Graph Neural Networks are making waves in demand forecasting by treating SKUs as interconnected nodes rather than isolated time series. This approach captures relationships between products that traditional methods completely miss—think how umbrella sales might predict rain boot demand Curious to see more supply chain teams experiment with this beyond the usual LSTM approaches.
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