Demand forecasting goes hand-in-hand with inventory management, and forecasting is one of the most significant supply chain challenges for retailers and suppliers. This challenge is complicated by the rapid swings in buyer demand and customer behavior.

Machine learning models can be trained on how different factors affect demand and then make predictions accordingly. And they can do it using both historical data and the latest information.

Machine learning models also deliver more accurate forecasts than traditional methods, which often rely solely on historical information that is outdated by the time all the data is cleaned and analyzed using manual methods.

3 Machine Learning Use Cases for Planning and Logistics

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