving towards a digitization of processes is the first step towards obtaining a smart supply chain.

Secondly, supply chain management software is expected to incorporate more advanced analytics and AI to support human decision-making. The ability to interpret and take action on the data and recommendations generated from AI/ML is at the core of data-driven decision making. However, a key challenge associated with providing advanced analytic recommendations to the user is model interpretability…

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