What can AI help us discover? How can we make better people and business decisions by looking at the data?
By using SOM maps https://en.wikipedia.org/wiki/Self-organizing_map to map personality for more than 85,000 applicants using their HEXACO scores, 47/53% male and female, candidates spread across 2 regions – the UK and Australia, we identified 400 unique personality profiles.
It turns out that personality is somewhat more complex than the 16 types long promoted by Myers Briggs.
Following SOM’s show the percentage density of male, female and sales candidates across the 400 different HEXACO profile groups. The size of each bubble represents the total count of individuals mapped to each profile. Darker shades represent higher % of each category.
Personality is widely accepted as an indicator of job performance. Until now, the only way to accurately measure personality was through long and repetitive 100+ item personality tests, where the candidate experience is proven to be weak. The Sapia team breaks new ground disrupting decades of assessment practice. They do this by showing that answers to standard interview questions related to past behaviour and situational judgement can be used to reliably infer personality traits. Thus by leveraging NLP, machine learning and personality theory, we validate that text is a reliable indicator of hidden personality traits. Additionally, this approach to candidate interviews is blind to gender, race and any characteristics that are not directly relevant in job selection. Instead, every applicant is given a fair opportunity to express themselves and be evaluated equally.
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Finally, you can try out Sapia’s SmartInterview right now, or leave us your details here to get a personalised demo.
It scares me sometimes when I think about the big decisions I’ve made on gut feel and will probably continue to make relying on my instincts.
Personally, I would love to be armed with meaningful data and insights whenever I make important life decisions. Such as what’s the maximum price I should pay for that house on the weekend, who to partner with, who to work for, and who to hire into my team. Data that helped me see a bigger picture or another perspective would be very valuable. For most of those decisions there is so much information asymmetry which makes it feel even riskier. For sure I could check out glassdoor when choosing my next job but it comes with huge sample bias and not much science behind it.
So why is there still an (almost) universal blind acceptance that these decisions are best entrusted to gut feel? Especially given the facts show we are pretty crap at making good ‘gut’ based decisions.
I’m one of those people that believe in the power of AI — to remove that asymmetry, to dial down the bias, to empower me with data to make smarter!
At a recent HR conference, a quick pulse around the room confirmed there is high curiosity and appetite to understand AI. What we’re missing is the clarity about the opportunities and what success looks like from using it. The concern about how to navigate the change management exercise that comes with introducing data and technology into a previously entirely human-driven process is daunting.
The best human resources AI is not about taking the human out of hiring and culture decisions. Far from it. It’s about providing meaningful data to help us make better decisions faster.
Having worked in the ‘People and Culture’ space for a while, I know building trust in how the organisation makes decisions — especially people decisions — is hard in the absence of data. Yet we all know that transparency builds trust. So how can you build that trust through transparency when the decision-maker is a human — and the humans make decisions in closed rooms and private discussions.
Remember that feeling when the recruiters call up and say you weren’t a good fit — who feels great about that call? A total black box cop-out response!
It doesn’t have to be this way, and the faster we can get to better decision making the better. Seven months ago, I joined a team of data scientists who had spent the prior three years building technology that relies on AI to work its magic and equip recruiters with meaningful and actionable insights when hiring.
I’m no data scientist. I have had to learn the ins and outs of our AI pretty fast. And because our technology is at work in the people space, I’m learning how to ensure the AI is safe, fair and our customers trust it and us to do the right thing with it.
If we reduce it to its core process, a machine learning algorithm is trying to improve the performance of an outcome based on the input data it receives. In some instances, such as in deep learning algorithms, it’s trying to simulate the functioning of the human brain’s neural networks, to figure out the patterns between the data inputs and data outputs.
Because it has no feelings, it’s going to be free of the biases humans bring to these critical decisions. Plus machines are more malleable to learning and way faster at it. This is more critical these days when roles are changing dynamically and swiftly as industries are disrupted.
Our team plays in predictive analytics for recruitment space. What this means is our AI seeks out the lead indicators of job success: the correlating factors between values, personality and job performance. We all intuitively know that behaviours drive leading indicators. But we struggle to assess for those consistently well.
Our job is to augment your intelligence and ability to make the right decision. By knowing how people treat others, what drives them, and their values, you become better informed about the real DNA of a person and how they might function in your team.
A powerful motivator to use AI is to build confidence and trust in the process from both candidates and people leaders by dialling down the human element (getting rid of the bias) and revealing the patterns for success. Less room for bias = more fairness for candidates = more diverse hiring. Key to this is we don’t look at any personal information — the machine doesn’t know or care about your age, gender, colour or educational background.
For our customers having this data is empowering and helps them make smart decisions. For all the people who are affected by those decisions, they can feel relieved that they were considered on their merits, not based on someone’s gut feel.
But if I have to choose between trusting biased humans and (a sometimes) biased machine they create, I know which one I would trust more. At least with a machine, you can actually test for the bias, remove it, and re-train it.
To find out how to improve candidate experience using Recruitment Automation, we also have a great eBook on candidate experience.
Is your recruitment team swamped by the sheer volume of job applications and CVs? Taking too long to get the right people in place? Spending too much time on administration and not enough time building relationships? Or building your business?
If you’ve just answered “yes” to these universal challenges for recruiters and hirers, recruitment automation can deliver the solution that you need. Especially at a time when unemployment is high and more candidates are seeking opportunities in all available roles.
Recruitment process automation can help to lift productivity, get to the best candidates quicker, fill roles sooner and reduce hiring costs.
All this while improving the candidate experience and lifting your organisation’s talent profile and brand reputation. It’s not surprising then that there are few if any, recruiters or hirers, who haven’t already brought automation into the hiring process.
From the way we shop or pay bills online, to how we order food or choose our entertainment, data-driven technology has changed the way we do everyday things. Technology helps us to make better use of our time and lets us transact or connect in more convenient and efficient ways.
In much the same way, recruitment automation is the technology that automates or streamlines tasks or workflows within the recruiting process that would previously have been done manually.
These new technology tools and platforms address tasks at every step of the hiring process. They often leverage technologies such as machine learning, predictive data analytics and artificial intelligence.
Reviewing and screening CVs and job applications is widely acknowledged as time consuming and repetitive tasks of the recruitment process. It’s often one of the first processes that recruiters prioritise for automation.
In an age of high volume briefs– such as team roles in retail, customer service or graduate internships – it’s standard to receive a high volume of candidate applications. Properly and fairly reviewing every candidate among hundreds or even thousands is beyond any recruiter. It’s not, however, beyond the capacity of technology.
Sapia is a leading innovator in the recruitment technology space.
Since 2013, Sapia has worked to solve and consistently improve the frontier problem of every recruiter and every employer. That is how to get to the right talent faster while consistently improving the candidate experience.
Sapia’s solution addresses top-of-funnel recruitment needs with an artificial intelligence-enabled automated interview platform, designed to integrate seamlessly with leading Applicant Tracking Systems (ATS).
While some automated interview platforms use video and voice technologies, Sapia uses mobile-based text. Candidates know text and trust text, and they welcome the opportunity to tell their own story in their own words and in their own time.
The automated interview is built around a few open-ended text questions that can be customised to the specific role family – sales, retail, call centre, service etc – and specific requirements relating to the employer’s brand and employment values.
The platform uses AI, ML and NLP to provide reliable personality insights into every candidate. It can accurately predict candidates’ suitability for the role. Additionally, it can guide their progression through the recruitment process. It delivers insights that recruiters and employers need to make better hiring decisions at scale.
See How Sapia’s Interview Automation Works Here >
Sapia provides blind-screening at its best. The platform effectively takes a candidate’s gender, age, ethnicity and other traits out of the process. There is no visual content, voice data or video that can act as triggers to subjective bias. Also for most customers, even CVs are removed from initial screening.
The blind screening means all candidates are competing on a level playing field and have the opportunity to tell their story without the subjective biases of a traditional human interview or a cursory review of their CV. Blind screening also supports employers’ diversity goals.
Integrated with an ATS, a simple Sapia interview link sent to an applicant’s mobile lets recruiters nail speed of recruiting, quality of candidates and a better candidate experience in one.
Sapia will help to:
Improving the candidate experience is a priority for every recruiter and employer. This is as the effect of a poor experience can cause lasting damage to reputations and brands. Sapia is the only conversational interview platform with 99% candidate satisfaction. Candidates enjoy the process and value the personalised feedback/coaching tips.
Recruitment automation doesn’t describe just one technology product or platform. Automation will generally involve a suite of platforms, software, tools and technologies. All of them work together to provide end-to-end functionality throughout the hiring process. Integration with an applicant tracking system (ATS) or candidate relationship management (CRM) platform helps bring all the tools and data together in one place.
The efficiencies and savings of recruitment automation can be gained through every step:
Recruiting and HR are all about human capital. So at first, glance using machines and technology can seem counter-intuitive.
Recruitment automation technology, however, is not designed to take the human touch out of the equation, it’s designed to help humans work smarter.
Here are ten of the benefits and advantages:
Finally, discover how Sapia’s Ai-powered interview platform can help support your recruitment needs today. It’s a powerful way to bring all the benefits of recruitment automation to your business. You can also take it for a test drive here >
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. In such situations, the truth of the matter is irrelevant.
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.