Predictive HR analytics : mastering the HR metric / created by Martin R. Edwards, Kirsten Edwards and Daisung Jang

Includes bibliographical references and index

Cover Contents Preface Acknowledgements 01 Understanding HR analytics Predictive HR analytics defined Understanding the need (and business case) for mastering and utilizing predictive HR analytic techniques Human capital data storage and 'big (HR) data' manipulation Predictors, prediction and predictive modelling Current state of HR analytic capabilities and professional or academic training Business applications of modelling HR analytics and HR people strategy Becoming a persuasive HR function References 02 HR information systems and data Information sources Analysis software options Using SPSS Preparing the data Big data References 03 Analysis strategies From descriptive reports to predictive analytics Statistical significance Examples of key HR analytic metrics/measures often used by analytics teams Data integrity Types of data Categorical variable types Continuous variable types Using group/team-level or individual-level data Dependent variables and independent variables Your toolkit: types of statistical tests Statistical tests for categorical data (binary, nominal, ordinal) Statistical tests for continuous/interval-level data Factor analysis and reliability analysis What you will need Summary References 04 Case study 1: Diversity analytics Equality, diversity and inclusion Approaches to measuring and managing D&I Example 1: gender and job grade analysis using frequency tables and chi square Example 2a: exploring ethnic diversity across teams using descriptive statistics Example 2b: comparing ethnicity and gender across two functions in an organization using the independent samples t-test Example 3: using multiple linear regression to model and predict ethnic diversity variation across teams Testing the impact of diversity: interacting diversity categories in predictive modelling A final note References 05 Case study 2: Employee attitude surveys engagement and workforce perceptions What is employee engagement? How do we measure employee engagement? Interrogating the measures Conceptual explanation of factor analysis Example 1: two constructs exploratory factor analysis Reliability analysis Example 2: reliability analysis on a four-item engagement scale Example 3: Principal Components Analyses with group-level engagement data Analysis and outcomes Example 4: using the independent samples t-test to determine differences in engagement levels Example 5: using multiple regression to predict team-level engagement Survey comments analysis Actions and business context References 06 Case study 3: Predicting employee turnover 200 Employee turnover and why it is such an important part of HR management information

A 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