People Analytics in HR Course

Lesson 1 • Ethical Principles in HR Analytics

Introduces fairness, transparency, and consent as non-negotiable foundations. Establishes the ethical lens applied throughout all subsequent chapters.

Lesson 2 • Defining People Analytics

Clarifies the distinction between HR metrics, reporting, and true analytics. Sets the conceptual baseline for the entire course.

Lesson 3 • Business Case for Workforce Data

Connects people analytics to organizational strategy and financial outcomes. Demonstrates how data-driven HR decisions create measurable value.

Lesson 1 • Core HR Systems Overview

Surveys HRIS, ATS, LMS, and payroll platforms as primary data sources. Grounds learners in the systems they will extract and integrate data from.

Lesson 2 • Data Governance and Documentation

Establishes policies for data ownership, access control, and metadata management. Governance prevents data misuse and ensures reproducibility of analyses.

Lesson 3 • Data Integration and Pipelines

Explains how data moves from source systems into analytics environments. Covers ETL concepts and common integration challenges in HR contexts.

Lesson 4 • Employee Surveys and Listening Tools

Covers pulse surveys, engagement platforms, and sentiment tools as supplementary data sources. Connects qualitative signals to quantitative workforce metrics.

Lesson 1 • Descriptive Statistics for Workforce Data

Covers central tendency, dispersion, and distribution shape using HR examples. Provides the vocabulary for summarizing any workforce metric accurately.

Lesson 2 • Hypothesis Testing in HR Contexts

Applies t-tests, chi-square, and ANOVA to common HR questions such as pay equity. Learners distinguish statistically significant findings from random variation.

Lesson 3 • Correlation and Regression Basics

Explains relationships between variables and introduces simple linear regression. Builds the foundation for predictive modeling covered in later chapters.

Lesson 4 • Avoiding Common Statistical Errors

Identifies pitfalls such as confounding variables, multiple comparisons, and base-rate neglect. Protects analytical credibility by teaching rigorous interpretation habits.

Lesson 1 • Turnover and Retention Analysis

Calculates voluntary, involuntary, and regrettable turnover rates with industry benchmarks. Retention analysis identifies flight-risk patterns before attrition occurs.

Lesson 2 • Recruitment and Time-to-Fill Metrics

Measures sourcing efficiency, offer acceptance, and quality of hire across the talent pipeline. Links recruiting metrics to downstream performance and retention outcomes.

Lesson 3 • Workforce Composition Metrics

Covers headcount, span of control, and demographic breakdowns as baseline measures. These metrics form the denominator for most downstream HR calculations.

Lesson 4 • Engagement and Productivity Indicators

Quantifies employee engagement scores, absenteeism, and output-based productivity measures. Connects people sentiment data to operational performance metrics.

Lesson 1 • Bias Detection in Hiring Processes

Uses adverse impact analysis and pass-rate comparisons to surface demographic disparities. Equips analysts to flag and remediate bias before it becomes a legal or ethical issue.

Lesson 2 • Sourcing Channel Effectiveness

Compares cost, volume, and quality metrics across job boards, referrals, and agencies. Data-driven sourcing allocation reduces cost-per-hire significantly.

Lesson 3 • Onboarding Analytics and Early Attrition

Tracks new-hire milestones, ramp time, and 90-day attrition to evaluate onboarding effectiveness. Early attrition data feeds back into sourcing and selection improvements.

Lesson 4 • Predictive Hiring Models

Introduces regression and classification models that predict candidate success and retention. Learners evaluate model fairness alongside predictive accuracy.

Lesson 1 • Drivers of Employee Engagement

Identifies key engagement drivers through factor analysis and regression on survey data. Prioritizes which levers HR should pull to maximize engagement ROI.

Lesson 2 • Stay and Exit Interview Analytics

Structures and analyzes stay and exit interview data to surface systemic retention issues. Qualitative themes are quantified and linked to turnover patterns.

Lesson 3 • Flight Risk Modeling

Builds predictive models using tenure, performance, and engagement signals to score attrition risk. Enables proactive retention conversations before employees decide to leave.

Lesson 4 • Measuring Retention Program ROI

Calculates the financial return of retention initiatives by comparing intervention costs to turnover savings. Provides the business case language needed for executive approval.

Lesson 1 • Demand Forecasting Techniques

Applies time-series analysis and regression to project headcount needs by role and function. Covers both top-down and bottom-up forecasting approaches.

Lesson 2 • Skills Gap and Capability Analysis

Maps current workforce skills against future capability requirements to identify critical gaps. Informs build, buy, borrow, and automate decisions for talent strategy.

Lesson 3 • Supply Analysis and Internal Mobility

Models the internal talent pipeline using movement, promotion, and attrition rates. Identifies gaps between current supply and projected future demand.

Lesson 4 • Communicating Workforce Plans

Translates complex workforce models into executive-ready narratives and financial projections. Covers scenario storytelling, risk framing, and investment recommendations.

Lesson 1 • Linking People Data to Business Outcomes

Builds integrated models connecting HR metrics to revenue, customer satisfaction, and innovation. Demonstrates the financial value of people analytics to the C-suite.

Lesson 2 • Organizational Network Analysis

Uses network graphs to map collaboration, influence, and information flow across teams. Reveals hidden organizational dynamics invisible in traditional HR data.

Lesson 3 • Causal Inference for HR Decisions

Introduces difference-in-differences, propensity scoring, and natural experiments for HR. Moves beyond correlation to establish causal evidence for HR program effectiveness.

Lesson 4 • Building an Analytics-Driven HR Culture

Develops the organizational capabilities, processes, and mindsets needed to sustain analytics adoption. Covers change management, capability building, and center-of-excellence models.