Applied Predictive Analytics

in HR

Cornell Course

As organizations strive to succeed in a continuously evolving world, talent must be continuously assessed and evaluated to ensure alignment with strategic goals. It is no longer acceptable to serve in a consultant capacity on problems that arise or to offer strategic advice based solely on experience and policy. Today, HR teams must partner with senior leadership in driving effective and efficient change using credible data and analysis.

Predictive analytics help organizations anticipate and plan appropriately for the future. In this course, learners will apply rigorous measurement and analysis techniques to common HR areas involving hiring top talent, evaluating workforce diversity, engaging the workforce, and managing retention. Through activities and assignments, learners will explore foundational HR metrics and measures to more advanced predictive models. As learners examine key inputs and data sources, they will use data to predict patterns and trends in areas such as diversity, engagement, and performance. Ultimately, students will use metrics and analytics to assess the current talent landscape of an organization and outline recommendations they would present to senior leadership.

This course assumes a basic comfort level in working with HR data and analysis. It is designed to equip students with the concepts, tools, and language specific to key areas within HR analytics. The course provides examples using Excel. Other data analytics software will not be presented, although the information shared is transferable for those fluent in other programs.