It’s been an exciting start to 2021 for Sapia (Formerly PredictiveHire) and I’m pleased to share that we have been nominated as one of six global HR Tech startups to watch, by the HR Technology Conference and Expo, which is taking place this week.
I’m extremely proud of my team for achieving this feat – it’s been a team effort, and after several months of implementing new processes and initiatives, it’s a wonderful accomplishment. I am thrilled that Sapia has been recognized as one of the leaders in the industry by the HR Technology Conference this year.
Sapia was among six companies chosen from 24,000 applications to have the honour of presenting. It gives us the opportunity to showcase our technology to over four-thousand viewers that will be tuning in over the week. It’s a huge honour to be showcasing how our Ai-enabled chat technology can truly change recruiting.
We launched our exclusive Ethics Charter called FAIR earlier this year; a call to arms commitment that includes a guarantee towards inclusivity, fairness for all, explainable AI, transparency, privacy policies and accountability. We also recently commissioned exclusive research with Aptitude Research to uncover global company attitudes towards automation, technology in talent acquisition and unconscious human bias.
We’ve hit several milestones when it comes to evolving our offering for the better, and presenting at the conference this weekend is the cherry on top. Our biggest priorities right now are raising awareness of the importance of ethical AI and abolishing unconscious human bias. The world right now is at a stage where this is critical for the success of companies of the future and we’re proud to be discussing this and more at Friday’s session.
Sapia will be featuring in a session on innovative HR tech startups on Friday March 19 at 2:00PM ET.
To register for the virtual webinar, guests need to enter their details via this link: https://blog.hrtechnologyconference.com/hr-technology-conference-exposition-spring-set-to-explore-industrys-startup-ecosystem.
More about Sapia
Sapia is a frontier interview automation solution that solves three pain points in recruiting – bias, candidate experience, and efficiency. Customers are typically those that receive an enormous number of applications and are dissatisfied with how much collective time is spent hiring.
Unlike other forms of assessments which can feel confrontational, Sapia’ Chat Interview™ is built on a text-based conversation – totally familiar because text is central to our everyday lives. Every candidate gets a chance at an interview by answering five relatable questions. Every candidate also receives personalised feedback (99% CSAT). Ai then reads candidates’ answers for best-fit, translating assessments into personality readings, work-based traits and communication skills. Candidates are scored and ranked in real-time, making screening 90% faster. Sapia fits seamlessly into your HR tech-stack and with it you will get ‘off the Richter’ efficiency, reduce bias and humanise the application process. We call it ‘hiring with heart’.
Before the onset of COVID-19, concepts like social distancing were unfamiliar to the majority of us.
However, as we navigate through over half a year in this COVID-influenced environment, it’s evident that our lifestyles, work routines, and social habits will undergo lasting transformations. As global economies start to rebound, the repercussions of these changes on organizational recruitment practices are becoming evident.
Historically, for roles in high demand, Assessment Centres or “Group Interviews” served as a cornerstone for volume recruitment.
Yet, with a growing inclination and necessity to uphold social distancing or reduce face-to-face engagements, global organizations are pivoting to fully digital assessment centers, powered by modern technology.
The first thing to consider when moving to remote assessment centres is what adjustment or changes you might need to make to the activities you run with the applicants. Group interviews (either 1:1 or 1:2) are generally unaffected, but you will need to remove group activities which involve materials (i.e. lego or straws). Group activities which tend to be most effective are:
While technology will be your best friend in the transition to remote assessment centres, you won’t be able to control all aspects of this. For example, assessors or applicants might have an unexpected issue with their computer or unstable internet connection. Don’t let this deter you, as the cases are rare – but be prepared for how you will respond or how you may need to adapt to minimise disruptions and keep the assessment centre on-track.
Scheduling won’t be anything new to seasoned Group Interviewers. The difference now is you need to be scheduling a few additional factors to make for a smooth day, and engaging applicant experience.
Consider scheduling your day in blocks:
1 – Introduction & roll call
2 – Interviews
3 – Group activities
4 – Wash up and calibration
Tip! You will need multiple video conference links and breakout rooms prepared and scheduled for each of these.
Most of our customers have been doing assessment centres for years, but doing them remotely is a different game.
Your best bet is to do a ‘dry run’ with your assessors, even if only to walk through the process, schedule and technology – that way, on the day, there are no surprises!
Last but by no means least, take advantage of technology to do all the heavy lifting for you. Most organisations will have a video conference or collaboration platform which works effectively with multiple ‘rooms’ and large groups. If not, we recommended Zoom, as it has one of the highest video compressions rates ensuring the best possible experience for applicants and assessors. After this, you will need an assessment centre platform, such as LiveInterview, which allows you to manage your remote assessment centres without the need for spreadsheets, hours of admin, and painful calibration discussions.
It is for these reasons that Sapia has launched LiveInterview – the app that specialises in making group interviews:
1. Easier to organise
2. A pleasure to be there
3. Yield better results – especially considering all attendees were preselected using FirstInterview!
4. Totally fair and equitable
5. Consistent and standardised
6. Easy to administer. No record-keeping needed anymore, ever
7. Data-driven objective decision making plus it delivers a better hiring yield.
Watch the video here:
The value is greatest when companies harness the differences between employees from multiple demographic backgrounds to understand and appeal to a broad customer base. But true diversity relies on social mobility and therein lies the problem: the rate of social mobility in the UK is the worst in the developed world.
The root cause of the UK’s lack of social mobility can be found in the very place that it can bring the most value – the workplace. Employers’ recruiting processes often suffer from unconscious human bias that results in involuntary discrimination. As a result, the correlation between what an employee in the UK earns today and what his or her father earned is more apparent than in any other major economy.
This article explores the barriers to occupational mobility in the UK and the growing use of predictive analytics or algorithmic hiring to neutralise unintentional prejudice against age, academic background, class, ethnicity, colour, gender, disability, sexual orientation and religion.
The UK government has highlighted the fact that ‘patterns of inequality are imprinted from one generation to the next’ and has pledged to make their vision of a socially mobile country a reality. At the recent Conservative party conference in Manchester, David Cameron condemned the country’s lack of social mobility as unacceptable for ‘the party of aspiration’. Some of the eye-opening statistics quoted by Cameron include:
The OECD claims that income inequality cost the UK 9% in GDP growth between 1990 and 2010. Fewer educational opportunities for disadvantaged individuals had the effect of lowering social mobility and hampering skills development. Those from poor socio economic backgrounds may be just as talented as their privately educated contemporaries and perhaps the missing link in bridging the skills gap in the UK. Various industry sectors have hit out at the government’s immigration policy, claiming this widens the country’s skills gap still further.
Besides immigration, there are other barriers to social mobility within the UK that need to be lifted. Research by Deloitte has shown that 35% of jobs over the next 20 years will be automated. These are mainly unskilled roles that will impact people from low incomes. Rather than relying too heavily on skilled immigrants, the country needs to invest in training and development to upskill young people and provide home-grown talent to meet the future needs of the UK economy. Countries that promote equal opportunity for everyone from an early age are those that will grow and prosper.
The UK government’s proposal to tackle the issue of social mobility, both in education and in the workplace, has to be greatly welcomed. Cameron cited evidence that people with white-sounding names are more likely to get job interviews than equally qualified people with ethnic names, a trend that he described as ‘disgraceful’. He also referred to employers discriminating against gay people and the need to close the pay gap between men and women. Some major employers – including Deloitte, HSBC, the BBC and the NHS – are combatting this issue by introducing blind-name CVs, where the candidate’s name is blocked out on the CV and the initial screening process. UCAS has also adopted this approach in light of the fact that 36% of ethnic minority applicants from 2010-2012 received places at Russell Group universities, compared with 55% of white applicants.
Although blind-name CVs avoid initial discriminatory biases in an attempt to improve diversity in the workforce, recruiters may still be subject to similar or other biases later in the hiring process. Some law firms, for example, still insist on recruiting Oxbridge graduates, when in fact their skillset may not correlate positively with the job or company culture. While conscious human bias can only be changed through education, lobbying and a shift in attitude, a great deal can be done to eliminate unconscious human bias through predictive analytics or algorithmic hiring.
Bias in the hiring process not only thwarts social mobility but is detrimental to productivity, profitability and brand value. The best way to remove such bias is to shift reliance from humans to data science and algorithms. Human subjectivity relies on gut feel and is liable to passive bias or, at worst, active discrimination. If an employer genuinely wants to ignore a candidate’s schooling, racial background or social class, these variables can be hidden. Algorithms can have a non-discriminatory output as long as the data used to build them is also of a non-discriminatory nature.
Predictive analytics is an objective way of analysing relevant variables – such as biodata, pre-hire attitudes and personality traits – to determine which candidates are likely to perform best in their roles. By blocking out social background data, informed hiring decisions can be made that have a positive impact on company performance. The primary aim of predictive analytics is to improve organisational profitability, while a positive impact on social mobility is a healthy by-product.
A recent study in the USA revealed that the dropout rate at university will lead to a shortage of qualified graduates in the market (3 million deficit in the short term, rising to 16 million by 2025). Predictive analytics was trialled to anticipate early signs of struggle among students and to reach out with additional coaching and support. As a result, within the state of Georgia student retention rates increased by 5% and the time needed to earn a degree decreased by almost half a semester. The programme ascertained that students from high-income families were ten times more likely to complete their course than those from low-income households, enabling preventative measures to be put in place to help students from socially deprived backgrounds to succeed.
Bias and stereotyping are in-built physiological behaviours that help humans identify kinship and avoid dangerous circumstances. Such behaviours, however, cloud our judgement when it comes to recruitment decisions. More companies are shifting from a subjective recruitment process to a more objective process, which leads to decision making based on factual evidence. According to the CIPD, on average one-third of companies use assessment centres as a method to select an employee from their candidate pool. This no doubt helps to reduce subjectivity but does not eradicate it completely, as peer group bias can still be brought to bear on the outcome.
Two of the main biases which may be detrimental to hiring decisions are ‘Affinity bias’ and ‘Status Quo bias’. ‘Affinity bias’ leads to people recruiting those who are similar to themselves, while ‘Status Quo bias’ leads to recruitment decisions based on the likeness candidates have with previous hires. Recruiting on this basis may fail to match the selected person’s attributes with the requirements of the job.
Undoubtedly it is important to get along with those who will be joining the company. The key is to use data-driven modelling to narrow down the search in an objective manner before selecting based on compatibility. Predictive analytics can project how a person will fare by comparing candidate data with that of existing employees deemed to be h3 performers and relying on metrics that are devoid of the type of questioning that could lead to the discriminatory biases that inhibit social mobility.
“When it comes to making final decisions, the more data-driven recruiting managers can be, the better.”
‘Heuristic bias’ is another example of normal human behaviour that influences hiring decisions. Also known as ‘Confirmation bias’, it allows us to quickly make sense of a complex environment by drawing upon relevant known information to substantiate our reasoning. Since it is anchored on personal experience, it is by default arbitrary and can give rise to an incorrect assessment.
Other forms of bias include ‘Contrast bias’, when a candidate is compared with the previous one instead of comparing his or her individual skills and attributes to those required for the job. ‘Halo bias’ is when a recruiter sees one great thing about a candidate and allows that to sway opinion on everything else about that candidate. The opposite is ‘Horns bias’, where the recruiter sees one bad thing about a candidate and lets it cloud opinion on all their other attributes. Again, predictive analytics precludes all these forms of bias by sticking to the facts.
Age is firmly on the agenda in the world of recruitment, yet it has been reported that over 50% of recruiters who record age in the hiring process do not employ people older than themselves. Disabled candidates are often discriminated against because recruiters cannot see past the disability. Even these fundamental stereotypes and biases can be avoided through data-driven analytics that cut to the core in matching attitudes, skills and personality to job requirements.
Once objective decisions have been made, companies need to have the confidence not to overturn them and revert to reliance on one-to-one interviews, which have low predictive power. The CIPD cautions against this and advocates a pure, data-driven approach: ‘When it comes to making final decisions, the more data-driven recruiting managers can be, the better’.
The government’s strategy for social mobility states that ‘tackling the opportunity deficit – creating an open, socially mobile society – is our guiding purpose’ but that ‘by definition, this is a long-term undertaking. There is no magic wand we can wave to see immediate effects.’ Being aware of bias is just the first step in minimising its negative effect in the hiring process. Algorithmic hiring is not the only solution but, if supported by the government and key trade bodies, it can go a long way towards remedying the inherent weakness in current recruitment practice. Once the UK’s leading businesses begin to witness the benefits of a genuinely diverse workforce in terms of increased productivity and profitability, predictive hiring will become a self-fulfilling prophecy.
A recent article in The New York Times declared “the relationship between American businesses and their employees is undergoing a profound shift: For the first time in a generation, workers are gaining the upper hand.”
It’s quite a statement, particularly within the US, where the issue of minimum wages has been an ongoing battle, with employers largely having the upper hand for decades. The article goes on:
“The change is broader than the pandemic-related signing bonuses at fast-food places. Up and down the wage scale, companies are becoming more willing to pay a little more, to train workers, to take chances on people without traditional qualifications, and to show greater flexibility in where and how people work.”
There are two things happening here to create this ‘moment in time’: the first is that companies are understanding that treating workers better has a long-term benefit in a market that has a talent shortage, which is something that we have seen signs of across markets emerging from COVID lockdowns. This is fantastic to witness and as a card carrying member of the “hire with heart” club I am profoundly excited to see candidates put front and centre. But, the second change is equally as groundbreaking and that is around qualifications and past experience. Companies are realising that qualifications and past experience can reduce a talent pool with very little to justify the benefit of doing so.
It’s a significant trend we’ve seen emerging over the last year, when Google and Microsoft announced that you didn’t need a college degree anymore to get a job there and also opted for on-the-job training certificates. Microsoft made it clear at the time that the move was a bid to address the lack of opportunity for underrepresented populations.
The NYT article highlighted the work done at IBM in taking a fresh approach through its apprenticeship program on how it views people’s qualifications for a job. Since 2017, in a bid to find better talent, executives concluded that the qualifications for many jobs were unnecessarily demanding and so they did away with them. Where jobs might have required applicants to have a bachelor’s degree in the past, for example, they realised a six-month on-the-job-training course would adequately prepare a person for the role. It’s been a huge success.
IBM’s senior vice president for transformation and culture is quoted as saying “By creating your own dumb barriers, you’re actually making your job in the search for talent harder.”
We couldn’t have put it better. You have to ask yourself when the world’s most innovative companies, and often the most competitive to work at, decide that qualifications don’t matter and that broadening their talent pool has better hiring outcomes, can you afford not to pay attention?
We think not.
In fact, Sapia was built specifically to ignore qualifications, CVs and past experience. That might seem like quite a radical thing, but we believe that is the only way we can truly empower companies to find the best talent and circumvent the (dumb!) barriers we all put up in our search for talent.
It’s not just qualification and past experience that don’t matter, CVs are a barrier as they are full of irrelevant information that only contribute to biased outcomes. Schools attended, past experience, gender, ethnicity, age can all be inferred from a CV even when names are removed. As hiring managers we scan them looking for queues that demote good hires based on no data, and no evidence – all while confirming our own biases.
Our technology was built so that companies can find undiscovered talent from attributes that qualifications, CVs and past experience can’t reveal by understanding the unique attributes that individuals bring to a job, and how those might align with the job requirements. We look further than any human can to understand what it is that motivates individuals, how they respond to things, what their strengths and weaknesses are and whether they might be a good fit for a job – based on real data.
If you want to attract talent and remain competitive in a market where the employee has the upper hand, you need to be doing more than”posting and ghosting”. You need to be doing more than looking at blind CVs, and haphazardly parsing information that does little to serve your company.
You need to draw a red line through past experience and qualifications. You need to treat everyone with heart. You need to be looking at what makes a person tick, and you need to respect the potential value everybody has. Anybody could be your next hire, and everybody should be considered.
That’s the only way you are going to be able to hire in this new – and welcome – world where candidates aren’t just numbers, but valuable, unique humans who you need, more than they need you. You need undiscovered talent.