Human Resources Analytics: What It Is and Why It’s Important

Human resources have always focused on people, but today’s HR professionals also use technology and workforce data to support decisions about hiring, performance, retention, and employee experience.

Human resources analytics (HR analytics) involves collecting, analyzing, and interpreting that data to identify patterns, answer workforce questions, and guide action. It helps HR teams understand what happened, investigate why it happened, and determine what to do next while accounting for data quality, privacy, and human judgment. The sections that follow will explain to you how HR analytics works, why it matters, and how it can support performance and efficiency, recruitment and hiring, and employee experience.

Key takeaways

• Human resources analytics connects workforce data to specific HR and business questions, such as why turnover is rising or which hiring channels produce successful hires.
• Common measures include time to fill, cost per hire, turnover, retention, engagement, absenteeism, and performance indicators; the right metric depends on the decision.
• Reliable analysis requires consistent definitions, appropriate access controls, careful interpretation, and human review.

What is human resource analytics?

Human resources analytics uses employee and workforce data to identify patterns, test assumptions, and improve people-related decisions. Depending on the question, the analysis may summarize past results, explore causes, forecast likely outcomes, or compare possible actions.

“Human resources analytics falls within the realm of digital HR,” says Tom Penque, lecturer for the Master of Science in Human Resources Management program at Northeastern University. “As HR technologies and platforms evolve, there is more information [available for us to] capture electronically. HR analytics is about the different ways that we capture, measure, and organize that information to create valuable insights for an organization.”

Due to the proliferation of this data, data-driven decision making has become a standard component of many human resources processes. The reasoning is simple: Access to numbers that can back up decisions regarding recruitment, employee performance, quality of human resource software, and other areas of HR, can often lead to improved business strategies.

How is HR analytics used?

HR analytics starts with a specific workforce or business question. You might ask why turnover has increased in one department, which recruiting sources lead to strong long-term hires, or where engagement and skills gaps are developing.

HR teams then select relevant data, establish a baseline, analyze patterns, test an intervention, and monitor the result. The goal is not to track every available metric; it is to connect reliable data to a decision the organization can make and measure.

Although the question changes, most HR analytics projects follow a similar cycle:

• Establish a benchmark of current performance so that the HR professional understands where their organization currently stands on the metrics that are most important to it.
• Make observations and draw conclusions from this benchmark in order to hypothesize potential solutions to the challenges being faced.
• Implement a change in process that is specifically designed to test the validity of that hypothesis.
• Monitor results so that the impact of the change can be measured, understood, and either rolled back (in the case of a failure) or embraced and rolled out to additional processes as appropriate (in the case of success).

Why is HR analytics important?

HR analytics can help organizations make more consistent, evidence-informed people decisions and connect HR initiatives to business outcomes. Its value is strongest when teams use data to answer a defined question, act on the result, and measure what changes over time.

As the general economy and HR industry continue to change to meet the demands of the digital era, those looking to create a future in HR will need to expand their skill sets and prepare to wear many hats within their roles. HR professionals must be capable of analyzing data and drawing valuable insights that they can leverage to help an organization meet its strategic goals.

Below we explore the three areas of an HR professional’s work most positively impacted by HR analytics.

1. Performance and efficiency

Many organizations measure the success of human resources activities and processes by overall performance and efficiency. Tracking metrics can offer valuable insights into how well certain processes are performing.

For example, as an HR professional, you might track the retention rate of new hires by source. Over time, as you collect this data, you may come to realize that certain sources (such as internal referrals) lead to much higher retention rates compared to other sources (such as LinkedIn postings). Armed with this knowledge, you might then reorganize your workflows to prioritize internal referrals over poorer performing channels, knowing that this is likely to make you more efficient during the hiring process.

Other commonly-tracked metrics that can be used in similar ways include hiring duration, hiring effectiveness, applications and hired by sources, applicants per opening, offer acceptance rates, and employee satisfaction rates, amongst others.

Using data to understand how your processes and workflows are performing will enable you to think critically about how to deploy your resources so that you can focus on the areas that will lead to the greatest overall impact.

2. Recruitment and hiring processes

Filling open positions can require significant time and resources. According to SHRM’s 2026 Recruiting Executives Benchmarking report, the median nonexecutive position took 39 calendar days to fill and had a median cost per hire of $1,300. These figures provide useful context for the recruiting decisions you may help shape as an HR professional, from identifying delays and improving sourcing to allocating resources more effectively.

Recruitment analytics can help HR teams monitor metrics such as time to fill, cost per hire, offer acceptance, candidate source, and early retention. By connecting recruiting data with later performance and retention outcomes, you can identify which hiring channels and assessment methods are associated with stronger results.

SHRM also found that only 20% of organizations measured quality of hire in 2026. Among those that did, commonly used measures included performance appraisals, retention rates, and post-hire interviews. Tracking these outcomes can help you evaluate whether hiring decisions create lasting value and identify opportunities for improvement.

These insights should support—not replace—your professional judgment. You should also review hiring data and analytical models for privacy concerns and potential bias. Because recruiting results vary by industry, role, location, and organization size, you should consider external benchmarks alongside an organization’s own historical data and business goals.

3. Employee experience

Human resources managers also use analytics to understand the employee experience, including engagement, development, and retention. Reviewing these measures together can help HR teams identify patterns and areas that warrant further investigation.

By monitoring metrics like employee attendance, productivity, and engagement, HR professionals can gain a greater understanding of the overall employee experience. This understanding can help HR determine where the organization shines and where there is room for improvement. Compensation, benefits, vacation policies, and professional training and development opportunities can all be optimized based on these insights.

“It’s not just about recruiting, but about retaining, motivating, and developing strong employees as well,” Penque says. “What HR analytics comes down to is being able to…use all of this information to improve the organization and its people.”

Building HR analytics skills for a data-informed career

HR analytics is most valuable when you can frame clear business questions, evaluate data quality, interpret findings responsibly, and communicate insights to decision-makers. These capabilities can help HR teams strengthen recruiting, performance, retention, and employee experience while aligning workforce decisions with organizational goals.

Northeastern’s Master of Science in Human Resources Management includes Workforce Analytics and Strategic Workforce Planning coursework. Students also complete a 12-week capstone course featuring a virtual HR consulting project with a leading company or their current employer.

Explore Northeastern’s online MS in Human Resources Management to learn how the program combines data-informed coursework with experiential learning.

Editor’s Note: This article was originally published in January 2020. It has since been updated for relevance and accuracy.