Nowadays, technology is everywhere we look. However, in companies all over the world there are still some departments that need to boost their efficiency and effectiveness, such is the case of Human Resources, that combine recruiting and staffing, benefits, compensation, employee relations, training and payroll.
Recruitment is key to IT companies like Polarising: for the past year, we have been working on a decision-support tool that will revolutionize the way these companies evaluate incoming candidates, and it has been very challenging and rewarding! By studying the integration of machine learning techniques in Polarising’s recruitment process, results are very promising.
I’m sure you’re familiar with the term but in case you’re wondering, machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.
The core idea of this tool is very simple; to process each collaborator cv in order to understand their overall attributes, a list of similar collaborators, open position rankings and group classification. The overall attributes represent candidate’s main characteristics, which will be verified against the list of similar collaborators resembling the evaluated candidate. As to the rankings, they analyse how adequate a candidate is for a certain job position and finally, the group classification represents the group to which the candidate is more adequate, based on his/her characteristics.
From a recruiter’s perspective, instead of analyzing the candidate just by its cv and make a decision based only on his/her understanding, extra and valuable information will be available in order to form a solid opinion and support the decision process of choosing the best candidate. With this tool, the recruiter just needs to fill the candidate’s technical skills and work experience in the system’s web application, instantly receiving a set of outputs generated by the system itself.
This said, it’s obvious for Polarising that our Recruitment process will benefit from machine learning, as it improves its efficiency. Performing a more deterministic procedure and finding structure and patterns in data, is the dream of any good recruiter in this area and we only go for the best! I hope this brief article can transmit the potential of machine learning to maximize your company’s processes too, it has certainly challenged me and my team.