Data-driven recruitment is big in the recruitment tech world right now. A survey conducted by LinkedIn found that 69% of companies believe that data-driven recruiting will become the standard in the near future. Data driven recruitment is something that any hiring manager or recruiter needs to take note of to streamline & enhance their hiring strategy as well as to have access to top talent and be at the forefront of recruitment tech.

What is data driven recruitment?

Data driven recruitment is a process of leveraging data and analytics to make more informed decisions about hiring the best candidate for a job. With the help of big data and analytics, companies can optimise their recruitment process, increase efficiency, and reduce hiring costs.

In fact, a study by McKinsey & Company found that data-driven recruiting can improve the quality of hires by 54%, reduce time to hire by up to 50%, and lower recruitment costs by up to 30%. How to implement data driven recruitment?

1. Use predictive analytics to identify the right candidates

One of the primary benefits of data-driven recruitment is the ability to use predictive analytics to identify the right candidates.

Predictive analytics use algorithms and machine learning to analyse data and predict future outcomes. In Layman’s terms, by using data based on the past, we can make adjustments to improve the future! By analysing data on successful candidates, such as their skills, education, experience, and personality traits, we can identify patterns and use them to predict the best candidates for future job openings. This can mean saving a lot of time that would otherwise be spent on interviewing and screening candidates who may not be a good fit.

2. Monitor the effectiveness of job postings

Another way that companies and recruiters can use data-driven recruitment is by monitoring the effectiveness of their job postings.

By tracking metrics such as the number of views, applications, and hires for each job posting, we can identify which job sites and channels are the most effective for reaching their target audience. You can then use this data to optimize your recruitment strategy and improve job adverts to attract more qualified candidates.

In the same token, if you are wanting to cut down the cost of job boards and drive more traffic to your website, you can implement a strategy to do this such as creating an engaging careers site and enhancing your employer brand and then track the metrics of your website traffic to see the progress and adjust your recruitment costs.

3. Use objective data to reduce bias in the recruitment process

Objective data in recruitment means using information that is measurable and verifiable to assess a candidate’s suitability, such as a candidate's test scores or job performance metrics. By using objective data to evaluate candidates, companies can eliminate biases that may exist in traditional recruitment methods. For example, subjective opinions about a candidate's qualifications can be influenced by unconscious biases, such as a preference for candidates who share similar backgrounds or experiences.

By using objective data in recruitment and relying on verifiable metrics rather than subjective opinions, you can create a more fair and inclusive hiring process. This can lead to a more diverse and inclusive workforce, as candidates are evaluated solely on their qualifications and skills, rather than their personal characteristics.

A simple way to bring in objective data is to create and use scorecards to rate skills and experience, taking the guess work out of potential performance.

Conclusion

Data-driven recruitment is an effective way to optimise your recruitment process, increase efficiency, and reduce costs.

By using predictive analytics, monitoring the effectiveness of job adverts and using objective data, you have an upper hand at identifying the best candidates, building a diverse workforce as well as speeding up your hiring process in a cost effective way.