Recruitment analytics is becoming increasingly important as “job hopping” is becoming more acceptable and the tech turnover tsunami for each company is rising.
Human resource directors and recruiters are confronted with a challenge they haven't encountered in a long time: they must do the pursuing and impressing of candidates.
As candidates are becoming more aware of their possibilities to work from anywhere and new income flows, recruitment leaders have to pitch their opportunities in an engaging and spectacular manner.
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According to LinkedIn's 2022 research, the number of U.S. LinkedIn members who switched jobs grew by 37% in 2021. The research found that Gen Z workers (those born in 1997 or later) were the "most restless." Nearly 25% of those surveyed said they wish or intend to leave their present jobs within the next 6 months
So, What are Recruitment Analytics & how are they relevant?
Recruitment analytics enables organizations to hire faster using a combination of real-time data and predictive analysis. By focusing on data and algorithm-based forecasts about the hiring process, recruiters can make smarter judgments, cut waste from procedures, avoid personal biases, and improve the applicant experience.
Recruitment analytics play a key role in addressing these issues and making more informed, data-driven hiring decisions. Bersin's research has found that while 78% of large companies rate people analytics as “important,” only 7% rate their organizations as having “strong” HR data analytics capabilities.
So what do we analyze?
There are three key categories of talent-related data that may be evaluated:
1.People data
Data that consists of demographics, engagement & skills
2.Project Data
data that consists of attendance, acceptance, involvement in training and leadership programs, and the overall results of key projects.
3.Performance Data
Data that consists of performance evaluations from tools like Zoho Corp, Bamboo HR or Workday
What are the most important KPIs I should evaluate for my hiring data?
By utilizing technology and your company's data inputs to identify trends and predictors of future behavior and outcomes, predictive analytics may provide answers to these issues. This is how you can compile a recruiting report for your company. We will help you build an overall perspective of your whole talent pipeline, as well as detailed analytics on specific jobs and each stage of your hiring process. These are the metrics you must include-
- Source of candidates:
Which hiring platforms are the candidates coming from? Are they coming from employee referrals, job boards (e.g., Indeed, LinkedIn), the company careers page, third-party recruiters, etc? - Number of Applicants :
How many qualified applicants are there for each job opening? Are there more junk applicants? - Time to hire :
How long did it take to hire an applicant? Is any department taking longer than normal?
This gives insight into how the process may be improved and the effect it has on drop-off rates. - Cost per hire :
What are the internal and external costs associated with hiring? - Quality of hire:
How is the performance of the new hire compared to the previous hires? Is the quality of hires getting better? - Retention :
How long do your employees stay in your company? Is the attrition rate high or low? - Overall velocity of hires:
What percentage of your jobs are filled on time? - Applicant to hire ratio:
How many interviews and applicants are required to fill one job role? - Hiring frequency :
How often do you need to hire new team members - Rejection reasons :
How many candidates drop after the offer is sent? Why are they rejecting your job offers? This can help you tailor your offerings & figure out the reason for the leak. - Hiring Diversity:
This is an important metric to track for all companies now. How diverse is your company? Recruitment analytics tools can track workforce diversity and you must devise a method for tracking your hiring pools. - Overall conversion rates:
The percentage of candidates that progress from one stage of the hiring process to the next. Application to screening to interview to test project to offer acceptance.
The data may either be combined and displayed in the ATS (Applicant Tracking System) or exported into a data visualization engine like Tableau or Power BI from Microsoft. A lot of companies are also integrating AI into their hiring processes. According to Stand’s research report, by 2023, 77% of HR businesses are projected to employ AI for talent acquisition. Businesses can reform numerous HR procedures, including recruitment, turnover, training, talent management, and performance management, by utilizing the functions of recruitment analytics tools and solutions.
Using Data to Analyse & Predict
When you want to identify bottlenecks anywhere in my hiring process, or if you want to streamline and simplify those processes for greater efficiency and efficacy, Fastjobs is your go-to solution.
The dashboard successfully serves as a unified location for tracking applicant progress across requisitions within a certain time frame, as well as allowing me to give my team the knowledge and insights they need from a genuine talent adviser during the hiring process.
According to SpringRecruit, data-driven recruiting can save up to 23 hours of manual labor a week by pre-screening and shortlisting candidates. FastHQ.io is a new way to look at your recruitment metrics. You will be able to continually optimize your hiring procedures with this built-in dashboard and pre-screen the top 2% of tech candidates.
If you'd like to learn more about Fastjobs, contact us, and we'll show you how we can help you recruit, retain, and engage great people no matter what the market conditions are.
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