While the 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 often 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

At the base of HR analytics is data. The wealth of data currently available to HR managers has increased exponentially in the past few years. As a result of high-performance HRIS and new technology such as employee tracking, HR managers now have a great deal of information at their disposal. Here is a list of the type of data that is commonly collected in organizations:

• 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 by 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 evaluating 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 identifying gaps in the employee experience that are contributing to voluntary attrition.
• Involuntary turnover rate: When an employee is terminated from their position, it is termed “involuntary.” The rate of involuntary turnover 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.

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 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

The people analytics company Sociometric Solutions 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%.

While it is easy to see the benefits of using this type of data which can lead to fantastic insights, there is also a legal and ethical angle to consider. How would you feel if your organization used these badges? What could the company do to make you comfortable with the technology? These are important issues to consider as technology is becoming more intrusive.