Supply Chains Become Self-Thinking
Many supply chain practitioners and researchers suggest that in the not-too-distant future, the supply chain will think by itself. Driven by the internet of things (IoT), robotics and artificial intelligence (AI), the supply chain will be self-aware and require minimum, if any, human intervention.
Information that was previously created by people will increasingly be machine-generated, while the entire supply chain will be connected.
Based on these data, supply chains will be able to make decisions automatically and in real time, to optimise operations, handle incidents that require risk-mitigation actions, avoid disruptions and satisfy an increasingly volatile demand.
Predictive Analytics
I’ve written previously about how artificial intelligence is having an impact in the shipping industry and the cargo it carries. But AI is having an impact throughout the supply chain.
A good example is the way some companies use predictive analytics to ship products close to (anticipated) customer demand. The self-thinking supply chain will thus push supply chain flexibility and agility to limits yet to be discovered.
The diagram below illustrates the way a self-thinking supply chain will work.
Source: Calatayud, A., Mangan, J. & Christopher, M. (2019) The self-thinking supply chain, Supply Chain Management: An International Journal, 24(1), 22–38.
First, there will be a high degree of connectivity between cyber systems and physical objects through the use of IoT. Such IoT technology will be ubiquitous through the deployment of sensors, short- and long-range networks and Internet-enabled applications.
Big data will be generated, stored and analysed through IoT and AI in real time. This will enable continuous monitoring of supply chain performance and early identification and management of potential risks.
Benefits of Self-Thinking Supply Chains
Increased connectivity among supply chain partners enabled by IoT, together with AI, will allow for more accurate demand forecasting, predictive maintenance and continuous optimisation.
With AI, decision making will be machine-generated and processes will be automated. Objects will be able to sense the environment (through IoT) and respond to it according to AI-made decisions. Changes will be made at the micro level (e.g. at individual nodes in the supply chain) in order to optimise supply-chain-wide performance.
Efficient, accurate, fast and simultaneously orchestrated responses will thus improve supply chain performance in an increasingly complex and uncertain world. Using real-time data on both demand and available production and distribution capabilities, we can regulate (speed up/slow down) the flow of materials downstream in the supply chain.
The potential benefits of self=thinking supply chains for efficiency, security and cost savings are beginning to be realised.
John Mangan is Professor of Logistics in the School of Engineering at Newcastle University, UK, Visiting Professor at the School of Business in Trinity College Dublin, and a recognised author and researcher on logistics and supply chains. He has also consulted widely with public and private organisations. He previously held the Peter Thompson Chair in Logistics the University of Hull and has held academic posts at University College Dublin and the Irish Management Institute.
