Recruiting in the past used to rely mostly on luck and intuition, from searching adverts in the newspaper or hunting down top workers around the globe, today's market has a whole other process of finding top recruits. The technological growth of software and analytic tools has provided scouts with new recruiting opportunities and a much more analyzed process.
Data-driven recruitment is better in so many ways: it's quicker, more accurate, helps find worthy candidates for a job, saves money as well, and a vast benefit of data-driven hiring is the personalization process, which can help boost recruitment efficiency.
A survey shows that about 50% of respondents said they declined a job offer because the recruitment experience was poor. This percentage is so high due to many companies that don't use data to find a special approach to candidates.
Data-driven recruitment refers to using a variety of data sources when making an objective hiring decision. The data recruiters use is an extension to the usual resume screening, interviewing, and extending job offers. Furthermore, then just supplying extra information about candidates, data can eliminate the guesswork and biases to ensure the best candidate is selected.
A great place to start implementing data is to figure out what data your already implementing through other technologies and then figure out what other data would be helpful. Here are some practices to apply to your business to shift toward data-driven recruiting:
There are various metrics for companies to track, like quality-of-hire, cost-per-hire, etc., but to start with, a company should choose a few. Different industries might want to pay attention to different data, it all depends on what the company cares about. A metric that almost any company can benefit from is quality of hire since it shows the overall effectiveness of the hiring process.
Even though data can save you a lot of time during the hiring process, the collection of data can often be time-consuming. To simplify that process, you can look into using various software like ATS or other ways via Google Analytics or simple surveys.
Even a team that chooses to hire based on intuition can track data and see a recurrence of similar people, interests, or approaches. By tracking the statistics of recruitment, you can also figure out what data is useful for you and which data isn't even worth collecting.
This isn’t so much of a practice, it's rather a tip you should understand when dealing with data.
The world of recruitment has changed dramatically over the past few decades; intuition was replaced with data, while hiring methods were replaced with software and tools. Here are some benefits of adopting a data-driven approach in recruiting:
Data can shine out the constrictions which are holding back the hiring process. A team can then work to remove or automate these elements. Recruiters can reduce their time looking for potential candidates by up to 80%. For example, if you have insights on application drop-offs, you can make these applications much easier at the start and, during the further process, little by little, collect the vital information you need.
You can reduce hiring costs in two main ways. Since data-driven recruitment is much faster, you'll need fewer costs for the recruitment budget. With data, you can track what hiring processes you need. There might be a whole team of people dedicated to a hiring process that doesn't even play a beneficial role in hiring talent.
Try to imagine you're a candidate for a job, you get a bunch of emails from different companies, and most likely, a personalized email is what's going to catch your attention. A report published by Experian shows that 50% of companies noticed that by using personalization, they can increase interaction within the email.
Implementing a data-driven recruitment process takes way more than just some data, it's the combination of gathering the right data and knowing how to implement it within your company. You need a mindset change to start working with data in a way to fully benefits from implementing better practices into important processes.
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