5 AI projects that will revolutionize the supply chain! (3/5)

Application 3 from The Slimstock Research Centre: "Identifying anomalies”

Using similar techniques to those relied upon in fraud detection, our team is applying machine learning techniques to enable supply chain teams to identify outliers in demand history and exclude this from any analysis. Furthermore, by utilizing advanced neural networks to cluster SKUs that are highly sensitive to anomalies, these products can be managed more proactively.

This development will help to detect anomalies in daily operations like customer transactions, availability and inventory status. As a result, the reliability of both processes and calculations will be drastically improved!