Supply chains under pressure: How can data science help?

The world has changed and companies are facing a perfect storm, with catastrophic risks that have a very low probability of occurrence, but for which the consequences are enormous. The war in Ukraine is impacting global supply chains already constrained by the COVID-19 pandemic. Ukraine is responsible for about 70% of the world's neon and Russia controls 44% of the world's supply of palladium, both of which are essential inputs in semiconductor production. Semiconductors are themselves essential to the manufacture of cars, smartphones or even medical equipment. With Taiwan producing nearly two-thirds of the world's semiconductors, China's move to reunify with the island of Taiwan raises significant concerns. In this complex geopolitical context, some companies are considering reshoring or nearshoring, i.e. the repatriation of specific activities within national ou regional borders. Is this the right solution or not?

In this short text, Thierry Warin, Fellow CIRANO and responsible of the CIRANO Pole on Data Science for Trade and Intermodal Transportationfor argues that the solutions to recent complex supply problems must themselves be complex. We need to use the tools we have access to today: massive data, computing power and new methods of analysis. The global trade system must adapt to a new technological paradigm, that of artificial intelligence and data science. The alternative of using the same mental patterns as in the past and proposing binary solutions is no longer acceptable today. There is no more time to lose.

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