Introduction
• HR hasevolved from administrative to
strategic role.
• HR Analytics enables evidence-based
decisions using workforce data.
3.
Definition of HRAnalytics
• Application of data analysis techniques to HR
data to improve decisions.
• Also known as People Analytics or Workforce
Analytics.
• Example: Predicting employee attrition to
design retention programs.
4.
Scope of HRAnalytics
• Covers all HR functions:
• - Recruitment & Selection
• - Training & Development
• - Performance Management
• - Employee Engagement
• - Compensation & Benefits
• - Workforce Planning
5.
HR Analytics Process
•1. Data Collection
• 2. Data Cleaning & Integration
• 3. Data Analysis
• 4. Insight Generation
• 5. Decision Making
• 6. Monitoring & Refinement
Case Study: Google’sPeople Analytics
• Google studied employee attrition trends.
• Project Oxygen identified lack of managerial
support.
• Introduced leadership training.
• Result: Higher satisfaction, lower attrition.
8.
Levels of HRAnalytics
• 1. Descriptive – What happened?
• 2. Diagnostic – Why did it happen?
• 3. Predictive – What will happen?
• 4. Prescriptive – What should we do?
• Example: Attrition analysis and retention
strategies.
9.
Conclusion
• HR Analytics= Data + Insights + Action →
Success
• • Moves HR from intuition to evidence.
• • Aligns workforce strategies with business
goals.
• • Essential for modern, competitive
organizations.
10.
Diagram: HR AnalyticsProcess Cycle
1. Data Collection
3. Data Analysis
4. Insight Generation
5. Decision Making
6. Monitoring
2. Data Cleaning
11.
Diagram: Gartner’s AnalyticsMaturity Model/
Levels of HR Analytics Pyramid
Prescriptive – What should we
do?
Predictive – What will happen?
Diagnostic – Why did it happen?
Descriptive – What happened?