Confidently use predictive analytic and statistical techniques to identify key relationships and trends in HR-related data to aid strategic organizational decision-making.

This is the essential guide for HR practitioners who want to gain the statistical and analytical knowledge to fully harness the potential of HR metrics and organizational people-related data. The ability to use and analyse data has become an invaluable skill for HR professionals to not only identify trends and patterns, but also make well-informed business decisions. The third edition of Predictive HR Analytics provides a clear, accessible framework for understanding people data, working with people analytics and advanced statistical techniques. Readers will be taken step-by-step through worked examples, showing them how to carry out analyses and interpret HR data in areas such as employee engagement, performance and turnover. Learn how to make effective business decision with this updated edition that includes the latest materials on biased algorithms and data protection, supported by online resources consisting of R and Excel data sets.

Online resources: Excel data sets and R syntax with worked case study examples

Autorentext
Daisung Jang is an Assistant Professor at Melbourne Business School. He has over a decade of experience in data visualization and analysis using R. He has conducted workshops for PhD students and academic staff on statistical analyses using R.

Inhalt

• • Chapter - 01: Understanding HR analytics;
  • Chapter - 02: HR information systems and data;
  • Chapter - 03: Analysis strategies;
  • Chapter - 04: Case study 1 Diversity analytics;
  • Chapter - 05: Case study 2 Employee attitude surveys engagement and workforce perceptions;
  • Chapter - 06: Case study 3 Predicting employee turnover;
  • Chapter - 07: Case study 4 Predicting employee performance;
  • Chapter - 08: Case study 5 Recruitment and selection analytics;
  • Chapter - 09: Case study 6 Monitoring the impact of interventions;
  • Chapter - 10: Business applications Scenario modelling and business cases;
  • Chapter - 11: More advanced HR analytic techniques;
  • Chapter - 12: Reflection on HR analytics Usage, ethics and limitations;
  • Chapter - 13: Appendix