Mosaic Data Science’s white paper presents how machine learning improves workforce planning through accurate demand forecasting. In the energy sector, a model using weather and service data helped predict heating technician needs, reducing resource strain. In healthcare, forecasting ICU saturation using historical ED data enabled hospitals to adjust staffing and manage patient flow. Techniques like XGBoost and ARIMA achieved accurate 12-week predictions, while ensemble models enhanced reliability. The approach improves efficiency, reduces costs, and can be adapted across industries for smarter, data-driven workforce deployment.

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