Unit 1: Introduction to HR Analytic

Introduction to HR Analytics

HR Analytics is the process of collecting and analyzing data related to Human Resources (HR) to make better business decisions.

It helps the HR department to:

• Understand employee behavior
• Improve hiring decisions
• Reduce employee turnover
• Increase employee productivity

 Simple Definition: HR Analytics means using data and numbers to make smarter HR decisions.

Why is HR Analytics Important?

• Helps in hiring the right people
• Finds out why employees are leaving
• Improves training and development
• Predicts future HR trends
• Aligns HR strategy with business goals

Evolution of HR Analytics

Stage	Name	Explanation
1️⃣	HR Reporting	Just keeping records (attendance, salaries, leaves). No analysis.
2️⃣	HR Metrics	Using numbers to track HR activities (e.g., how many joined/left).
3️⃣	Advanced Analytics	Start analyzing “Why” things happen (e.g., Why are employees leaving?).
4️⃣	Predictive Analytics	Use data to predict future HR trends (e.g., Who might leave next?).
5️⃣	Prescriptive Analytics	Suggest best solutions based on predictions (e.g., How to retain top talent?).

Example for Better Understanding

Imagine you are the HR of a company:

• You see many employees leaving → HR Metrics
• You ask why they are leaving → Advanced Analytics
• You find they leave due to poor managers → Predictive Analytics
• You suggest management training for managers → Prescriptive Analytics

Conclusion (Exam-Oriented Point)

HR Analytics is a powerful tool that helps HR departments make data-driven decisions. Over time, it has evolved from simple reporting to predicting and solving HR problems using data. In today’s digital world, HR Analytics plays a key role in improving employee performance and achieving business success.

 HR Information Systems (HRIS)

HRIS is a software or system used to collect, store, manage, and analyze employee-related data in an organization.

Main Functions of HRIS:

Function	Explanation (Simple Words)
Employee Records	Keeps details like name, age, salary, experience, etc.
Payroll Management	Calculates salary, taxes, bonuses, and deductions.
Attendance & Leave Tracking	Tracks working hours, absences, and leave balances.
Recruitment & Onboarding	Manages hiring, job applications, and new employee joining process.
Training & Development	Records training programs and employee learning progress.
Performance Management	Helps evaluate and monitor employee performance.

Examples of HRIS Software

• SAP SuccessFactors
• Oracle PeopleSoft
• Workday
• BambooHR
• Zoho People

Data Sources in HR Analytics

Data sources are places from where HR gets data to analyze and make decisions.

Types of Data Sources in HR

Type of Source	Examples	Explanation
1️⃣ Internal HR Systems	HRIS, payroll software, attendance logs	Data stored inside the company
2️⃣ Surveys & Feedback	Employee engagement surveys, exit interviews	Direct input from employees
3️⃣ Performance Data	Appraisals, KPI records, 360-degree feedback	Tracks how well employees perform
4️⃣ Recruitment Data	Resumes, interview scores, hiring portals	Data from hiring process
5️⃣ External Sources	LinkedIn, Glassdoor, market salary surveys	Info from outside the company
6️⃣ Learning & Development	Training systems, course participation	Who is taking what training, and how they perform
7️⃣ Social Media & Reviews	Company reviews, social mentions	Public opinions about the company and HR policies

Conclusion

HRIS is the backbone of modern HR departments. It helps in storing and managing employee data efficiently. These systems collect data from many sources, which can then be used for HR Analytics to make better decisions and improve business outcomes.

Evolution of HR Analytics

HR Analytics has evolved in stages—from just keeping records to using data to predict and solve problems.

Stage	What it Means	Example
1. HR Reporting	Basic record keeping – tracking headcount, salaries, leaves	Just keeping employee data in Excel
2. HR Metrics	Measuring HR activities using numbers	Calculating turnover rate or average training hours
3. Advanced Analytics	Understanding why things happen	Analyzing why employee satisfaction is low
4. Predictive Analytics	Predicting future HR issues using data trends	Predicting who might resign next year
5. Prescriptive Analytics	Giving solutions based on predictions	Suggesting actions like promotions or training

HR Metrics vs. HR Analytics

Aspect	HR Metrics	HR Analytics
Definition	Basic measurements of HR activities	Deep analysis to understand trends and make decisions
Focus	What happened	Why it happened and what will happen
Data Use	Descriptive (past and present)	Predictive and prescriptive (future)
Example	Absenteeism rate, cost per hire	Analyzing why absenteeism is increasing
Tool	Excel, simple reports	Statistical tools, dashboards, AI models

In short:

• HR Metrics = What is happening?
• HR Analytics = Why it's happening and what to do next?

Intuition vs. Analytical Thinking

Intuition (Gut Feeling)

Aspect	Explanation
Based on	Personal experience, judgment, or instinct
Strength	Fast decisions in uncertain or emotional cases
Weakness	May be biased, not always accurate
Example	Manager thinks an employee will leave soon, without data

Analytical Thinking

Aspect	Explanation
Based on	Facts, data, and logical reasoning
Strength	More accurate, objective, and data-driven
Weakness	May take time, needs data and tools
Example	Using performance and engagement data to predict resignation

Comparison Table

Point	Intuition	Analytical Thinking
Basis	Experience & feelings	Facts, data, logic
Speed	Fast	Slower
Accuracy	Can be risky or biased	More reliable
Use in HR	Initial guesses, interviews	Workforce planning, performance

Final Exam-Oriented Conclusion

• HR Analytics has evolved from simple record-keeping to smart, predictive tools.
• HR Metrics give raw numbers, while HR Analytics gives insights and solutions.
• In today’s data-driven world, analytical thinking is more reliable than intuition for making HR decisions.

HRMS / HRIS and Data Sources

HRMS / HRIS:

Both terms are often used interchangeably.

Term	Full Form	Meaning (In Simple Words)
HRIS	Human Resource Information System	A system to store and manage employee data
HRMS	Human Resource Management System	A more advanced system that includes HRIS + extra functions like payroll, performance, etc.

Key Functions of HRIS/HRMS:

• Employee data management
• Payroll processing
• Recruitment tracking
• Attendance & leave management
• Performance appraisals
• Training & development records

Examples of HRIS/HRMS Software:

• SAP SuccessFactors
• Workday
• Oracle PeopleSoft
• Zoho People
• BambooHR

Data Sources in HR Analytics

Type	Examples	Explanation
Internal Sources	HRIS/HRMS, performance reviews, payroll, attendance	Data from inside the company
External Sources	LinkedIn, Glassdoor, job portals, labor market surveys	Information from outside platforms
Employee Feedback	Engagement surveys, exit interviews	Direct input from employees
Operational Data	Department productivity, project completion rates	Shows how HR affects business outcomes

Analytics Frameworks: LAMP, HR Scorecard & Workforce Scorecard

LAMP Framework

LAMP = Logic + Analytics + Measures + Process

Component	Meaning
Logic	Clear thinking and reasoning behind what to measure
Analytics	Using data analysis tools/statistics to find patterns
Measures	Actual numbers and metrics (e.g., turnover rate, training hours)
Process	Using insights to improve decision-making and implement HR strategies

Example:

If employee turnover is high:

• Logic = Why is turnover a problem?
• Measures = What’s the turnover rate?
• Analytics = Which departments are worst affected?
• Process = What retention steps can we take?

HR Scorecard

A tool to measure HR’s contribution to business goals using a balanced approach.

Focus Areas	What is Measured
HR Deliverables	Key goals like hiring quality, employee development
HR System Alignment	How well HR systems support those goals
HR Efficiency	Cost-effectiveness of HR activities (like recruitment cost)
Strategic Alignment	How HR practices support overall business strategy

It connects HR metrics with business success.

Workforce Scorecard

An extended version of the HR Scorecard that includes employee behavior and capabilities.

Component	Focus
Workforce Mindset	Are employees motivated and aligned with company goals?
Workforce Competencies	Do employees have the skills needed for business success?
Leadership & Culture	Are managers building the right culture and guiding teams?

It helps track how people performance affects business performance.

Final Exam-Oriented Conclusion

• HRIS/HRMS helps store and manage employee data, which becomes the base for HR Analytics.
• Data sources can be internal (HR systems) or external (job platforms, surveys).
• LAMP, HR Scorecard, and Workforce Scorecard are key frameworks that help convert HR data into business action.