An inefficient recruitment process brings hires who impact your performance. Thus, you want to use every strategy in the book to attract suitable candidates. Have you considered using recruitment data? For instance, you can analyze the qualifications of successful hires for patterns to help you find candidates most suited for the new role. Additionally, such data can make your team more inclusive by eliminating subjective bias. Below, we discuss ways to use this data.

Tips on How to Leverage Recruitment

Data collected during various stages of recruitment is enormous. For instance, a company can collect sourcing data showing which channels candidates used. You can also track the time to hire, which explains how long candidates take from when they make an application to when you make an offer. You can use such data in the recruitment process in the following ways:

Analyze Sourcing Channels

Track all the sources of top candidates, and you may discover an interesting pattern. For instance, you may be spending on job boards, yet referrals are bringing you top talent. Doing this helps you prioritize channels to use for specific roles. Additionally, the talent acquisition software data can help you tailor job postings to platforms instead of using a generic one across channels.

Refine Candidate Screening

The data you collect over the years can help you refine your screening criteria. For instance, you can analyze historical data to highlight the top skills of managers hired in the past. It might reveal interesting patterns. Imagine finding out that all previous hires had certification in project management. It makes such a qualification a priority. Imagine also discovering that despite receiving applications from various external channels, you end up hiring internally. 

As such, promoted employees tend to fill most vacancies. It means you should reconsider using external channels and focus on internal job boards. You can use such data to automate screening. For instance, the criteria can be to shortlist all candidates with a diploma in project management. It helps you screen dozens of applications to shortlist only the ones that fit that criterion.

Track Time-to-Hire Metrics

A slow hiring process affects operations. Hence, track how long it takes from when you receive applications to when you give job offers. You might discover that some departments take longer to recruit staff than others. Such data can help you identify specific issues that affect hiring time. 

Maybe your candidate sourcing channels have limited reach, which reduces the number of candidates available for shortlisting. The whole process slows down until recruiters can achieve the targeted number of applications. Your metrics can also show that it takes too long for recruiters to schedule interviews.

Assess Candidate Quality

Candidate assessment continues even after successful hires join the company. The data you collect post-hire helps you improve the hiring process. For instance, find out if the candidate meets targets. Does the candidate meet KPIs? Do you need to retrain them to fit into that role? 

Another way to assess candidates after they take on the role is by examining how they fit into the team. Do they have suitable communication skills? Did you overlook their soft skills and end up with a hire who does not collaborate well?

Measure Hiring Diversity

Demographic data can show if your company is meeting its inclusivity goals. For instance, you may realize recruitment fails to target an underrepresented gender in particular departments, yet you receive diverse applications. Such data shows a likely hiring bias. It may be an intentional or unconscious decision by recruiters.

As such, the data helps you adjust the criteria they use to ensure they also screen and shortlist the underrepresented group. It can also help you evaluate recruiters to see where bias occurs and if there is a need to change recruiters altogether.

Forecast Future Recruitment Needs Using Predictive Analytics

Use historical data to predict emerging roles. For instance, your company may be expanding and creating roles for specific candidates. The company may also be adapting to market changes, which could result in some roles becoming redundant. Such data can help you adjust the job posting specifications to tap candidates with more advanced skills.

Analytics can also show industry trends. For instance, trends may combine some roles into one or create new roles out of traditional ones. One common change is in marketing. Do you need a digital marketer and a graphic designer as separate candidates? Should they also have web development skills? Or, is having one candidate with all of those skills more competitive?

Improve Candidate Experience

Use past hiring information to enhance candidate-company interactions. You want them to have a positive experience, as it can impact how the industry views you as an employer. For instance, data can show stages that frustrate candidates to the point of causing them to drop off.

It could be a lack of communication from recruiters. It could also be a lengthy recruitment process without clear steps. The data can also help you refine the techniques used to interview candidates. You want to select the ones that lead to the most hires.

Measure Offer Acceptance Rate

Your recruitment goal is to get candidates who accept your offers. However, you may not always get positive responses to job offers. Thus, use data to analyze how often candidates agree to work for you. It helps you understand if your offers are appealing.

Some candidates may even state why they refused your offer. Was it the salary? If it’s the package, inform the concerned departments to reconsider their compensation. Do more candidates decline offers because you took too long, and they received alternative offers from competitors? If that’s the case, adjust the recruitment workflow. Find ways to reduce the time to hire. Additionally, let candidates know how long they should wait.

Conclusion

Recruitment produces immense data. Use it to improve your decisions from how you screen candidates to when you make offers. For instance, select a suitable sourcing channel. The data can also help you improve your interviewing technique. If it’s inconsistent, it can cost you qualified candidates. Data also shows your inclusivity rate and whether a hiring bias is affecting your diversity.

Rajesh Kumar

I’m a DevOps/SRE/DevSecOps/Cloud Expert passionate about sharing knowledge and experiences. I have worked at Cotocus. I share tech blog at DevOps School, travel stories at Holiday Landmark, stock market tips at Stocks Mantra, health and fitness guidance at My Medic Plus, product reviews at TrueReviewNow , and SEO strategies at Wizbrand.

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