Artificial intelligence works its way into supply chains

Adding Artificial Intelligence to supply chains is delivering tangible benefits for companies putting it in place. Recent research out of McKinsey finds 61% of executives report decreased costs and 53% report increased revenues as a direct result of introducing Artificial Intelligence into their supply chains. More than one-third report a revenue bounce exceeding five percent. Areas generating revenue in supply chain management include sales and demand, forecasting, spend analytics, and logistics network optimization. 

Sounds good. So what's standing in the way of getting more AI into supply chain management systems? I ran this question past Arnaud Morvan, senior engagement director at Aera Technology, a company that focuses on AI. "A reliance on obsolete legacy technologies creates a great deal of time-consuming and error-prone manual work for supply chain practitioners," Morvan points out. "They often spend about 50% of their time collecting and crunching numbers from disparate global systems. That adds weeks or months of delay to core processes that need to run faster to keep up with market demand."

Increasing complexity in supply chain IT infrastructure "makes it difficult to achieve the speed and agility that's required in today's markets," Morvan adds. "With globalization, it's common for large companies to operate hundreds of sourcing, production and distribution systems around the world, both internally and with partners."   

Today's supply chains look a lot different than just a few years ago, and they continue to evolve in a fiercely competitive economy. The latest innovations include "the creation of pop-up warehouses, ship-from-store models and other speed-oriented innovations," he says. "And supply chains are challenged to effectively manage growing product portfolios that can include many thousands of SKUs. SKU volumes continue to rise as companies strive to meet customer expectations for multiple sizes, colors and other variations in product configurations."  

AI can help keep enterprises on top of these shifts. Morvan calls the type of AI best suited for supply chain management as "cognitive automation," which is essentially extremely scalable AI that can "process terabytes or even petabytes of data." Such a platform can execute "thousands of Google-like data crawls a day across any number of internal or external systems, then aggregates and normalizes that data in what's called a cognitive data layer. There, AI and ML algorithms are applied to produce recommendations on optimal actions to improve supply chain speed and cost-efficiency," he states.