Workforce planning and scheduling is one of the major challenges in the hotel industry, with multiple variables impacting guest demand and attendance. For operational efficiency, however, effective forecasting and workforce planning is crucial. In this article, we reveal a case study for a large hotel chain which sought to identify the most accurate forecasting methods to optimize workforce planning. We tested various forecasting models to forecast customer visits, broken down into different parts of the hotel (restaurant, lounge-bar, lobby, etc.) and at different times of the day (breakfast, lunch, etc.). We compare the performance of traditional time-series models and Machine Learning, revealing the forecast accuracies of each, and the dollar savings of the most effective ...

From Issue: Strategy-Driven S&OP For Greater Business Value
(Spring 2022)

Case Study: Time Series Vs Machine Learning for Workforce Planning in the Hotel Industry