Employers no longer have to rely solely on their experience and instincts when making a new hire. Thanks to the rise of user-friendly data analysis software, it’s increasingly easy for HR professionals to make smarter and faster recruitment decisions.
What does “data analytics” actually mean?
“Big data” is a term used to describe very large data sets. “Data analytics” is the practice of collecting, cleaning, and transforming data to discover useful information.1 You may analyse data you have collected internally, data found online, or both.
Insights from big data allow you to solve various hiring problems. For example, they can help you choose the right candidates from a vast online talent pool, or select recruiting channels that give you the best ROI.
What are the benefits of data-driven recruitment?
Data-driven recruitment helps you make informed decisions at every step of your recruitment process. For example, by looking at your existing employees’ performance data, you’ll learn exactly which qualities you need to look for in a new hire for a similar position.
With this knowledge, you can refine your selection criteria and assessments. For example, if you discover a reliable link between employee performance and their scores on a test you use as part of your hiring process, you have proof that the test is useful.
By using data-driven hiring, you make yourself more valuable to your organisation.2 Instead of merely providing raw figures and relying on your judgment to make new hires, you will be in a position to make long-term, strategic hiring recommendations.
You can also use data to help you build a good reputation and strong employer brand, which will attract the best candidates.3 Analysing how people describe your brand online – for example, by looking at the words they use, and how often they use them – gives you a real-time picture of your reputation. Social media posts and company review sites like Glassdoor are valuable sources of data.
Data analytics can save you money. When you collect data on the number of hires made through each recruitment channel you use, you are in a better position to refine your strategy and make more costeffective hires. You’ll soon realise which platforms are offering you the best ROI.
Finally, data-driven hiring can reduce bias. If you can justify your hiring decisions with objective facts and figures, you may be better-protected against accusations of unfair hiring practices or discrimination.4
4 ways to leverage data in your hiring process
Start by choosing a user-friendly tool that makes it easy to store, access, and analyse your data. You may already have a suitable Applicant Tracking System (ATS) or database that records key metrics, or you might need to invest in specialist analytic software. Once this is in place, you can then start leveraging data.
1. Build a talent pool
Use existing performance data to establish which skills and experience your perfect hire should have, then use the job criteria as a starting point to search for the best talent. Use keywords to filter through online profiles. Tweak your searches until they return your star candidates’ profiles. That way, you know that your method will connect you with the right kind of candidate, allowing you to take a more proactive approach to recruitment.
2. Reduce time-to-hire
Recording total time-to-hire is a good start when you’re trying to improve your hiring process, but looking at the time between each step is more helpful. You can then identify weak points and adjust your strategy accordingly. For example, if there is a noticeable lag between the initial application and phone interview stages, this suggests your employers are not processing applications effectively.5
3. Understand what your competition are offering your ideal candidates
Your ideal candidates are unlikely to apply if they can get a better salary elsewhere. Glassdoor allows you to compare your company to your direct talent competitors across a range of data points. Collect and analyse data on your rivals. Competitive intelligence can also give you valuable insight into the kind of language your competition uses. Use this information to write descriptions that resonate with your target group.6
4. Prioritise your metrics
As a recruiter, data collection and analysis should be a regular part of your job. However, collecting data isn’t helpful unless it’s relevant to your business goals. Before you invest time analysing any metric, check that it aligns with your broader vision. For example, if your business has a problem with employee turnover, then retention and new hire performance data should be your priority. If your main concern is improving diversity among your workforce, these metrics probably won’t be so important.
In summary, data-driven recruitment makes it easier to whittle down the candidate pool, retain the best talent, and build your reputation. When used in conjunction with human expertise, it can save your business time and money.
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1. Southern New Hampshire University. (2016). What Is Data Analytics? snhu.edu
2. Moore, J. (2018). A Modern Take on Data-Driven Recruiting from a Google Recruiting Leader. hire.google.com
3. Marr, B. (2018). Data-Driven HR: How Big Data And Analytics Are Transforming Recruitment. forbes.com
4. Bika, N. (n.d.) Data-driven recruiting 101: How to improve your hiring process. resources.workable.com
5. J Moore, J. (2018). A Modern Take on Data-Driven Recruiting from a Google Recruiting Leader. hire.google.com.
6. LinkedIn Talent Solutions. (n.d.). Data Driven Recruiting. business.linkedin.com