How to Use Predictive Hiring to Improve Recruitment

by Mike Tannian on May 24, 2022

Learn how predictive hiring analytics can help improve traditional hiring practices, streamline candidate selection, and predict future job performance.

Article Highlights

Hiring for open positions in the public sector can be time-consuming, taking as much as 58 hours to fill one position. HR professionals spend most of their time sorting through résumés, only spending a few seconds perusing each one and quickly discarding those that don't quite match up with their expectations. Afterward, they conduct multiple phone screens just to create a candidate shortlist of people they would like to invite for an in-person interview.

From there, it's a matter of a few more interviews before making a final job offer to the best-fit candidate. It's a long, arduous process, and you have 20+ more positions to fill this quarter.

Predictive hiring tools can cut your traditional hiring process time in half, help you find the type of candidate you want to interview, and improve the overall candidate experience. Predictive hiring saves time and money, finds candidates that will fit into your company culture, and even helps you reduce your company turnover rate.

So, let’s discuss what predictive hiring is, how to use predictive analytics for hiring, and the benefits of predictive hiring technology.

What is Predictive Hiring?

Predictive hiring means applying data analytics to the recruitment and selection process of an organization. It's the use of historical hiring/recruitment data to predict future events, such as future job performance or possible hiring rushes.

With predictive hiring, also called analytical hiring, you can create a predictive model to find insights on possible events, pinpoint trends, and identify challenges. This way, you can prepare for these new events to avoid any difficulties when they happen or take advantage of a new trend before your competitors.

What are predictive analytics in recruitment?

Predictive analytics are also called recruitment analytics, which is just another term for predictive hiring. Different organizations use any of the terms to mean the same thing. 

Predictive hiring analytics allow companies to hire faster by examining historical and current data, and then extrapolating possible trends. It can also help you leverage real-time data to make sure you're meeting recruitment goals, increasing diverse candidate ratios, and improving your time to hire.

Predictive hiring analytics takes your organization's own data, including employee turnover and offboarding, to identify job applicants you'd like to interview. It also pulls data from unemployment rates, recruiting sites, job boards, and social media. The system then uses artificial intelligence to create a predictive algorithm that will help you anticipate future hiring needs and candidate availability. They’ll even identify passive candidates who aren’t actively job-hunting but would be a good fit for your open roles.

These systems can also examine your current candidate pool and recruitment funnel, make reports on things like EEO and diversity efforts, and show whether you're meeting your organization's goals to build a more diverse workforce.

Predictive hiring analytics are usually baked into applicant tracking systems (ATS), like NEOGOV’s Insight, where it can be used to find weak points and bottlenecks that are slowing down your recruiting process and eating up your budget. Depending on your predictive hiring software, you can save your organization countless hours per position in screening qualified candidates and scoring their degree of fit to create a shortlist of people to call in for interviews.

How to Use Predictive Analytics for Hiring

Predictive analytics has been around for quite a while. It's only in the last 10 years that we've been able to apply advanced data processing and artificial intelligence to the problem. And while predictive analytics for hiring used to only be the purview of large corporations with equally large budgets, now Software-as-a-Service providers like NEOGOV make it possible for smaller organizations and government agencies to take advantage of the predictive hiring model.

Use Cases and Examples of Predictive Analytics

There are several ways that predictive analytics can be used in the workplace. While some companies primarily apply them during the hiring process to help make an accurate hiring decision,there are plenty of ways to use historical data to improve recruitment.

Identify skill gaps in candidates and even current employees. You should already have your employees' résumés in your ATS, and you can turn the same analytical eye toward your colleagues as your candidates. The software can measure employee performance and identify where they need additional training and certification. Then, you can use your training management platform to deliver that to them.

Stop employee churn. Look for areas and departments that see a lot of employee turnover. You can work to identify the problem and fix it as well as start setting up new hiring plans to replace employees who are likely to leave. (Hint: Identifying these high turnover departments may also help you spot managers who need additional leadership training.)

Similarly, you can identify roles and departments with the highest accident/injury rates. This is another indication that you need additional safety training and protocols.

Increase your employee retention rate and engagement by analyzing top performers, predicting declining productivity, and identifying employee engagement.

Improve recruiting numbers. Predictive analytics can not only help you find more suitable candidates within your talent pool, but you can also measure the effectiveness of your current sourcing strategies, time to hire, cost to hire, and even whether potential employees will be more or less loyal to the company.

Why You Need Hiring Analytics Software

As we've learned over the last decade, the fields of finance, digital marketing, sales, and manufacturing can all benefit from constructive scrutiny under an analytics microscope. By using AI-driven analytics, it's possible to find patterns and potential issues before they would ever be obvious to a person. 

HR and recruiting can also benefit from hiring analytics. By making predictions about candidates based on patterns in their previous experience, you can uncover budding problems and stop bad hires before they can ever happen. Analytical hiring can also tell you if a particular candidate is going to be a valuable one, or find ideal candidates that you might have overlooked during a human review.

Understandably, this is often referred to as people analytics – and it can better equip your recruitment team to make informed decisions about candidate fit that lead to strong hires.

Benefits of Predictive Analytics

Predictive hiring analytics software can help government agencies work towards their targeted business outcomes while saving time and money, thus paying for itself and helping you reduce your recruiting budget. Here are a few benefits predictive analytics software can provide your organization.

Increase Quality of Hire

One thing predictive analytics in recruiting can do is help you identify suitable candidates much faster than traditional phone screening and reviewing résumés by hand. This helps ensure you won’t miss out on top talent because they were snapped up by another agency with a quicker time to hire.

You're able to apply metrics like current employees' productivity to your candidate assessments, which can help recruiters predict how successful candidates might be on the job.

This also means you're not left with second-tier candidates who may be less suited to the job or are missing some important qualifications. And you won't have to rely on gut feelings and end up choosing a lower-tier candidate. By using predictive analytics and a standardized interviewing process, you can find high performers and weed out a potential bad hire to make more consistent hiring decisions.

Decrease Time to Hire

We said earlier that predictive hiring can also save you as much as 30 hours in hiring for a single position. Consider the typical hiring process: You get 100 applicants for an open position and screen 50 of them, which takes 25 hours (at 30 minutes each). Next, you interview 20 of those candidates for an hour each (20 hours), then hold a second round of interviews for 10 candidates (10 hours), and then a third round of three candidates (three hours) before you finally make an offer.

That's a total of 58 hours spent trying to narrow down prospective employees and extend the job offer. (Of course, all this assumes that the long interview process doesn't scare off any candidates or your top candidate doesn't accept another offer in the weeks you spend interviewing for this one open position.)

Now, compare that to a system using predictive hiring analytics.

To begin, you can have job applicants complete self-assessments and use the predictive algorithm to narrow it down to the 20 most ideal candidates. Then, you conduct 30-minute phone screenings with all of them (10 hours), interview 10 of them in person for an hour each (10 hours), and narrow that down to your top five (five hours). Finally, you select your top two for one last interview (two hours) before you make a final offer.

Even with an extra round of interviews at the end, this process only took 27 hours and was likely weeks shorter than the first scenario, which relied on hand sorting résumés and phone screening twice as many candidates.

The predictive hiring system took 21 staff hours less than the traditional hiring practice, shortened the time to hire, and decreased the likelihood that your top candidate would be scooped up by a faster agency.

Lower Cost to Hire

The time saved by predictive hiring translates into lower costs, as well: If you could reduce the time spent on every position you hired by 27 hours, that translates into more than two-thirds of a reduction of one person's workload. Rather than bloating the HR budget with overtime and extra employees, you can keep your departmental numbers down by reducing time-to-hire and your recruitment team can perform their other job functions.

And that’s not all. Since people analytics helps you create a more effective and efficient recruitment strategy, you’ll see improvements across HR metrics in other areas, too. Notably, you can reduce your turnover cost – calculated at 150% of an employee's annual salary – by hiring the best candidate right off the bat. That means employees stay around longer, which means you're not spending more time interviewing more people to replace the ones who left. Which helps to… 

Reduce Attrition (Increase Retention)

Predictive hiring analytics can also reduce the turnover risk of each potential hire. The predictive analytics software, combined with candidate assessments, can help you predict which employees are at increased risk of resigning, and can even show you the potential cost of that resignation. You can also use predictive hiring analytics to target current employees for an increased retention campaign.

By reducing attrition, you reduce the need to hire new candidates and you don't need to onboard new employees – and you’ll likely see an increase in overall job satisfaction, too.

Find Gaps in Training

Since you already have your employees' résumés in your ATS, you can cross-reference that with your training management software. This helps you identify which candidates have skill gaps in their work history, as well as which ones are in danger of letting any certifications expire. 

You can also use predictive analytics to identify trends in skills shortages among your workforce. Predictive analytics software ensures you’re providing important training elements to fill any problem areas.

Make Better Candidate Offers

Are you seeing a pattern of candidates turning down your job offers? How do your salary and benefits measure up to the industry standards? 

It’s important to understand what similar jobs in the industry are going for and what kinds of employees are commanding those salaries. (Hint: The same ones you wanted to hire.) Predictive hiring can show you what your target salary should be to get candidates to bite on your job offers.

Eliminate Unconscious Bias

Hiring for "culture fit" can be a problem at times, as it can lead hiring teams to fall victim to unconscious bias. But predictive hiring software can help you eliminate those biases by helping you quantify and standardize those qualities. Then, the software can make sure each candidate fits the objective criteria without relying on a hiring manager's or HR manager's gut feeling.

Final Thoughts

Using predictive analytics in recruitment is the 21st century's answer to sorting through résumés by hand, trying to find the gems in a lot of coal. Since job openings can often get hundreds of applicants, it's easier to disqualify candidates for small reasons just to winnow the pool down to a more manageable number.

But with people analytics, you can save yourself the time of hand sorting and searching and set criteria that the predictive algorithm can use to find more gems in less time. This leaves you with fewer phone screenings and interviews, and yet you end up with a stronger roster of prospective employees for your organization.

NEOGOV's applicant tracking system, Insight, incorporates predictive hiring tools that will help you cut hours and budget spent recruiting for open positions. Insight also helps you improve the candidate experience, onboard new hires much faster, and create dozens of different compliance reports and EEO reports.

Learn more about how your organization can use predictive hiring to improve your recruitment process and reduce costs with our complete guide to data-driven recruiting and recruitment analytics.

Mike Tannian

Mike Tannian is the Director of Content Marketing at NEOGOV. With a talented team of writers by his side, he aims to produce content that delivers real value to public sector HR professionals at every stage in the buying journey.