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Supplychain; What Did We Learn Featured

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According to the New York Federal Reserve Bank, international supply chain pressure continues to ease. As of March, The Global Supply Chain Pressure index indicated a reading of -1.06 – the lowest since August 2009.

Negative readings stipulate minimal supply chain disruptions. On the other hand, positive values, like the one observed in December 2021 (+4.32) show significant pressure on the supply chain industry resulting from the pandemic. As a result, inflation rises and items can be hard to come by like we saw with semi-conductor chips, baby formula, eggs, and just recently Girl Scout cookies.  While this doesn’t mean we won’t see items out of stock occasionally – it does mean we are trending in the right direction.

Although disruptions may have temporarily eased, it raises the question of whether the supply chain industry has gained any insights from the pandemic.

The supply chain was already fragile prior to the pandemic due to practices like the “Just in Time” model. Created by Toyota in the 1950s – companies would order materials as they were needed. According to Keely Croxton, a professor of logistics at Ohio State University – “this method worked well. Operations stayed lean and ensured companies restricted unnecessary spend”.  

The model worked on the basis that there would be no hiccups in the supply chain process. It doesn’t take into effect shortages of raw materials, shortages of workers to create the items, and disruptions to last mile delivery - the last step of the product’s journey from warehouse to doorstep. The high demand for raw materials and commodities was fueled by stimulus checks and the extended period of time people spent at home, allowing them to engage in home improvement projects that they previously may not have had the opportunity to pursue.

To ensure they are prepared for future disruptions  - companies are embracing AI, blockchains and machine learning to build more resilient supply chain processes that they can utilize for future disruptions. 

“It is about building on better people and technology for more accurate and accessible solutions,” said Paul Noble, founder and CEO of Verusen - cloud-based, AI-driven platform that specializes in inventory optimization in supply chain management. With their platform, Verusen hopes to enhance the “Just In Time” Model by using AI to make sure companies have the right materials at the right time utilizing both historical and real-time data.

As more companies turn to AI-powered supply chain management - their goal is to minimize disruptions and work more efficiently. AI-enablemed supply chain management can save companies time; and increase revenue while reducing cost. According to a 2021 McKinsey study - “Successfully implementing AI-enabled supply-chain management has enabled early adopters to improve logistics costs by 15 percent, inventory levels by 35 percent, and service levels by 65 percent, compared with slower-moving competitors.” 

While the supply chain industry is still fragile - more companies are learning from their mistakes and embracing AI and technology within their supply chain management to limit disruptions. While AI and machine learning won’t solve all of the supply chain industry's woes - it is a leap in the right direction.  

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 Danielle Loughnane

Danielle Loughnane earned her B.F.A. in Creative Writing from Emerson College and has currently been working in the data science field since 2015. She is the author of a comic book entitled, “The Superhighs” and wrote a blog from 2011-2015 about working in the restaurant industry called, "Sir I Think You've Had Too Much.” In her spare time she likes reading graphic novels and snuggling with her dogs.

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