What is HR Analytics? All You Need to Know to Get Started

HR analytics allows HR professionals to make informed decisions to benefit employees and support organizational goals, significantly impacting organizational performance.

Contents

• What is HR analytics?
• What is HR analytics used for?
• Importance of HR analytics
• HR analytics examples
• Key HR metrics
• Data analytics in HR: How to get started
• How to transition from descriptive to predictive and prescriptive analytics in HR
• HR analytics certification
• FAQ

What is HR Analytics?

• Referred to as people analytics or workforce analytics
• Involves gathering, analyzing, and reporting HR data to drive business results
• Helps in understanding workforce and making data-driven decisions
• Difference between HR and people analytics: HR analytics focuses on HR functions; people analytics includes data from other sources
• Shift from operational to strategic HR management

Types of HR Analytics

• Descriptive HR Analytics: Examines historical data (e.g., employee turnover rate).
• Diagnostic HR Analytics: Investigates causes of past events (e.g., drivers of absenteeism).
• Predictive HR Analytics: Predicts future behaviors and events (e.g., ideal candidate attributes).
• Prescriptive HR Analytics: Proposes recommendations for future scenarios (e.g., onboarding needs).

What is HR Analytics Used For?

• Improves HR functions by identifying patterns in turnover, recruitment, talent management, etc.
• Optimizes compensation and predicts future workforce needs

Importance of HR Analytics

• Expands HR’s role to a strategic partner in organizations
• Uses data to enhance decision-making, improve productivity, and reduce costs
• Evaluates effectiveness of HR interventions
• Supports DEIB efforts and navigates change and uncertainty

HR Analytics Examples

1. Google: Used predictive analytics in recruitment to reduce interview rounds and source candidates.
2. Under Armour: Reduced attrition by identifying attrition drivers and improving retention efforts.
3. E.ON: Addressed absenteeism by encouraging vacation time usage.

Key HR Metrics

• Employee Turnover: Percentage of employees leaving the organization.
• Absenteeism Rate: Habitual non-presence of employees.
• Revenue per Employee: Reflects organization’s efficiency.
• eNPS (Employee Net Promoter Score): Employee loyalty and satisfaction.
• Cost per Hire: Cost to recruit an employee.

Data Analytics in HR: How to Get Started

1. Ask a Relevant Business Question: Start with end goal in mind
2. Data Selection: Identify necessary information and sources
3. Data Cleaning: Remove duplicates and errors
4. Data Analysis: Summarize data to reveal trends
5. Actionable Insights: Interpret data for actionable decisions

Transitioning to Advanced Analytics

• Move beyond descriptive analytics to predictive and prescriptive analytics
• Develop analytical capabilities and invest in data infrastructure
• Use pilot projects and establish a data-driven culture

HR Analytics Certification

• Valuable for expanding career opportunities
• AIHR’s People Analytics Certificate Program offers skills and experience for leveraging HR data
• Online, self-paced course with case studies and community access

FAQ

• 4 Types of HR Analytics: Descriptive, diagnostic, predictive, prescriptive
• HRIS vs. HR Analytics: HRIS gathers data; analytics examines it
• HR Analyst Role: Collects, analyzes, and reports HR data
• Skills for HR Analytics: Business consulting, analytical skills, stakeholder management, storytelling

Erik van Vulpen

• Founder and Dean of AIHR, expert in modern HR practices and technological innovations

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