We’re long past the days when the role of an HR was limited to merely filling up vacancies as and when required. In the current corporate scenario, HR has a much more substantial role to play. With the significance of the severe reliance on the workforce slowly being comprehended there is escalating stress on uncovering and engaging the most suitable talent.
The employees are no longer willing to limit themselves, being constantly on the lookout for better opportunities, hence making the responsibility of HR even more crucial. They are tasked with the duty of filling up the uninhabited positions, identifying and recruiting top talent as well as responsible for retaining them.
As the roles and responsibilities of the HR modify, there has also been a modification in their approach. The decision making which had once been guided by intuition and instinct has now become factual, relying on data analytics and algorithms for arriving at business solutions. (Since we are discussing decision making, explore the new approach of decision making, i.e., Fuzzy Logic)
The journey to Data-Driven HR
“It’s now moving from transaction to interaction” - Fast Company magazine
In other words, technology and data are now altering the way HR responds to both its employees and stakeholders. Over time, the organizations have started realizing the gravity of data’s significance in improving the human resources functions as well as in developing business analytics processes.
In the scope of this blog, you get to learn about the concept of HR Analytics, the metrics based on which the HR analytics data is measured, it’s features and challenges, and also briefly how HR Analytics has played an imperative role in removing gender bias in organizations.
You can also sneak a peek at our blog on People Analytics
But what is HR Analytics?
A simple way to define this term can be that HR analytics is a sector within the field of Analytics that is concerned with applying the process of analytics into the human resource department. This is done as an endeavor to improve employee performance and get a greater return on investment.
At the same time, the sector is not limited to enhancing employee performance but also provides an insight into each process by accumulating data and then makes pertinent decisions on how to boost these processes using this data. (Learn how such accumulated data is analyzed using Tableau and Power BI)
The data collected through HR Analytics offers a variety of benefits for the organization including;
To boost the hiring process of the company,
Reducing the rate of employee reduction,
Improving employee experience,
Making the workforce more productive,
Improving talent processes, as well as,
In gaining the trust of employees.
This data gets assembled from an array of sources across the organization which include employee surveys, their databases, attendance records, salary and promotion history, work history, personality data.
There are several common metrics on the basis of which HR analytics measures data and these broadly include :
The metrics based on which HR Analytics is measured
Revenue per employee i.e calculating the average revenue generated by the employee.
Offer acceptance rate i.e calculating the rate at which a firm’s job offers are accepted during a certain period.
Training expenses per employee i.e calculating the expense extended by the firm on each employee’s training.
Training efficiency i.e calculating the efficiency of employees post-training by assessing their performance and test scores.
Voluntary turnover rate i.e calculating the rate at which employees exit the organization voluntarily to identify the gaps in employee experience.
Involuntary turnover rate i.e calculating the rate at which employees exit the organization involuntarily to implement changes in the recruitment strategy.
Time to fill i.e calculating the number of days between advertising for a job opening and hiring someone to fill it.
Time to hire i.e calculating the number of days between approaching a candidate for a job offer and the candidate accepting it.
Absenteeism i.e calculating the number of days an employee is absent from work to get an insight into the overall employee health and happiness.
Human capital risk i.e calculating the employee-related risks such as lack of a particular skill to fill a new type of job.
On the contrary, while benefiting the organization in a variety of areas, HR Analytics also poses certain challenges that are required to be overcome to achieve the desired results. (Various agile software are deployed in the direction of smooth conducting o such huge processes independently).
These broadly include :
Lack of Data Analytics Skills: The organization often comes across predicaments while attempting to find people with the right skill set for the gathering, managing, and reporting of data.
You can also spare a glance at our blog on Data Analytics Consulting.
Data cleansing: It is crucial for data to be collected, cleansed, merged, and evaluated from numerous departments as well as a multitude of business functions, making the need for experts who can properly gather and organize the data alongside evaluating it highly imperative.
Excess of Data: Often excessive data is collected leading to too much data to parse and a lack of clarity on which data is more imperative.
Data privacy and compliance: As data is collected regarding an employee or potential employee the privacy of the same needs to be kept in mind as violating the privacy of its employees could get the company in trouble.
Deciding the tools: There may be a lack of clarity while identifying the most suitable HR technologies for keeping track of the data.
HR Analytics’s role in reducing gender bias
“People working at companies often see HR as the key agents of change when there’s a problem like a lack of women in leadership. So if HR isn’t committed to gender diversity and isn’t championing it, the needle won’t move.” - Ursula Mead, CEO and founder of InHerSight
1. HR using Artificial Intelligence
The application of artificial intelligence (AI) by HR during hiring has the potential to prove a solution for getting rid of gender bias which could surface in hiring practices. AI tools look at the characteristics that make a person excel in a role, thus making the HR repeatedly choose professionals that fit into those characteristics.
For instance, an AI tool scans various career sites tracking systems for applicants to find candidates and remove their names from the process to reduce bias. It also goes on to create a profile specifying the characteristics of an ideal candidate based on data and scoring the applicants against the ideal profile.
At the same time, there are various drawbacks to this method. For instance, if the majority of resumes offered to create the ideal profile consisted of men it will cause the tool to discriminate against women. Thus AI has to be used in a very structured and vigilant manner for it to be effective. (You can also take a look at our blog on Emotional Artificial Intelligence)
2. Databases shed light on the gender gap
A solution can only be produced when there is an awareness of the problem. What if HR is not even aware of the gender bias existing in their company due to not being regularly exposed to each segment of it?
This is where the relevance of Data comes into play. The data analytics platform can display relevant statistics like the detailed gender dissection in every department and section of the company. This database thus helps HR stay updated regarding the state of their company and make them aware of the sections where gender bias is prevalent.
3. Delving regularly through general data illuminates relevant social issues
The gender gap is often discussed by wage discrepancies cited in various public outlets. Understanding and staying updated on how the society at large is operating with reference to gender bias helps the HR to ensure that these mistakes are not repeated in their own firms.
“I believe that the data will set you free. At the end of the day, it’s about how you turn those pieces of information into insights that will improve business.” – Steven Rice, Executive VP, Human Resources, Juniper Networks
With the world increasingly advancing towards a more data-driven approach, HR analytics is leading the way towards guiding the talent, management, and recruitment decisions of all small and large scale organizations. Data Analytics added in the HR’s workings has considerably aided in their accuracy and boosted the efficiency of their functions.