While HRIS is responsible for collecting and organizing HR data, HR analytics is the process of analyzing this data in order to improve an organization’s workforce performance. The process can also be referred to as talent analytics, people analytics, or even workforce analytics.

HR analytics: HR analytics specifically deals with the metrics of the HR function, such as time to hire, training expense per employee, and time until promotion. All these metrics are managed exclusively by HR for HR.

People analytics: People analytics, though comfortably used as a synonym for HR analytics, is technically applicable to “people” in general. It can encompass any group of individuals even outside the organization. For instance, the term “people analytics” may be applied to analytics about the customers of an organization and not necessarily only employees.

Data

• Employee surveys
• Telemetric Data
• Attendance records
• Multi-rater reviews
• Salary and promotion history
• Employee work history
• Demographic data
• Personality/temperament data
• Recruitment process
• Employee databases

Revenue per employee: Obtained by dividing a company’s revenue by the total number of employees in the company. This indicates the average revenue each employee generates. It is a measure of how efficient an organization is at enabling revenue generation through employees.

Offer acceptance rate: The number of accepted formal job offers (not verbal) divided by the total number of job offers given in a certain period. A higher rate (above 85%) indicates a good ratio. If it is lower, this data can be used to redefine the company’s talent acquisition strategy.

Training expenses per employee: Obtained by dividing the total training expense by the total number of employees who received training. The value of this expense can be determined from measuring the training efficiency. Poor efficiency may lead you to re-evaluate the training expense per employee.

Training efficiency: Obtained from the analysis of multiple data points, such as performance improvement, test scores, and upward transition in employees’ roles in the organization after training. Measuring training efficiency can be crucial to evaluate the effectiveness of a training program.

Voluntary turnover rate: Voluntary turnover occurs when employees voluntarily choose to leave their jobs. It is calculated by dividing the number of employees who left voluntarily by the total number of employees in the organization. This metric can lead to the identification of gaps in the employee experience that are leading to voluntary attrition.

Involuntary turnover rate: When an employee is terminated from their position, it is termed “involuntary.” The rate is calculated by dividing the number of employees who left involuntarily by the total number of employees in the organization. This metric can be tied back to the recruitment strategy and used to develop a plan to improve the quality of hires to avoid involuntary turnover.

Time to fill: The number of days between advertising a job opening and hiring someone to fill that position. By measuring the time to fill, recruiters can alter their recruitment strategy to identify areas where the most time is being spent.

Time to hire: The number of days between approaching a candidate and the candidate’s acceptance of the job offer. Just like time to fill, data-driven analysis of time to hire can benefit recruiters and help them improve the candidate experience to reduce this time.

Absenteeism: Absenteeism is a productivity metric, which is measured by dividing the number of days missed by the total number of scheduled workdays. Absenteeism can offer insights into overall employee health and can also serve as an indicator of employee happiness.

Human capital risk: This may include employee-related risks, such as the absence of a specific skill to fill a new type of job, the lack of qualified employees to fill leadership positions, the potential of an employee to leave the job based on several factors, such as relationship with managers, compensation, and absence of a clear succession plan. HR analytics can be used to measure all these metrics.

Analytics and the law

The sort of data collection that HR analytics uses is governed heavily by compliance laws. Some legal considerations to keep in mind when implementing an HR analytics solution are:

1. Employee privacy and anonymity
2. Consent from employees about the amount and type of data being collected
3. Establishing the goal of data collection and informing employees accordingly
4. IT security when using third-party software to run HR analytics
5. Location of the HR analytics vendor – with whom the data will be stored – and their compliance with local laws

People analytics company Humanyze offers electronic badges that capture information from employee conversations as they go about their day, including the length of the conversation, the tone of voice involved, how often people interrupt, how well they show empathy, and so on. Using this technology, a major bank noticed that its top-performing call centre workers were those who took breaks together and let off steam collectively. Based on this knowledge, the bank implemented group break policies. The result? Performance improved by 23% and stress levels dropped by 19%.