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Data-Driven Recruitment: What It Is and How to Use It

Recruiting is a crucial aspect of any company. People are a company’s most valuable asset, and so recruiting them is an essential task. When it comes to attracting top talent, recruiters must use cutting-edge technology solutions to better their odds of success and reduce expenditures. Recruiters that use data have a greater chance of doing well and saving money than those who don’t. It is estimated by CognitionX that the cost of hiring candidates could be reduced by up to 71% and improve recruiters efficiency up to three times. 

There are several types of recruitment technologies that utilise data, such as Applicant Tracking Systems (ATS), Recruitment CRMs, HR Analytics and Recruitment Marketing software. Each of these perform various different functions from candidate management to managing the candidate application system. 

In one of its most simple forms, data is used in ATS to filter candidates. ATS manages the application process digitally, automating the process of filtering candidates via their attributes. These attributes include previous work experience, location, tangible skills in different technologies and the probability of them accepting the offer. Using data to deploy data-driven recruitment, you can effectively sort through many applications for applicants that fulfill your criteria and easily streamline the recruitment process. This will effectively reduce manual time required from HR professionals, allowing them to allocate it to more valuable tasks. According to Getapp, 86% of recruiting professionals say that using an ATS has helped them hire faster.

Recruiters who stick to data-driven recruitment use tangible facts and statistics to influence their hiring decisions, from selecting people to creating recruiting strategies.

How does data-driven prospecting in recruitment work?

Data-driven prospecting in recruitment entails gathering, measuring, collating, and analyzing candidates, as well as employee data in order to efficiently hire the candidates best suited to your firm. According to Linkedin, talent acquisition teams with mature analytics are 2x more likely to improve their recruiting efforts through reducing time and cost. 

To effectively recruit, you need to determine traits that reflect your ideal candidate. This might be 3-5 different characteristics including but not limited to previous experience, skill set and personality. To determine these characteristics, you can look internally to your best employees to determine ideal traits. This will largely help standardize your recruiting when seeking in house human resource departments or externally outsource your recruiting to a recruiting company during high volume seasonal periods. 

Here are some ideal candidate traits that you can seek to set: 

Location – If not a remote position, geography can be important in determining the probability of the candidate accepting your job. Additionally, location can be reflective of a specific subset of knowledge. For example, if you were seeking lawyers who specifically were well versed in US laws. 
Skillset – Skillset of individuals can be indicative of how well an individual performs in a role. This is particularly relevant for highly technical roles. 
Time in role – Knowing the time a candidate has been in a position can be a great indication of how likely they are to accept a new position. Holding a position for longer (12+ months) greatly increases the likelihood that they would switch. 
Job titles – Titles are reflective of the experience an individual holds. 
Previous work experience – Previous work experience can assist in validating their ability to do transferable tasks, qualification for the job and basic understanding of the work environment. Looking at your existing employees and their previous work experience can also help determine which organizations you may have better success sourcing from. 
Technology the candidate has used in previous work – Knowing the technology the candidate previously has experience with can be indicative of the skills they have. Again, this is particularly important for jobs that work with highly technical and sophisticated technologies. 

As a recruitment firm, setting these ideal candidate traits will only help your current portfolio of clients. To improve your opportunities of getting new clients, you need to search for businesses who are hiring roles that you have a portfolio of strong candidates for. This way, by being more intentional, you can bring on more clients by making more placements. Further, data such as where your client usually sources from, live jobs data and hiring trends will all help you gain an edge over the competition. 

What is more important than the data itself is being able to react in real time when information is available so that you can act first. Given the volume of data that exists on the web and the different sources you need to pull, it can be very difficult to collate together. Thus, there are different recruitment technologies out there that assist in pulling all of this information and alerting you when your specific criteria is met, allowing you to reach candidates first. 

Benefits of data-driven recruitment

Historically, recruiting was heavily reliant on job boards, careers pages, social media and referrals. This left a very large talent pool that was not necessarily targeted. 

There are many benefits of data and how it can help your recruiting team: 

Make more informed decisions – When choosing between candidates, using data-driven recruitment can help remove bias when making decisions. Specific bits of data will place one candidate ahead of another such as previous technology their firm adopted that might make the transition to a new job easier. Recruitment data will help you holistically rank your candidates to make unbiased decisions
Reduces bad hires & improves ROI – Data on previously qualified candidates can help you improve the quality of hire going forward. Getapp research shows that 78% of recruiters who use an ATS have improved the quality of candidates they hire. This will ultimately improve the ROI on candidates, as bad hires can be extremely costly. The U.S. Department of Labor estimates that the average cost of a bad hiring decision is at least 30 percent of the individual’s first-year expected earnings.
Better manage timing in the hiring process – With data-driven prospecting, stakeholders such as your HR team, candidates, and management will better understand timelines. This is because they have better decision making frameworks and forecasted work loads. Estimated times for different processes will be able to be calculated. Overall, this will improve your candidate experience when getting new hires. Thus, this will in turn improve the acceptance rates from candidates. 
Make future forecasts – Understanding what the future pipeline of talent is will significantly help smooth your recruiting efforts. It will allow your organization to properly prepare budget, allocate time, resources and frequency. Using the correct data points can help your team choose the correct recruitment channels and improve the overall hiring funnel. 
Better employee retention – Data such as predictive analytics can be used to determine culture fit. Assuming that this data is used, culture fit can help improve employee retention, as the fit extends beyond just a job description, reducing turnover rate. Retention will also ultimately help improve your overall employer branding and reduce future hiring costs. 

Future of having a data-driven recruitment strategy

Prospecting in recruitment is a very complex activity that requires various tasks at different levels and stages. By operating in a data-driven environment, it can greatly enhance the process, specifically during prospecting. If they manage to unlock the potential data has for the recruitment space, firms may hire better quality candidates, reduce costs and hiring time.

Data will be a great benefit to any hiring team, even one that is comfortable making decisions based on intuition. Data will assist them in seeing what worked and what didn’t in prior hiring processes so that they may improve future hiring decisions.