How to Get Started with HR Analytics in 2023? (with 10+ Examples)

by Hiration

Now more than ever, data has become a crucial factor that affects businesses and companies across all industries.

It is the era of Big data and human resource is just another aspect that can be refined by leveraging data.

Studies show that insight or data-driven companies grow at an average rate of 30% yearly and experience an 8% increase in their profit.

Likewise, using data to optimize human resource processes and decisions is known as HR analytics, which undoubtedly is pivotal for getting an insight into the company’s attrition and turnover rate among other factors.

HR analytics can help companies increase their employee retention and workforce productivity.

However, having a clear purpose and proper data management is key to making the most out of HR analytics.

Read on to learn more about HR analytics and get clarity on related FAQs like the following:

HR Analytics Definition


HR analytics can be defined as a process that ethically gathers, analyzes, communicates, and uses data-backed HR research and analytics to help companies achieve their goals and objectives.

In simpler terms, it is data analytics for HR that improves processes, decision-making, and employee retention.

However, HR analytics is not intended to collect data to track how your employees perform at work.

Rather its purpose is to provide the organization with deeper insight into which of your human resource practices are actually beneficial, along with potential solutions to overcome HR mistakes that are costing the company resources that can be otherwise utilized for its growth.

Usually, HR managers use two types of analytics to gather insights into the company’s workforce - descriptive and predictive analytics in HR.

While descriptive analytics help HRs understand past and present workplace scenarios, predictive analytics help them forecast what is likely to happen in the near future based on the current patterns.

Also Read: What is employee attrition rate and why does it matter?

HR Analytics Benefits


Business practices like having a vague understanding of how your human resource department functions and basing decisions on assumptions are medieval approaches that won’t do your company any good.

While most companies already have large amounts of collected raw data, they don’t have a direction or a structured pipeline that can leverage the data for appropriate usage.

Thus the need for HR data analytics.

HR analytics helps you get clarity on the following questions about your human resource system:

  • How high are your employee attrition rate and turnover rate?
  • Which employees are most likely to leave the organization within a year?
  • What percent of your employee turnover is a loss for the company?
  • What is your company’s time-to-hire?
  • What are the recurrent patterns in employee turnover?
  • What is the cost borne by your company to get a recruit up to speed and fully productive?
  • Which HR practices are having a positive impact on employee productivity and performance?
  • What job boards work best for you?

With HR analytics data, you can make statistics-backed decisions that mitigate risks and optimize current and future strategies, leaving no room for guesswork.

Also Read: What are some great exit interview questions to ask employees?

How to Set Up HR Analytics Process?


As stated earlier, a lack of proper direction and purpose can render HR data analytics useless.

Therefore, it is necessary to take well-thought-out steps to set up efficient HR analytics by collecting and analyzing raw data.

Given below are some tips to help your company implement HR analytics:

Establish Goals and Direction


Before your HR team looks out for data sources, formulate key questions about your workforce that correlate to the organization’s goals.

What does your company need to measure? How are these metrics interrelated? How can these metrics be calculated? And at what frequency do these metrics need to be taken?

Asking questions like these can help your HR team formulate clear objectives and a sense of direction.

Gather Employee Data Sources


The essence of HR analytics is resourceful data. However, having dispersed sources makes accessing data a time-consuming, unreliable, and inefficient process.

Therefore, to streamline things, identify and unify various data sources like varying HR systems, paper records, spreadsheets, etc., into a central repository to streamline things.

For instance, the HR team can put together good sources of indicators that can help calculate and predict employee engagement rates like the following in a single archive:

  • Social media posts
  • Messages and comments in work chats
  • Tenure
  • Number of meetings
  • Overtime hours
  • Vacation and leave used

When you have all the raw data in one place, you can easily identify key metrics or patterns to refine the data as per the organization’s goals.

Create a Visual or Graphic HR Dashboard


Working with raw data is like staring at endless excel sheets with a large number of figures which is not only boring but also incomprehensible to stakeholders or executives.

Thus making data visualization a part of HR analytics essential for presenting data in a graphic and visually comprehensible manner.

This will enable your HR team to refine, monitor, and benchmark data for deriving insights into various metrics like cost-per-hire, time-to-hire, attrition rates, etc., that are crucial to measuring workplace success.

Train Your HR Team


Since the concept of HR analytics is fairly new to most companies, it is advisable to train the HR team on the basic principles of HR analytics so that they have adequate skills to implement the required initiatives.

When your HR team is armed with the right skills and knowledge, it is easier to get the best out of HR analytics and establish efficient pipelines.

Or, consider hiring tech specialists like Data Analysts or Data Engineers who can work with the HR team and handle the technical aspects of HR analytics.

Focus on Steadily Refining HR Analytics


Once you’ve established HR analytics initiatives to resolve business problems in your organization, ensure to continuously keep tabs on the process to identify any loopholes and inefficiencies.

Follow up on the recurrent problems and administer required changes to avoid them in the future.

Hiration pro tip:
Once you’ve refined the HR analytics process within your organization and emitted any discrepancies, you can set up Predictive HR analytics, which is a tech tool used by human resource teams to analyze past and present data to forecast future outcomes.

Leverage HR Metrics and Analytics


HR metrics are parameters that help compare data points to determine the efficiency and effectiveness of HR policies.

For instance, if your company’s attrition rate was 5% in the previous year and 7.5% in the current year, these are data points. While the rate of increase, i.e., 50% is the metric.

Listed below are some examples of specific metrics that can be assessed by HR:

  • Time to hire
  • Recruitment
  • Cost to hire
  • Turnover
  • Absenteeism
  • Engagement rating

Also Read: Why should you consider being an equal opportunity employer?

Key Points


  • HR analytics can be defined as a process that ethically gathers, analyzes, communicates, and uses data-backed HR research and analytics to help companies achieve their goals and objectives.
  • HR analytics can help companies increase their employee retention and workforce productivity.
  • HR managers use two types of analytics to gather insights into the company’s workforce - descriptive and predictive analytics.
  • To streamline HR analytics, identify and unify various data sources like varying HR systems, paper records, spreadsheets, etc., into a central repository.
  • Data visualization is an essential part of HR analytics for presenting data in a graphic and visually comprehensible manner.
  • Once you’ve refined the HR analytics process within your organization and emitted any discrepancies, you can set up predictive HR analytics.
  • Some common HR analytics examples include time to hire, recruitment, cost to hire, and turnover.

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