In many organizations, HR has earned a reputation for being emotionally-driven and making things difficult for everyone. As a result, HR is often overlooked when it comes to making strategic decisions. But the role of HR professionals has recently been shifting from handling problems on a daily basis to being a valued business partner. This is in part thanks to HR analytics.
HR analytics has helped organizations recognize the importance of data-driven human resource management. What was once considered intangible and emotional, we can now quantify and analyze. Businesses today are even starting to realize that the HR function can become a competitive advantage.
What is HR Analytics?
HR analytics is the process of quantifying and understanding existing HR data to develop insights that allow organizations to make strategic human resource management decisions that align with business needs.
The insights gained from HR analytics should tell you how your investment in human capital is contributing to the business. In other words, it should integrate talent management, financial and operational data to measure HR productivity and ROI.
HR analytics is often used interchangeably with other terms such as "people analytics" and "workforce analytics". But it is important to note that there is a slight difference between them. People and workforce analytics focus on metrics that pertain to employees. HR analytics, on the other hand, is measuring the performance of the HR function.
Why Should You Use HR Analytics?
Whether or not you are aware of it, data is changing the way HR professionals work on a daily basis. It shapes the processes they carry out and the new initiatives they promote to employees. For this reason, it is important to understand how analytics can help you take your HR department to the next level.
Here are five ways that HR analytics can help business leaders recognize HR as a high-performing and productive function:
1. Improve the Employee Experience
There are many touch-points in the employee lifecycle that contribute to the employee experience. Every day is a step in the employee's journey. Every day, they make observations and engage with other employees and systems.
HR analytics is an opportunity to collect data at each of these points and develop strategies to improve the work environment. This can include making positive changes to certain processes or creating better ones. Using employee feedback in decision making makes employees feel valued. Building this trust with employees can enhance employee engagement and employee retention.
2. Gain Powerful Insights About Your Workforce
Don't just collect and track metrics. Turn them into actionable insights. You need to know what your turnover rates are, but what is crucial to know is how to keep this number down. Which employees are most likely to leave and how can you avoid it? By answering these questions, you will be able to develop insights to improve your employee retention initiatives.
You can also test HR initiatives to see if they are as effective as you anticipated. For example, are the learning and development programs you put in place last quarter having a real impact on employee performance?
Remember that the best insights often come from the integration of several data sources.
3. Prioritize the Right HR Initiatives
Let's be honest. HR KPIs are not what CEOs care most about. What they really want to know is what resources the business needs to invest to improve these KPIs and what the return on the investment will be. For this reason, HR Managers need to build a business case for and prioritize the HR initiatives they propose. HR analytics can help you do exactly that.
Use the insights you have gained to identify and drive the most impactful HR initiatives while keeping business goals in mind. For example, by knowing the time it takes to fill positions and collecting feedback from new employees in the onboarding process, you can recommend leveraging HR technology to help automate or simplify certain HR functions. Looking at the KPI alone may not have given you the same insight about your talent acquisition process and could leave you prioritizing the wrong initiatives.
4. Make Data-Driven Decisions
Transforming data into actionable insights allows HR to have a seat at the table when it comes to strategic decision making. You can recommend changes to existing HR processes to make them more efficient. For example, if you have learned which factors contribute to a new hire leaving within the first year of employment, you can integrate these into the hiring process. A year later, you can test the effectiveness of this intervention.
Talent management is comprised of all HR processes for attracting, onboarding, developing and retaining top talent. HR should always be evaluating these processes to overcome any challenges or make them more efficient.
Here are some talent management HR analytics examples you can start implementing today:
Knowing how much to invest in training activities can be tricky. In fact, training expenses are one of the first things to get cut from the budget during economically tough times. In this case, there are two metrics you can refer to in order to measure the effectiveness your training program:
Training efficiency can be determined by analyzing improvements in performance, evaluation scores, and upward advancement after training.
Training expenses is dividing total amount of training expenses by the total number of trainees. Combined with training efficiency, you can assess the ROI of the training program.
To understand the factors that lead to employee turnover, you will need to collect and analyze historical turnover data. HR can collect relevant data through an exit interview, employee satisfaction survey, performance appraisal, etc. You can then identify the patterns and trends in the behavior that correlate with turnover.
Comparing voluntary and involuntary turnover can also provide important insights about your attrition. By looking at voluntary turnover, HR can identify gaps in the employee experience that are causing them to voluntarily choose to leave their jobs. At the same time, involuntary turnover can be traced back to the recruitment process. By understanding the reasons for letting people go, you can develop a strategy to improve the quality of recruited candidates.
HR analytics in recruiting can be helpful in identifying and attracting top talent. For example, HR can identify candidates that have similar competencies as high-performing employees. It can also help recruiters avoid casual biases and make competency related selections.
Here are some other metrics to keep an eye on when it comes to the recruiting process:
Time to fill is measured by calculating the number of days between creating a job requisition and filling that job opening. Knowing this can allow recruiters to be better prepared and allows for better resource planning.
Offer acceptance rate is the number of accepted job offers divided by the total number of offers extended by recruiters. To reduce this metric, strategies can be put in place to enhance the candidates' experience in the hiring process.
HR analytics can be used to measure metrics related to employees' levels of productivity such as absenteeism and revenue per employee.
Absenteeism is calculated by dividing the total number of absences by the total number of scheduled workdays. Not only does high absenteeism reduce productivity, it increases labor costs needed for staffing. It can also be an indicator of the workforce morale and satisfaction.
Revenue per employee is determined by dividing total revenue by the total number of full-time-equivalent employees (FTE). This tells you how much revenue each employee contributes to the bottom line on average. The benchmark for this metric can vary significantly from industry to industry. On its own, it is a productivity measure which allows HR professionals to understand the growth of the company. However, labor costs should also be taken into consideration to get the complete picture of the company's profitability.
HR Predictive Analytics
Predictive analytics is different than HR analytics in the way that data is applied. HR analytics is used to measure effectiveness and identify opportunities for improvement. On the other hand, predictive analytics uses data to make predictions about the future concerning individual employees or HR initiatives. This is also known as forecasting.
The process uses data mining techniques which takes historical data and uses it build a predictive model or an algorithm. The algorithm is then applied to new data to forecast future results.
For example, predictive analytics can be used for predicting employee performance over the next five years or whether an employee is at risk of leaving the company within one year of being hired. It can also be used to determine the impact of certain HR interventions such as a using social media profiles like LinkedIn as a selection factor in recruitment.
Collecting high-quality and reliable data is the first step to implementing HR analytics. This data is monitored and tracked, compared to benchmarks, historical information, norms and averages. Analyzing HR data also involves identifying trends and patterns which can be turned into actionable insights. To streamline HR analytics, many organizations choose to invest in analytics tools and hire business intelligence teams. What you learn about the workplace and your existing HR processes are opportunities for business leaders and HR professionals alike to transform your company’s HR department into a competitive advantage.