Assessing Culture Fit Without Assessments

Assessing Culture Fit Without Assessments
From Recruiter - November 17, 2016

While working in the executive recruiting field, Chris Daniels ran into an all too familiar problem.

Wed source about 100 people for a role, and when we gotdown to the last two or three candidates, it was always frustrating, Daniels says. We had a good recruiting team, but Id do a lot of interviews where the resume and LinkedIn profile looked good, but when I would get on the phone with someone, I knew in the first five minutes they wouldnt be a fit with either the hiring executive or the company.

Often, when faced with cultural fit issues, recruiters and hiring managers turn to assessmentsbut Daniels and his team were already using assessments. The problem was those assessments were coming too late in the process.

Itsgreat to have assessment tools at a much later stage of the process, Daniels says. But I wondered if there was any technology we could use to assess a large candidate pool for culture fit so that we could prioritize and rank them. That way, the chances were better that when I got on the phone with someone who looked good on paper, they would actually be a fit.

And so, Daniels drew on his previous experience in theenterprise software and big data field to create Candidate.Guru, a culture fit prediction engine that uses artificial intelligence and big datato determine candidates potential culture fits without requiring every single applicant to go through an assessment process.

Culture Fit at the Top of the Funnel

Daniels stresses that Candidate.Guru doesnt exactly compete with or replace more traditional assessments, which come at the end of the recruiting process when the field has been narrowed down significantly. Instead, Candidate.Guru acts as a sort of first line of defense against bad fits by evaluating cultural alignment at the top of the funnel. That way, recruiters and hiring managers can spend more time with potentially qualified candidates and less time with candidates who turn out to be total mismatches.

Candidate.Guru is an early-stage tool, Daniels explains. When a company posts a job and they get a whole bunch of people applyingor when internal talent acquisition sources a whole bunch of peoplethey can do some vetting based on skill, but then they can run all of those candidates through our prediction engine. Well rank them for fit, and then [companies]can start [the recruiting process] at the top of our list.

Candidate.Guru works by analyzing publicly available data. The company has access to an attribute database, which was created by one of its partners for completely different reasons.


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