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Submit a ProposalHuman Capital Analytics
 | Exploring the HR Spectrum in Industry 5.0 Edited by Deepa Gupta, Mukul Gupta, Pawan Budhwar, Jim Westerman, Rajesh Kumar Dhanaraj, Balamurugan Balusamy Copyright: 2025 | Status: Published ISBN: 9781394238323 | Hardcover | 406 pages Price: $225 USD  |
One Line Description
The book equips readers with essential insights and strategies for leveraging cutting-edge technology and human capital analytics, ensuring organizations thrive in the era of human-robot collaboration and sustainable workforce development.
Audience
Human resource developers, analysts, professionals, business executives, data scientists, consultants, professors, academics, and students exploring ways to leverage technology for Industry 5.0
Human resource developers, analysts, professionals, business executives, data scientists, consultants, professors, academics, and students exploring ways to leverage technology for Industry 5.0
Description
Human Capital Analytics: Exploring the HR Spectrum in Industry 5.0 provides a comprehensive investigation into the ever-changing junction of human capital and cutting-edge technology in the context of the Fifth Industrial Revolution. This volume emphasizes the revolutionary role that human capital analytics plays in changing workforce management, talent development, and HR strategies. This position is particularly relevant as organizations transition into Industry 5.0, where human-robot collaboration is the norm. The purpose of this book is to provide a forward-looking perspective on how data-driven human resource strategies will become vital for boosting worker potential and driving organizational success. This is accomplished by integrating developing technologies such as artificial intelligence, machine learning, and robots.
Readers will find that this book:
• Explores the transformative role of human-robot collaboration, emerging technologies, and strategic HR planning in the context of the Fifth Industrial Revolution;
• Provides a comprehensive overview of how predictive analytics and human capital analytics can enhance workforce management, employee engagement, and performance measurement;
• Focuses on how HR 5.0 contributes to advancing the United Nations Sustainable Development Goals, driving both social and business impact;
• Includes empirical studies, case studies, and real-world examples of implementing Industry 5.0 in organizations;
• Provides actionable strategies for HR professionals to navigate the digital transformation of human resource management, incorporating AI, robotics, and data-driven approaches.
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Human Capital Analytics: Exploring the HR Spectrum in Industry 5.0 provides a comprehensive investigation into the ever-changing junction of human capital and cutting-edge technology in the context of the Fifth Industrial Revolution. This volume emphasizes the revolutionary role that human capital analytics plays in changing workforce management, talent development, and HR strategies. This position is particularly relevant as organizations transition into Industry 5.0, where human-robot collaboration is the norm. The purpose of this book is to provide a forward-looking perspective on how data-driven human resource strategies will become vital for boosting worker potential and driving organizational success. This is accomplished by integrating developing technologies such as artificial intelligence, machine learning, and robots.
Readers will find that this book:
• Explores the transformative role of human-robot collaboration, emerging technologies, and strategic HR planning in the context of the Fifth Industrial Revolution;
• Provides a comprehensive overview of how predictive analytics and human capital analytics can enhance workforce management, employee engagement, and performance measurement;
• Focuses on how HR 5.0 contributes to advancing the United Nations Sustainable Development Goals, driving both social and business impact;
• Includes empirical studies, case studies, and real-world examples of implementing Industry 5.0 in organizations;
• Provides actionable strategies for HR professionals to navigate the digital transformation of human resource management, incorporating AI, robotics, and data-driven approaches.
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Author / Editor Details
Deepa Gupta, PhD is a distinguished academician with over 24 years of experience in management studies, currently serving as Dean at GL Bajaj Institute of Management. Her expertise extends to organizational development, corporate relations, and international collaboration.
Deepa Gupta, PhD is a distinguished academician with over 24 years of experience in management studies, currently serving as Dean at GL Bajaj Institute of Management. Her expertise extends to organizational development, corporate relations, and international collaboration.
Mukul Gupta, PhD is a professor at GL Bajaj Institute of Management with over 25 years of experience in teaching and the corporate sector. His research and expertise in consumer behavior are invaluable for understanding the human-centric aspects of Human Capital Analytics, offering insights into user behavior, adoption, and interaction with AI-driven systems and services.
Pawan Budhwar, PhD is a professor of International Human Resource Management and the Associate Deputy Vice Chancellor International at Aston Business School. His research interests include personnel and human resource management, organizational performance, and artificial intelligence.
Jim Westerman, PhD is a professor in the Department of Management at Appalachian State University, Boone, North Carolina, USA. His areas of expertise include human resource management, organizational behavior, leadership, sustainable business, and business ethics.
Balamurugan Balusamy, PhD is an Associate Dean of Students at Shiv Nadar University with 12 years of teaching experience. He has published over 200 papers and over 80 books in collaboration with professors worldwide. His research interests include engineering education, blockchain, and data sciences.
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Table of Contents
Preface
Part 1: Foundation and Strategic Framework of Human Capital Analytics in Industry 5.0
1. Human Capital Analytics in Industry 5.0: Opportunities and Challenges
Veena Grover, Manju Nandal, Divya Sahu and Mahima Dogra
Abbreviations
1.1 Introduction
1.2 Evolution of Industry 5.0
1.3 Concept and Definition of Human Capital Analytics
1.4 Features of Human Capital Analytics
1.5 Advantages and Disadvantages of Human Capital Analytics
1.6 Uses of Human Capital Analytics
1.7 How Human Capital Analytics Help in Industry 5.0?
1.8 Difference Between Industry 4.0 and Industry 5.0
1.8.1 The Pillars of Industry 4.0
1.8.2 The Pillars of Industry 5.0
1.9 Human Capital Analytics Enabled in Different Sectors
1.10 Challenges and Opportunities of Human Capital Analytics
1.10.1 Challenges of Human Capital Analytics
1.10.2 Opportunities of Human Capital Analytics
1.11 HR Analytics and Artificial Intelligence
1.12 HR Analytics and Blockchain
1.13 HR Analytics and the Internet of Things
1.14 Level of Analytics Used in Human Capital Analytics
1.15 The Shift of People Analytics
1.15.1 People Analytics
1.15.2 Why People Analytics More Effective at Driving Value
1.15.3 Example of How People Analytics Can Improve Business Value
1.16 Conclusion and Future Direction
References
2. Human Capital Analytics and Emerging Technologies in Industry 5.0
Harpreet Kaur Channi and Surinder Kaur
2.1 Introduction
2.1.1 Background and Motivation
2.2 Industry 5.0 and the Role of Human Capital
2.2.1 Evolution of Industrial Revolutions: From Industry 4.0 to Industry 5.0
2.2.2 The Significance of Human Capital in the Modern Industrial Landscape
2.2.3 Synergy Between Technology and Human Expertise in Industry 5.0
2.3 Emerging Technologies Shaping Human Capital
2.3.1 Emerging Technologies’ Revolutionary Effect on Workforce Management
2.3.2 Integrating Human and Technological Capabilities for Optimal Outcomes
2.4 Human Capital Analytics: Enhancing Workforce Management
2.4.1 Role of Data Analytics in Human Capital Management
2.4.2 Data-Driven Insights for Employee Performance and Skill Assessment
2.4.3 Predictive Analytics for Workforce Planning and Employee Retention
2.4.4 Harnessing Data to Optimize Resource Allocation and Training Strategies
2.4.5 Case Studies
2.5 Challenges and Ethical Considerations
2.5.1 Data Privacy and Security Concerns in Human Capital Analytics
2.5.2 Fairness, Bias, and Transparency in AI-Driven Workforce Management
2.5.3 Ethical Guidelines and Governance
2.5.4 Bus Automation with Human Empowerment
2.6 Recommendations for Organizations
2.6.1 Building a Data-Driven Culture
2.6.2 Developing a Comprehensive Human Capital Analytics Strategy
2.6.3 Investing in Continuous Learning and Development
2.6.4 Balancing Technology with Human-Centric Approaches
2.7 Conclusion
References
3. Fifth Industrial Revolution and an Overview of its Impact on Human Resources
Aduku Alex Akubo, Okpanachi Linus Odiji and Muhammed Bature Muhammed
3.1 Introduction
3.2 Trajectory of Industrial Revolutions
3.3 An Overview of the Fifth Industrial Revolution
3.4 The Fifth Industrial Revolution and Human Resource Management of the Organizations
3.5 Fifth Industrial Revolution: Implications of the Technological Advancements on the Workforce
3.6 The Fifth Industrial Revolution: Opportunities and Challenges
3.7 Conclusion
References
4. Human Capital Transformation - Revolutionizing HR Practices with Advanced Technologies and Ethical Insights
Vijeyata, Chitra Jha and Sunil Tegwal
4.1 Introduction
4.2 Systematic Review
4.2.1 The Industrial Revolution
4.2.2 What are the Key Technologies Driving the Development of Industry 5.0?
4.2.3 Different Industrial Revolutions’ Effects on Human Resource Functions
4.2.4 Industry 5.0 Technologies
4.2.5 A Summary of Journal Search Results
4.3 Its Impact on HR
4.3.1 How these Technologies are Transforming Industries
4.3.2 Changing Workforce Dynamics
4.3.3 Talent Acquisition and Recruitment Activities
4.3.4 Challenges in Industry 5.0 Revolution
4.3.5 Limitations of Industry 5.0
4.4 Conclusion
References
5. HR 5.0 Strategic Planning and Evolution of HR Functions in the Business Environment
M. Bharathi, K. Praveena, M. Dharani, V. Madhurima, Krithikaa Mohanarangam, G. Sandhya Kumari and Saleha Tabassum
5.1 Introduction
5.2 Evolution Cycle of HR Functions
5.2.1 Analytics for HR and HR Driven by Data
5.2.2 Digital HR and Employee Experience
5.2.3 Future of Work and Agile HR
5.3 Factors Influencing the Business Environment and its Connection to Strategic Planning
5.3.1 Economic Factors
5.3.2 Political and Legal Considerations
5.3.3 Social and Cultural Factors
5.3.4 Challenging Factors
5.3.5 Environmental Factors
5.3.6 Scientific Advances
5.4 Three Steps to Strategic Planning in HR 5.0
5.4.1 Environmental Assessment
5.4.2 Goal Setting
5.4.3 Strategic Planning
5.5 Summary and Conclusion
5.5.1 Future Perspective
References
Part 2: Analytical Techniques and Applications in Workforce Management
6. Investigating the Transformative Effects of AI, Machine Learning, and Robotics on Human Capital Analytics - An Empirical Study
Gagandeep, Jyoti Verma and Deepa Gupta
6.1 Introduction
6.1.1 Background and Significance of the Study
6.1.2 Research Problem and Research Questions
6.1.3 Objectives of the Study
6.1.4 Contribution and Value-Add of the Study
6.2 Literature Review
6.2.1 Overview of AI, Machine Learning, and Robotics in the Context of Human Capital Analytics
6.2.2 Theoretical Frameworks and Models
6.2.3 Previous Empirical Studies on the Impact of AI, Machine Learning, and Robotics on Human Capital Analytics
6.2.4 Conceptual Framework and Hypotheses
6.3 Research Design and Methodology
6.4 Data Analysis
6.4.1 Descriptive Analysis
6.4.2 Inferential Analysis
6.4.2.1 Structural Equation Modeling (SEM)
6.4.2.2 Hypothesis Testing
6.5 Practical/Managerial Implications
6.5.1 Implications of the Study for Business Practitioners and Managers
6.5.2 Recommendations for Implementing AI, Machine Learning, and Robotics in Human Capital Analytics
6.6 Limitations of the Study
6.7 Future Research
6.8 Conclusion
References
Appendices (if applicable)
7. Unleashing Human Capital Analytics for Data-Driven Workforce Management
Princi Gupta, Deepa Gupta and Mukul Gupta
7.1 Introduction
7.2 Theoretical Background
7.2.1 From Metrics to Strategy: The Evolution of Human Capital Analytics
7.2.2 Dissecting HR Analytics: Exploring Different Types and Applications
7.3 Illustrative Case Studies: Transforming HR with Data-Driven Strategies
7.4 Strategic Integration: Deploying Data Analytics and Technology Solutions in HR Operations
7.5 Optimizing Talent Acquisition Through Data-Driven Human Capital Analytics
7.6 Data-Driven Strategies for Optimal Workforce Performance in Industry 5.0
7.7 Engage and Retain: Data-Driven Success
7.8 Navigating Complexities: Challenges and Strategic Solutions in Deploying Human Capital Analytics
7.9 Emerging Technological Solutions: AI and Machine Learning in HR Optimization
7.10 Conclusion
References
8. Mastering the Art of HR Data Collection and Management Techniques
Deepa Gupta, Mukul Gupta, Priti Rai, Karishma Sharma and Parth Mukul Gupta
Introduction
Importance of HR Data in Modern Organizations
Overview of HR Data Collection and Management
Data Collection Techniques
Data Management Systems
Leveraging HR Data for Decision-Making
Future Trends
Objectives and Benefits of Mastering HR Data Techniques
Fundamentals of HR Data
Data Privacy and Compliance Considerations
Data Collection Techniques
Manual Data Collection Methods
Computerized Data Collection Strategies
Best Practices for Accurate and Reliable Data Collection
Integrating HRIS with Other Business Systems
Data Quality and Accuracy
Best Practices for Data Storing
Analyzing HR Data
Techniques for Data Examination
Using HR Data for Free Course
Using Data to Enlighten HR Game Plans and Strategies
Case Studies of Data-Driven HR Decision Making
Future Trends in HR Data Management
The Occupation of HR in the Time of Cutting-Edge Change
Assumptions for the Inevitable Destiny of HR Data Collection and Management
References
9. Communicating Human Capital Analytics Insights to Decision-Makers Effectively
Sandeep Singh Chandel, Astha Shukla, Sakshi Shukla and Shivansu Sachan
Introduction of Analytics for Human Capital Analysis
Role of Retention in Analytics for Human Capital Analysis
Analytics for Human Capital Analysis
Human Capital Analysis Analytics Framework
Factors Affecting Human Capital Analysis (HCA) Analytics
Understanding the Needs and Inclinations of Choice Makers
Human Capital Analysis Calculations
Employee Turnover
New Contract Turnover Rate
Retention Rate
Offer Acceptance Rate
Cost per Hire
Time to Productivity
Types of HR Analytics
Training and Development Work Metrics
Conclusion
References
10. Predictive Analytics - Next Chapter in Talent Management
Swati Rai, Rakesh Kumar Yadav and Rajesh Kumar Dhanaraj
10.1 Introduction
10.1.1 Role of Predictive Analytics in Talent Management
10.1.1.1 Recruitment and Selection
10.1.1.2 Candidate Assessment
10.1.1.3 Retention and Employee Engagement
10.1.1.4 Succession Planning
10.1.1.5 Performance Management
10.1.1.6 Human Resource Planning
10.1.1.7 Learning and Development
10.1.1.8 Continuous Feedback and Improvement
10.2 Predictive Analysis - A Game Changer
10.3 Challenges in Predictive Analytics
10.3.1 Quality and Availability of Data
10.3.2 Privacy and Security of Data
10.3.3 Complexity of Models
10.3.4 Overfitting and Underfitting
10.3.5 Lack of Domain Expertise
10.3.6 Scalability Issues
10.3.7 Changing Data Patterns
10.3.8 Interpretable Models
Conclusion
References
11. Employee Engagement and Performance Management - Critical Role of Employee Potentials
Asma Bano and Ayesha Khatun
11.1 Introduction
11.1.1 Human Resource Analytics (HR Analytics)
11.2 Literature Review and Theoretical Concepts of the Study
11.2.1 Literature Review on Theoretical Concepts of Employee Potential
11.2.1.1 Factors of Employee Potential
11.2.1.2 Ways to Unlock the Employee Potential
11.2.2 Literature Review on Theoretical Concepts of Employee Engagement
11.2.2.1 Definitions of Employee Engagement
11.2.2.2 Factors of Employee Engagement
11.2.2.3 Methods of Attaining Employee Engagement
11.2.2.4 Outcomes of Employee Engagement
11.2.3 Literature Review on Theoretical Concepts of Organizational Performance
11.2.3.1 Factors of Organizational Performance
11.2.3.2 Steps to Achieve Organizational Performance
11.2.3.3 Outcomes of Organizational Performance
11.3 Conceptual Framework
11.3.1 Employee Potential
11.3.2 Employee Engagement
11.3.3 Organizational Performance
11.4 Research Objectives
11.5 Research Methodology
11.5.1 Research Method and Design
11.6 Findings and Discussions
11.7 Practical Implications
11.8 Limitations and Future Directions
11.9 Conclusions
References
12. Performance Evaluation and Measurement of Human Capital Analytics in the Information Technology (IT) Sector in India
Manoj Kumar, Pratibha Maurya and Rinki Verma
12.1 Introduction
12.2 Literature Review
12.2.1 Need for Evaluation of Human Capital
12.3 Objective of the Study
12.4 Methodology Adopted
12.4.1 Human Capital Return on Investment (HCROI)
12.4.2 Human Capital Value Added (HCVA)
12.4.3 Human Economic Value Added (HEVA)
12.5 Data Analysis
12.5.1 Objective 1
12.5.2 Objective 2
12.5.3 Objective 3
12.6 Discussion
12.7 Conclusion
12.8 Implications
References
13. Data-Driven Strategies to Improve Workplace Diversity, Equality and Inclusion (DEI)
Arkja Singh, Rakesh Kumar Yadav and Deepa Gupta
13.1 Introduction
13.1.1 Data-Driven Strategies in Workplace
13.1.1.1 Demographic Analysis
13.1.1.2 Sentiment Analysis
13.1.1.3 Network Analysis
13.1.2 DEI Initiatives within the Workplace
13.2 The Coalesce
13.2.1 Data-Driven Strategies and DEI
13.3 The Contraption
13.3.1 Data-Driven Mindset among the HR and Technology Leaders
13.3.1.1 Diversity
13.3.1.2 Equality
13.3.1.3 Inclusion
13.3.2 DEI Software
13.4 Challenges and Deliberations
13.4.1 Data Precision
13.4.2 Data Confidentiality
13.4.3 Steer Clear of Tokenism
13.4.4 Persistent Loyalty
13.5 Conclusion
13.5.1 Attracting Apex Talent
13.5.2 Driving Employee Retention and Loyalty
13.5.3 Nurturing Belonging and Inclusion
13.5.4 Identifying Gaps in Employee Representation
13.5.5 Tracking Progress Alongside Representation Goals
13.5.6 Furnishing Teams for Victory
13.5.7 Gaining an All-Inclusive View of DEI Experience
References
Part 3: Future Trends, Challenges, and Sustainable Development in HR Practices
14. Role of Human Capital Analytics and Industry 5.0 in Advancing the United Nations’ Sustainable Development Goals
Agagu A. A., Odiji O. L. and Akubo A. A.
14.1 Introduction
14.2 Review of Extant Literature
14.3 Conceptual Clarification
14.3.1 Human Capital Analytics
14.3.2 Fifth Industrial Revolution
14.4 The UN SDGs
14.4.1 Nexuses Between HCA, Industry 5.0, and the SDGs
14.5 Inherent and Emerging Challenges
14.5.1 Measures to Address the Challenges which Bedevils HCA and Industry 5.0 from Advancing UN SDGs
14.6 Concluding Remarks
References
15. Transforming Workplaces with Human-Robot Collaboration
B. Swathi
15.1 Introduction
15.2 Sustainability and Industry 5.0
15.2.1 Human-Robot Co-Working (HRC)
15.2.2 Literature Review
15.2.3 Objectives and Methodology
15.3 Industry 5.0, Human Resources, and Robots
15.3.1 Human and Robot Interaction
15.3.2 Industry 5.0 - Advantages
15.3.3 Concerns in Industry 5.0
15.4 Conclusion
References
16. Human Capital Analytics in Industry 5.0 for Sustainable Growth
Channi Sachdeva, Veena Grover and Veer P. Gangwar
16.1 Introduction of SDGs and the Role of Humans in Organization
16.2 Human Capital Analytics: Concepts and Applications
16.3 Literature Review
16.4 Integrating SDGs with Human Capital Strategies
16.5 Utilizing Data Analysis for Managing Talent and Development
16.6 Industry 5.0 Principles for Sustainable Value Creation
16.7 Challenges and Opportunities for Promoting Sustainable Development via Insights and Industry 5.0
16.8 Future Directions
References
17. HR 5.0 – Demystifying the Way Forward
Ritu Saxena, Priyanshi Jindal and Harshit Gouri
17.1 Introduction
17.2 Literature Review
17.2.1 Challenges in Implementing in HR 5.0
17.2.2 Opportunities in Implementing HR 5.0
17.3 Recommendations for Solving the Challenges Faced in HR 5.0
17.4 Conclusion
References
18. The Digital Transformation of HRM: Comparing Traditional and Technology-Based Practices
Pardeep Kaur
18.1 Introduction
18.2 Background of HRM and Related Work
18.2.1 Literature Review
18.3 Research Methodology
18.3.1 Research Objectives
18.3.2 Limitations of the Study
18.4 Data Analysis and Interpretation
Conclusion
References
19. Technological Implementation of Industry 5.0 at Kinara Capital – A People’s Welfare Organization
Kala Raja Mohan, R. Narmada Devi, Nagadevi Bala Nagaram, Sathish Kumar Kumaravel and Regan Murugesan
19.1 Introduction
19.2 Kinara Capital
19.3 HR Team Responsibility
19.3.1 Growth of the Organization
19.3.2 Employee Growth
19.3.3 Industry 5.0
19.3.4 Predix
19.4 Highlights of HR in Employee Welfare
19.4.1 Newsletter
19.4.2 Mental Wellness Stories
19.4.3 Health Tips
19.4.4 Birthday and Work Anniversary Wishes
19.4.5 Children’s Day Celebration
19.4.6 Annual Day Celebration
19.5 Kinara and Industry 5.0
19.6 Conclusion
References
Index
Back to Top
Preface
Part 1: Foundation and Strategic Framework of Human Capital Analytics in Industry 5.0
1. Human Capital Analytics in Industry 5.0: Opportunities and Challenges
Veena Grover, Manju Nandal, Divya Sahu and Mahima Dogra
Abbreviations
1.1 Introduction
1.2 Evolution of Industry 5.0
1.3 Concept and Definition of Human Capital Analytics
1.4 Features of Human Capital Analytics
1.5 Advantages and Disadvantages of Human Capital Analytics
1.6 Uses of Human Capital Analytics
1.7 How Human Capital Analytics Help in Industry 5.0?
1.8 Difference Between Industry 4.0 and Industry 5.0
1.8.1 The Pillars of Industry 4.0
1.8.2 The Pillars of Industry 5.0
1.9 Human Capital Analytics Enabled in Different Sectors
1.10 Challenges and Opportunities of Human Capital Analytics
1.10.1 Challenges of Human Capital Analytics
1.10.2 Opportunities of Human Capital Analytics
1.11 HR Analytics and Artificial Intelligence
1.12 HR Analytics and Blockchain
1.13 HR Analytics and the Internet of Things
1.14 Level of Analytics Used in Human Capital Analytics
1.15 The Shift of People Analytics
1.15.1 People Analytics
1.15.2 Why People Analytics More Effective at Driving Value
1.15.3 Example of How People Analytics Can Improve Business Value
1.16 Conclusion and Future Direction
References
2. Human Capital Analytics and Emerging Technologies in Industry 5.0
Harpreet Kaur Channi and Surinder Kaur
2.1 Introduction
2.1.1 Background and Motivation
2.2 Industry 5.0 and the Role of Human Capital
2.2.1 Evolution of Industrial Revolutions: From Industry 4.0 to Industry 5.0
2.2.2 The Significance of Human Capital in the Modern Industrial Landscape
2.2.3 Synergy Between Technology and Human Expertise in Industry 5.0
2.3 Emerging Technologies Shaping Human Capital
2.3.1 Emerging Technologies’ Revolutionary Effect on Workforce Management
2.3.2 Integrating Human and Technological Capabilities for Optimal Outcomes
2.4 Human Capital Analytics: Enhancing Workforce Management
2.4.1 Role of Data Analytics in Human Capital Management
2.4.2 Data-Driven Insights for Employee Performance and Skill Assessment
2.4.3 Predictive Analytics for Workforce Planning and Employee Retention
2.4.4 Harnessing Data to Optimize Resource Allocation and Training Strategies
2.4.5 Case Studies
2.5 Challenges and Ethical Considerations
2.5.1 Data Privacy and Security Concerns in Human Capital Analytics
2.5.2 Fairness, Bias, and Transparency in AI-Driven Workforce Management
2.5.3 Ethical Guidelines and Governance
2.5.4 Bus Automation with Human Empowerment
2.6 Recommendations for Organizations
2.6.1 Building a Data-Driven Culture
2.6.2 Developing a Comprehensive Human Capital Analytics Strategy
2.6.3 Investing in Continuous Learning and Development
2.6.4 Balancing Technology with Human-Centric Approaches
2.7 Conclusion
References
3. Fifth Industrial Revolution and an Overview of its Impact on Human Resources
Aduku Alex Akubo, Okpanachi Linus Odiji and Muhammed Bature Muhammed
3.1 Introduction
3.2 Trajectory of Industrial Revolutions
3.3 An Overview of the Fifth Industrial Revolution
3.4 The Fifth Industrial Revolution and Human Resource Management of the Organizations
3.5 Fifth Industrial Revolution: Implications of the Technological Advancements on the Workforce
3.6 The Fifth Industrial Revolution: Opportunities and Challenges
3.7 Conclusion
References
4. Human Capital Transformation - Revolutionizing HR Practices with Advanced Technologies and Ethical Insights
Vijeyata, Chitra Jha and Sunil Tegwal
4.1 Introduction
4.2 Systematic Review
4.2.1 The Industrial Revolution
4.2.2 What are the Key Technologies Driving the Development of Industry 5.0?
4.2.3 Different Industrial Revolutions’ Effects on Human Resource Functions
4.2.4 Industry 5.0 Technologies
4.2.5 A Summary of Journal Search Results
4.3 Its Impact on HR
4.3.1 How these Technologies are Transforming Industries
4.3.2 Changing Workforce Dynamics
4.3.3 Talent Acquisition and Recruitment Activities
4.3.4 Challenges in Industry 5.0 Revolution
4.3.5 Limitations of Industry 5.0
4.4 Conclusion
References
5. HR 5.0 Strategic Planning and Evolution of HR Functions in the Business Environment
M. Bharathi, K. Praveena, M. Dharani, V. Madhurima, Krithikaa Mohanarangam, G. Sandhya Kumari and Saleha Tabassum
5.1 Introduction
5.2 Evolution Cycle of HR Functions
5.2.1 Analytics for HR and HR Driven by Data
5.2.2 Digital HR and Employee Experience
5.2.3 Future of Work and Agile HR
5.3 Factors Influencing the Business Environment and its Connection to Strategic Planning
5.3.1 Economic Factors
5.3.2 Political and Legal Considerations
5.3.3 Social and Cultural Factors
5.3.4 Challenging Factors
5.3.5 Environmental Factors
5.3.6 Scientific Advances
5.4 Three Steps to Strategic Planning in HR 5.0
5.4.1 Environmental Assessment
5.4.2 Goal Setting
5.4.3 Strategic Planning
5.5 Summary and Conclusion
5.5.1 Future Perspective
References
Part 2: Analytical Techniques and Applications in Workforce Management
6. Investigating the Transformative Effects of AI, Machine Learning, and Robotics on Human Capital Analytics - An Empirical Study
Gagandeep, Jyoti Verma and Deepa Gupta
6.1 Introduction
6.1.1 Background and Significance of the Study
6.1.2 Research Problem and Research Questions
6.1.3 Objectives of the Study
6.1.4 Contribution and Value-Add of the Study
6.2 Literature Review
6.2.1 Overview of AI, Machine Learning, and Robotics in the Context of Human Capital Analytics
6.2.2 Theoretical Frameworks and Models
6.2.3 Previous Empirical Studies on the Impact of AI, Machine Learning, and Robotics on Human Capital Analytics
6.2.4 Conceptual Framework and Hypotheses
6.3 Research Design and Methodology
6.4 Data Analysis
6.4.1 Descriptive Analysis
6.4.2 Inferential Analysis
6.4.2.1 Structural Equation Modeling (SEM)
6.4.2.2 Hypothesis Testing
6.5 Practical/Managerial Implications
6.5.1 Implications of the Study for Business Practitioners and Managers
6.5.2 Recommendations for Implementing AI, Machine Learning, and Robotics in Human Capital Analytics
6.6 Limitations of the Study
6.7 Future Research
6.8 Conclusion
References
Appendices (if applicable)
7. Unleashing Human Capital Analytics for Data-Driven Workforce Management
Princi Gupta, Deepa Gupta and Mukul Gupta
7.1 Introduction
7.2 Theoretical Background
7.2.1 From Metrics to Strategy: The Evolution of Human Capital Analytics
7.2.2 Dissecting HR Analytics: Exploring Different Types and Applications
7.3 Illustrative Case Studies: Transforming HR with Data-Driven Strategies
7.4 Strategic Integration: Deploying Data Analytics and Technology Solutions in HR Operations
7.5 Optimizing Talent Acquisition Through Data-Driven Human Capital Analytics
7.6 Data-Driven Strategies for Optimal Workforce Performance in Industry 5.0
7.7 Engage and Retain: Data-Driven Success
7.8 Navigating Complexities: Challenges and Strategic Solutions in Deploying Human Capital Analytics
7.9 Emerging Technological Solutions: AI and Machine Learning in HR Optimization
7.10 Conclusion
References
8. Mastering the Art of HR Data Collection and Management Techniques
Deepa Gupta, Mukul Gupta, Priti Rai, Karishma Sharma and Parth Mukul Gupta
Introduction
Importance of HR Data in Modern Organizations
Overview of HR Data Collection and Management
Data Collection Techniques
Data Management Systems
Leveraging HR Data for Decision-Making
Future Trends
Objectives and Benefits of Mastering HR Data Techniques
Fundamentals of HR Data
Data Privacy and Compliance Considerations
Data Collection Techniques
Manual Data Collection Methods
Computerized Data Collection Strategies
Best Practices for Accurate and Reliable Data Collection
Integrating HRIS with Other Business Systems
Data Quality and Accuracy
Best Practices for Data Storing
Analyzing HR Data
Techniques for Data Examination
Using HR Data for Free Course
Using Data to Enlighten HR Game Plans and Strategies
Case Studies of Data-Driven HR Decision Making
Future Trends in HR Data Management
The Occupation of HR in the Time of Cutting-Edge Change
Assumptions for the Inevitable Destiny of HR Data Collection and Management
References
9. Communicating Human Capital Analytics Insights to Decision-Makers Effectively
Sandeep Singh Chandel, Astha Shukla, Sakshi Shukla and Shivansu Sachan
Introduction of Analytics for Human Capital Analysis
Role of Retention in Analytics for Human Capital Analysis
Analytics for Human Capital Analysis
Human Capital Analysis Analytics Framework
Factors Affecting Human Capital Analysis (HCA) Analytics
Understanding the Needs and Inclinations of Choice Makers
Human Capital Analysis Calculations
Employee Turnover
New Contract Turnover Rate
Retention Rate
Offer Acceptance Rate
Cost per Hire
Time to Productivity
Types of HR Analytics
Training and Development Work Metrics
Conclusion
References
10. Predictive Analytics - Next Chapter in Talent Management
Swati Rai, Rakesh Kumar Yadav and Rajesh Kumar Dhanaraj
10.1 Introduction
10.1.1 Role of Predictive Analytics in Talent Management
10.1.1.1 Recruitment and Selection
10.1.1.2 Candidate Assessment
10.1.1.3 Retention and Employee Engagement
10.1.1.4 Succession Planning
10.1.1.5 Performance Management
10.1.1.6 Human Resource Planning
10.1.1.7 Learning and Development
10.1.1.8 Continuous Feedback and Improvement
10.2 Predictive Analysis - A Game Changer
10.3 Challenges in Predictive Analytics
10.3.1 Quality and Availability of Data
10.3.2 Privacy and Security of Data
10.3.3 Complexity of Models
10.3.4 Overfitting and Underfitting
10.3.5 Lack of Domain Expertise
10.3.6 Scalability Issues
10.3.7 Changing Data Patterns
10.3.8 Interpretable Models
Conclusion
References
11. Employee Engagement and Performance Management - Critical Role of Employee Potentials
Asma Bano and Ayesha Khatun
11.1 Introduction
11.1.1 Human Resource Analytics (HR Analytics)
11.2 Literature Review and Theoretical Concepts of the Study
11.2.1 Literature Review on Theoretical Concepts of Employee Potential
11.2.1.1 Factors of Employee Potential
11.2.1.2 Ways to Unlock the Employee Potential
11.2.2 Literature Review on Theoretical Concepts of Employee Engagement
11.2.2.1 Definitions of Employee Engagement
11.2.2.2 Factors of Employee Engagement
11.2.2.3 Methods of Attaining Employee Engagement
11.2.2.4 Outcomes of Employee Engagement
11.2.3 Literature Review on Theoretical Concepts of Organizational Performance
11.2.3.1 Factors of Organizational Performance
11.2.3.2 Steps to Achieve Organizational Performance
11.2.3.3 Outcomes of Organizational Performance
11.3 Conceptual Framework
11.3.1 Employee Potential
11.3.2 Employee Engagement
11.3.3 Organizational Performance
11.4 Research Objectives
11.5 Research Methodology
11.5.1 Research Method and Design
11.6 Findings and Discussions
11.7 Practical Implications
11.8 Limitations and Future Directions
11.9 Conclusions
References
12. Performance Evaluation and Measurement of Human Capital Analytics in the Information Technology (IT) Sector in India
Manoj Kumar, Pratibha Maurya and Rinki Verma
12.1 Introduction
12.2 Literature Review
12.2.1 Need for Evaluation of Human Capital
12.3 Objective of the Study
12.4 Methodology Adopted
12.4.1 Human Capital Return on Investment (HCROI)
12.4.2 Human Capital Value Added (HCVA)
12.4.3 Human Economic Value Added (HEVA)
12.5 Data Analysis
12.5.1 Objective 1
12.5.2 Objective 2
12.5.3 Objective 3
12.6 Discussion
12.7 Conclusion
12.8 Implications
References
13. Data-Driven Strategies to Improve Workplace Diversity, Equality and Inclusion (DEI)
Arkja Singh, Rakesh Kumar Yadav and Deepa Gupta
13.1 Introduction
13.1.1 Data-Driven Strategies in Workplace
13.1.1.1 Demographic Analysis
13.1.1.2 Sentiment Analysis
13.1.1.3 Network Analysis
13.1.2 DEI Initiatives within the Workplace
13.2 The Coalesce
13.2.1 Data-Driven Strategies and DEI
13.3 The Contraption
13.3.1 Data-Driven Mindset among the HR and Technology Leaders
13.3.1.1 Diversity
13.3.1.2 Equality
13.3.1.3 Inclusion
13.3.2 DEI Software
13.4 Challenges and Deliberations
13.4.1 Data Precision
13.4.2 Data Confidentiality
13.4.3 Steer Clear of Tokenism
13.4.4 Persistent Loyalty
13.5 Conclusion
13.5.1 Attracting Apex Talent
13.5.2 Driving Employee Retention and Loyalty
13.5.3 Nurturing Belonging and Inclusion
13.5.4 Identifying Gaps in Employee Representation
13.5.5 Tracking Progress Alongside Representation Goals
13.5.6 Furnishing Teams for Victory
13.5.7 Gaining an All-Inclusive View of DEI Experience
References
Part 3: Future Trends, Challenges, and Sustainable Development in HR Practices
14. Role of Human Capital Analytics and Industry 5.0 in Advancing the United Nations’ Sustainable Development Goals
Agagu A. A., Odiji O. L. and Akubo A. A.
14.1 Introduction
14.2 Review of Extant Literature
14.3 Conceptual Clarification
14.3.1 Human Capital Analytics
14.3.2 Fifth Industrial Revolution
14.4 The UN SDGs
14.4.1 Nexuses Between HCA, Industry 5.0, and the SDGs
14.5 Inherent and Emerging Challenges
14.5.1 Measures to Address the Challenges which Bedevils HCA and Industry 5.0 from Advancing UN SDGs
14.6 Concluding Remarks
References
15. Transforming Workplaces with Human-Robot Collaboration
B. Swathi
15.1 Introduction
15.2 Sustainability and Industry 5.0
15.2.1 Human-Robot Co-Working (HRC)
15.2.2 Literature Review
15.2.3 Objectives and Methodology
15.3 Industry 5.0, Human Resources, and Robots
15.3.1 Human and Robot Interaction
15.3.2 Industry 5.0 - Advantages
15.3.3 Concerns in Industry 5.0
15.4 Conclusion
References
16. Human Capital Analytics in Industry 5.0 for Sustainable Growth
Channi Sachdeva, Veena Grover and Veer P. Gangwar
16.1 Introduction of SDGs and the Role of Humans in Organization
16.2 Human Capital Analytics: Concepts and Applications
16.3 Literature Review
16.4 Integrating SDGs with Human Capital Strategies
16.5 Utilizing Data Analysis for Managing Talent and Development
16.6 Industry 5.0 Principles for Sustainable Value Creation
16.7 Challenges and Opportunities for Promoting Sustainable Development via Insights and Industry 5.0
16.8 Future Directions
References
17. HR 5.0 – Demystifying the Way Forward
Ritu Saxena, Priyanshi Jindal and Harshit Gouri
17.1 Introduction
17.2 Literature Review
17.2.1 Challenges in Implementing in HR 5.0
17.2.2 Opportunities in Implementing HR 5.0
17.3 Recommendations for Solving the Challenges Faced in HR 5.0
17.4 Conclusion
References
18. The Digital Transformation of HRM: Comparing Traditional and Technology-Based Practices
Pardeep Kaur
18.1 Introduction
18.2 Background of HRM and Related Work
18.2.1 Literature Review
18.3 Research Methodology
18.3.1 Research Objectives
18.3.2 Limitations of the Study
18.4 Data Analysis and Interpretation
Conclusion
References
19. Technological Implementation of Industry 5.0 at Kinara Capital – A People’s Welfare Organization
Kala Raja Mohan, R. Narmada Devi, Nagadevi Bala Nagaram, Sathish Kumar Kumaravel and Regan Murugesan
19.1 Introduction
19.2 Kinara Capital
19.3 HR Team Responsibility
19.3.1 Growth of the Organization
19.3.2 Employee Growth
19.3.3 Industry 5.0
19.3.4 Predix
19.4 Highlights of HR in Employee Welfare
19.4.1 Newsletter
19.4.2 Mental Wellness Stories
19.4.3 Health Tips
19.4.4 Birthday and Work Anniversary Wishes
19.4.5 Children’s Day Celebration
19.4.6 Annual Day Celebration
19.5 Kinara and Industry 5.0
19.6 Conclusion
References
Index
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