The future of HR! Be the change you want to see

To find out how to use Recruitment Automation to ‘hire with heart’, we also have a great eBook on recruitment automation with humanity.

New insights from Aptitude Research suggests Ai can play a much greater role in talent acquisition than just improving efficiency for hiring managers,  it can also make the interview process more human for candidates, something Sapia has long advocated

Aptitude Research has published a new paper showing that when you shift the focus in automated Talent Acquisition from an employer-driven view to a candidate-first then it is possible to reduce bias in hiring,  and improve the overall human element of recruitment.

The research, sponsored by Sapia , an Australian technology company that has pioneered transparent Ai-assisted hiring solutions, shows that humanistic automation creates a personal connection at scale, and works to reduce bias, something no other technology or even human-centred solution can deliver.

Madeline Laurano, CEO of Aptitude comments “The misperception that candidates do not want automation and prefer to keep the current talent acquisition is one of the most significant misperceptions in talent acquisition. Candidates want a fair recruitment process and consistency in communication. Automation can support all of these initiatives and enhance the humanity of the experience.”

There are four main ways that talent acquisition is made more human with automation when the candidate is the focus, rather than  simply moving candidates through the process:

1. Automation can understand what candidates want: Ai considers the unique expectations and experiences of candidates and adapts to them as it learns. Collecting feedback about the recruitment experience and continually improving the candidate journey can help candidates feel connected and heard.
2. The correct data can interrupt bias early in the process: By creating a consistent and fair experience for candidates early in the process, and not relying on CV data as the determinate of job suitability,  companies are more successful at reducing bias and increasing inclusivity.
3. Trust can be built through transparent data: Both employers and candidates need to trust the data and methodologies for the technology that they are using, something that can be achieved through transparency. Companies looking at automation should consider providers that will partner with them and provide transparency.
4. Provide feedback to every candidate:  Though natural language processing every candidate receives personalized feedback and messaging. Leaving unsuccessful candidates feedback they can use for future job searches is empowering and a big leap from ‘ghosting’ or a standard rejection email.

The research can be downloaded here https://sapia.ai/recruitment-automation-humanity/

About Aptitude Research
Aptitude Research Partners is a research-based analyst and advisory firm focused on HCM technology. We conduct quantitative and qualitative research on all aspects of Human Capital Management to better understand the skills, capabilities, technology, and underlying strategies required to deliver business results in today’s complex work environment. 

About Sapia

Sapia has become one of the most trusted mobile-first Ai recruitment platforms, used by companies across Australia, India, South Africa, UK and the US, with a candidate every two minutes engaging with their unique Ai chatbot Smart Interviewer.

What makes their approach unique in its a disruption of three paradigms in recruitment -candidates being ghosted, biased hiring and the false notion that automation diminishes the human experience.

The end result for companies – bias is interrupted at the top of the funnel, your hiring managers make more objective decisions empowered by Smart Interviewer their co-pilot, inclusivity is enhanced, and your hired profile starts to look more like your applicant profile.

Media contacts
Barb Hyman, CEO Sapia
barb@sapia.ai

Madeline Laurano , Researcher Aptitude Research
madeline@aptituderp.com

To find out how to use Recruitment Automation to ‘hire with heart’, we also have a great eBook on recruitment automation with humanity.

Start with the end in mind – always hire for performance first  

Most people are very familiar with a performance review. It’s the annual anxiety fest when every employee has their performance assessed and rated, perhaps against benchmarks agreed at last year’s review or defined by their job description.

So is a talent review basically the same thing? Well yes and no. While a talent review will still see employees rated and ranked, the focus extends beyond current and recent performance to consider their potential as future leaders in senior or key roles within the business. It’s all about mapping an organisation’s business needs against the capabilities and potential of its people.

Talent review plays an essential role in business planning, pinpointing skill gaps and helping organisations to develop and retain their best talent.

Forward-thinking organisations believe that talent review is bigger than an annual event. Rather, it’s an essential part of an always-on process of talent management that fosters a high-performance culture from the very first engagement with employees. 

Sapia’s Ai-enabled chat interview platform helps businesses to plan for future success by ensuring candidates with the very best potential are identified and engaged upfront. This approach provides talent momentum from the outset, ensuring every hire is building ‘bench strength’ and providing leaders with confidence that the next generation is ready to step-up and step-into key roles as needed.

How do you hire for the values and behaviours that result in high-performance? 

It’s no secret that high performers and team leaders share certain personality traits and behaviours. In fact, it’s a science that organisations have long embraced in their pursuit of excellence and competitive advantage.

Since it was first published in 1962, The Myers-Briggs Type Indicator that classified 16 personality types has been at the heart of most personality assessments and recruitment science. Much of the appeal of Myers-Briggs was its simplicity in reducing complexity to concise descriptors. These descriptors may have sufficed when only human intelligence was doing the processing and decision-making.

But in an age of data, it’s a big compromise – a compromise in accuracy, nuance, and the real diversity of personality types that exist in our population. It’s also a compromise we no longer need to make.

Read: Hire for Values

Moving beyond the limitations of Myers-Briggs

Sapia is a leading innovator and advocate of leveraging data and technology to enhance the recruitment process. In developing our award-winning automated chat interview platform, our data science team looked at how we could move beyond the limits of Myers-Briggs personality testing.

Our data team fed text responses to interview questions from 85,000 job applicants into our personality classifier. Spread across two regions, the UK and Australia, 47% of applicants were identified as male, 53% as female.

Instead of the standard 16 personality types, we directed the machine to group the data into 400 unique personality groupings.

Identifying 400 unique personality groupings and how they could be usefully applied to decision-making is beyond the ability of the human brain… but not beyond technology. Using Natural Language Processing (NLP) and machine learning, our artificial-intelligence enabled platform got to work with findings that were both surprising and not surprising at all.

What did we find?

 The ‘not surprising’ part of our research is that even at 400 groupings, there are distinct differences in personality profiles. It’s not surprising when you consider that humans are not linear beings and that our personalities are highly complex and nuanced.

The most surprising thing we discovered was that personality types by role were distinct. The personality profiles attracted to sales roles, for example, were noticeably different from the profiles attached to a carer role. Even more surprising were the imperceptible differences in the personality distribution across the 400 types between men and women –  a sign of how conscious or unconscious biases can play into our decision processes.

What does the talent review look like?

Differentiated by size, sector, structure and history, every organisation is unique.  So every talent review will be unique too.  Talent reviews need to be designed around the specific needs of the business but generally will bring performance management, learning and development and succession planning together.

When senior leaders meet for a talent review, their principle objective is to talk about the performance of individual employees in their teams and how those employees might take on more responsible roles in the future. Through this process, the critical positions in an organisation will be identified. Critical positions mean any role that business operations would stop or be seriously compromised if no one was able to step into the role immediately. 

Keep in mind that these critical roles may not necessarily be management roles and will also depend on the nature of the business. In a manufacturing business, for example, the chief engineer might be solely responsible for keeping a production line in working order. Talent reviews need to consider every employee across an organisation.

Talent review improves business focus 

An ongoing talent review process not only matches an organisation’s talent to existing roles, but it also helps identify new roles that will need to be created to achieve plans for future growth or expansion. It’s also possible that as a company moves forward, key roles may change or even become redundant. The most successful businesses are dynamic and flexible. 

A structured review process reviews employees in terms of key strengths, career ambitions and readiness for promotion. Talent reviews provide a forum for a range of important conversations that every organisation interested in best practice needs to have: 

• What matters most to our organisation?
• What are our business objectives?
• Does our existing talent pool and policy align with business strategy?
• Are our managers reviewing performance and potential in the best way possible, without favour or bias?
• Are we doing enough to support our people’s learning, development and growth?
• Do we have the right continuous performance management process in place?
• Are we identifying and recruiting the talent at the early career stage with identified potential to be the leaders of the future?
• Is our business (or part of the business) at risk without appropriate successors?
• What needs to be done to mitigate any risk?
• Do we need to embed new values and improve culture?

Planning a talent review

There is a range of methods that organisations use to assess their employees for talent reviews. While some will arrive at a ranking or score, others may use a more nuanced approach to assessing their talent.

Talent reviews can often reveal glaring disparity and bias in team leaders’ expectations of employees and how they rate them. An agreed and standardised approach across the organisation is essential. By ensuring employee expectations are aligned among leaders and cultural values are socialised across the organisation, potential friction around accountability can be diffused.

Rank and yank – what not to do

Though their ranking process has long been dropped, Jack Welch, the celebrated or controversial (pick your own path!) CEO of General Electric once insisted on an evaluation that reduced every employee’s performance to a number. Following evaluations each year, the lowest ranking 10% were fired across the business. In contemporary business, this ‘rank and yank’ approach would not be considered best-practice HR.

The 9-box performance and potential matrix

A less controversial ranking for employees is the 9-box matrix. This commonly-used assessment tool assigns employees to one of nine boxes on a grid that on one axis rates their performance (underperformance, effective performance, outstanding performance) and on the other rates their potential (low, medium, high).  Employees ranked in the box where outstanding performance and high potential meet are those assessed most likely to be future leaders.

What matters most – agreeing your assessment criteria for hiring

Taking a step back from the talent review process, Sapia has worked to solve and improve the frontier problem of every recruiter and every employer – how to get the right talent on board sooner.

With policies and process to put the best candidates in place every time, ongoing talent management and talent reviews can be more streamlined and rewarding for employers and employees alike. 

The first step to creating a step-change in the process is ensuring that everyone is assessing talent on the same criteria. These need to align with your organisation’s specific needs and values, which are ideally defined and documented as part of your business, brand and employer brand plans. 

How Sapia helps you get to the best talent (much faster) 

While Sapia’s early data breakthroughs were based on 85,000 interview responses, machine learning and artificial intelligence means that our platform never stops learning. Today, our Ai-powered platform has analysed more than 165 million words in text-based interviews from more than 700,000 candidates.

Continuous learning means that Sapia can help recruiters and employers make smarter, evidence-based employment decisions at the early career stage.

Within our science-based approach, behavioural interview questions are tailored around the agreed assessment criteria for the role. These questions are related to past behaviour to reliably assess personality traits. They can be customised to the specific role family – sales, retail, customer service etc– and aligned to the organisation’s agreed values and characteristics that will define their leaders of tomorrow.

Sapia’s bespoke Ai-platform analyses candidates’ responses across a range of criteria including readability, text structure, semantic alignment, sentiment and personality to identify candidates with the best future potential.

Nurturing your talent culture

Making the wrong choices for future leaders can put your business at risk. At times of talent review, careers can be derailed and employees demotivated. A properly executed talent management process that begins with smarter recruitment choices is one of the best investments in the future of your business. 

The insights delivered through a disciplined, standardised and ongoing process of talent assessment can be used at both organisational and managerial levels to drive your business forward. Creating a culture of high performance begins with best practice in early career candidate assessment. With Sapia’s platform as a key element, a robust talent review and management process will work to:

• support continuous performance management
• deliver robust succession planning
• optimise talent performance
• support skills assessments and gaps analysis
• lift employee retention
• support talent development and career pathways
• drive employee engagement through career conversations
• inform talent planning and decisions with better data
• embed culture and values throughout your organisation

This article is presented by Sapia as part of our mission to promote best practice in contemporary recruiting and HR. Our Ai-enabled text chat interview platform can help any organisation identify future leaders while providing candidates with an efficient, empowering and enjoyable experience. The user satisfaction rate for our award-winning platform is 99%.  

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You can try out Sapia’s Chat Interview right now – here –  or leave us your details to get a personalised demo

Previously, I’ve written about how the world of recruitment has evolved.

It seems that using AI could consign fantastical or over-optimised resumes to the dustbin of history, along with the Rolodex and fax machines.

But how do we go about selecting the perfect (or as close to perfect as possible) candidates from AI-created shortlists?

It should be so easy to learn how to conduct an interview that adds the human element to the AI selection. The web is awash with opportunities to earn recruitment qualifications from a variety of bodies, both respected and dubious. There are so many manuals, guides and blog-posts on the best ways of interviewing. People have been interviewing people for hundreds of years.

And yet…

Why are there no perfect interviews?

We’ve all heard about bizarre interview questions (no explanation needed). We’ve felt the pain of people caught up in interview nightmares (from both sides of the desk). And we’ve scratched our heads and noses over the blogs on body language in face-to-face interviews(bias klaxon).

Even without the extremes, people have tales to tell. Did you ever come away from an interview for your ideal job, where something just felt wrong?

It’s clear that adding human interaction to the recruitment process is by no means straightforward. Highlighting these recurring problems doesn’t solve the underlying question, which is:

“We’ve used an algorithm to better identify suitable candidates. How do we ensure that adding the crucial human part of hiring doesn’t re-introduce the very biases that the algorithm filtered out?”

Start by asking better questions

Searching for “Perfect interview Questions” gives 167,000,000 results. Many of them include the Perfect Answers to match. So it’s not simply about asking questions that, once upon a time, were reckoned to extract truthful and useful responses.

Instead we want questions that will make the best of that human interaction, building on and exploring the reasons the algorithm put these candidates on the list. Our questions need to help us achieve the ultimate goal of the interview: finding a candidate who can do the job, fit with the company culture AND stay for a meaningful period of time.
It’s generally agreed that we get better interview answers by asking open questions. I’d expand on that. They should ideally be questions that don’t relate specifically to the candidate’s resume, or only at the highest level, to get an in-depth understanding.

We should try to avoid using leading questions that will give an astute candidate any clues to the answers we’re looking for. And we should probably steer clear of most, if not all, of the questions that appear on those lists of ‘Perfect Interview Questions’, knowing that some candidates will reach for a well-practised ‘Perfect Answer’. We want them to display their understanding of the question and knowledge of the subject matter. Not their ability to recall a pre-rehearsed answer.

And so, we need to remember that we’re looking for the substance of the answers we get, not the candidate’s ability to weave the flimsiest material into an enchanting story.

Five new interview questions to ask your AI-shortlisted candidates

So, here are some possible questions to get you thinking.

1. We use an algorithm as part of our hiring process to ensure we’re not missing the right candidates. Considering everything you know about us and this rlie, why do you think the algorithm has suggested you might be a good hire?
2. If asked, what would your colleagues in your current or previous role say about your work-related exchanges with them?
3. Tell me about any of your previous personal or career achievements that you feel relate to this role
4. We strive to be as diverse and inclusive as possible. Tell me about the places where you’ve most enjoyed working and the communication styles of people you’ve worked best with. Please expand on your reasons
5. Can you recall a time you’ve needed to make a business decision with incomplete information? How did you move forward?

Of course, you’ll need to frame and adjust those questions to match the role and your company.

How AI for HR helps interviews – and interviewers – get closer to perfection

AI equips recruiters with impartial insights that resumes, questionnaires and even personality profiles can’t provide. Well-constructed, supervised algorithms overlook all the biases that every human has. And that can only be a good thing.

Statistically robust AI uses an algorithm, derived from business performance and behavioural science, to shortlist candidates. It can predict which ones will do well, fit well and stay. We can trust it to know what makes a successful employee, for our particular organisation and this specific role. It can tell us to invest effort with the applicants on that shortlist. However unlikely they seem at first glance.

So we can use all of our knowledge and skills to understand a candidate’s suitability and look beyond things that might have previously led us to a rejection.
AI is the recruiter’s friend, not a competitor. It can stop us wasting time chasing candidates who we think will make great hires but instead fail to live up to the expectation. And it can direct us to the hidden gems we might have otherwise overlooked.

Technology like AI for HR is only a threat if you ignore it.

Don’t be that company that still swears by dated processes because that’s the way it’s always been done. The opportunity here is putting technology to work, helping your organisation evolve for the better. The longer the delay, the harder it will be. So don’t be left at the back playing catch-up.

There are very few businesses these days that communicate by fax machines – and that’s for a reason. In a few years, you’ll look back and wonder “Why didn’t we all embrace Artificial Intelligence sooner?”