Absenteeism Prediction

I developed the Absenteeism Prediction project at Heineken to forecast the number of employees and the number of days they will be temporarily absent due to sickness across various company locations in Brazil. By using advanced data analytics and predictive modeling, this project helps in proactive workforce planning and resource allocation. This initiative not only enhances operational efficiency but also generates significant cost savings, amounting to $1 million per year. Through accurate predictions, Heineken can better manage absenteeism, ensuring minimal disruption to operations while maintaining employee well-being.