HR Analytics syllabus

1: Introduction to HR Analytics

• Understanding HR Analytics: Definition, Scope, and Importance
• Evolution of HR Analytics: Historical Perspective
• HR Metrics vs. HR Analytics: Differentiating Concepts
• Benefits and Challenges of HR Analytics Implementation
• HR Analytics in Contemporary Business Environment

2: Data Collection and Management

• Sources of HR Data: Internal and External
• Data Collection Methods: Surveys, Interviews, Observations
• Data Quality Management: Ensuring Accuracy and Reliability
• Data Privacy and Ethics in HR Analytics
• Tools and Technologies for HR Data Management

3: Statistical Foundations for HR Analytics

• Descriptive Statistics: Measures of Central Tendency and Dispersion
• Inferential Statistics: Hypothesis Testing, Correlation, Regression
• Probability Distributions: Normal, Binomial, Poisson
• Sampling Techniques in HR Analytics
• Data Visualization Techniques

4: Predictive Modeling in HR Analytics

• Introduction to Predictive Analytics
• Regression Analysis for HR Predictions
• Classification Techniques: Decision Trees, Random Forests, SVM
• Time Series Analysis for HR Forecasting
• Model Evaluation and Validation

5: Employee Attrition and Retention Analytics

• Understanding Employee Attrition
• Predictive Models for Attrition Risk Assessment
• Factors Influencing Employee Retention
• Retention Strategies Based on Analytics Insights
• Case Studies on Attrition and Retention Analytics

6: Talent Acquisition Analytics

• Recruitment Metrics: Time-to-Hire, Cost-per-Hire, Quality-of-Hire
• Predictive Modeling for Candidate Sourcing and Selection
• Applicant Tracking Systems (ATS) and HR Analytics Integration
• Recruitment Channel Analysis
• Optimization Strategies for Talent Acquisition

7: Performance Management Analytics

• Performance Metrics: KPIs, Balanced Scorecard
• Predictive Analytics for Performance Improvement
• Performance Appraisal Data Analysis
• Identifying High Performers and Low Performers
• Feedback and Development Strategies

8: Employee Engagement and Satisfaction Analytics

• Measuring Employee Engagement: Surveys, Feedback Mechanisms
• Factors Affecting Employee Satisfaction
• Sentiment Analysis and Text Mining for Employee Feedback
• Action Planning Based on Engagement Analytics
• ROI of Employee Engagement Initiatives

9: Diversity and Inclusion Analytics

• Importance of Diversity and Inclusion in the Workplace
• Metrics for Diversity Measurement
• Analyzing Bias and Discrimination through HR Data
• Inclusive Hiring Practices
• Case Studies on Diversity and Inclusion Analytics

10: HR Analytics Implementation and Case Studies

• Developing an HR Analytics Strategy
• Overcoming Challenges in HR Analytics Implementation
• Change Management in HR Analytics Adoption
• Case Studies: Successful Implementations in Various Industries
• Future Trends in HR Analytics

11: Hands-on Workshops and Projects

• Data Preparation and Cleaning
• Exploratory Data Analysis (EDA)
• Predictive Modeling Exercises
• Interpretation of Analytics Results
• Project Presentation and Feedback

12: Advanced Statistical Techniques

• Multivariate Analysis: Regression Analysis, Logistic Regression
• Time Series Analysis
• Survival Analysis
• Cluster Analysis
• Factor Analysis
• Discriminant Analysis
• ANOVA and MANOVA

13: Data Visualization and Interpretation

• Advanced Data Visualization Techniques using tools like Tableau, Power BI, or Python libraries (Matplotlib, Seaborn)
• Dashboard Design and Interactive Reporting
• Storytelling with Data
• Visualizing Complex HR Metrics and KPIs

14: Predictive Modeling in HR

• Introduction to Predictive Modeling
• Predictive Modeling Techniques: Decision Trees, Random Forest, Gradient Boosting Machines
• Model Evaluation and Validation
• Feature Engineering and Selection
• Predictive Models for Attrition, Performance, and Talent

15: Strategic HR Analytics

• Linking HR Analytics to Business Strategy
• HR Analytics for Organizational Development
• Strategic Workforce Planning
• HR Scorecard and Key Performance Indicators (KPIs)
• Ethics and Privacy in HR Analytics

16: Advanced Tools and Techniques

• Natural Language Processing (NLP) for HR Analytics
• Sentiment Analysis of Employee Feedback
• Text Mining and Text Analytics
• Social Network Analysis
• Advanced Machine Learning Techniques for HR

17: Case Studies and Practical Applications

• Real-world Case Studies in HR Analytics
• Hands-on Projects using HR Data
• Practical Application of Analytics in Recruitment, Training, Performance Management, and Employee Engagement
• Presentations and Discussions on Analytical Insights

18: Emerging Trends in HR Analytics

• AI and Machine Learning in HR
• Predictive Analytics for Employee Well-being
• Augmented Analytics
• Continuous Monitoring and Feedback Systems
• Future Directions and Innovations in HR Analytics