Demand Forecasting

From Connections to Meaning: Why Heterogeneous Graph Transformers (HGT) Change Demand Forecasting

forecasting errors are usually not brought on by bad time-series models. They're brought on by ignoring structure. SKUs don't behave independently. They interact through shared plants, product groups, warehouses, and storage locations. A requirement shock...

Time Series Isn’t Enough: How Graph Neural Networks Change Demand Forecasting

in supply-chain planning has traditionally been treated as a time-series problem. Each SKU is modeled independently. A rolling time window (say, last 14 days) is used to predict tomorrow’s sales. Seasonality is captured, promotions are added,...

What If I Had AI in 2020: Rent The Runway Dynamic Pricing Model

of Shopify, recently told his employees in an internal memo: “Before asking for more headcount and resources, teams must exhibit why they can not get what they need done using AI”. Having worked in...

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