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2023: A Bubbly Year In Hiring 🥂

In 2023, the world embraced the transformative power of artificial intelligence (AI) more than ever before. With the explosion of ChatGPT into individuals’ pockets at the end of last year, we’ve seen interest and trust in AI solutions from organizations skyrocket.

The year 2023 stands as a testament to the potential of AI in creating an enriched, unbiased, and empowering hiring experience.

We’ve compiled the highlights that have made this year our most exciting so far – click the button below to immerse yourself in the year that’s been.

The Sapia.ai Difference: Our Candidate Experience 

Numbers speak louder than words. And our 2023 candidate numbers resound with success. Almost 1.4 million candidates shared their stories this year in a Chat Interview, giving every one of them a fair and equal chance at success.

450,000 candidates completed a Video Interview, giving them the chance to share more about who they are, and enabling hiring teams to ‘meet’ shortlisted candidates at a time that suited them.

Of the candidates who started a Chat Interview, 91.8% completed it, showing that candidates appreciate the opportunity to open up and bring their real and best selves when applying for a job.

The impact that allowing candidates to interview, and receive personalised feedback that they can use in their lives and careers, is huge.

Not only did 96% of candidates find the feedback they received useful, but the follow-on effect to our customer’s brands is a testament to the visionary talent leaders seeing the benefits of investing in their candidate experience.

79% employer brand advocacy and 84% consumer brand advocacy show how a candidate’s experience with AI, when curated in a respectful, low-pressure way, can positively impact your consumer brand.

Reducing Bias: A Key Achievement in 2023

One of the most significant pillars of our mission that we’re proud of is our unwavering commitment to reducing bias in the hiring process. In 2023, we’ve made substantial strides in ensuring that every candidate gets a fair chance, regardless of their background, making the hiring process more equitable and just.

In March of 2023, independent research was published that underscored the transformative impact of Sapia.ai in workplaces. The study highlighted how our platform significantly reduces the gender gap in technology hiring, a traditionally male-dominated sector. This research serves as a testament to our commitment to fostering diversity and inclusion, and our unwavering pursuit to level the playing field in the recruitment process.

The strides we’ve made with Sapia.ai are not just about challenging the status quo; they are about shaping a future where opportunities are boundless, and talent is recognized, irrespective of gender, ethnicity, age, or any other irrelevant piece of information about a person other than their potential to perform in the role.

Customer Impact: The True Measure of Our Success

Our customer’s satisfaction is the heartbeat of Sapia.ai. And in 2023, the pulse is strong. Our customer testimonials echo our commitment to excellence in the hiring process. They tell a story of transformed hiring experiences, saved time and resources, and how Sapia.ai has been a game-changer for businesses.

You can read our testimonials in our Year in Review highlight here.

By automating the screening and assessment of candidates, we’ve made a remarkable difference in streamlining the recruitment process. This year, we’re proud to share that we’ve saved each recruiter and hiring manager who uses Sapia.ai almost 30 hours per month. This has not only led to improved efficiency but has allowed hiring teams to focus more on their people. The time saved translates to increased productivity, enhanced candidate experience, and a more personable approach to hiring.

New Customer Partnerships: Strengthening Our Reach in 2023

This year, we had the pleasure of welcoming some esteemed brands to our growing network. These organizations are not just our valued clients; they are visionary leaders who embrace Responsible AI to make the hiring process better and more equitable.

We’re proud to collaborate with Kmart and Target Australia, global entities renowned for their commitment to diversity and fairness. Starbucks Australia, another of our prestigious customers, is making strides in efficient, responsible hiring practices with our platform. We’re also excited about our global partnerships with Joe & the Juice, a dynamic and innovative brand with a presence across the UK, Europe, and the US; Edge, an American organization known for its forward-thinking leadership; and Ecentric Payments, a pioneer in the South African digital payment solutions sector.

These partnerships demonstrate our shared vision to transform the hiring landscape, making it fairer and more efficient for all.

Expanding Our Integrations in 2023

This year, we also made meaningful strides in strengthening our partnerships with other major organizations in the HR space.

We’re thrilled to announce the successful completion of our integrations this year with SAP SuccessFactors, LiveHire, iCIMS, and Avature.

These partnerships have been instrumental in expanding our reach and capabilities. Through these integrations, we can now offer a seamless, comprehensive experience encompassing every stage of the hiring process for users of these platforms.

This simplifies the recruitment workflow and ensures a smooth, hassle-free journey for both candidates and hiring teams.

Product Innovations of 2023

In April we introduced our multilingual capability, starting with French and Spanish, and rapidly expanding to Danish, Dutch, Finnish, German, Italian, and Swedish. This significant expansion in our language offering for candidates facilitates easier communication for speakers of languages other than English fostering inclusivity and paving the way for a more diverse talent pool. The ability to accommodate various languages is instrumental in meeting our goal of making hiring equitable and accessible on a global scale.

In July we uplifted the review section of our Video Interviews, enabling a panel-style review process with multi-assessor capability. With new permissions sets that ensure hiring managers can only see their ratings, this feature helps to reduce the possibility of conformity bias, encouraging hiring managers to rate candidates solely based on their perspective and not be influenced by others’ opinions.

Also in July, we achieved a significant milestone with the development of our first proprietary large language model, which played a crucial role in the creation of our innovative Artificially Generated Text Detector. This language model, built with advanced machine-learning techniques, represents a significant leap forward in our commitment to innovation in AI. It can differentiate human-like text from artificially generated text, thanks to our large collection of human answers.

The detector can efficiently and effectively scan for artificial content, created with tools like ChatGPT. This innovative feature has been instrumental in ensuring the authenticity of our Chat Interview, reducing plagiarism by an astounding 78% almost overnight. By curbing plagiarism, we ensure each candidate has a fair opportunity to showcase their unique skills and competencies; and preserve the integrity of our platform in maintaining fairness in the recruitment process.

In October we launched Talent Hub, a game-changing feature that has accelerated the shortlisting process for recruiters and hiring managers. This tool provides a central hub for all Sapia.ai insights and data, reducing the clicks to review and progress a candidate by an impressive 75%. Now, the entire recruitment process is faster, smoother, and more efficient than ever before.

This month we released SMS reminders, which will help to boost our already industry-leading completion rates, enabling our customers to assess a broader talent pool.

Lastly, one of the most exciting innovations to have kicked off in 2023 was the proof of concept of Phai, our career site chatbot powered by generative AI.

Our customers have been crying out for us to bring the power of chat earlier in the candidate journey, connecting with candidates on a personalized level from the moment they land on the career site. Phai is the first step in this direction, with general availability slated for Q1, 2024; and a roadmap of functionality planned that will elevate the candidate experience even further.

To interact with Phai, simply click the chat button on the bottom left of your browser window. 

Global Recognition: Our Scientific Research

In 2023, our efforts in scientific research and practical application of AI garnered global recognition, amplifying our commitment to innovation and responsible AI. We were profoundly honored to have had the opportunity to present four research papers at the 2023 Society for Industrial and Organizational Psychology (SIOP) annual conference, the leading global event for I/O psychologists.

This recognition underscores our dedication to rigorous scientific research and our quest for knowledge, driving us to continue exploring new frontiers. We are also thrilled to announce the news that 6 research papers from Sapia.ai have been accepted for presentations at the 2024 SIOP conference and a poster at the NVIDIA GTC conference, one of the leading venues for showcasing Gen AI innovations.

Moreover, our work has been acknowledged by the National AI Centre in Australia, emphasized in a recent paper on the country’s expanding AI ecosystem. This recognition serves as a testament to our impactful contributions to the Responsible AI ecosystem in Australia and beyond. It also highlights our pivotal role in shaping the future of AI and its practical applications, further reinforcing our commitment to enhancing the recruitment process using ethical AI.

Looking Forward to 2024

As we reflect on an extraordinary 2023, we’re filled with immense gratitude for our partnerships, innovations, and recognitions that have shaped the year.

Leaping into 2024, we have some incredibly exciting plans shaping up that will elevate the experience for candidates and hiring teams and move us closer to achieving our mission of using ethical AI to make hiring fairer, more efficient, and more effective.


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Contact Centre recruitment & retention – this will blow your mind!

Imagine being able to dial-up (or down) any chosen metric such as NPS, retention, absenteeism, staff turnover or any performance data point simply through smarter, predictive, data-driven hiring.

Predictive Talent Analytics turns the imaginary into reality, presenting a variety of businesses, including contact centres, with the opportunity to improve hiring outcomes and raise the performance bar. With only a minor tweak to existing business processes, predictive talent analytics addresses challenge faced by many contact centres.

Recruitment typically involves face-to-face or telephone interviews and psychometric or situational awareness tests. However, there’s an opportunity to make better hires and to achieve better outcomes through the use of Predictive Talent Analytics.

Many organisations are already using analytics to help with their talent processes. Crucially, these are descriptive analytical tools. They’re reporting the past and present. They aren’t looking forward to tomorrow and that’s key. If the business is moving forward your talent tools should also be pointing in the same direction.

Consider a call-waiting display board showing missed and waiting calls. This is reporting.

Alternatively, consider a board that does the same but also accurately predicts significant increases in call volumes, providing you with enough time to increase staffing levels appropriately. That’s predictive.

Descriptive analytical tools showing the path to achievement taken by good performers within the business can add value. But does that mean that every candidate within a bracketed level of academic achievement, from a particular socio-economic background, from a certain area of town or from a particular job board is right for your business? It’s unlikely! Psychometric tests add value but does that mean that everyone within a pre-set number of personality types will be a good fit for your business? That’s also unlikely.

The simple truth is that, even with psychometric testing and rigorous interviews, people are still cycling out of contact centres and the same business challenges remain.

With only a minor tweak to talent processes, predictive talent analytics presents an opportunity to harness existing data and drive the business forward by making hiring recommendations based on somebody’s future capability.

Telling you who is more likely to stay and produce better results for your business.

But wait, it gets better!

Pick the right predictive talent analytics tool and this can be done in an interesting, innovative and intriguing way taking approximately five minutes.

Once the tool’s algorithm knows what good looks like, crucially within your business (because every company is different!), your talent acquisition team can approach the wider talent market armed with a new tool that will drive up efficiency and performance.

Picking the right hires, first time.

Predictive talent analytics boosts business performance

  • Volume & time – with the right choice of tool, your talent team can simultaneously engage hundreds or thousands of candidates and, within a few minutes, be shown which applicants should be at the top of the talent pile because the data is showing they’ll be a good hire.
  • Retention – Each hiring intake is full of talent with the capability to perform for the business. An algorithm has effectively asked thousands of questions and subsequently identified the people who will be capable performers, specifically for your business.
  • Goodbye generic – Your business is unique. If the algorithm provided by your predictive analytics provider is unique to your business, then every single candidate prediction is personalised. A contact centre has the potential to analyse thousands of candidates and pick the individuals who best fit the specific requirements of the business or team, driven by data.

Consider this. Candidate A has solid, recent, relevant experience and good academic grades, ticking all the right hiring boxes but post-hire subsequently cycles out of the business in a few months.

Candidate B is a recent school-leaver with poor grades, no work history but receives a high-performance prediction and, once trained, becomes an excellent employee for many years to come.

On paper candidate A is the better prospect but with the fullness of time, candidate B, identified using predictive talent analytics, is the better hire.

Instead of using generic personality bandings to make hiring decisions, use a different solution.

Use predictive talent analytics to rapidly identify people who will generate more sales or any other measured output. Find those who will be absent less or those who will help the business achieve a higher NPS. Bring applicants into the recruitment pipeline knowing the data is showing they will be a capable, or excellent, performer for your business.

Now that’s an opportunity worth grasping!

Steven John worked within contact centres whilst studying at university, was a recruiter for 13 years and is now Business Development Manager at Sapia, a leading workforce science business providing a data-driven prediction with every hire. This article was originally written for the UK Contact Centre Forum


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Algorithmic Hiring to Improve Social Mobility

It is a widely held belief that diversity brings strength to the workplace through different perspectives and talents.

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 government wants to promote equal opportunity

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:

  • 7% of the UK population has been privately educated.
  • 22% of FTSE 350 chief executives have been privately educated.
  • 44% within the creative industries have been privately educated.
  • By the age of three, children from disadvantaged families are already nine months behind their upper middle class peers.
  • At sixteen, children receiving school meals will on average achieve 1.7 grades lower in their GCSEs.
  • For A levels, the school one attends has a disproportionate effect on A* level achievement; 30% of A* achievers attend an independent school, while children attending such schools make up merely 7% of the general population.
  • Independent school graduates make up 32% of MPs, 51% of medics, 54% of FTSE 100 chief executives, 54% of top journalists and 70% of High Court judges.
  • By the age of 42, those educated privately will earn on average £200,000 more than those educated at state school.

Social immobility is an economic problem as well as a social problem

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.

How are employers supporting the government’s social mobility policy?

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.

How can algorithmic hiring help?

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.

An example of predictive analytics at work

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.

What can be done to combat the biases that affect recruitment?

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.”

Bias works on many levels of consciousness

‘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.

https://sapia.ai/blog/workplace-unconscious-bias/

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.

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Predictive Analytics: Your resolution will fail, here’s a promise you can keep

When technology is used in the right way it can enhance and improve our lives

During this seasonal holiday a great many of us will start to create plans for the forthcoming New Year. We’ll think about events, occurrences and happenings of the year gone by and many will commit to doing things better next year.

Even though studies have shown that only 8% of people keep their New Year’s resolutions , we still make (and subsequently break) them. But the intention was there, so good work!

Have you ever stopped to think about the processes your brain undertakes to enable you to set your goals for the New Year? No? Well, luckily I’ve done that bit for you. To make that resolution you combined your current and historical personal data and produced a future outcome, factoring in the probability of success, based on your analysis. A form of predictive analytics, if you like!

Predictive Analytics.

Using historical data to predict tomorrow’s outcomes

Thinking about those things you did (and didn’t do) this year and predicting/projecting for next year.

So now you know what it involves and we are (loosely) agreed that you’re on board with predictive analytics, when better than to tell you now that 2016 is going to be the year when we really start to see the benefits of predictive analytics within our jobs and people functions at work.

I think it’s now universally accepted that when technology is used in the right way it can enhance and improve our lives across every sector and industry. Most fields have seen significant developments over the last 20-30 years as technology is increasingly used to further our understanding of the way things work, enabling us to make better decisions in areas such as medicine, sport, communication and, arguably, even dating (predictive analytics is used in all of those sectors by the way!) so why not use it to help us find the right people for the right organisations?

Did you know you no longer need a top-class honours degree to work at Google?

Every employee is put through their analytics process allowing the business to match the right person with the right team, giving each individual the best environment to allow their talent to flourish.

Companies such as E&Y and Deloitte are using different methods to tackle the same problem – removing conscious and subconscious bias attached to the name and/or perceived quality of the university where applicants studied.

Airlines, retail, BPOs, recruitment firms a growing number of businesses within these sectors are using or on-boarding predictive analytics to achieve upturns in profits, productivity and achieving a more diverse and happier workforce.

Predictive analytics helps us make people and talent decisions to positively influence tomorrow’s business performance without bias, so I guess the question is this – if it’s already a proven science to achieve results, why isn’t everyone doing it? How long until everyone starts to use, and see the benefits, of predictive analytics?

Which logically raises the question: what are the benefits?

  • Time efficiencies – wouldn’t it be great for all parties in an interview to know that the data is indicating this role and person are a good fit before the candidate walks into the room? Hopefully reducing the reliance on both parties to be having a “good day”.
  • Diversity, inclusion removing the optics so often associated with a role. No more stated, or implied, previous sales / retail / PR experience but instead you can attract people from as broad a spectrum as possible knowing the data will help identify those candidates who have the foundation for success within your business and could well be your next superstars!
  • Churn/attrition – wouldn’t it be great to know that you can fill your 10 / 50 / 2000 seasonal/part-time roles from a pool of candidates who will have a higher chance of staying with the business longer, becoming successful brand ambassadors for your company leading to happier staff and customers alike.
  • Unique to your business – wouldn’t it be fantastic to know that all of these predictions are tailored purely for your business? For example, knowing that a candidate not overachieving in their previous role at one of your competitors isn’t reflective of their potential and that you can take advantage of their previous training and knowledge because the data says they’re going to be a better performer within your business.

Data can be big and it can be daunting, but it can also be invaluable if you ask and frame the right questions and combine the answers with human knowledge and experience. You will be surprised by the insights, knowledge and benefits that your business can obtain from even the smallest amounts of data. Data you probably already collect, even if it’s unknowingly or unwittingly!

List of Recruiting Resolutions

So as you start rummaging through your brain trying to remember where you filed your finest seasonal outfit(s) (that might just be me!), start prepping for the new year budgets, or start writing your list of resolutions let me help you frame a few questions:

  • Does your sector suffer from a skills shortage?
  • Would your company like to know which candidates from another sector have a higher likelihood of success post-training?
  • Would your business like to see an upturn in performance or people metrics such as increased sales, decreased absenteeism, longer tenure for better performers or a more diverse workforce? Would your Finance, Talent or HR head of department like to see an improvement in the variety of measures that indicate a better, more productive and happier workforce?

Statistically, your personal New Year’s resolution is unlikely to be on course in 12-months time so instead, why not make a resolution to bring predictive analytics into your talent processes in the upcoming year?

You’ll see the benefits for years to come, and that’s a promise we can both keep.

Happy holidays!

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