Human Resource Metrics and Workforce Analytics Training Course

This course equips participants with practical skills to measure, analyze, and report on workforce performance and HR effectiveness. It focuses on HR metrics, data management, descriptive and predictive analytics, dashboards, and using insights to drive talent decisions.

Target Groups

• HR managers and business partners
• HR analysts and information system officers
• Talent and workforce planning specialists
• Finance and operations managers
• Senior executives
• Recruitment and learning professionals
• Managers and supervisors seeking to strengthen organizational practice in this field
• Consultants and professionals supporting related organizations

Course Objectives

By the end of this course, participants will be able to:

• Explain the value of HR metrics and workforce analytics
• Select metrics aligned with business strategy
• Collect and prepare HR data
• Calculate key metrics for turnover, engagement, and productivity
• Analyze recruitment, learning, and performance data
• Apply statistical methods to HR questions
• Introduce predictive analytics for attrition and performance
• Build HR dashboards and reports
• Communicate insights to leadership
• Manage HR data privacy and ethics

Course Modules

Module 1: Introduction to HR Metrics and Analytics

• Levels of HR analytics
• Metrics versus analytics
• Linking HR to business outcomes
• Analytics maturity
• Roles and skills

Module 2: Designing an HR Measurement Framework

• Strategic alignment
• Balanced HR scorecard
• Metric selection
• Data sources
• Setting targets

Module 3: HR Data Management and Quality

• Data collection from HRIS
• Cleaning and integrating data
• Data definitions
• Data governance
• Common data issues

Module 4: Core Workforce Metrics

• Headcount and turnover
• Absenteeism
• Cost per hire and time to fill
• Training and productivity metrics
• Compensation metrics

Module 5: Employee Engagement, Retention, and Diversity Analytics

• Engagement survey analysis
• Retention drivers
• Exit data analysis
• Diversity and inclusion metrics
• Pay equity analysis

Module 6: Talent Acquisition and Performance Analytics

• Recruitment funnel analysis
• Source effectiveness
• Performance distribution
• Learning impact
• Succession metrics

Module 7: Statistical Methods for HR

• Descriptive statistics
• Correlation and regression
• Hypothesis testing
• Segmentation
• Interpreting results

Module 8: Predictive Workforce Analytics

• Attrition prediction
• Workforce planning models
• Predictive modeling concepts
• Evaluating predictions
• Ethical limits

Module 9: Dashboards, Storytelling, and Ethics

• HR dashboard design
• Data visualization
• Communicating insights
• Privacy and consent
• Bias and fairness

Module 10: Practical Exercises and Capstone Project

• Calculating core HR metrics from sample data
• Analyzing turnover and engagement
• Building an HR dashboard
• Developing a predictive attrition outline
• Presenting workforce insights to a mock executive team