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How AI Can Help Address Emerging Supply Chain Risks

In the News

SupplyChainBrain – Boris Khazin

How AI Can Help Address Emerging Supply Chain Risks

Artificial intelligence and machine learning are equipping global supply chains with the tools they need to address heightened risk in the era of COVID-19.

Along with the effects of the pandemic come tougher regulations to meet carbon-emission standards and reduce greenhouse gases. In Europe, new rules cover emissions generated throughout the supply chain, from the acquisition of raw materials to the delivery of finished goods. Meanwhile, the International Maritime Organization has agreed to a new set of guidelines for reducing the carbon intensity of ships. Together, these measures could mark the end of the era of cheap international shipping.

Companies have long taken the logistics links between distinct parts of their global supply chains for granted. Predictable performance by the major transportation modes meant that they could confidently build geographically distributed supply chains based on the cost advantages of Asian manufacturing. But recent events have challenged the validity of these assumptions. Today, there’s a need to respond rapidly to unanticipated issues with real-time information.

AI and machine learning can help companies accurately forecast demand, improve inventory management and reduce emissions and waste in their supply chains. One maritime transportation provider applied machine learning to existing historical data to create more reliable baseline probability forecasts. It was also able to reduce waste through fewer stockouts and instances of excess inventory.

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