To provide the students understanding of concepts, tools and techniques of HR Analytics that could be applied to make human resource management evidence based.
- Describe the importance and potential uses of HR Analytics in measuring human resources and how it drives an organization’s performance
- Analyze HR data from a practical perspective and determine what analytic techniques to apply based on the business context
- Employ measurement and analytical techniques around intangibles and identify ways to benchmark performance and create standards
- Learn how to create meaningful HR reports
- Learn how to use predictive modeling techniques
- learn how to measure and forecast budget numbers for HR costs
- Demonstrate how to connect HR results to business results
- Discuss how to prove whether an HR program obtained its intended results
Introduction to HR Analytics: Evolution of HR Analytics; HR Metrics and HR Analytics; Intuition versus analytical thinking; HRMS/HRIS and data sources; Analytics frameworks like LAMP, HCM:21(r) Model.
Creating business understanding for HR initiatives: Workforce segmentation and search for critical job roles; Statistical driver analysis – association and causation; Linking HR measures to business results; choosing the right measures for scorecards; Identifying and using key HR Metrics
Forecasting budget numbers for HR costs: Workforce planning including internal mobility and career pathing; training and development requirement forecasting and measuring the value and results of improvement initiatives; optimizing selection and promotion decisions
Predictive modeling in HR: Employee retention and turnover; workforce productivity and performance; scenario planning
Communicating with data and visuals: Data requirements; identifying data needs and gathering data; HR data quality, validity and consistency; Using historical data; Data exploration; Data visualization; Association between variables; Insights from reports; Root cause analysis of HR issues.