Do You Need Recruitment Platforms to Improve Diversity? Here’s What Really Works

Skill-based assessments

Post-anonymisation, you’ll be left with just someone’s education and past experience.

Whilst this alone is undoubtedly a step in the right direction, its only the tip of the iceberg when it comes to building a more ethical, diversity-centric hiring process.

Education and experience tell us more about someone’s socioeconomic background than they do their skills.

A degree from an elite university might be a signifier of intelligence… but we have no easy way of adjusting for the start someone had in life.

Instead, there are means of testing directly for skills, without making assumptions based on proxies.

At Applied, we don’t use CVs at all… we ask candidates 3-5 work sample questions.

Work samples are interview-style questions that take scenarios that would realistically occur in the role and ask candidates to perform them. Think of them as a means of seeing candidates do the job before they actually get it.

When choosing which type of assessments to use, you’ll want to ensure that they’re predictive.

Predictive validity is a measure of accuracy used in science and psychology, used to quantify how accurately an assessment can predict future behaviour.

If an assessment is predictive, then it means those who score highly are likely to perform better on the job.

If we look at the results of the Schmidt–Hunter meta-analysis, we can see that education and experience are some of the least predictive assessments, and work samples are one of the most predictive.

By using predictive assessments instead of CVs, we’re able to give every candidate a fair chance to show what they can do, without ruling anyone out based solely on their background.

There are recruitment platforms like Applied that will speed up the work sample creation process, but this part can absolutely be implemented without our help.

If you’re still skeptical about parting ways with the CV, we’d recommend starting out using both work samples and CVs.

Review the work sample questions first, and then see if these are the same people you would’ve shortlisted looking at their CVs.

You can also use work samples for interviews.

Rather than having candidates write their reply, you can ask them how they’d approach a task, or even role play things like client calls, meetings and presentations.

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Data-proofing/ scoring criteria 

Since our judgment can be warped by someone’s identity and our memories are far from perfect (we can only hold around 10 pieces of information in our head at any one time), giving yourself criteria to score candidates against will help you stay objective.

When making hiring decisions, we want to be able to point at someone’s performance, and not how we felt about them.

You’ll need scoring criteria (we call them review guides) for each work sample and interview question.

These should consist of a scale to score against (a 1-5 star scale will do) and a few bullet points letting reviewers know what a good, mediocre and poor answer might look like.

When you put this all together, it will look something like the below:

Scoring candidates’ answers can easily be done manually, no recruitment platforms required. However, if you’re dealing with high volumes of candidates, collating and averaging scores could be challenging.

Interview panels

Having multiple reviewers for each stage of the hiring process will ensure that any individual’s biases are averaged out.

Using panels will also result in more accurate scoring.

This is due to a phenomena known as Crowd Wisdom - the general rule that collective judgment is more accurate than that of an individual.

And the more diverse your panel is, the less biased the scores will be. 

Ideally, you'd have a fresh panel for each interview round, with reviewers scoring candidates' answers either in the interview itself or immediately afterwards, with no conferring.

Groupthink is the practice of thinking or making decisions as a group, which typically results in unchallenged, poor-quality decision-making. We generally desire group harmony or conformity, which means that we may agree with something that we otherwise wouldn’t.

This is why it's vital that reviewers score candidates independently, without being influenced by the opinions of others.

Interview panels are something that can be implemented without using recruitment platforms. Technology would assist with the admin - allocating interviewers, reminding them and calculating their scores. 

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Tracking diversity metrics

Tracking/analytics are crucial components of a diversity-optimised hiring process.

How can you improve diversity if you're not measuring it?

Whilst there's no shortage of metrics you could be tracking, collecting basic background information from candidates is a good place to start.

Once you know which demographics candidates belong to, you can see how they progress through your hiring process.

This will allow you to see if there are any stages or questions that cause certain groups to drop out - it may be the phrasing of a particular question that disadvantages or favours one group.

If you claim to have an anonymous hiring process, asking for this information can be sensitive.

We use an Equal Opportunities Form to do this (made with the help of the Government Equalities Office and the Equality and Human Rights Commission).

Although diversity data can be useful, your equal opportunities form should never be made mandatory in order to apply for a job.

Make sure you make it clear to candidates that this information is being used to ensure the process is fair at an aggregate level - and never to identify candidates or make hiring decisions.

Diversity tracking is one of the few things that does require a recruitment platform. Yes, you could track how people move through your process using Google Sheets, but this will require a lot of data entry at every step of the process and it would be hard to keep candidates anonymous.

How do recruitment platforms help with this process?

In the case of your typical recruitment platform - the short answer is they don’t.

That being said, there are recruitment platforms designed for diversity and ensure your process is fair (full disclosure: Applied isn’t the only platform that does this, but we are most science-based).

If we use our own platform as an example, Applied will automate things like anonymisation, which means all you have to spend time on is the reviewing itself.

Whilst biases around someones identity are probably the most pervasive when it comes to hiring decisions, there are also ordering effects that also affect our judgment.

Here are a few examples:

• Rank order effect: applications viewed first tend to be scored more favourably
• Peak-end effect: we remember the peaks and the end of an experience more vividly
• Halo/horn effect: a single good or bad attribute can overshadow how we perceive something
• Nobel Prize winner effect: those who follow a particularly good performer will be rated more harshly

To negate some of these effects, we chunk and randomise applications

This means that candidates are reviewed question by question and their answers are never viewed in the same order twice.

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Here are a few of the key ways in which a recruitment platform could make diversity-focussed hiring more effective:

Anonymised assessing

Recruitment platforms can be used to easily anonymise applications. The benefit of using technology here - aside from time-saving - is that candidates can stay anonymous whilst still being kept in the loop, which would be difficult to pull off manually.

Building work samples

The best work samples are job and company-specific, however we do have a library to get you started. The practice of using work samples doesn’t require any specific software, although Applied would enable you to remove a layer of lesser known ordering biases.

Inclusive job descriptions

If you want to attract a diverse talent pool, a text analysis tool is fairly essential. There are a few of these available, you can try our own Job Description Tool for free here. Tools like this will help you identify and swap out things like gendered language and reading burden.

Managing the hiring process

Organising and communicating with candidates is something that will be a lot easier with a recruitment platform. Although this won’t help with diversity, it will save you time and energy on things like sending invites, managing candidates, building questions and running the interviews.

Analytics & reporting

Tracking diversity metrics is where you’ll see real value from using recruitment platforms. 

At any time, you can access and download diversity data and analyse the quality of your questions to make informed decisions on how to optimise your hiring process.

Make no mistake: none of the above features are completely necessary in order to make an impact on diversity. Recruitment platforms like Applied will handle the de-biasing, candidate management and analytics, but the core practices we use can be implemented without us!

By anonymising applications and testing for skills, you will see improvements.

What recruitment platforms will do, is save you time and ensure that your process is demonstrably fair, ethical and predictive.

Should we use AI to speed up hiring?

Unlike other recruitment platforms, we don't use AI to make hiring decisions at Applied.

Why? Because it perpetuates rather than reduces inequalities. 

The process of using ‘training data’ to build future recommendations is often where problems arise.

This is because human judgment (which we know is less than perfect) is used to build the initial data set.

This means that human biases will be baked into your AI and so hiring decisions might not be any more objective than if done by humans.

Our CEO, Khyati, broke down why we don't use AI for hiring decisions here.

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Applied is the essential platform for fairer hiring. Purpose-built to make hiring ethical and predictive, our platform uses anonymised applications and skills-based assessments to improve diversity and identify the best talent.

Start transforming your hiring now: book in a demo