– By Sumit Sabharwal, CEO of TeamLease HRtech
The Human Resources division is in charge of making sure that the workplace is productive and that the workers are in a comfortable setting. The HR department typically maintains a record of every applicant and worker that works with them for this purpose, providing them with access to a sizable database of information about the labour force in their company. Whether structured or not, it is used to assess the workforce in order to offer more useful information and make better hiring decisions.
However, HR analytics is more than merely compiling statistics on worker productivity. By gathering data and using it to make informed decisions about how to enhance these processes, it seeks to give insight into each process instead.
HR professionals can use advanced analytics using HR technology to enable:
1. Better hiring: Employers can uncover successful features in their current employees by running machine learning algorithms on them. But doing so can also legitimise prejudices already present in the workplace. In order to ensure that unjustified prior prejudices based on characteristics like gender or ethnicity do not get incorporated into the decision-making, HR managers should examine machine learning outputs. Managers can tailor their brand marketing, outreach, and candidate engagement activities accordingly once they are aware of the ideal prospect for the organization.
2- Increased retention: HR executives can identify the problem’s fundamental cause and forecast when and why employees will quit with the use of attrition analytics. With the help of analytics, it is possible to identify trends in churn and identify employees who are most likely to leave. This can help HR control churn in a proactive manner and adjust their attrition rates. If certain difficulties lead to churn, such information can also help enhance onboarding, training, and performance management systems.
3- A deeper comprehension of motivation and output: Discovering the factors that influence motivation and output can aid in establishing HR strategy, which includes training, performance management, and other HR regulations. For instance, if it is possible to examine the productivity of remote employees, the company’s policy towards remote work might be improved.
4- Objective performance management: Mid-year reviews are dreaded because they are ineffective and subjective. Granular performance data can enable face-to-face reviews with data-supported face-to-face feedback that is objective, frequent, and automatic.
5- Better comprehension of corporate culture: HR managers can gain a thorough understanding of company morale and culture by using sentiment and network analysis of anonymized employee communication. Care must be taken to protect anonymity because this task necessitates the study of private and secret data.