Chapter 1. Analytics Introduction

• Evolution of HR Analytics & People Analytics: From Reporting to Predictive
• Data Management and Types
• Descriptive, Diagnostic, Predictive & Prescriptive Analytics Framework
• Problem Solving and Decision Making
• HR Analytics Maturity Model (Levels 1–4: Operational Reporting → Predictive)
• Business Case for HR Analytics: ROI and Stakeholder Buy-in
• HRIS & HR Tech Ecosystem Overview (SAP SuccessFactors, Workday, Darwinbox)

Chapter 2. Using Spreadsheets for Analytics

• Excel Formulas
• Excel Functions
• Excel Add-Ins for Analytics: Power Query, Analysis ToolPak, Solver
• What is Spreadsheet Modeling
• Key HR Functions in Excel: VLOOKUP/XLOOKUP, COUNTIFS, AVERAGEIFS, IFERROR
• Introduction to Power BI / Tableau for HR Dashboards
• Introduction to Python / R for HR Analytics (optional/advanced track)

Chapter 3. Visualizing Data in Spreadsheets

• Excel Data Visualization Tools
• Data Queries in Excel
• Data Summarization in Excel
• PivotTables and Pivot Charts
• HR-Specific Chart Types: Headcount Waterfall, Attrition Funnel, Tenure Histogram
• Data Storytelling: Designing Insights for HR Leadership & Board Presentations

Chapter 4. Descriptive Statistical Measures

• Measures of Location (Mean, Median, Mode)
• Measures of Dispersion (Variance, Std Dev, Range)
• Skewness/Kurtosis overly theoretical for target audience; remove or make supplementary
• Measures of Association (Correlation)
• Frequency Distributions
• Excel Descriptive Statistics Tools
• Applying Descriptive Stats to HR Data: Salary Bands, Age/Tenure Distribution

Chapter 5. Probability Distributions

Probability Basics

Discrete Probability Distributions (e.g., modelling offer acceptance rates, headcount scenarios)

Continuous Probability Distributions (e.g., time-to-fill, performance score distributions

Distribution Fitting

Chapter 6. Sampling and Estimation

• Sampling Methods
• Sampling Distributions
• Estimation & Confidence Intervals
• Employee Survey Sampling: Sample Size Calculation for Engagement Surveys

Chapter 7. Statistical Inference

• Hypothesis Testing
• One-Sample Hypothesis Tests
• Two-Sample Hypothesis Tests
• ANOVA
• Chi-Square Tests for HR: Testing Pay Equity, Promotion Parity by Gender/Grade
• A/B Testing in HR: Pilot Programs, Recruitment Campaign Testing

Chapter 8. Regression Analysis

• Simple Linear Regression
• Residual Analysis and Regression Assumptions
• Multiple Linear Regression
• Regression with Categorical Independent Variables
• Nonlinear & Logistic Regression
• Regression for HR: Predicting Salary, Performance Scores, Time-to-Fill
• Multicollinearity, Overfitting & Model Validation in HR Contexts

Chapter 9. HR Management

• Functions of Human Resource Management
• Strategic HRM: Aligning People Strategy with Business Goals
• Strategic Planning and Human Resource Practices
• HR Operating Models: HR Business Partner, Centre of Excellence, Shared Services

Chapter 10. HR Analytics

• HR Analytics Basics
• Talent Life Cycle
• HR Metrics (Time-to-Fill, Cost-per-Hire, Turnover Rate, Absenteeism Rate, Revenue-per-Employee, eNPS, Offer Acceptance Rate)
• HR Data Collection (HRIS data, survey tools (Qualtrics, Culture Amp), ATS data, payroll data, LMS data
• HR Data Analysis (a) Workforce Segmentation Analysis and (b) Trend & Cohort Analysis
• Data Quality in HR: Missing Data, Inconsistent Records, Master Data Governance
• Workforce Planning Analytics: Headcount Forecasting, Supply-Demand Modelling

Chapter 11. Recruitment and Talent Management Analytics

• Recruitment and Talent Acquisition
• Workforce Capability
• Job Analysis and Design
• Compensation Management
• Performance Appraisal, Planning and Execution
• Rewards and Recognition
• Attrition & Churn Analysis: Voluntary vs Involuntary, Regrettable vs Non-Regrettable
• Talent Development
• Career Progression
• Employee Retention
• Employee Engagement
• Recruitment Funnel Analytics: Source of Hire, Conversion Rates, Pipeline Health
• Predictive Attrition Modelling: Flight Risk Scoring
• Compensation Benchmarking & Pay Equity Analysis
• 9-Box Grid & Succession Planning Analytics

Chapter 12. Learning, Training and Development Analytics

• L&D Landscape: Instructor-Led, e-Learning, Blended & On-the-Job Learning
• Introduction to Learning and Development
• Models of Evaluation (Kirkpatrick Model (all 4 levels), Phillips ROI Model, Net Promoter Score for Training)
• LMS Data Analytics: Completion Rates, Assessment Scores, Learning Hours per Employee
• Linking L&D Investment to Business Outcomes (Skills Gap → Performance → Revenue)
• Skills Analytics & Competency Mapping

Chapter 13. Advanced HR Analytics

• KPI and HR KPI Dashboards
• Talent Analytics Maturity
• HR Cost Benefit Analysis
• Social Media & Talent Intelligence (LinkedIn Data, Employer Brand Analytics, Glassdoor Insights)
• HR Balanced Scorecard
• Attrition Prediction
• Machine Learning in HR: Classification Models (Random Forest, Logistic) for Attrition
• Natural Language Processing (NLP) for HR: Sentiment Analysis of Exit Interviews & Surveys
• Organisational Network Analysis (ONA): Collaboration Patterns & Influence Mapping
• AI-Powered HR Tools: Chatbots, Resume Screening, Predictive Scheduling

Chapter 14. DEI Analytics (New Section)

• Diversity, Equity & Inclusion (DEI) Metrics: Representation, Pay Gap, Promotion Parity
• Measuring Inclusion: Belonging Index, Psychological Safety Scores
• Bias Detection in Hiring & Performance Data
• Reporting DEI Progress: Dashboard Design & Stakeholder Communication

Chapter 15. HR Data Ethics, Privacy & Compliance (New Section)

• Data Privacy in HR: GDPR, India's DPDP Act 2023, Employee Consent
• Ethical Use of People Analytics: Surveillance vs Insight
• Algorithmic Bias in HR AI Tools: Detection & Mitigation
• HR Audit & Compliance Analytics: Labour Law Reporting, Statutory Compliance Tracking

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