The Workday Technology Blog post, "Workday’s Deep Dive into ML-Powered Labor Demand Forecasting," By Madhura Raut discusses how Machine Learning (ML) is revolutionizing workforce scheduling.

The article explains how Workday shifted from directly forecasting volatile labor demand to predicting stable, underlying drivers like customer traffic and transaction volumes, which are then translated into staffing needs.

It details the challenges of traditional forecasting methods, such as their inability to adapt to complex factors like changing trends, holidays, and promotions.

The text highlights Workday's ML approach, emphasizing data quality, rich feature engineering, and adaptive modeling to achieve granular and accurate labor predictions, ultimately leading to improved operational efficiency and cost savings.