HR Analytics: Benefits, Examples, and Trends

Human resource management system data

HR management system (HRMS) data, also known as a human resource information system (HRIS), is internal data stored and managed within a human resource software system.

It includes data such as individual employee information, benefits information, payroll information, time cards, confidential employee and employer documentation, and more.

With HRMS data, companies are able to perform human resource analytics processes, including predictive HR analytics.

For example, companies utilize HR management systems such as Oracle and PeopleSoft to log and oversee recruiting, talent management, entrance interviews, exit interviews, employee compensation, and benefits information, just to name a few.

People data 

People data covers a broad range of data categories, sources, and data fields. Nonetheless, HR analytics enables HR professionals to utilize people data such as:

• Feedback surveys
• Company employee reviews
• Professional development information
• Absence information
• Wellness information

HR leaders can use this data to gain deeper qualitative insights into specific indicators for retention, turnover, employee satisfaction, and work environment, to name a few examples.

Also, you could use employee data collected from publicly available web sources.

With this data, you will receive relevant data points such as employee experience, name, location, education, connections, employment length, and more.

As a result, you will be able to enrich and scale your existing candidate data.

What's more, you won't ever need to worry about the freshness and accuracy of the data. At Coresignal, it's our primary goal to always keep the data fresh.

Company data

Company data, also sometimes referred to as firmographic data, is useful within HR analytics as it can provide insights into company-wide organizational structures, revenue, sales, and more.

In addition to firmographic data, which is typically purchased externally from verified third parties, some companies utilize company data that is internally collected within the organization’s larger project management systems and CRM.

Key metrics for HR analytics

There are many HR metrics that HR professionals use to enable data-driven insights and seek to develop strategies for performance improvement. Some of them are listed below.

Employee turnover

Turnover, also known as employee churn, is a measure of how long employees work at a particular company before termination of employment.

When analyzing this number over time, organizations are able to determine their average turnover rate.

This provides the company with insights on how to improve this number, ultimately increasing employee retention and saving money and resources on recruiting, training, etc.

Cost-per-hire

Cost-per-hire is the measurement of how much it costs a company to hire a new employee. According to Zippia, it was found that in 2022 companies spent on average $4,700 to hire new employees.

As with understanding and improving employee turnover, tracking this number is crucial, as it can provide direct information about how much money is either being wasted or properly dedicated to the recruiting and training processes within an organization.

Time-to-hire

Time-to-hire measures the time it takes to fill the position once the candidate has applied for the job. It's similar to time-to-fill, the only difference being the starting point.

With time-to-fill, the beginning of the process starts when the job openings are published.

Acceptance rate

Acceptance rates are calculated by dividing the number of job candidates given a job offer by the number of job candidates who accepted a particular company’s job offer.

Acceptance rates provide rich insights into how to optimize recruitment and talent sourcing strategies for future hires.

Employee retention

The opposite of employee turnover is the measure of employee retention. HR analytics measure employee retention by dividing the number of total employees that remained employed at a particular company by the total number of employees that were hired during a given period of time.

Specifically, this information is useful for better understanding workplace health, engagement, and even the quality of hire.

Human resources analytics implies a significant correlation between the quality of hire and employee retention, as the quality of hire is measured with various data points.

For instance, according to Achievers, organizations that provide consistent recognition see a 34% increase in employee retention, directly improving one’s employee retention rate.

Demographics

In addition to collecting quantitative data surrounding hiring, recruiting, and training processes, HR analytics is also interested in analyzing qualitative information about current and potential employees.

For example, companies are able to collect and analyze their current employees’ demographic information such as age, gender, experience level, and external interests to generate insights about the overall cultural make-up of the company.

Further, suppose HR professionals for a particular company notice a lack of younger employees that might have fresh or different perspectives on outreach and marketing.

In that case, it is in the company’s best interest to expand the age range of its employees, as a diverse workforce offers many revenue-generating benefits.

Company culture 

Similar to measuring demographics, getting a better understanding of company culture relies on the collection of qualitative employee information.

For instance, some HR professionals collect data via regular surveys from employees, record check-ins between employees and their managers, and track employee engagement with team building activities, etc.

Productivity (Capability)

Lastly, but certainly one of the most crucial HR analytics metrics is employee productivity, sometimes referred to as employee capability.

Employee productivity is measured in a variety of ways, such as time-to-productivity, employee capability scores, competency scores, etc.

For example, a company with a high employee turnover rate might also be interested in measuring time-to-productivity, as a high turnover rate coupled with a high time-to-productivity rate can lead to a chaotic and unstable workplace, negatively affecting the overall productivity of the company.

What is the HR analytics process?

The HR analytics process, similar to workforce analytics and other internal company analytics processes, involves three major steps: data collection, evaluation, and implementation.

Today, many companies outsource this process to HR technology companies, which provide businesses with automated tools and software to help smooth this process.

According to AIHR, some of the most popular tools utilized internally and externally by HR tech companies include R, Python, Tableau, and Excel.

Additionally, to expand on this process, let’s take a look at the steps involved in HR analytics.

HR data collection

For many companies, the data collection process involves both the retrieval of internal and external data. Internal data collection might include collecting and storing qualitative information about employees’ names, ages, interests, and even survey responses.

External or third-party data collection might consist of purchasing human capital-related data from public web data providers or HR tech companies.

Further, external data is helpful for recruiting, understanding a competitor’s workforce, and fueling AI-based HR tools that need larger samples of data beyond just one company’s internal data.

Evaluation

The evaluation process involves not only HR analysts but also other HR team members, as well as HR software and tools.

HR tools and software are able to help human resources by collecting and analyzing people data, performance data, and business data, generating insights on the impact current systems, strategies, and team members have on the company's overall success.

The evaluation process for quantitative data can be processed quickly with software; however, qualitative data, such as survey results, take longer to analyze but are just as important.

Likewise, it is important for HR teams to develop an evaluation process that dedicates ample time to utilizing AI-based tools and software for quick insights and unpacking more lengthy qualitative information.

Implementation

After the collection and analysis of HR-related data, HR teams are able to implement the actionable insights generated from the above steps.

This might look like implementing more team-building events, increasing the number of employees at a given company, or even simply adding more amenities in work offices.

The benefits of utilizing HR analytics

Companies are able to leverage HR analytics platforms and software for the following benefits:

• Increasing employee trust and work engagement
• Improving talent sourcing processes and strategies
• Boosting workforce productivity
• Enhancing workforce planning
• Measuring revenue and expenditures of employees and teams
• Optimizing and enhancing the recruitment process
• Reducing talent turnover & increasing retention

HR analytics trends for 2022 and beyond

Just as many other departments within an organization turn to a data-driven approach, so do the human resources departments.

HR analytics trends in 2022 suggest that HR managers realize the importance of public web data, data-driven HR tools, and AI-based solutions.

Optimized and AI-based HR analytics processes 

As new technology surrounding data in HR analytics and similar processes roll out, companies will need to shift or update their current AI-based HR tools in order to stay on top of their competition.

For instance, HR tech companies such as Tableau and Sisense, provide users (companies) with HR data solutions, including data visualization dashboards, HR data reports, and management tools.

Implementation of predictive HR analytics 

Predictive analytics, a subset of AI analytics processes, involves analyzing quality data in order to generate insights that will be useful in the future.

Many companies are able to stay up-to-date and implement new HR strategies that are relevant today.

However, only a few companies are proactive in making HR decisions. Organizations that utilize HR analytics to predict workforce trends, improve employee performance, and enhance the hiring process are able to stay ahead of unexpected shifts within the organization or even within a given industry.

For example, companies that implemented virtual training, hiring, and working were able to stay ahead of many challenges caused by the COVID-19 pandemic.

Wrapping up

In all, using HR analytics offers a gateway for companies to expand and improve their human capital and overall people-related functions and strategies. Which, in turn, could affect business outcomes.

However, in order to see real growth and progress from utilizing HR analytics, companies must harness public web data and HR analytics tools to implement the actionable insights generated from such resources.