HR metrics and organizational people-related data are an invaluable
source of information from which to identify trends and patterns in
order to make effective business decisions. But HR practitioners often
lack the statistical and analytical know-how to fully harness the
potential of this data. Predictive HR Analytics provides a clear,
accessible framework for understanding and working with people analytics
and advanced statistical techniques. Using the statistical package SPSS
(with R syntax included), it takes readers step by step through worked
examples, showing them how to carry out and interpret analyses of HR
data in areas such as employee engagement, performance and turnover.
Readers are shown how to use the results to enable them to develop
effective evidence-based HR strategies.
This second edition has been updated to include the latest material on
machine learning, biased algorithms, data protection and GDPR
considerations, a new example using survival analyses, and
up-to-the-minute screenshots and examples with SPSS version 25. It is
supported by a new appendix showing main R coding, and online resources
consisting of SPSS and Excel data sets and R syntax with worked case
study examples.