Recruitment has long relied on personal judgement but with the rise of Big Data, it’s time we made decisions based more on numbers and less on our gut feeling. Sadly, only 14% of HR departments feel confident enough to analyse data and only 4% of those use it for predictive purposes.
What is predictive recruitment?
Predictive recruitment analytics looks at a wide array of candidate data from sourcing channels, social media, ATS and assessment tools, and helps recruiters optimise their hiring campaigns and improve talent quality moving forward.
There are two key conditions to mastering predictive analytics:
- Having access to the right and accurate data
- Having the necessary skillset to analyse the data and use it to generate return on investment
With the right analytics tools in place, the data will come easy. It’s just a matter of making sense of it all.
What are the benefits?
Data analysis across the entire recruitment process can improve candidate quality and satisfaction, as well as saving time and money. Here are some examples of how data can optimise your recruitment:
- Social engagement rates and sourcing channel application rates can help identify the best routes to the right talent pool
- Data from psychometric tests can improve decision making and identify the best skilled candidates during assessment
- Candidate drop-out rates and a post-application survey can help improve the candidate experience
Predictive analytics has the potential to eliminate discrimination from recruitment, by offering an objective review of the candidate. That is not to say recruitment should only be based on hard data, though! By automating the initial selection process, recruiters will have more time to focus on the softer skills of shortlisted candidates.
Be one step ahead of your competitors! Join our breakfast on 1st November 2018 at the Goldmsith’s Centre in London to get expert insights to master predictive recruitment.