What is HR analytics?
HR analytics is where Human Resource (HR) data is collected and analyzed to benefit a company’s workforce performance.
By collecting and analyzing the data, patterns begin to emerge which demonstrate possible improvements for the company and how to strategically plan for the future.
One way this could be beneficial would be in a company with a high turnover rate. Understanding why people are leaving could help HR reduce it.
There are four levels of analytics: descriptive, diagnostic, predictive and prescriptive.
This article looks at how HR analytics support a range of areas such as company culture, employee engagement, turnover rate and absenteeism.
Why are they important?
Even though HR has a lot of information about their employees, without analytics it would be raw data. In a large company this could be thousands of employees, and their raw data on its own can’t identify problems or offer solutions.
HR analytics uses data-supported evidence and patterns that can help HR to understand the reasoning behind what is happening in the company, such as the general wellbeing, employee engagement and the amount of training each team has had.
Descriptive analytics, which is made up of observations and reports, are important as they consist of observing the workplace to gain initial insight into what is going on.
Diagnostic analytics takes the observations to the next level to understand why and what is the cause. It may be clear that employees are unhappy, but it is important to find out why.
Predictive analytics is used less than the others, but is where organizations can predict ways of improving the situation and attempt them.
Prescriptive analytics is the final step where it considers the cause of the issue and uses the data to prescribe what needs to be done to fix it. Prescriptive analytics relies on the other three forms of analytics to get the best outcome.
HR Analytics In Practice
In recent years, there has been a growing interest in HR analytics and its potential to improve organizational decision-making. Here are some practical applications of HR analytics that are being used today:
Having a positive company culture is important for all members of the team. Both the physical environment and the mentality of staff are important factors in keeping the company culture balanced.
Improving the company culture can increase the health, both physical and mental, of employees. It can reduce the turnover rate, increase loyalty and improve performance outcomes.
By monitoring this closely, all employees and the company would benefit.
This would be done by using descriptive analysis to observe the workplace closely, followed by diagnostic analysis to narrow down the reason behind any negative company culture.
Employee engagement is one of the most impactful parts of a company. The higher the engagement the more successful a company could be.
With a high level of engagement, there is more productivity, efficiency and customer satisfaction. All of these things are important within any business, therefore HR needs to understand if it changes and why.
By using descriptive analysis and observing workplaces, you could gain initial insight into employee engagement and how it compares to previous days, weeks or months. If there was a decrease observed, it would be important to understand what had impacted the levels of engagement and how the company could improve them.
Following all four stages of analytics, and implementing prescriptive analytics to lay out steps to move forward, a company could support its workers and continue to benefit from the outcome.
When employees leave a business, it often isn’t understood why. Individuals may offer a reason, however, individual reasons cannot support an organization in decreasing widespread causes.
All HR teams will know their current turnover rate, however, they may not know of any current employees planning on leaving or what percentage of employee turnover in the last year had a large impact on the company.
By using HR analytics, a company could identify patterns to find out if there are consistent reasons that employees are leaving. They can also gain an understanding of current employees’ behavior and attitude towards work to identify if anyone else is considering leaving.
Using diagnostic analysis to understand the why is crucial here, as employees may leave for a variety of reasons, but using the analysis to identify the patterns and improve them.
By correlating the data of why people have left previously and what current employees like and dislike, HR can implement changes to reduce the negative factors leading to a high turnover rate.
Absenteeism tracks the amount of time and frequency that an employee is absent from their job. If an employee is regularly absent or absent for a long time, it could have a direct impact on their engagement, wellbeing or ability to complete tasks.
High absences can be looked into by HR to ensure that there is a valid reason. Monitoring the reasons why employees take regular absences could offer HR a chance to improve any work-related causes, such as negative work culture.
Absenteeism can often be expensive, therefore by using diagnostic analysis and identifying the cause of each employee's absence, it offers the company a chance to show support to employees who may need it, as well as hold all employees to their code of conduct and compare to the average amount of leave.