Understanding the process of HR Analytics
HR Analytics is made up of several components that feed into each other.
- To gain the problem-solving insights that HR Analytics promises, data must first be collected.
- The data then needs to be monitored and measured against other data, such as historical information, norms or averages.
- This helps identify trends or patterns. It is at this point that the results can be analyzed at the analytical stage.
- The final step is to apply insight to organizational decisions.
Let’s take a closer look at how the process works:
1. Collecting data
Big data refers to the large quantity of information that is collected and aggregated by HR for the purpose of analyzing and evaluating key HR practices, including recruitment, talent management, training, and performance.
Collecting and tracking high-quality data is the first vital component of HR analytics.
The data needs to be easily obtainable and capable of being integrated into a reporting system. The data can come from HR systems already in place, learning & development systems, or from new data-collecting methods like cloud-based systems, mobile devices and even wearable technology.
The system that collects the data also needs to be able to aggregate it, meaning that it should offer the ability to sort and organize the data for future analysis.
What kind of data is collected?
- employee profiles
- performance
- data on high-performers
- data on low-performers
- salary and promotion history
- demographic data
- on-boarding
- training
- engagement
- retention
- turnover
- absenteeism
2. Measurement
At the measurement stage, the data begins a process of continuous measurement and comparison, also known as HR metrics.
HR analytics compares collected data against historical norms and organizational standards. The process cannot rely on a single snapshot of data, but instead requires a continuous feed of data over time.
The data also needs a comparison baseline. For example, how does an organization know what is an acceptable absentee range if it is not first defined?
In HR analytics, key metrics that are monitored are:
Organizational performance
Data is collected and compared to better understand turnover, absenteeism, and recruitment outcomes.
Operations
Data is monitored to determine the effectiveness and efficiency of HR day-to-day procedures and initiatives.
Process optimization
This area combines data from both organizational performance and operations metrics in order to identify where improvements in process can be made.