1. Anonymise Applications
No matter how well-intentioned hirers may be, all humans are prone to unconscious bias.
Left unchecked, this bias leads to candidates from underrepresented backgrounds being disproportionately overlooked.
Our brain makes 1000’s of decisions every day – and to lighten the load, our brain’s decision-making is broken down into two systems – one fast thinking, and one slow thinking, a theory popularized by Daniel Kahneman’s ‘Thinking Fast and Slow’.
System 1: used for everyday, intuitive decisions – like how much milk to put into your coffee. For the most part, this sort of decision making is a bit like being on autopilot.
System 2: used for bigger, more important decisions like planning a trip or working on a big presentation. System 2 thinking tends to be slower, considered, and more mentally taxing.
We use unconscious bias to simplify and make sense of our complicated world but it can also come with some negative consequences…
We often fall back on our intuitive system 1 thinking when we should be using system 2.
Our brains use shortcuts and patterns to draw conclusions, by using the information subconsciously stored in our mental lockers.
When it comes to hiring, our natural tendency to resist the unfamiliar and warm to those most like ourselves leads to outcomes like those shown in the chart below.
Awareness and good intentions alone won’t have any impact on these outcomes.
This is why unconscious bias/diversity training doesn’t work.
The only way to make genuine change is to design a process that removes bias.
You can’t debias a person (because it’s human nature), but you can debias a process.
We know that the following information can all trigger unconscious bias:
- Names
- Photos
- Addresses
- Dates of Birth
- Hobbies
The more we know about someone, the more likely it is that bias will be triggered.
If you want to make measurable improvements when it comes to diversity, your ATS should have anonymisation options – even if just to hide the basic information above.
2. Use Predictive Assessments
To hire a diverse array of talent, you need to make sure you’re testing for what matters… which is skills and not background/credentials.
And when testing for these skills, you’ll want to use assessments that are predictive.
Predictive validity is a measure of accuracy used in science and psychology – it’s essentially a means of quantifying how likely a given assessment is to predict future behaviour or outcomes.
Keeping the emphasis on predictive validity means that there’s never a tradeoff between diversity and the quality of a candidate.
Predictive validity studies take a long time to complete and demand large sample sizes in order to draw any meaningful conclusions.
However, we can look to the Schmidt–Hunter meta-analysis for answers – which summarises the findings of 100 years of research in personnel selection.
The purpose of this meta-study was to evaluate how accurately various assessment methods can forecast an individual’s future job performance.
The most predictive assessment – ‘work samples’ – are interview-style questions designed to test the specific skills required for the job.
They’re not too dissimilar from ‘tell me a time when…’ interview questions – the key difference is that they pose questions hypothetically, so that experience isn’t necessitated.
The basic idea is to simulate the tasks and challenges candidates would face, should they get the job.
Work samples take a realistic task or scenario that candidates would encounter in the role and ask them to either perform the task or explain how they would go about doing so.
Below is an example for a fundraising role…
Whilst a work sample-based approach won’t be possible through all ATS’, the Schmidt-Hunter study should give you a rough overview of what works and what doesn’t.
Just ask yourself: can we prove that our assessment process actually identifies the best people for the job?
No matter which ATS you use to manage your recruitment, having review guides for your assessments is essential.
Ideally, you’d use a 1-5 star scale for each work sample – with bullet points noting what a good, bad and mediocre answer would include.
If every assessment is given a number score, then you can simply average out candidates’ scores to decide who to bring through to the next round.
Having even the most rudimentary scoring system will give you data points to use in decision making.
What we might call our ‘gut instinct’ is actually just unconscious bias.
So, adding structure and scoring to your assessments should result in fairer outcomes.
3. Diversity Reporting
You can’t change what you can’t measure.
To be able to make any meaningful changes to your organisation’s diversity, you first need to be able to track the diversity of the candidates that are sourced and eventually hired.
Once you know how different groups progress through your hiring process, you can begin to identify and tweak any stages or individual assessments that might favour one approach over another.
Corporate hiring processes in the U.S, for example, have been shown to prefer a masculine style of leadership.
You’ll also want to ensure that you start the process with a diverse candidate pool.
The less diverse your initial pool is, the higher the chance you’ll hire someone from an overrepresented demographic.
Studies have shown that when there’s just one woman in the finalist pool, their chances of being hired are statistically zero.
Before asking for any personal background information, it’s absolutely essential to communicate to candidates that this information is only ever going to be used at an aggregate level (meaning candidates will remain anonymous) and will never be used to identify individuals.
This information should be collected at the start of the process via an equal opportunities form – which should always be optional.
Partner
Applied is the essential platform for debiased hiring. Purpose-built to make hiring more ethical, efficient and predictive, our platform uses anonymized applications and skill-based assessments to identify talent that would otherwise have been overlooked. Hire with purpose, supported by science.
