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Machine learning can be used in planning and logistics to provide timely, accurate, and repeatable predictive insights.The process can be automated, allowing for improvements in multiple areas of supply and demand departments' analytics.

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• Dynamic Demand Forecasting: Machine learning models can train on how different factors affect demand and make predictions accordingly, using both historical data and the latest information.
• Inventory Management: Machine learning can be used to build accurate predictive models that help understand when to place orders.
• Avoiding Shipping Delays: Machine learning models can predict the ideal safety stock level using both historical sales data and the latest information.
• Benefits for Stakeholders: The advantages of machine learning extend to retailers, partners, suppliers, manufacturers, and third-parties who share data.

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