Data Analytics for HR

Data Analytics and Business Intelligence October 25, 2025
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Introduction

This essential course empowers HR professionals to move beyond anecdotal evidence and leverage data analytics for strategic talent and workforce decisions. Participants will learn how to collect, clean, and analyze HR data points related to recruitment, engagement, retention, and performance. We focus on calculating key metrics, building predictive models for turnover, and using visualization to tell compelling stories about the workforce. This program transforms the HR function into a strategic, data-driven partner that can directly influence organizational profitability and culture.

Objectives

Upon completion of this course, participants will be able to:

  • Identify, calculate, and benchmark essential HR metrics, including turnover rate, time-to-hire, and cost-per-hire.
  • Design effective data collection strategies across various HRIS and survey platforms.
  • Conduct comprehensive workforce analysis, including demographic, salary, and diversity reporting.
  • Build predictive models (e.g., using regression) to forecast voluntary employee turnover and attrition risks.
  • Analyze the effectiveness and ROI of training and development programs.
  • Use data visualization tools (e.g., Tableau, Power BI) to present actionable insights on talent gaps and flight risks.
  • Understand ethical and legal considerations when handling sensitive employee data.
  • Translate analytical findings into strategic HR interventions and policy recommendations.

Target Audience

  • HR Business Partners (HRBPs)
  • Talent Acquisition and Recruiting Specialists
  • Compensation and Benefits Analysts
  • Learning and Development (L&D) Managers
  • Workforce Planning Specialists
  • Senior HR Leadership and Directors

Methodology

The methodology centers on analyzing real-world HR datasets. **Case studies** involve examining anonymized employee engagement survey results to identify cultural drivers of turnover in a large tech firm. **Group activities** focus on designing a dashboard to track the ROI of a new talent acquisition strategy. **Individual exercises** guide participants through using statistical tools (e.g., Excel, Python libraries) to run regression analysis on salary data to detect potential pay inequities. **Scenarios** involve presenting complex turnover data to an executive team, requiring participants to practice data storytelling and policy formulation during **syndicate discussions**.

Personal Impact

  • Elevate role from operational execution to strategic workforce planning and policy influence.
  • Gain credibility with leadership by presenting data-backed insights, not just intuition.
  • Acquire technical skills in predictive modeling and advanced reporting tools.
  • Improve decision-making confidence in high-stakes areas like compensation and performance management.
  • Develop a nuanced understanding of employee data ethics and privacy laws.

Organizational Impact

  • Reduce high-cost voluntary turnover by accurately predicting and intervening with at-risk employees.
  • Optimize recruitment spending by identifying the most effective and high-quality talent channels.
  • Improve employee engagement and productivity by scientifically measuring program effectiveness.
  • Ensure compliance and mitigate legal risk through data-driven diversity and compensation analyses.
  • Position HR as a true strategic partner contributing directly to organizational profitability.

Course Outline

UNIT 1: Fundamentals of People Analytics

Metrics and Data Sources
  • Defining HR Analytics vs. HR Reporting and Business Intelligence
  • Identifying the Core HR Data Domains (Talent, Compensation, Performance)
  • Key HR Metrics: Calculation and Benchmarking Standards
  • Structuring Data from HRIS, Performance Management, and Survey Systems
  • Data Cleaning, Transformation, and Data Quality Checks

UNIT 2: Recruitment and Talent Acquisition Analytics

Optimizing the Hiring Funnel
  • Analyzing the Full Recruitment Funnel (Source to Offer Acceptance)
  • Calculating Cost-Per-Hire (CPH) and Time-to-Hire (TTH) Efficiency
  • Evaluating Sourcing Channel Effectiveness and Quality of Hire
  • Predicting Candidate Success using Pre-Hire Data

UNIT 3: Retention and Engagement Modeling

Forecasting Attrition Risk
  • In-depth analysis of Employee Turnover and Flight Risk Factors
  • Building Predictive Attrition Models using Regression and Survival Analysis
  • Analyzing Survey Data and Text Responses for Engagement Drivers
  • Identifying Key Demographics and Segments for Targeted Retention Efforts
  • Measuring the Financial Cost of Employee Turnover

UNIT 4: Performance and Development Analytics

Measuring HR Program ROI
  • Analyzing the correlation between Learning & Development (L&D) spend and performance
  • Using Performance Data to Identify High and Low Performers and Skill Gaps
  • Analyzing Compensation and Equity Gaps (e.g., Gender/Diversity Pay Analysis)
  • Measuring the effectiveness and utilization of HR programs and tools

UNIT 5: Ethics, Storytelling, and Strategy

Communicating Impact
  • Data Ethics, Employee Privacy, and Legal Compliance (GDPR, CCPA)
  • Techniques for Data Storytelling and Visualizing Workforce Insights
  • Designing Executive Dashboards for HR Directors and the Board
  • Translating Analytical Findings into Actionable HR Policy Changes
  • Building an Analytics Roadmap for the HR Function

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