At the heart of the hiring process is a treasure trove of information about candidates—education, work experience, skills, values, work ethic, and more. But in order to ensure that recruiters hire the right person for a position, they need to make sense of this massive amount of data—and using intuition alone isn't enough to accomplish this.
That’s where data analytics comes in. The use of data analytics in recruiting is an effective and efficient way for recruiters to take advantage of the information they receive from candidates to choose the best hires, as well as increase the retention of employees in their organizations. And this approach is becoming increasingly popular among businesses: In fact, according to Human Resources Today, 78% of large companies report that they consider people analytics to be important, or even urgent.
Want to learn more about data analytics in recruiting and how you can benefit from incorporating it into your hiring process? Continue reading this article for the facts.
What Is Recruitment Analytics?
One way that data is employed by recruiters is through recruitment analytics, which is the use of information to make sound hiring decisions. During this process, recruiters use programs that help with the employee selection process by tracking, measuring, and analyzing candidate information to create a profile of prospective employees. Armed with this information, recruiters are able to speed up the process of shortlisting applicants who have the best profiles among the candidate pool.
What Exactly Is Predictive Analytics in Recruitment?
Predictive analytics in recruitment is another strategy that hiring managers can use in order to get the best results from the candidate information they have amassed. This approach allows recruiters to use data about job applicants to make predictions on the kind of employee they will be if hired. As a result, predictive analytics takes some of the guesswork and chance out of the hiring process and allows recruiters to choose the best candidates based on the specific criteria they define.
What Can You Measure and Improve Using Predictive Analytics?
Predictive analytics can be used to improve several areas of the recruitment process by measuring things like:
- - The most effective candidate sources, which is where recruiters find the most quality hires, whether it be from a specific job board, social media platform, or referrals from people that are known to them personally.
- - The efficiency of the candidate screening process, which includes how long it takes to screen and hire employees, as well as any factors that can slow down the hiring process. Also, predictive analytics provides a look at how much it costs to fill different roles, so organizations can make changes to the process in order to reduce costs.
- - The hiring needs of an organization, including when a specific role will likely need to be filled promptly and which ones will become vacant in the future.
How Can Data Analytics Be Used to Improve Employee Recruitment and Retention?
Not only does data analytics make the hiring process itself more efficient, but it also results in better hiring decisions, as well as employee retention, in numerous ways, such as:
- - Increasing the chances of choosing a quality hire. Data analytics recruitment programs make evaluations about potential employees based on their resumes, cover letters, social media activity, assessments, and pre-screening interviews. By processing all of this information, data analytics technology can determine if someone is a good or bad choice for a job.
- - Increasing diversity in the workplace. Since data analytics programs only look at information that is pertinent to a specific position, the chances of hiring people from diverse backgrounds increases because the process reduces the likelihood of unconscious bias being introduced into hiring.
- - Increasing the chances of employees staying at an organization longer. Using data can help an organization determine the likelihood that a candidate will stay there based on their employment and performance history. Predictive analytics can also give hiring managers an idea of how well a prospective worker is likely to perform in a position if they’re hired, or whether they will end up being fired.
Getting Started With Predictive Analytics in Recruitment
Predictive analytics is an effective tool for recruitment, but companies have to set themselves up for success in order to get the most out of them. To get started with recruitment analytics, organizations must know what metrics they need to track so the tool focuses on the right information. Also, recruiters should collect data that is relevant to making hiring decisions, format data visually in a way that makes it the most accessible, and create a plan for how the data will be used.
Recruiters handle a great deal of information during the hiring process, and data and analytics recruitment tools are an excellent way to manage it all and really use it to their advantage when making decisions. Also, the use of predictive analytics can give recruiters a glimpse into what they might expect when they hire a certain candidate, as well as get invaluable information on how to streamline their processes.
Want to learn more about implementing a data-driven approach into your hiring strategies? Jumpstart can help. By using our recruiter analytics tool, you will be able to understand your candidate pool, as well as the effectiveness of your job postings and events, in order to optimize your hiring strategies. In addition, our tool can help you increase the response rates of your messages to candidates and provide useful information to help company decision-makers create budgets. For more information on how Jumpstart’s recruiter analytics tool can help you meet your goals, contact us today.
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