05439nam a22002177a 450000500170000000800410001702000180005804000180007608200230009410000320011724500900014925000120023926000320025130000270028350004620031050438290077250505250460165000410512665000260516765000280519320260305173143.0260218b |||||||| |||| 00| 0 eng d a9789357461733 cAIMIT LIBRARY 22a658.30015bBHAD aBhattacharyya, Dipak Kumar. aHR analytics :bunderstanding theories and applications /cDipak Kumar Bhattacharyya. a2nd ed. aNew Delhi :bWiley ,c2024. axix,222p. ;bPBc24 cm aHR Analytics: Understanding Theories and Applications, 2nd edition, delves deeper into the transformative world of data-driven human resource management. In an era defined by the rapid evolution of technology, it discovers the latest insights on artificial intelligence (AI) and machine learning (ML), and explores the major advances and applications of big data, providing HR professionals with the tools they need to make strategic, data-driven decisions. aPreface to the Second Edition Preface to the First Edition About the Author Acknowledgements Chapter 1 Evolution of Human Resource Management Function 1.1 Introduction 1.2 History of Different HRM Perspectives 1.3 HRM and Strategy 1.4 Reinforcement of HR Strategy Factors with HR Analytics 1.5 Human Resource Management as a Process 1.6 Human Resource Management as a System 1.7 Better Clarity on Roles of HR Managers 1.8 Transition of Human Resource Management to Human Capital Management 1.9 Sustainable Competitive Advantage through Human Capital 1.10 Emergence of Human Resource Control Systems 1.11 Measurement Tools Used in Human Resource Controlling Chapter 2 HR Decision-Making and HR Analytics 2.1 Introduction 2.2 HR Decision-Making 2.3 Descriptive HR Decision-Making 2.4 Correlational HR Decision-Making 2.5 Predictive HR Decision-Making 2.6 Concept and Definitions of Analytics 2.7 Importance and Significance of HR Analytics 2.8 Benefits of HR Analytics 2.9 Steps to Implement HR Analytics 2.10 Critical HR Decision-Making and HR Analytics 2.11 Predictive HR Analytics 2.11.1 Benefits of Predictive Analytics 2.12 HR Analytics and Changing Role of HR Managers Chapter 3 Introduction to HR Analytics 3.1 Introduction 3.2 Concepts and Definitions 3.3 Aligning Human Resources to Business through HR Analytics 3.4 Steps for Alignment of HR Analytics with Business Goals and Strategies 3.5 Checklists for Strategies and Business-Aligned HR Analytics 3.6 History of HR Analytics 3.7 Applications of HR and Predictive Analytics 3.8 Importance and Benefits of HR Analytics 3.9 HR Analytics Framework and Models Chapter 4 HR Business Process and HR Analytics 4.1 Introduction 4.2 Statistics and Statistical Modelling for HR Research and HR Decision-Making 4.3 HR Research Tools and Techniques 4.4 Data Analysis for Human Resources 4.5 Parametric and Non-Parametric Tests 4.6 HRIS for HR Decision-Making 4.6.1 Objectives of HRIS 4.7 HR Metrics 4.8 Recruitment Metrics 4.9 Metrics for Training and Development Function 4.10 HR Scorecard 4.11 HR Dashboards 4.12 HR Analytics as a Better Tool for HR Decisions 4.13 Compelling Reasons for HR Analytics Chapter 5 Forecasting and Measuring HR Value Propositions with HR Analytics 5.1 Introduction 5.2 Value Proposition and HR Decisions 5.3 Sustainability in HR Decisions 5.4 HR Analytics and HR Value Propositions 5.5 HR Optimization through HR Analytics 5.6 HR Forecasting, HR Plan and HR Analytics 5.7 Predictive HR Analytics Chapter 6 HR Analytics and Data 6.1 Introduction 6.2 HR Data and Data Quality 6.3 HR Data Collection 6.3.1 Steps for HR Data Collection 6.4 Big Data for Human Resources 6.5 Transforming HR Data into HR Information 6.6 Process of Data Collection for HR Analytics 6.7 Data Collection for Effective HR Measurement 6.8 HR Reporting 6.9 Types and Forms of HR Reports 6.10 Data Visualization or HR Report Visualization 6.10.1 Performing Root Cause Analysis 6.11 Datafication of Human Resources Chapter 7 HR Analytics and Predictive Modelling 7.1 Introduction 7.2 Different Phases of HR Analytics or HR Predictive Modelling 7.3 Examples of Predictive Analytics 7.4 Data and Information for HR Predictive Analysis 7.5 Software Solutions 7.6 Predictive Analytics Tools and Techniques Chapter 8 HR Analytics for Future 8.1 Introduction 8.2 Understanding Future Human Resources 8.3 Generic Future HR Skillsets and Knowledge 8.4 Ethical Issues in HR Analytics 8.5 HR Feel More Empowered with HR Analytics 8.6 Artificial Intelligence and HR 8.7 Different Types of AI for HR Functions 8.8 AI and Machine Learning Summary Multiple-Choice Questions Review Questions Critical Review Question Case Study References Appendix Glossary Index rAbout the Author Dipak Kumar Bhattacharyya is an Ex-Professor of Xavier Institute of Management, Bhubaneswar (XIMB). He has more than 15 years of professional experience and over 25 years of teaching experience. He was previously the Corporate Director at the Camellia School of Business Management, Kolkata. Before that, he was the Dean of the Indian Institute of Social Welfare and Business Management (IISWBM); Director, Centre for Management Education, AIMA, New Delhi; Professor, Institute of Management Technology. aHR decision- making and HR analytics aHR analytics and data aHR analytics for future