Forecasting Online Demand for Labour Planning

Explore a 38-minute conference talk from the Data Science Festival featuring Charles Douse and Andreas Yiannakou from M&S. Delve into the application of data science for improving online demand forecasting in fulfilment centers. Learn how machine learning models can enhance resource planning for picking, packing, and dispatching online orders, potentially reducing costs and maintaining customer delivery times. Discover the importance of model interpretability in explaining findings and understanding accuracy. Gain insights into breaking down forecasts to display each feature's incremental impact, providing a more nuanced understanding of the prediction process.