Unprecedented and continued supply chain disruption has become a major business problem that places huge demands on organizational resilience and agility . Many industries face significant upheaval from the spike in energy prices , war in eastern Europe , skills shortages , commodity and shipping cost inflation , port delays , congestion , container shortages and Chinese Covid-19 lockdowns . The seemingly never-ending problems represent disruption to the point of disorientation .
The consequences are visible in poorly-stocked shelves and warehouses , drops in manufacturing output , delays in on-time delivery to customers , and loss of revenue . As organizations attempt to satisfy demand they may feel forced to engage in heavy expenditures on expedites like air freight , adding to their cost pressures ( and carbon footprint , a growing area of pressure for companies ). While there is no way of preventing unexpected events , integrating AI into supply chain systems can help improve supply chain efficiency and resilience , enabling organizations to manage the disruption far more effectively .
For example , by automating mundane tasks so planners focus on the complex exceptions , their productivity can be increased . Additionally , they can use AI to predict demand , increasing the accuracy of the signal that kicks off the rest of the supply chain planning steps . AI can also be fused with optimization and custom heuristics to address supply allocation , such as maximizing revenue from existing inventory by determining what could be built with the least additional budget .
Organizations integrating AI and advanced analytics have advanced warning of likely events and can respond far more quickly . Take demand-sensing , for example , which uses AI to enhance shortterm forecasting by incorporating external signals along with the usual sales history inputs . These external signals could include data from the downstream supply chain , market information , social media and commodity price indices . To give one example of how this works – planners with these inputs can act fast to secure raw materials that become available at a smaller increase in price before the rest of the market piles in .
In a control tower approach , an AI application will monitor disruption signals and prescribe recommendations based on what it has learned from the efficacy of previous interventions .
AI provides a variety of techniques to deal with a wide range of events . A machine learning approach called clustering , for example , will aggregate sales patterns into groups used to adjust forecasts . These clusters offer guidance on how to order and replenish .
As the significant gains AI delivers become better understood , adoption has increased . The MHI Annual Industry Report for 2021 showed an increase in AI adoption from 12 percent to 17 percent , with almost another quarter ( 24 percent ) of respondents expecting to implement AI within a couple of years . scw-mag . com 29