Time Series Isnt Enough: How Graph Neural Networks Change Demand Forecasting

Graph Neural Networks (GNNs) are transforming demand forecasting by modeling stock-keeping units (SKUs) as interconnected networks rather than isolated entities, capturing complex relationships and dependencies among products. This approach addresses limitations of traditional forecasting methods, enabling more accurate predictions by leveraging the structural information within SKU networks to better understand demand patterns and substitution effects.