Demand Forecasting

AI in the supply chain has many applications, not least of which includes logistics. While historically logistics teams may have operated in siloes and relied on manual, labor-intensive processes, they are now leaning into AI-powered tech to gain greater visibility into their operations.

Artificial intelligence can be used to quickly gather and analyze massive amounts of data flowing from a large number of sources. As a result, AI in the supply chain is a prime candidate for the tech investments that can move the needle in improving business performance.

While AI in the supply chain is far from a magic salve, both it and IoT can deliver an elevated level of visibility into the supply chain.

There’s no shortage of AI logistics use cases, whether it’s through demand forecasting, enhancing warehouse efficiencies, or improving route planning. In all of these cases, AI in the supply chain can translate to streamlining, predicting, and automating key aspects of logistics operations. 

Businesses across the world are increasingly recognizing sustainability as a critical element of their operations. From reducing environmental impact to improved margin expansion, organizations everywhere have embraced sustainable practices but how can they make sure these measures pay off?

For Tyson Foods, the future of supply chain management depends on automated, near-real-time insights. Find out how the company is laying the foundation for a supply chain control tower as part of this goal.

In this edited webinar transcript, Scott Isaacson, manager of data science for Citrine Informatics and Rob Kieschke, former senior director for AI and software research in the 3M Digital Science Community paint a picture of what the future of automation within product innovation might look like, and how to manage change as the pace of these innovations gains momentum.

Pullings Hart will be replacing Magdi Batato, who is retiring from the role after a 30-year career with Nestlé.