HR Data Analytics

Everything To Know About HR Data Analytics

In this article, we will help you understand HR data analysis. We’ll show you the positive impact it can have on your business and how you can use it as part of your current business strategy.

The most important facts

• HR data analysis helps gain insights into employee trends and patterns. This information can be used to make improvements across the organization.
• As a result of this data analysis, you can improve various aspects of the workplace, from payroll to training to recruiting.
• Using data in business decision making can help steer your business in a new direction with confidence.

What is HR data analysis?

The term HR data analytics, also known as people analytics, refers to collecting data about your workforce based on predetermined HR metrics. This information can then be used to improve your business overall. For example, HR data analytics is often used to gain insights into metrics such as employee engagement and retention. This way you can determine which measures have the most positive impact on employees.

Who is responsible for HR data analysis?

Who is responsible for HR data analysis can vary from company to company. Some companies have HR managers dedicated solely to analyzing workforce data, while others split their HR teams to analyze specific parts of the workforce. Third-party analysts are also a commonly used option.

How HR data analysis can influence decisions

People data analysis can impact your business from top to bottom, as long as you have the tools necessary to correctly interpret the data you collect. Below are just a few areas of your business that can be impacted by workforce data analytics:

Employee recruitment and onboarding

Your company can collect data about new employees and identify the methods, hiring channels and offers that attract the best candidates. This analysis can also be used to determine the actual costs of hiring new employees, so you can better fit the process into your budget.

Payroll

Analytics can provide a comprehensive overview of salary costs, overtime costs, and other non-salary compensation, allowing fine-tuning of employee compensation across departments. You can use this anonymized information to change policies to better manage labor costs and equalize salaries within your organization.

Services

An HR data analytics report can provide insight into whether the benefits you offer are actually meeting employee needs. The results will give you insight into what employees expect from their benefits package. They can also highlight what you should include to improve employee satisfaction and retention, and what you can safely eliminate from your benefits package.

Training and development

This data can be used to gauge the success of initiatives that invest in your employees, particularly professional development programs and specialized training. You can use this information to offer these courses to more employees, expand offerings, or explore more effective options. In addition, the analysis can show where the greatest need for training exists in your company. You can tailor your new training and development programs to meet these needs.

Employee engagement

Data analysis for HR can also examine employee engagement across the organization and determine what contributes to lower or higher levels, such as: between departments. You can use this information to fine-tune your company policies so that as many of your employees as possible are engaged.

How HR Data Analytics helps human resources management

Data analysis in the HR department not only helps the entire company, but also offers numerous benefits to the HR department itself. The benefits of an in-depth workforce analysis include:

• Better decision making: With data from workforce analytics, it’s easier to make the right decisions for your workforce strategy. This information can give you and your team confidence that you are making the right decisions by being guided by data.
• Highlight the value to the organization: The data itself increases the value of HR to an organization. They do this by increasing the accuracy and effectiveness of the solutions that HR develops and deploys.
• Make a better case for deploying resources: Data can help support the need for a new program, revamping an ongoing program, or removing a program from current offerings. This can be applied in many ways, in professional development or social benefits.

The four levels of HR analytics

There are four levels of HR analytics. These are: descriptive, diagnostic, predictive and prescriptive.

1.Descriptive

This is a superficial observation of what is going on in an organization or a particular department. Descriptive analysis helps construct a first case or provide insight into a potential problem. It also helps show how workforce data analysis can help solve the problem.

2.Diagnostic analysis

This particular level examines why a problem occurs. The diagnostic level provides context and understanding as to why the observations made at the descriptive level actually occur.

3.Prediction

As the name suggests, this method makes an educated guess that something might happen and takes steps to prevent it before it happens. This method is not as common as the descriptive and diagnostic levels, but some organizations prefer to use this model to prevent problems before they arise.

4.Prescriptive

At this level, a solution is developed and implemented. The prescriptive approach builds on the descriptive, diagnostic and predictive levels. When using HR data analytics, the information collected is used to identify, guide, and implement the proposed solution.

Examples of HR analytics in practice

Below are some examples of HR analytics in practice to illustrate the benefits of this information in the workplace.

Example 1: Employee turnover

Company A has a turnover rate of around 20%, which it would like to reduce to 15%. The HR team can use people analytics and information from exit interviews to identify the most common reasons why employees leave the company. The HR team can also use employee engagement data to identify areas where employees are dissatisfied. Using this information, they can make changes to reduce turnover rates and correct course.

Example #2: Hiring decisions

Company B wants to increase employee productivity in the long term by hiring higher quality applicants. Instead of sifting through resumes, Company B’s HR team uses analytics to find out which online job boards offer the most suitable candidates for their needs. It also collects data on the company’s top performing employees to compare it with applicants’ resumes to make decisions faster.

Example #3: Employee performance

Company C wants to improve the performance of its entire workforce by redesigning its workplace to increase productivity. Human resources collects data on the aspects of the office that impact employee morale and engagement. The elements that have a positive influence are then highlighted. Analysts can then collect more data and determine how effective the changes are, and provide appropriate advice if results are unsatisfactory.

Example #4: Training programs

Company D is interested in directly improving the performance of its employees by giving them the skills they need to excel in the workplace. The analytics team conducts a skills gap analysis to determine which skills need improvement. Implementable recommendations are then developed to further train the workforce as needed.

How to implement an HR analytics strategy

It is important that HR managers apply data analysis correctly to avoid biased or misinterpreted results. The following steps are required to use HR data analytics effectively:

• Define the problem and goals for developing a solution: Determine the company’s challenges and set goals for developing data-driven solutions. Consider implementing SMART goals to best define the problem you want to solve.
• Put the results in context: The analysis should be linked to current business goals to show stakeholders the value of their solutions.
• Verify your data: Analysts should verify their data before presenting it so that the organization does not act based on erroneous results.
• Develop a communication strategy: Your analysts should develop a strategy for presenting their findings clearly and concisely. This presentation can help convince stakeholders to take the direction you suggest.
• Act on your findings: After the HR team has ensured their data is accurate and convinced executives to support their recommendations, it’s time to act on them.

Can you use HR reporting software to support HR analytics?

Your HR team may already have tools in place to properly collect and analyze their employees’ data. However, there are some special tools that can simplify this process. HR reporting software can both expand the scope of data collected by an analyst and provide more accurate data.