“Is the pool big enough for me to hire candidates with the given criteria?”
“Why is there a sudden spike in employee attrition?”
“Has my offer to join ratio changed only this year or is there a trend?”
“Historically, which has been the best source for joiners?”
If you are an HR professional, you can easily relate to all these questions. In this age of social recruiting, traditional hiring alone is not enough to tackle these kinds of challenges.
Thankfully, advancements in technology have made it possible to harness a huge amount of data, with analytics now being applied in the recruitment field.
The term “data analytics” may seem daunting at first glance, but if leveraged properly, it can improve almost every area of HR and assist managers in making smarter decisions.
HR analytics offers many benefits compared to the traditional recruitment model.
The advantages of using analytics in hiring are numerous and can completely change a company’s approach to sourcing fresh talent. It allows a firm to spend resources, time, and effort more efficiently. Moreover, it also helps hiring managers attract the best individuals for their organization through measurable metrics and properly extracted data.
Let’s look at why it is high time to adopt data analytics in your end-to-end recruitment process:
1. Determining Hiring Criteria
The first step in any recruitment process involves defining the ideal candidate and identifying what skills, education, and experience are required for that open position. Data analytics helps companies improve their candidates’ understanding by providing a deeper insight into what they are looking for.
Data analytics provide benchmarking metrics for the company. HR can understand the hard and soft skills necessary for the job opening by looking at top-performing past hires. They can use this data model to establish appropriate qualifying and evaluation criteria for the job applicants.
2. Analysing Source Effectiveness
Next is the sourcing stage. Here, companies look for both active and passive candidates. Hence, they use a mix of various recruitment channels, including head-hunters, online job portals, social media campaigns, etc. As a recruitment manager, you need to understand which channels give the best return on investment. So, you’ll know where to put your energy, money, and time.
With data analytics in recruitment, it is possible to test various hiring sources and evaluate their success rates with more precision. By evaluating indicators like the number of responses received through each channel and the number of job offers sent to candidates through a specific channel, you can evaluate the effectiveness of every hiring source. You can also check the conversion ratio of individuals per role and use those channels to carry out further recruitment.
3. Screening the Candidates
Gone are the days when recruitment was dependent on the “hunch of the employer.” Now, HR professionals make data-driven decisions to find the right talent for their company so that there is less room for error and more predictability.
Usually, HR professionals have to look through a large number of resumes to determine which candidates are qualified. But with data and analytics, you create a data model that helps you match candidates and pick the ones that have the highest chances of selection.
Data analytics tools like the ATS software search through candidates’ profiles to help better gauge a candidate’s suitability. Of course, the final decision will be made by a human, but with data, you can save plenty of time by narrowing your search from hundreds of candidates to the most suitable ones. The saved time can be used by the hiring team to focus on other important tasks.
4. Assessing the Likelihood of Joining
So, you have interviewed the candidates and selected the one you want to hire. But what is the probability that they will join your company?
In this case, companies use predictive analytics to determine if the candidate would join and, if they did, what their possible average tenure would be.
Data analytics incorporates statistics, modeling techniques, and machine learning to predict what could happen in specific scenarios, like whether an employee joins the company, how well the employee will perform in the future, etc.
5. Increasing Retention Rate
Attrition and turnover incur a lot of expenses for the company. Hence, it becomes crucial for the company to understand how long an employee stays with them. And if they leave, what are the reasons for their leaving?
Analytics in recruitment can be used to answer these questions and create better strategies to retain employees and reduce turnover. It can also be used to figure out which employees are more likely to quit and which metrics lead to high turnover or attrition.
6. Boosting the Overall Employee Experience
Understanding your workforce is crucial to building an engaging team that serves a long way to the organization’s success. Hence, companies now use data and analytics to frequently measure their “employees’ pulse.”
HR professionals can obtain a better understanding of the overall employee experience by tracking metrics such as employee attendance, leaves, engagement, and productivity on a regular basis. This offers them an idea of where the organization stands and where it might need improvement.
It not only helps them devise strategies to keep their employees engaged but also develops a stronger employer brand.
For instance, it can help you determine how well the image that your organization projects align with the perceptions of the workforce. For example, a survey can be conducted to see how likely the employees are to recommend the company to others and the reasons for low recommendations.
Accordingly, you can make changes to your company’s culture and working policies to boost the overall employee experience.
Even if traditional recruitment has worked in the past for your company, embracing new trends and using data to your advantage could make a significant difference in your organization’s success. It will also make it easier to keep employees happy and make sure they are managed well so that business goals are met.