You're elbow deep in CVs.
You’ve managed to shortlist a handful of promising-looking candidates.
But how do you know you’ve chosen the right people?
What if we told you that there is a way to prove you’ve got the best people...
And that you could be interviewing 3x as many suitable candidates, just by switching your candidate screening method?
At Applied, we’ve made it our mission to make hiring as data-driven and predictive as humanly possible…
And this is the science-backed, repeatable candidate screening process we’ve found to reliably spot talent and improve diversity.
Where does traditional candidate screening go wrong?
Your standard CV screening process is boring, biased and unlikely to identify who is most likely to perform on the job.
With a looming pile of CVs to wade through, we tend to skim for any details that 'jump out' at us, whether that be a Cambridge degree or a stint working for a big-name organisation like Google.
Although we may think of ourselves as having nothing but pure intentions, irrelevant details like names, photos and hobbies also play a significant, measurable impact on who gets shortlisted.
Unconscious bias is the term used to describe certain prejudices that we may be unaware of, and are therefore out of our direct control, often stemming from stereotypes that arise from our backgrounds, cultures, and personal experiences.
Although this bias is actually completely natural, it can have serious negative consequences when it comes to candiate screening.
The science behind bias (a quick summary)
Everyday we make 1000s of micro-decisions...
What to wear, what to have for breakfast, where to stand on the platform, when to get off the train… and that’s before you even arrive at work.
System 1: Quick, initiative thinking that relies on short-cuts and associations (like being on auto-pilot).
System 2: Slow, considered thinking that requires more effort and reasoning.
Without system 1, we’d be having a meltdown before leaving the house in the morning due to all the decisions we need to make.
System 1 is absolutely necessary to make sense of our everyday world. However, since this way of thinking relies on shortcuts to draw conclusions, it can lead to some candidates being unfairly overlooked or favoured.
When we're on autopilot, we tend to gravitate towards those who we find most familiar, resist change and subconsciously look to confirm any initial assumptions we might jump to.
The problem is, we can't control which decision-making system we're using at any given time.
And when confronted with a pile of CVs, we're likely to fall back to our autopilot mode (hence why the average hirer spends less than 10 seconds reviewing a CV).
The impact of bias: poor diversity and lost talent
When it comes to real-life impact, the effects of bias have been measured all around the western world.
No matter where you are, those from minority backgrounds are disproportionately overlooked.
There isn't much use in pointing the finger at individuals - we're all prone to biases, it just means we're human.
Stereotypes dictate who we expect to see in certain roles. They're bred into us as children and perpetuated throughout our lives.
When googling nurse, 81% of people pictured were women, and when searching for images of surgeons, 68% were male.
This sort of stereotyping trains us to think of nurses as women and surgeons as men.
Although this is a very basic example, you can begin to see how this could play out in hiring.
We have a certain image in our head of the type of person we expect to see in a given role and naturally tend to look for someone who fits that mould.
… which can have a detrimental effect on minority groups.
We often refer to this German study to drive this point home.
The same resume was sent out, changing only the name and appearance of the candidate.
The result: Maryem Ozturk would have to send 40% more applications to get the same number of callbacks.
Just because bias is natural, doesn't mean we don't have a duty to address it.
Although training bias out of individuals is near-impossible, we can use a candiate screening process that significantly reduces that opportunities for bias to creep in.
Anonymize your candidate screening to reduce bias
One of the most cost-effective changes you can make to your candiate screening is to simply remove any identifying information.
Think about the sort of information provided on CVs:
- Date of birth
All of this information is grounds for bias and says nothing about someone’s ability to do the job.
In one of the earliest trials of anonymous hiring - orchestras managed to double the number of women getting through auditions by doing them from behind a curtain.
Try structured CV scoring
If you're not ready to let go of CVs, there are still steps you can take to make candidate screening a more fair, predictive process.
Give yourself a set list of questions to score CVs against.
- Does this person show evidence of leadership skills?
- Have they got experience in a similar environment to the one they'll be working in?
- Have they been promoted quickly in previous roles?
By scoring CVs (start with either a 3 or 5 star scale), you'll be able to build a more objective, skill-based candidate leaderboard.
We built our CV Scoring Tool to help turn your CV reviewing into a science.
Our Focus Questions are designed to focus on exactly what you're looking for - so you can spot the best talent (with the data to prove you've made the right call).
Invite reviewers, score CVs and manage your candidate leaderboard all within the Applied Platform.
Use candidate screening questions to test for skills
Below you can see the results of the landmark Schmidt & Hunter meta-study.
This study looked at 100+ years of research around assessment methods to find out which actually predict future job performance.
As you can see, things like education and years of experience don't actually count for much when it comes to finding genuine talent.
That's because they're proxies for skills.
Whilst a certain degree or previous employer might signal raw ability, it's extremely difficult to separate from socioeconomic factors.
Sure, someone’s degree or years of hard-earned experience can (and often do) make them the best person for the job.
But instead of just assuming they’re the best based on this alone, wouldn't it be better if we could test for these skills directly?
This is why here at Applied, we use work samples.
Work samples are job-specific questions designed to test how a candidate would think and perform in the role.
They simulate small parts of the job by getting candidates to think as if they were already in the role.
Since the best person for the job often isn’t who you think it is - this is a fair, science-based means of assessing skills without making assumptions based on background.
Work samples have been proven to be 3x more predictive than CVs making them the single most predictive candidate screening method.
Where most typical hiring processes centre around background and experience, work samples flip this on its head by instead posing scenarios hypothetically.
True, past behaviour can offer some insight into future behaviour...
But asking someone about how they've acted in the past relies on them being truthful, having encountered a given scenario before and their confidence to talk up their skills.
Here's a work sample we used for a Customer Success Manager role...
Consider this stat: We found that 60% of people hired through our work sample process would’ve been missed in a traditional CV sift.
Whilst there might be some candidates who stand out on paper and deliver in real-life... most gems are hidden.
By looking past background and skipping straight to skill-based assessments, you're likely to find talent that would have otherwise been overlooked.
Yes, losing the CV seems like a daunting proposition but the evidence speaks for itself - work samples are actually a safer option than a resume screening.
Our candidate screening process made simple: how to create work samples
Work samples can be created in 4 easy steps:
- Decide on the 6-8 skills you want to test. Ideally, these would be a mix of technical and soft skills/ characteristics.
- Think of real situations that the candidate would come across in the job that would test these skills.
- Turn these into questions, posing them hypothetically (ask ‘what would you do…’)
- Give yourself scoring criteria so you can stay objective. What would a 1-star and a 5-star answer look like?
Before you can start coming up with questions, it’s best to start by thinking about the role itself, and the skills that would be required for the new hire to succeed.
They don’t all need to be job-specific, technical skills - they can include working characteristics like teamwork or entrepreneurship as well as one or two of your organisation's core values.
Imagine real situations that might occur
The best work samples are the ones closest to real life.
So, why not use real situations that have come up in the past to see how candidates would’ve reacted.
Similarly, if there’s an upcoming project or a daily duty the candidate would be tackling, why not use this as the basis for a work sample question?
Turn situations into questions
Since we’re not concerned with experience, simply take the situations you thought up above, and pose them as hypothetical, ‘what would you do’ questions.
It can be as straightforward as outlining the situation/ context and then asking what the candidate would do to address the situation.
A few other ideas:
- List of tasks to prioritise
- Email to draft
- Small blog post to write
- Project to plan
- Conflict to resolve
If you have a combination of 3-5 of these, you should be able to test candidates on the key areas of the role before even interviewing them, so that you only need to interview those who have proven they can do the job.
Give yourself scoring criteria
Your review process should be as objective as the candidate screening method itself.
Instead of going with the answer that you ‘feel’ is the best, or jumps out the most, write down rough criteria for each question.
We use a 1-5 star scale for scoring work samples. It doesn’t need to be too detailed, just bullet point what a good, bad and average answer would look like.
What should candidates have taken into consideration?
Should they be scored higher if they’ve done their research?
Below, you can see what a fully fleshed out scoring matrix might look like:
Use review panels for more accurate decisions
You may also want to get other team members to score answers too...
Having at least two other reviewers will draw on crowd wisdom - the rule of thumb that says collective judgement is generally more accurate than that of an individual.
This will also average out an individual's biases, so that you get fairer, more objective scores.
Do you need candidate screening tools to be more predictive?
Anonymizing applications, scoring CVs and using work samples can all be done cost-free without any special software.
If you're starting out from a traditional candidate screening process, we'd recommend trying 3 work samples alongside CVs.
Whilst the CV process is far from perfect, this'll give you a means of quantifying skills. You'll likely find that you shortlist people who wouldn't have made it through otherwise.
Whilst everything above can be implemented for free, using candiate screening tools like Applied will save a serious amount of time and give you all the data you need to report on things like predictivity, ROI and diversity.
We've work with organisations who were manually anonymizing CVs - and managed to save them 30+ hours of admin.
The Applied Platform was designed specifically to reduce bias and use only the most accurate, science-based assessments.
By automating things like anonymization, interview scheduling and personalized feedback, you can concentrate your time purely on what matters - spotting talent.
Applied is the essential platform for debiased hiring. Purpose-built to make hiring empirical and ethical, our platform uses anonymized applications and skill-based assessments to identify talent that would otherwise have been overlooked.