Supporting and Challenging Round-table discussions
The Prime Minister recommends name- blind recruitment – but what’s next?
It is not every day you get an invite from Downing Street, but Raphael Mokades, Founder of Rare Recruitment discovered otherwise earlier this year. Raphael speaks of the merits and disadvantages of name-blind, CV-blind and contextual recruitment.
afternoon. So I gave her a ring. “The Prime Minister’s office has been on the phone,” she said. I told her I was not in the mood for pranks, and only realised she was serious after a few minutes. It transpired that the PM’s office had indeed asked me to come to a ‘round table’ on name-blind recruitment. David Cameron was making the eminently reasonable point that it is easier to get an interview if you are called Sam Johnson than if you are called Oluwatobi Adeyemi, and that is not fair. He therefore proposed firms should take names off CVs or job applications, and many firms said that they would. (Amazing what an invite to Downing Street can do).
A number of firms have
moved to CV-blind
recruitment; not just taking names off, but also schools and universities.
Of course, name-blind recruitment is only the start. A number of firms have moved to CV-blind recruitment; not
just taking names off, but also schools and universities.
Now, 21 firms have signed up to use
contextual data, with more choosing to do so all the time.
What are the merits of name-blind, CV- blind and contextual recruitment? Can all three be used together?
24 Graduate Recruiter | www.agr.org.uk
all the office NOW’. This is the text message I got from a colleague one October
Name-blind recruitment simply means that your recruitment system is configured so that you do not see a candidate’s name when considering his or her application. It has been shown to reduce institutional bias against people with obviously African, Asian or Caribbean names. Systems may need reconfiguring but, beyond this, there is little fundamental change to the traditional recruitment approach.
CV-blind recruitment does not mean that you do not look at a candidate’s CV. It means that you look at their CV (or application form) when you are considering their application but that you do not have it with you when you interview (often, of course, the person interviewing is not the person who did the sifting). Therefore, the interviewer may go in, knowing absolutely nothing about the candidate they are about to meet. This is a significant change, because many interviewers like to ask questions based on a candidate’s CV. I know that I do. “Ah, so tell me about being captain of the basketball team”. I cannot help myself, and it is harder to understand where a candidate is coming from, harder to build rapport, harder to probe for gaps, without a CV.
Here lies the point. Over the last ten years I have observed over a dozen graduate assessment processes. In doing so, I have come to the conclusion that the most pernicious type of bias is, in fact, positive bias. It is interviewers seeing things on a CV that excite them or that they understand, making them think “this one will be good”, and therefore, looking forward to the interview. It is candidates and interviewers building rapport quickly
because of commonalities and thinking “ah, there’s a fit here”. This all sounds fair enough, until you consider it from the perspective of someone who does not have the commonalities, did not play basketball, did not study the same subject. This person does not have the interviewer champing at the bit to see them, or have the easy rapport born of shared experience, and so they and the interviewer are less comfortable. All too often, the candidate therefore does not do as well, not because they are any less good, but because neither the candidate nor interviewer feels they belong in the role.
Contextual data balances that out. Contextual data identifies the candidates whose lack of experience in team sports or debating stems from a lack of social and cultural capital: the candidates who come from disadvantaged postcodes, from low performing schools, who have been working 20 hours a week throughout university. It shines a new light on their achievements and explains why their ABB and lack of professional working experience is a lot more impressive than it looks.
And what if you do all three? What if your system removes names but includes contextual data, and what if your interviewers don’t have any information about the candidates before they meet them, and then the full biographical detail, including contextual data, is made available after interview at decision phase? Clearly, no system is perfect. There is quite a lot of process change in this approach, and some of the technical challenges may take a season to resolve fully. However, if you are serious about reducing bias, it is clear that this is the best way of doing it.
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