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Identifying demand shifts in real-time

Published by E2open

E2open helped a global candy maker optimize their demand planning process by implementing advanced AI and machine learning-driven solutions. The company faced challenges with fluctuating seasonal demand, which led to inefficiencies and an inability to detect demand shifts in real time. By adopting E2open's Demand Planning and Demand Sensing applications, they automated forecasts, integrated external data like point-of-sale (POS) information, and improved demand accuracy by 23%. These solutions enhanced productivity, allowing planners to focus on higher-value tasks while improving decision-making with dynamic what-if analysis.

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Related Categories Artificial Intelligence, AI Ethics, AI Platforms, AI Integration, Supply Chain & Manufacturing, Demand Forecasting, Inventory Management, Predictive Maintenance, Logistics Optimization, Quality Control, Supply Chain Visibility, Manufacturing Analytics, IoT in Manufacturing

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