Role of HR Analytics in Modern Human Resource Management (HRM)

HR analytics plays an important role in human resources management (HRM) by empowering HR teams to optimize their core business operations.

Almost every modern Human Resource Management (HRM) department is either using or plans to use HR analytics to improve workforce performance. HR analytics applies to all the core HR management functions, including payroll, compliance, and workforce engagement. The growing use and easy availability of Big Data ( squeezed into workforce data) have provided HRM departments with powerful analytics and reporting tools. Though HR professionals are still working primarily on the “human” aspects of running a corporation, they are not averse to using analytics for HRM as a potent tool to make a difference to the overall organizational structure and performance management.

People Analytics is the New Currency 

Many HRM departments across the industry are taking analytics very seriously to improve their performance. Relying on accurate data can empower any business department, especially HR teams that have to spend 70 percent of their time and resources on people. That’s why people analytics is an important component in an HR Technology stack.

People analytics is the combination of Big Data Intelligence, HR data visualization, People Management practices, and Business analysis. When Big Data and Analytics combine with HRM practices, it gives rise to a powerful data-backed framework called ‘People Analytics.’ This is the crux of any HRM analytics tool that is currently available in the marketplace. Every analytics in the HR TECHNOLOGY stack would be entrusted to deliver relevant and actionable insights on any (or all) of these core HR processes:

  • Talent Acquisition
  • Training and Induction
  • Performance Review
  • Compensation
  • Rewards and Benefits
  • Retention
  • Marketing

The emergence of this organization’s information and the influence it holds over these HR processes has given rise to a new term and discipline: human resources analytics.

Here, we explore what analytics entails and the important role it’s playing within the field of human resources management (HRM)

What is HR Analytics?

HRM analytics is the method of collecting and analyzing Human Resource (HR) information in order to enhance an organization’s workforce performance. The process can also be referred to as talent analytics, folk analytics, or even workforce analytics.

This method of data analysis takes data that’s routinely collected by HR and correlates it to HR and organizational objectives. Doing so provides measured evidence of how HR initiatives are contributing to the organization’s goals and techniques.

Analytics provides data-backed insight on what’s working well and what is not so that organizations will make improvements and plan more effectively for the future.

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Roles of Analytics in HRM

1. Collecting data

Big information refers to the massive quantity of data that are collected and aggregated by HR for the purpose of analyzing and evaluating key HR practices, including recruitment, talent management, training, and performance.

Collecting and tracking high-quality information is the first vital component of analytics.

The data needs to be easily obtainable and capable of being integrated into a reporting system. The information can come from HR systems already in place, learning & development systems, or from new data-collecting strategies like cloud-based systems, mobile devices, and even wearable technology.

Types of Data Collected for Analytics For HRM

  • Employee Profiles
  • Performance
  • Data on High-Performers versus Low-Performers
  • Salary and Promotion History
  • Demographic Data
  • on-Boarding
  • Training
  • Engagement
  • Retention
  • Turnover
  • Absenteeism

2. Measurement

At the measurement stage, the information begins a method of continuous measurement and comparison, also called HR metrics.

HR analytics compares collected information against historical norms and organizational standards. The process cannot rely on one snapshot of information, but instead requires a continuous feed of information over time.

Monitoring Key HRM Analytics Metrics

Organizational performance

Data is collected and compared to better perceive turnover, absenteeism, and recruitment outcomes.


Data is monitored to determine the effectiveness and potency of HR daily procedures and initiatives.

Process optimization

This area combines information from each organizational performance and operations metrics in order to spot where improvements in the process can be created.

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The analytical stage reviews the results from metric reportage to identify trends and patterns that will have an organizational impact.

There are different analytical methods used, depending on the result desired. These include descriptive analytics, prescriptive analytics, and predictive analytics.

  1. Descriptive Analytics is concentrated only on understanding historical information and what can be improved.
  2. Predictive Analytics uses statistical models to analyze historical information to forecast future risks or opportunities.
  3. Prescriptive Analytics takes predictive Analytics a step further and predicts consequences for forecasted outcomes.

4. Application

Once metrics are analyzed, the findings are used as actionable insight for organizational decision-making.

Examples of how to apply analytical insights:

Here are some examples of how to apply the analysis gained from analytics to decision-making:

  • Time to hire – If findings verify that the time to hire is taking too long and the job application itself is discovered to be the barrier, organizations will build an informed decision about how to improve the effectiveness and accessibility of the job application procedure.
  • Turnover – Understanding why employees leave the organization means decisions are made to prevent or reduce turnover from happening in the first place. If lack of training support was identified as a contributing factor, then initiatives to enhance ongoing training can be put together.
  • Absenteeism – Understanding the reasons for employee long-term absence allows organizations to develop methods to enhance the factors within the work atmosphere impacting employee engagement.


With the world increasingly advancing towards a more data-driven approach, analytics is leading the way towards guiding the talent, management, and recruitment selections of all small and huge scale organizations. Data Analytics added within the HR’s workings has significantly aided in their accuracy and boosted the potency of their functions.

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