To create an organisation that hires and promotes everyone equitably, and has a diverse representation of people, you must confront uncomfortable truths – and have the confidence to employ compassionate solutions. The path to meaningful change cannot be done without data. Data allow us to clearly diagnose issues in a company, and also, just as importantly, to measure what is working. Without data-backed accountability, it’s unlikely that much will change.
The good news is that, these days, most organisations believe that diverse teams are beneficial to business outcomes, innovation, customer loyalty and employee trust. The better your team represents its customers, the fewer blind spots you’ll have when it comes to meeting customer needs.
The biggest challenge is not often not around intention, but rather diagnosing what is happening inside an organisation. The reasons contributing to bias are often numerous and complex, like company history, systemic racism and sexism, leaving decisions to ‘gut feelings’, and well-intentioned directives to hire based on “culture fit” that only result in more homogenous teams.
This is where data are so powerful.
Data help us look at the facts objectively, and while we might “feel” we hire fairly, it is impossible for a human to hire without bias. Data allow organisations to have an honest look at where they are falling short, assess how specific groups are not being treated equally, and address these issues before churn becomes an issue.
Here are five things you need to be doing to help data drive better Diversity, Equity and Inclusion (DEI) in your organisation.
In order to measure and track your progress on DEI you need to look at what current data you have and identify any data gaps. This is more than just identifying the demographics of who you have historically hired. For example, of the women you hired recently, do you know what percentage were represented in applying for a job versus landing a job? If 70% of people applying for the job are women, and 30% are only getting jobs, you need to identify where in the funnel there is a drop-off.
Note: There are sensitivities and legalities to collecting data around demographics and there are differing laws within countries about how you can do this.
Sapia’s reporting dashboard DiscoverInsights (Di) takes that worry away and gives you all the real-time metrics needed, and can instantly fill any data gaps you have. Candidates are never asked a personal or intrusive question and this data is not used in vetting candidates (keeping it blind and equatable.)
When hiring managers complain that they only had men applying for a role, or that there wasn’t any representation of Indigenous peoples, or that no one under 40 applied, they are talking about lagging indicators on inclusion. These point to issues in a hiring process that is not inclusive. Leading indicators might be a real-time analysis of the demographics of applicants so that hiring managers can change their approach quickly.
DiscoverInsights (Di) also reduces the the risk of lag indicators on DEI, by giving you real-time lead indicators so you can instantly assess the inclusiveness of your approach to hiring.
The data and platform you are using to track metrics and assess your progress needs to be agreed on from the outset, and should become your single source of truth. This is an important part of keeping everyone accountable (improving DEI is the responsibility of everyone in a company.) This should be a platform that cannot be used to present a desired outcome, but rather it should aim to be a robust fact-driven dataset that shines a light on issues. Identifying problems is the only way an organisation can address them.
Building trust among your employees on issues around DEI is foundational to the success of your initiatives. Be transparent about your findings, even if they feel uncomfortable. Part of what makes successful DEI measures is the leadership shown by the C-suite in acknowledging faults, identifying how they will be addressed, and making themselves accountable to employees on delivering these changes.
This is being accountable. Measure where you are at on DEI, learn from it, and set on improving on where you are. Then do it again. This is where the power of data really lies: By trying initiatives and testing what is working, and then measuring the outcomes, you can iterate quickly when no headway is being made. This takes all the guesswork out of whether there is improvement or not.
We have helped scores of the world’s biggest and best companies implement, track, and achieve their DEI goals. To find out more, check out our guide on data, equity and inclusion.
Last week I had two conversations, one with my partner, the other with Barb Hyman, Sapia’s new CEO.
Both wanted me share my story. To tell you and anyone else who might be interested, or care, about a journey that took me from being a recruiter to working in a business at the cutting edge of a technology, science and people triumvirate.
They wanted me to share my journey of discovery that every single recruiter is going to experience sooner, rather than later.
To begin, we first need to acknowledge that we humans are odd folk. How often do we see examples of people ignoring evidence in favour of something that instead reinforces their pre-set opinions?
AI in HR and Recruitment, it’ll never catch on
I’ve been doing this job for 10 years, I don’t need a machine to tell me how to recruit
I just don’t believe it, to be honest
These are just a few of the comments / opinions I’ve received from Talent professionals when discussing Recruitment AI. (I should also acknowledge that there are many folk who are genuinely curious or are already embracing the technology).
A while ago a recruitment manager posted on LinkedIn, asking their network for advice on Sapia solutions. A contact of mine figured I could help and tagged me.
Someone else in the Rec Manager’s network provided this advice:
“use a common-sense approach to recruitment… software misses the point… Imagine if your Dr used this sort of software to see if you are ‘likely to….’”
I refrained from posting something akin to this BBC article discussing AI accurately identifying skin cancers. As for “common sense recruiting”… well, i’ll come to that in a subsequent post.
Many people have already formed an opinion on AI. They’ve decided it won’t make a difference, it’s not for them nor will it help their company.
Let me tell you why I think they’re ever so wrong.
It’s a fact: People lie on resumés, whether the format is a LinkedIn profile, or an old-fashioned document.
Checkster reports that 78% people who applied for a job in 2020 lied about their skills or experience.
Another poll by LendEDU found that 34% of LinkedIn users lie, to some extent, on their profiles. Of that number, 55% said they padded out their ‘Skills’ section. To win roles, it seems, many of us are not above a little trickery.
In 2023, when talent acquisition specialists and hiring managers have hours (and sometimes less) to assess candidates, interview them, and woo them, the risk of resumé skill-creep is magnified.
For a rushed and overworked hiring manager, who is fed up with losing talent and looking bad because of it, the process of vetting becomes less about careful analysis and more about keyword-matching.
All of this culminates in a series of statistics that should not be surprising: According to a 2022 Aptitude Research report of more than 300 HR leaders at major companies, 50% of companies have lost quality talent due to the way they interview and hire.
At the same time, 50% of companies do not measure the ROI of their interview process. One third are not confident in their interviewing game as a whole.
The process is broken.
That same Aptitude Research report examined the average company recruitment funnel, laying out the points at which candidates typically drop out. It found that, on average:
So you might be losing anywhere from 20 to 40% of your talent pool while you spend time vetting resumés and sifting through cover letters.
Aside from the fact that this is a massive time-waster and a prime source of frustration of hiring managers, enforcing the use of resumés is not an effective way to ensure quality of hire.
That’s for two reasons:
Therefore, our over-reliance on resumés creates problems when we go to interview candidates. It’s a classic problem: Overworked hiring managers formulate questions on-the-fly after making cursory glances at candidate submissions.
It’s little wonder that 25% of candidates bail at this point – often, they’re just reconfirming information they’ve already told you about who they are and what they’ve done.
There is an alternative: Structured interviews. Schmidt and Hunter found that structured interviews are the best predictor (26%) of on-the-job success.
The biggest companies are starting to focus more on this.
According to the Wall Street Journal, employers like Google, Delta and IBM are combatting the tight labor market by easing strict needs for college degrees, focussing instead on interview and assessment processes that accurately measure soft skills and behavioral traits.
In its simplest form, the structured interview is based around a predefined set of questions.
These questions are typically behavioural and situational in nature: It’s about giving candidates the opportunity to explore how they think, solve problems, formulate plans, and deal with success and failure.
Therefore, questions like ‘Tell me how you’d respond if [specific situation] occurred’ don’t belong in a structured interview.
Instead, you might ask, ‘Tell me about when something went wrong with work, and you had to fix it. How did you go about it?’
Importantly, the questions you ask must be the same for all candidates. A critical component of the structured interview is fair and balanced comparison of candidates.
If you ask each candidate something different – as so often happens in a fast-paced hourly hiring setup – you can never accurately compare one candidate against another.
In that uncertainty, bias creeps in. It becomes a case of ‘I like this guy, he leans forward when he speaks.’
We’ve developed a handy tool to help you get started with structured interviews today: Our HEXACO job interview rubric. It comes with step-by-step instructions to help you figure out what skills and traits you need based on your open roles and company values.
From there, we’ve supplied you with more than 20 science-backed questions and a scorecard. It’s something simple enough for a busy hiring manager to use.
There is a possible world in which the resumé serves hiring managers as a kind of back-up validation document, used purely to verify the veracity of a candidate’s skills and experience.
In this world, the first stage of your recruitment funnel is the actual candidate interview.
That’s what our Ai Smart Interviewer can do. It’s a conversational Ai that takes candidates through a chat-based interview, using questions tailored to your open roles.
Candidates give their responses – with plenty of time to think – and Smart Interviewer analyses their word choices and sentence structures using its machine learning brainpower.
A candidate may be able to lie about their years of experience, or their knowledge of CSS, but our Smart Interviewer can accurately determine their cognitive ability, language proficiency, and personality traits.
Then it can make recommendations to you on the best candidates, according to the criteria you’ve set – and, at this point, you haven’t even looked at a single resumé.
But, as with traditional processes, you have the final say in who you hire.
In 2023, the name of the game is efficiency. Success will be measured in time saved NOT having to screen, review resumes and cover letters, compile candidate feedback, communicate with candidates, or improve hiring manager interview techniques.
When you’re saving that much time and money, your recruitment (or HR) function has more bandwidth to focus on long-term talent acquisition and people initiatives.
Don’t struggle in 2023 – speak to our team today about how we can solve your hiring challenges.
To create an organisation that hires and promotes everyone equitably, and has a diverse representation of people, you must confront uncomfortable truths – and have the confidence to employ compassionate solutions. The path to meaningful change cannot be done without data. Data allow us to clearly diagnose issues in a company, and also, just as importantly, to measure what is working. Without data-backed accountability, it’s unlikely that much will change.
The good news is that, these days, most organisations believe that diverse teams are beneficial to business outcomes, innovation, customer loyalty and employee trust. The better your team represents its customers, the fewer blind spots you’ll have when it comes to meeting customer needs.
The biggest challenge is not often not around intention, but rather diagnosing what is happening inside an organisation. The reasons contributing to bias are often numerous and complex, like company history, systemic racism and sexism, leaving decisions to ‘gut feelings’, and well-intentioned directives to hire based on “culture fit” that only result in more homogenous teams.
This is where data are so powerful.
Data help us look at the facts objectively, and while we might “feel” we hire fairly, it is impossible for a human to hire without bias. Data allow organisations to have an honest look at where they are falling short, assess how specific groups are not being treated equally, and address these issues before churn becomes an issue.
Here are five things you need to be doing to help data drive better Diversity, Equity and Inclusion (DEI) in your organisation.
In order to measure and track your progress on DEI you need to look at what current data you have and identify any data gaps. This is more than just identifying the demographics of who you have historically hired. For example, of the women you hired recently, do you know what percentage were represented in applying for a job versus landing a job? If 70% of people applying for the job are women, and 30% are only getting jobs, you need to identify where in the funnel there is a drop-off.
Note: There are sensitivities and legalities to collecting data around demographics and there are differing laws within countries about how you can do this.
Sapia’s reporting dashboard DiscoverInsights (Di) takes that worry away and gives you all the real-time metrics needed, and can instantly fill any data gaps you have. Candidates are never asked a personal or intrusive question and this data is not used in vetting candidates (keeping it blind and equatable.)
When hiring managers complain that they only had men applying for a role, or that there wasn’t any representation of Indigenous peoples, or that no one under 40 applied, they are talking about lagging indicators on inclusion. These point to issues in a hiring process that is not inclusive. Leading indicators might be a real-time analysis of the demographics of applicants so that hiring managers can change their approach quickly.
DiscoverInsights (Di) also reduces the the risk of lag indicators on DEI, by giving you real-time lead indicators so you can instantly assess the inclusiveness of your approach to hiring.
The data and platform you are using to track metrics and assess your progress needs to be agreed on from the outset, and should become your single source of truth. This is an important part of keeping everyone accountable (improving DEI is the responsibility of everyone in a company.) This should be a platform that cannot be used to present a desired outcome, but rather it should aim to be a robust fact-driven dataset that shines a light on issues. Identifying problems is the only way an organisation can address them.
Building trust among your employees on issues around DEI is foundational to the success of your initiatives. Be transparent about your findings, even if they feel uncomfortable. Part of what makes successful DEI measures is the leadership shown by the C-suite in acknowledging faults, identifying how they will be addressed, and making themselves accountable to employees on delivering these changes.
This is being accountable. Measure where you are at on DEI, learn from it, and set on improving on where you are. Then do it again. This is where the power of data really lies: By trying initiatives and testing what is working, and then measuring the outcomes, you can iterate quickly when no headway is being made. This takes all the guesswork out of whether there is improvement or not.
We have helped scores of the world’s biggest and best companies implement, track, and achieve their DEI goals. To find out more, check out our guide on data, equity and inclusion.