AI in Inventory Management
Inventory management is a crucial step of the supply chain process and has a significant impact on a retailer’s fulfillment capabilities. Being able to track and understand your inventory levels at any given time is a tricky balancing act, in which retailers must be sure to have enough stock to keep up with orders, but not so much stock that cash reserves are drained. One effective method that has been on the rise recently, is the implementation of artificial intelligence into inventory management processes.
Amazon is a prime example of successful AI implementation. The ecommerce giant utilizes AI in almost every facet of their inventory operations, including time series prediction, supplier backorders, and warehouse optimization. Such wide scale AI implementation is likely not feasible for smaller retailers, but nevertheless, improvements can be made with smaller scale implementation as well.
Remi AI asserts that there are two key areas in which AI can yield strong improvements - the first being Demand Prediction, which is intended to estimate demand in coming days across all areas of your inventory. And the second being Reinforcement Learning, which is where AI models are able to make predictions and then act on them - one study even saw a 32% reduction in cost after using Reinforcement Learning.
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