What is HR Analytics? Types, Key Metrics, AI Use Cases and Careers in India

01What Are HR Analytics? The Easy Way Out

HR analytics is a process of gathering information about the workforce and analyzing it in order to make decisions regarding recruitment, retention, performance, compensation, training and workforce planning.

Sometimes you may come across other terms like people analytics or workforce analytics. Though there may be some nuances between all of these concepts, their core idea is the same - make decisions regarding people based on facts and not on opinions.

What does it mean in action?

• Not "we need to recruit more", but "we will have to hire 40 additional support staff by March taking into account the existing attrition and growth rates."
• Not "we have an excellent training", but "staff, who went through this course, were rated as better performers after 6 months."
• Not "people leave for money", but "most frequent early leavers are from two departments, exit interviews indicate problems with managers, not salaries."

In fact, most of this information is available within your organization - HRMS, payroll, applicant tracking system, performance appraisal and employee engagement survey are full of it.

02Why HR Teams Need to Embrace Data Now

People are often the highest cost and greatest asset for organizations. However, for a long time, HR teams have been the only department which reports on activity ("we had 30 training sessions") instead of impact ("training reduced early turnover by a third"). And that is because...

That last point surprises many people. The "S" in ESG is largely people data: headcount, turnover, gender ratio, training hours, safety and grievances. So, HR teams are now directly involved in ESG disclosures. If you're curious how that works, read our guide to the best ESG certification courses in India, or explore the ESG & Sustainability Reporting program.

03Four Types of HR Analytics

HR analytics happens at four levels. Each subsequent level attempts to answer a more difficult question than the previous level.

1. Descriptive analytics – what happened?

   Every HR department uses it. Employee headcounts, monthly attrition, time to hire, absenteeism rates. Descriptive analytics is helpful, but it tells you the numbers without any context.

2. Diagnostic analytics – why did it happen?

   At this stage, you dig into the data to identify root causes. Is attrition higher in specific locations, by tenure band or by teams? Is engagement levels low before resignation? Most of the insights are found here.

3. Predictive analytics – what is likely to happen?

   Based on the patterns in historical data, you forecast future events such as employee turnover rates, number of hires for next quarter, or likelihood of candidate success in a particular job. Here is where machine learning starts paying off.

Most Indian companies are still at levels one and two. That's exactly why people who can work at levels three and four are so valuable, and why our HR analytics certification focuses heavily on predictive work.

04HR Metrics Every Analyst Tracks

You don't need hundreds of metrics. A handful, tracked well, tells you most of what you need to know.

It’s not about calculating them. It’s about how you link them together. By themselves, attrition is a statistic. When you tie attrition to the manager, the tenure, engagement score, and pay band, now you have a story.

05The Role of AI in HR Analytics

Just a few years ago, developing a flight risk model required hiring a team of data scientists. In today’s world, AI capabilities are becoming an integral part of most HR software solutions, and the use of generative AI can enable an HR analyst to summarize several thousand survey comments in a matter of minutes. Here are some areas where AI is having an impact:

• Recruitment: Resume screening, job fit analysis, and scheduling interviews.
• Attrition prediction: Detecting patterns such as low engagement, missed promotion opportunities, or long commute times that indicate the likelihood of an employee leaving the company.
• Sentiment analysis: Analyzing open comments in surveys or exit interviews to detect any underlying themes, rather than just reviewing comments manually.
• Workforce planning: Predicting recruitment needs taking into account business growth, attrition rates, and seasonal factors.
• Personalized learning programs: Suggesting learning programs for employees according to their role and career aspirations.
• HR bots: Answering simple questions related to leave, payroll, and other HR policies.

The important word there is use. You don't need to build AI models from scratch. You need to know what questions to ask, what data to feed in, how to read the output and when not to trust it.

06The Perils: Bias, Privacy and Poor Data

HR data pertains to real people and misinterpretations can be serious. Here are some of the risks to keep in mind:

• Biased models: If the past practice in recruitment was biased, then the AI system trained using the same will reproduce the bias. A fairness check is needed for every model.
• Privacy: The data being processed pertain to people. The recently enacted Digital Personal Data Protection Act, 2023 outlines the guidelines regarding collection and use of personal data and hence, consent is necessary.
• Bad data: The presence of duplicate employee ID, unknown reasons for leaving and inconsistent job roles is a potential source of bad data that goes unnoticed and can invalidate your analysis.
• Finding patterns in numbers without context: An increase in attrition rate could be due to restructuring and planning. Discussion with the business is a necessity.
• Turn into surveillance: Analytics must help both the manager and the employee and not put them under a microscope. Trust is difficult to recover once lost.

These are exactly the kinds of judgment calls that separate a good HR analyst from someone who just runs reports, and they're covered in depth in our HR Management & Analytics Using AI course.

07HR Analytics Jobs & Skills

With Indian businesses shifting their focus from basic HR reporting to actual analytics, here is an array of job roles for HR professionals in IT services, GCCs (Global Capability Centres), consulting companies, banking firms, manufacturing and start-ups:

• HR Analyst: Creating reports and dashboards, monitoring critical HR metrics.
• People Analytics Specialist: Conducting further analysis on issues like attrition, engagement, and performance.
• HR Business Partner (data-focused): Assisting business leaders by providing insights about their workforces.
• Talent Acquisition Analyst: Optimizing the recruitment process, sources of hire, and quality of hire.
• Compensation & Benefits Analyst: Analyzing compensation and performing pay equity check.
• HR Tech / HRIS Specialist: Overseeing HR information systems and the data flow through them.

And here's the good news: you don't need to come from HR. Commerce, engineering, science, arts and even medical graduates move into HR analytics, because the field values a mix of people sense and analytical thinking. MBA students in particular are finding that analytics gives them an edge, much like we described in why MBA students are choosing ESG careers.

08HR Analytics with eAsia Academy

Knowing HR analytics by heart is something. Working with an unruly dataset of employees, understanding the reasons behind their exit, and presenting a strategy to the management is something else entirely. It’s the latter that employers seek.

Professional Certificate in Human Resource Management & Analytics Using AI provided in partnership with the Continuing Education Centre of IIT Roorkee is designed to provide both: solid HR management knowledge and useful analytics & AI skills right away.

In case you are also looking into sustainability, our other courses at IIT Roorkee will go well with your choice of Human Resources Management. ESG’s social pillar functions on the back of people data; thus, ESG & Sustainability Reporting is the next course to take after your choice of course. For climate & carbon courses, check out Carbon Credits, Carbon Markets & Net-Zero Pathways course that we covered in our guide to carbon credits.

Seats are getting booked for the November cohort. Check out more details for HRMA cohort or all eAsia Academy courses.