HR Analytics: Tools, Types, and Benefits

Data plays a crucial role in nearly every business function, including human resources (HR). The right data can help teams produce crucial insights to improve their work. HR analytics refers to data pertaining to a company's workforce, and it's quickly becoming a required skill for any HR professional.

Learn more about HR analytics, including key tools and benefits. Afterward, if you're interested in building your HR analytics skills, consider enrolling in IBM's Generative AI for Human Resources (HR) Professionals Specialization, where you'll learn how GenAI can support strategic aspects of HR, such as workforce planning and employee engagement.

What is HR analytics? 

HR analytics is the process of examining employee-related data. Often, this is done using specific software designed to help an HR team generate insights about its workforce, including their performance, engagement, and retention. As with other types of analytics, which all rely on strong data analysis skills, HR analytics includes collecting, sorting, and analyzing workforce data.

Working with HR analytics can strengthen decision-making, improve conflict resolution, and produce more empathetic leadership—three key HR skills.

4 types of HR analytics

There are four main types of HR analytics. The kind you employ will depend on what you're trying to understand about your workforce.

• Descriptive analytics: Used to discover answers to present-day scenarios, such as "What is happening?"

• Diagnostic analytics: Used to elevate your descriptive analytics inquiries by answering "Why is this happening?"

• Predictive analytics: Used for future scenarios, predictive analytics help HR teams understand what could happen.

• Prescriptive analytics: Used to elevate predictive analytics by helping companies address the steps they'd need to take to make something happen.

What can you use HR analytics for?

You can use HR analytics to inform all sorts of best practices, including:

• Talent recruitment

• Hiring decisions

• Staff retention

• Salary standards

• Absences

• Policy making

HR analytics tools

There are many different software apps available to use when you're interested in implementing HR analytics. These programs are great for helping take a company's workforce data and delivering insights around factors like performance, compensation, and remote engagement.

Please note that not every tool below includes a full range of HR functionalities, so it's helpful to determine the key factors you'd like to measure and then make sure the software you're considering will help you achieve those insights.

• Insightful

• Paycor

• Crunchr

• Trinet

• Deel

• intelliHR

• PerformYard

• BambooHR

• Qualtrics

• DreamTeam

• ChartHop

There are also data analytics tools you can use to parse your company's data and find insights. These include:

• R or Python

• Excel

• Tableau

• Power BI

• Qlik

Importance of HR analytics

HR analytics provides companies with accurate and measurable data across a range of functions. This valuable information can offer greater insight into employee behavior, improve retention and lower recruitment costs, and help HR teams measure their impact. Let's review some of the reasons why incorporating HR analytics into any HR team can be beneficial.

Enhances decision-making

The use of HR analytics allows managers and company leaders to make better, data-driven decisions affecting all areas of human resources, from hiring and employee benefits to training methods. Analytics can enhance decision-making in the following ways:

• Predicting events before they occur for more strategic decision-making

• Analyzing employee experience, skills, and education to make better hiring decisions

• Automating some tasks to free up time for more important, decision-dependent tasks

Improves employee retention

Losing employees can cost companies valuable time, money, and institutional knowledge. In fact, the Society for Human Resource Management (SHRM) reports that it costs companies an average of $4,700 per new hire, though that number can often be much higher [1].

Improving retention can lower recruitment costs so teams aren't having to unnecessarily fill positions because of high turnover. Analytics can help improve employee retention by:

• Explaining why employees leave (lack of training, staff issues, irregular raises, etc.)

• Analyzing feedback from employee surveys and evaluations

• Identifying high-performing employees and promoting them or having them train others

Boosts productivity

In many companies, employee productivity drives success. Ways analytics might boost productivity include:

• Tracking worker output (like reports written, sales made, etc.) instead of hours worked

• Using data to create better work processes

• Analyzing employee work patterns with time-tracking software 

Potential HR analytics challenges

Although your HR team can benefit from using analytics, it's important to know some challenges you could face. These might include:

• Limited analytics skills: Members of your HR staff may not be as knowledgeable about analytics as the employees in your IT department. Therefore, you may want to incorporate data analysis into your HR training program. 

• Access to enough data: Predictive analytics requires large sets of relevant data. Therefore, smaller HR departments may have a harder time using data to make predictions.

• Employee privacy issues: Your employees may have concerns about how you're using the data you're collecting. You can quell employee concerns by being transparent with employees about how you'll use their data, being aware of the legal risks when collecting employee data, and investing in quality data security tools.

How to create an HR analytics plan for your business

When incorporating HR analytics, it's important to have a plan. Consider using this basic HR analytics strategy:

1. Define your objectives.

Identify what HR challenges your company faces and consider how analytics might help. Some common challenges in HR include:

• Disciplinary issues

• Inability to recruit qualified talent

• Inability to keep qualified talent

• Problems with workplace safety

• Reduced productivity

2. Decide what types of data you want to collect.

The types of data you collect depend on the problem you're addressing. For instance, if your problem has to do with employee retention, you may want to collect data involving:

• Employee satisfaction

• Employee retention rate

• Employee turnover rate

If your problem involves lower annual sales, you may want to collect data involving:

• Goal tracking per sales agent

• Work performance assessments

• Revenue per agent

3. Gather the tools you'll need.

A variety of software programs, like those we listed above, help companies track HR data. Choose software that addresses your particular issues and look for platforms that offer free trials or demos so you can get a feel for the software's capabilities. 

4. Analyze the data, and make changes as needed.

Once you've collected the data you need, examine it carefully. Use what you learn to make a plan for correcting your problem.

Build your HR analytics skills on Coursera 

HR can be a lucrative and evolving career path. On Coursera, you'll find options to build or expand your HR skill set.

• Get started in an HR career today with the HRCI Human Resource Associate Professional Certificate. Designed for beginners, you'll learn about employee relations, compensation & benefits, and compliance and risk management.

• Or advance your HR knowledge with IBM's Generative AI for Human Resources (HR) Professionals Specialization. Over three courses, you'll learn how you can use the capabilities and tools of generative AI to enhance your career in HR.