PREDICTIVE HR ANALYTICS: MASTERING THE HR METRIC
Book ID/图书代码： 07682016B88962
English Summary/英文概要： While other departments in an organization deal with profits, sales growth, and strategic planning, Human Resources (HR) is responsible for employee well-being, engagement, and staff motivation. Even though it may not be immediately obvious, the management of these duties often requires a great deal of measurement and technical skill. Predictive HR Analytics provides a clear and accessible framework to understanding and learning to work with HR analytics at an advanced level, using examples of particular predictive models, such as diversity analysis, predicting turnover, evaluating interventions, and predicting performance.
When dealing with metrics, management information, and analytics, HR practitioners rarely use any advanced statistical techniques or go beyond describing the characteristics of the workforce. Authors Martin Edwards and Kirsten Edwards explain the business applications of HR predictive models; the ethics and limitations of HR analytics; how to carry out an analysis; predict turnover, performance, recruiting, and selection outcomes; and monitor the impact of interventions.
Chinese Summary/中文概要： 企业的人力资源部门主要负责管理员工的福利、雇佣和激励。即使这种管理并没有立竿见影的效果，这些工作还是需要用到大量的测量和技术技巧。本书提供了一个简单明了的框架，帮助大家理解并学习如何利用人力资源分析来进行工作，使用各种预测模型，包括多样性分析、预测人员流失率、评估干预措施和预测绩效等。
在处理指标、管理信息和分析时，人力资源从业人员很少使用任何高级的统计技术，往往局限于描述员工的特征。本书作者解释了人力资源预测模型的商业应用；人力资源分析的职业道德和局限性；如何进行分析；预测人员流动、绩效、招聘和选择结果；监测干预措施的影响等。
目录：
第一章：理解人力资源分析
第二章：人力资源信息系统和数据
第三章：分析策略
第四章：案例研究1：多样性分析
第五章：案例研究2：员工态度调查
第六章：案例研究3：预测员工离职率
第七章：案例研究4：预测员工绩效
第八章：案例研究5：招聘和选择分析
第九章：案例研究6：监测干预措施的影响
第十章：业务应用：场景建模 和业务案例
第十一章：更高级的人力资源分析技术
第十二章：反思人力资源分析:使用、道德和局限性(LYR)
Awards/获奖情况：“任何阅读和学习这本书的人都将成为更有效的人力资源专家。对于所有的人力资源管理专业的学生来说，都应该阅读本书。”——David Guest，教授
“本书对任何对这个激动人心的新领域感兴趣的专业人士来说，是一份全面而详细的指南。这本书将帮助你理解应该分析哪些数据，如何解释和分析数据，以及不同类型的模型是如何工作的。强烈推荐给人类分析专家！”——Josh Bersin，行业分析师
"Anyone reading and learning from this book and applying its lessons will be a more effective HR professional. It should certainly become compulsory reading for all HRM students."
(David Guest, Professor of Organizational Psychology and HRM King’s College, London)
"Predictive HR Analytics is a comprehensive and detailed guide for any professional interested in this exciting new field. The book will help you understand what data to analyze, how to interpret and analyze the data, and how different types of models work. Highly recommended for people analytics specialists!"
(Josh Bersin, Industry Analyst, Principal and Founder Bersin by Deloitte)
"Detailed, precise and clearly written, this book isn’t just about statistics; it’s about the future of HR. Essential reading for everyone in HR."
(Professor Binna Kandola OBE, Business Psychologist Senior Partner and co-founder of Pearn Kandola)
Table Of Contents
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
About the Author/作者介绍： Martin R. Edwards在伦敦国王学院教授人力资源管理和组织心理学。他曾为许多公司举行人力资源分析研讨会，并对员工参与调查提供咨询，还进行过多次员工态度调查。
Kirsten Edwards是一家专注于多元化、评估和发展的商业心理学咨询公司的专家。她在伦敦国王学院和肯特大学教授多样性和包容性课程。
Martin R. Edwards teaches HRM and Organizational Psychology at King’s College London. He has run many HR analytic workshops with companies including AstraZeneca, advised on employee engagement surveys, and run multiple employee attitude surveys.
Kirsten Edwards is a Diversity Specialist at Pearn Kandola, a business psychology consulting company specializing in diversity, assessment, and development. She has taught diversity and inclusion at Kings College London and the University of Kent.
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