If our goal is to put the right people, at the right time, in the right jobs… how are we determining who the right people are? And how many candidates are we not even considering simply due to lack of time?
Research by Oleeo has found that the average time from apply to hire runs at 6 weeks with little variation by industry segment, and involves an average of 91 actions in the hiring funnel. This means that, for many employers, numerous applicants aren’t even considered, due to recruiter time constraints and high volumes of applicants.
At the same time, human bias is built into the selection process: recruiters and hiring managers bring both objectivity and subjectivity to the table when reviewing candidates, and - even those with the best intentions - can down-select candidates influenced by those biases.
Objectively, candidates may be screened based on “hard data” related to their educational background, work experience, location, and so on.
Subjectively, candidates may be screened on keywords that the recruiter or manager feels indicate a fit for the role, and on biases related to factors such as name, nationality, gender, age, and so on.
The result of these factors - lack of time, high volumes of applicants, and human bias in selection - is a narrower, less diverse pool of candidates being considered.
This is where the use of intelligent selection - the use of artificial intelligence and data science - comes in, providing a way to widen the pool of applicants considered, while also removing bias from the selection process.
Instead of relying solely on humans for selection, intelligent selection uses data science, applying machine learning to historical data - such as the resumes/CV's of past applicants coupled with outcomes like hires, retention, performance, etc. - to score candidates. Candidates with top scores can be fast-tracked to the interview stage, while recruiters further assess the lower scoring candidates.
Done well, using well-designed algorithms that have been checked and validated, intelligent selection helps companies consider a wider, more diverse pool of candidates, and increase diversity in hiring, without introducing adverse impact - defined by the US Equal Employment Opportunity Commission as "a substantially different rate of selection in hiring which works to the disadvantage of members of a race, sex, or ethnic group."
Oleeo Recruit includes Intelligent Selection, a machine learning capability that leverages your historic data and advanced analytics to automatically score candidates for selection, while removing bias from the equation.