A difficult morning
9AM. Now fully caffeinated, you’ve just sat down to your grad CV mountain. Another day in the life of a manual sifter.
You get to fine-tooth-combing. Reject. Reject. Reject. Progress. Reject, and so on (and on, and on). Hungry work – you’re almost glad it’s lunchtime. Wait, it’s lunchtime?!
You get the point. Manual sifting is a pain encountered by too many, too often – especially those of you now preparing high-volume graduate campaigns.
But time isn’t the only problem here. This post looks at three reasons to save yourself from manual sifting, as well as a bonus: one easy way to do just that. Spoiler: that last bit involves us.
Firstly, as we’ve hinted so subtly, manual sifting takes time. Lots of it, generally. Some of our customers have reported spending up to half an hour screening each CV in their previous processes. Often, that amounts to whole weeks lost to manual sifting.
And it’s not just that this is a stressful experience for recruiters in itself. It also throws up the question of opportunity cost: what else could they be doing that would add more value to the business? Look at diversity and candidate experience, for example – two areas we regularly see organisations clamouring for improvements. Time (or the lack of it) is often one of the main things stopping them.
In a working world experiencing hugely important shifts, big changes are necessary. But they’ll be tough to put in place when hands are tied by time-stealing manual sifts once grad season rolls around
The holy hiring grail is surely the ability to predict the right people for any given role. But, when the majority of graduates have very little real work experience to shout about (71% of young people have never worked), CVs give you little data to go on.
It’s a problem crystallised nicely in our recent conversation with Capita’s Group Resourcing Director, Andrew Porter:
“For a lot of those people, they don’t have huge amounts of work experience. So the traditional way of assessing a candidate coming into an organisation, with a CV, is really not that useful to us. What we’re really looking for is to make sure we can identify candidates’ potential”.
So, not only is manual CV sifting a huge time investment. It also yields low-quality data when you’re trying to establish which grads actually have the skills and behaviours to succeed down the line.
In effect, it’s far easier to read the tea leaves if you’ve actually got some tea leaves to read. The ability to predict graduate performance – that holy grail – relies simply on finding rich, diverse and empowering sources of data beyond the CV.
Fairness & bias
Going back to the point on diversity, there’s another problem when with manual CV sifting:
We all have unconscious biases – it’s a hardwired survival mechanism, a remnant of our days on the savannah planes. While that’s fantastic when you’re trying to avoid becoming dinner, it’s less useful when you’re hiring. And manual sifting only makes it worse.
That’s because, no matter how long the competency checklist, or the training available to recruiters, CV data will always be subjective. It’s no fluke that you’re 28% less likely to get an interview if you’ve got a Chinese, Indian or Pakistani-sounding name. And blind CVs, for all their benefits, still leave breadcrumbs which can speak to age and background.
This means that an over-reliance on manually sifting graduate CVs will introduce bias into the hiring process. At best, this means an unfair process that narrows access to great talent. At worst, it runs some pretty serious legal risks.
Arctic Shores & manual sifting
So there are problems with manual CV sifting. But is there any real alternative? What might the gold standard of early-stage sifting look like? Maybe something like:
- Ability to sift at high thresholds
- No adverse impact
- Fast & simple
That’s where the Arctic Shores behaviour-based assessment lends a hand. By measuring natural behaviour, employers can move beyond experience and instead see deeper into candidates’ potential. Behavioural insight also gives recruiters a more objective data point, letting them sift fast (at times shaving weeks off the process) and fairly. And we guarantee no adverse impact, ever.