With finding and hiring top talents becoming more complex, it is only right that analytics play an active role in recruitment processes.
The recruitment industry has become a competitive field. The limited dose of top talent available has pushed companies to seek alternative ways to stay ahead of the curve.
One of the popular alternatives most companies now subscribe to is using some social platforms to source talent. Another alternative is using recruitment data analytics to determine the right candidate to hire.
But not all and sundry of the industry has adopted it.
Recruitment analytics has the potential to improve the quality of hires companies make. Recruitment analytics should no longer be on the edge of recruitment processes. Instead, it should be at the forefront as it can revolutionize recruitment, retention, and a company's growth.
We’ll like to pique your interest with a breakdown of what recruitment analytics is & why analytics and recruitment should go hand in hand. Tag along!
What is recruitment analytics?
Recruitment analytics uses statistical and predictive analyses to optimize top talent's sourcing, selection, and hiring.
Recruiters may use it to assess the efficiency and smoothness of their hiring process. In fact, it helps them discover deficiencies and recruitment areas that need improvement.
Recruitment analytics can help recruiters monitor plenty of data, for instance:
Time to hire
Time to hire refers to the time from when a job offer is made public to when a decision is finally made. Roughly speaking, it’s a measure of how fast the process of landing talent was. And when collecting enough data, recruiters can spot processes that take more than they should, thus accelerating the entire process.
Cost per hire
Cost per hire is a measure of the resources you devote to your recruitment process. With it, you can determine if you are spending too much or too little on recruitment.
Quality of hire
Quality of hire helps recruiters assess whether new hires are meeting expectations. When too many hires aren’t meeting a given set of criteria, a recruiter should realize that the employed practices aren’t doing well & may need to be changed.
Retention rate
The retention rate will help recruiters determine if they have been able to keep employees or if they are experiencing employee turnover.
Applicant-to-hire ratio
With this, you can determine if and how frequently your job offers are being accepted.
These metrics are frequently overlooked. But with the help of recruitment analytics, they have been brought to the forefront of recruitment. As a result, recruiters now make more informed selections during the hiring process.
The importance of analytics in recruitment
Data analytics entails gathering and analyzing relevant data. Replicating this in recruitment helps recruiters make better hires and forecast better ways to source and retain top talents.
Here are some of the ways analytics proves its importance in recruitment:
Helps build an effective recruitment strategy
Prioritizing recruitment data analytics helps recruiters make selected changes to guarantee that each stage of the recruitment funnel runs well. One would be able to predict and order how each stage of the recruitment funnel should go without any hiccups.
Also, applicants will get the best experience when your hiring process is smoother.
Improves employee retention
If a person is employed in a role that they are dissatisfied with, they are more likely to leave the job in the near future.
Data analytics aids recruiters in selecting the best candidate for a position. This enhances the likelihood of an employee remaining with a company, hence enhancing employee retention.
Employee data can disclose employees' interests, preferences, as well as their talents. With this type of data, recruiters can acquire insights into the best methods to keep employees engaged and thereby reduce employee turnover.
Minimizes hiring bias
Hiring bias prevents companies from acquiring the finest employees. On the contrary, recruitment bias can be overcome with data analytics!
Using artificial intelligence tools and monitoring metrics that focus on aspects affecting the job position can help make the right hire. It will erase sentiments like religion, gender, and race.
Also, data analytics can help hiring managers identify areas where they may be biased and pay attention to avoiding it during recruitment.
Determine future hiring needs
Data analytics can be used to predict future hiring needs. It can help recruiters determine whether teams need to expand or will require more hands soon.
This has compelled firms to make significant investments in predictive analytics in their hiring processes. Thus, giving them a chance to get ahead of the curve!
Improves the quality of hiring
Analytics can help recruiters find top prospects, make smarter hiring decisions, and increase the quality of hires. That’s because it gives recruiters a better understanding of what to look for when filling open positions.
With analytics, recruiters and HR managers can improve the hiring process and make it more efficient. It also helps save a lot of time since recruiters won't have to screen hundreds of people to identify the best fit.
Improves candidate sourcing
Recruiters can use recruitment data analytics to examine the quantity and quality of candidates from various job sites. With this data, you can spot and prioritize the platform that works best for your needs.
This process preserves resources and protects the company's time and cost-per-hire ratio.
Improves company brand
Aside from improving recruitment processes, recruitment analytics can also be a brand booster for companies.
Recruiters can run surveys to determine how candidates perceive a company. They can do a sentiment analysis by asking applicants to complete a survey. The replies will help determine if a company's brand value is positive and indicate areas that need improvement.
Final thoughts
It is clear that data analytics greatly influences recruitment. It can be what makes the difference and keeps you ahead of the curve.
However, recruitment analytics is not just about measuring data. You need to ensure you are collecting and measuring the right metrics your business needs. You also have to look for the right analytics tool; investing in the wrong analytic tool can send your efforts down the drain.