Managing inventory can be a tricky balancing act. In some ways it’s reminiscent of “Goldilocks and the Three Bears,” always looking for the perfect amount. Warehouses without enough inventory have unsatisfied customers. On the other hand, those with too much inventory run out of storage and accrue costs.
Fortunately, machine learning and predictive analytics have made it much easier to keep track of products and predict future needs based on client behavior, helping keep warehouses properly stocked. With the help of machine learning, supply chains can be greatly improved through predictive inventory management.
Image and Pattern Recognition Image recognition and machine vision is already fairly common in warehouses where it is used to inspect products and guide robots. In the supply chain, it has further use in recognizing products and knowing when it is time to restock.
Coca-Cola has partnered with Salesforce to use its Einstein AI image recognition platform. When shown a picture of a display cooler, Einstein AI can recognize types of Coca-Cola products and determine how many of each are in the display. The partnership was announced in 2017 and is being refined, but it could eventually eliminate the need for those delivering the soda to count inventory on their stops.
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