This is a line credited to Peter Drucker, a well-known management guru. Organisations have been selective on whether they use quotas or targets in the diversity space. It is still a hot political issue for many. Targets are said to help align organisational investment and effort to achieve a given goal. Whether it be a sales target or an internal promote target. But any good Sales Director/ CEO will tell you, you need the data to track it, and that means ‘lead’ not just lag indicators.
When it comes to bias around hiring and promotion, its mostly unconscious bias we have to worry about.
With AI enabled interviewing and assessment, there is now no excuse. The bias is trackable, visible, at the micro level, so your CHRO can hold the mirror up to every manager to show their bias. A game-changer for changing behaviours. Something no amount of bias training will give you.
Given that we do not collect the above demographic details from our candidate, we use an external service, NamSor, to derive ethnicity and gender from candidate names. NamSor is one of the leaders in name to gender, ethnicity and origin classifications.The ability to measure bias is one reason to use AI based screening tools over traditional processes. Growing awareness that AI can be fairer for people prompted the California State Assembly to pass a resolution to use unbiased technology to promote diversity hiring. Not all AI tools are equal however. The US is shining the spotlight on video interviewing with HireVue. This AI-driven recruitment company, recently taken to the US Federal Trade Commission claiming unfair and deceptive trade practices in their use of face-scanning technology to assess job candidates’ “employability”.
One US state introduced legislation this year, the Artificial Intelligence Video Interview Act. This requires companies to secure applicant’s consent to use AI. It also imposes limits on who can view an applicant’s recorded video interview and requires that companies delete any video that an applicant submits within a month of their request.
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…
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?”
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.
So, here are some possible questions to get you thinking.
Of course, you’ll need to frame and adjust those questions to match the role and your company.
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?”
If done effectively, interviews are a great means of assessing a candidate. We trust them to enable us to determine if our candidates have the attributes, traits, behaviours, skills, experience and personality to meet the role requirements.
Here’s the problem. It is physically impossible to interview every candidate. So, we rely on CV screening as the first step. A recruiter on average spends six seconds looking at the resume. In six seconds, a snap judgement is made on shortcuts (biases).
At the starting block, the process has failed. You cannot possibly pick qualities like grit and initiative from a CV, right? Then, of the people who applied for the job, around 13% of applicants may get an interview. During C-19 times – you can more than half that number.
In this way, you realise the value of interviews without investing one-minute of your time in them.
Imagine this. Everyone has already been interviewed before you have read one CV. A pre-qualified, pre-assessed, high-quality shortlist before you have read ONE CV. That’s the dream! Because now you are not wasting time reading resumes of people who either can’t do the job, won’t do the job, or they just don’t fit. And, instead of flicking through 100 resumes for a puny 6 seconds each, you can take the space to consider the best. The best? Those candidates who have already been pre-selected for that grit and initiative you so badly want in your team.
You can try out Sapia’s FirstInterview experience here.
Time to hire measures recruiting efficiency. It is the number of days between the first contact with a candidate to the day the candidate accepts the offer. Screening is your first time-to-hire bottleneck.
Even if you’re using an ATS you may be able to easily rank resumes, but you still have to consider them. And there’s your block.
A new generation of interview automation is here so that you can have every candidate interviewed in a flash. Of course, it integrates and works seamlessly within your ATS. It saves recruiters from screening resumes and boosts the efficiency of your recruiting process.
Reducing time to hire is great for candidates who get the job faster (or can move onto the next job). It is terrific for recruiters who get the reward of quicker placements and attaining their metrics. It is a relief for hiring managers who get their team to a full complement and can get back to their actual job.
Interviewing automation makes your recruiting process much faster – usually around 90% faster.
Hiring managers want their best team. They want people who can do the job, who will do the job and who will perform. With interview automation, Ai assesses traits, communication skills, optimism and temperament prior to you getting involved.
As a Recruiter, you get a complete picture of a candidate beyond what is written on their CV. You learn a lot of information about the candidate. Ai will rank and grade all your candidates for you. It pre-qualifies those who are a fit to move forward.
Have you ever thought to yourself: “If only I could hire 10 more Julie’s!” (*insert name)? With Ai, you can. And, as far as quality goes, this is the distinction from all other forms of pre-employment.
AI learns what a successful hire looks like and pin-points more like them. AI bases this learning on your historical recruiting decisions and then applies that knowledge to new candidates to automatically screen, grade, and rank them.
Interviewing automation gets you to the best of your talent pool much quicker resulting in, on aggregate, much better quality in your hires.
Diversity and Inclusion have been on the HR agenda for a long time. And in more recent years, it’s made its way onto the Business agenda too. In 2020, global management consulting company McKinsey again confirmed that companies with both ethnic and cultural diversity and gender diversity in corporate leadership are outperforming non-diverse companies on profitability. They found: “The most diverse companies are now more likely than ever to outperform non-diverse companies on profitability”
Diversity improves employee productivity, retention and happiness. Settled then. We want businesses that are diverse and fair.
Here’s the King of Recruiter biases: The Dunning-Kruger Effect. It’s where we lack the self-awareness to accurately assess our own skills meaning that we overestimate our ability. You think you are a brilliant totally unbiased Recruiter, right? You may well be, but it’s not uncommon to think you’re smarter or better than the average person. Haven’t we all skipped over candidates who don’t have the requisite ‘Big 4’ employer on their resume, or the ‘right kind of degree’?
Even when we don’t mean to be, human bias is pervasive. We keep these biases alive, through our relentless refusal to admit our shortfalls. And unfortunately, this isn’t great when it comes to hiring for diversity.
The reason for this is you can test, adjust and get rid of biases. The good news is Ai doesn’t resist stubbornly while claiming absolute fairness and denying any bias. This means that undesirable machine learning biases will tend to decrease over time. In Sapia’s case, its blind screening at its best. Nothing that typically influences human bias is introduced into the algorithms – no CV’s, no socials, no videos, no facial recognition – it’s just the candidate and their text answers. Much fairer for candidates of course and a richer experience where they can just be themselves.
Interviewing automation makes your recruiting process much fairer and your hiring decisions far more diverse.
Your ability to hire cost-effectively will be hampered if you don’t have the right tools. Make sure that all your recruitment technology is pulling in the same direction – to make hiring as seamless, streamlined and stress-free as possible – rather than working against you. The money you invest in the right technology will soon pay off when it comes to time and efficiency savings.
Significant costs are borne by an organisation when an employee voluntarily leaves.
These include replacement costs such as costs associated with advertising, screening and selecting a new candidate. A study conducted by the Australian HR Institute in (AHRI) 2018 across all major industry sectors in Australia (Begley & Dunne, 2018) found that on average companies face an annual turnover rate of 18%. Within the age group of 18 to 35 it worsens significantly, at 37%. That is, more than 1 in 3 people in the youngest age group leave an organisation within a year.
Imagine if you could predict those with a likelihood of churning before you had met them? Then think about the enormous savings that would be derived across your organization if you could do so.
If you haven’t yet automated your interviews, you are spending too much on hiring.
Chances are that reading CV’s and running interviews are not the hardest part of your job but are the most time-consuming. What if you could have available time for those high-value tasks. Like managing your stakeholders. Getting to know the business better. Improving your business partnership skills. Learning the essence of what Hiring Managers actually want. Networking and improving talent pools, particularly for those hard-to-fill roles.
So, if interview automation can take care of all of your first interviews for you then ask yourself:
Of how much value am I when buried knee-deep in screening? Visualise less of that and more of the buzz you get when you find the perfect fit. There’s no better feeling than knowing you’ve helped someone further their career AND helped your Hiring Manager find someone who ‘just fits’ and will perform. Nothing can replace the collaboration and empathy that you as a live person can extend.
According to this Sapia research paper published by IEEE: Structured interviews (where the same questions are asked from every candidate, in a controlled conversation flow and evaluated using a well-defined rubric) have not only shown to reduce bias but also increase the ability to predict future job performance. With interview automation, the questions asked in a structured interview are derived using a job analysis as opposed to interviewer preference and are typically based on past behaviour and situational judgement.
Interviewing automation frees up recruiter’s time to perform higher-value tasks with far greater output.
With interview automation you can move from an elongated process that leaves candidates in the dark, not knowing where they stand, to a super-efficient experience that feels empowering.
According to the Society for Human Resource Management (SHRM), 82% of candidates report the ideal recruiter interaction is a mix of innovative technology and personal, human interaction.
Improving your candidate experience is so much easier by adopting technology that is inclusive, personalised and relatable. Sapia’s interview automation offers a mobile-first, chat interview that interviews everyone in-depth and at scale. Giving every candidate personalised feedback.
Here is what interview automation offers above a manual interview process for candidates:
Interviewing automation enhances candidate experience, with no further time investment from you.
Download the 2020 Candidate Experience Playbook here
Gartner predicts by 2021, 50% of enterprises will spend greater budget on chatbot creation and bots than traditional mobile app development.
Businesses are adopting Sapia’s chat interviews across various job families – especially in front-line customer service roles. The quickest payback you will get on an investment in interview automation is to apply it to your high-volume roles first. Interview automation can truly enhance your high-volume recruitment process and help you make it more efficient (and pleasant) for everyone involved. This will help you get your time-back really quickly and release the budget for automation in other areas of recruiting.
The future of all first interactions between candidates and your business will be through automation. The only decision, for now, is where you will adopt interview automation first.
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If there was ever a time for our profession to show humanity for the thousands that are looking for work, that time is now.
It’s an understatement to say that recruiters and talent acquisition managers have had it tough over the last four-odd years. The pressures have compounded like a line of falling dominoes: First it was the COVID-19 pandemic; then came the mass talent migration; then the advent of new concepts like ‘quiet quitting’ and ‘acting your wage’, which, like them or not, seem to be the manifestations of a tired and existentially anxious workforce.
Now, in 2023, it’s likely that we’ll have to contend with a global recession.
Hiring is tougher. Candidates are wary and they expect more. Duh.
So do companies and their CEOs. However – and somewhat counter-productively – many companies have sought to cut recruitment budgets, lay off recruiters and talent acquisition managers en masse, and deprioritize long-term recruitment marketing strategies. We’re facing troubled times, and recruitment (and perhaps HR, more generally) is being treated as a cost center.
This misunderstanding of HR as a money sink is nothing new. It happens during every trough in the market. But, if we don’t make efforts to change this perception, 2023 will be a particularly painful valley to climb out of.
CEOs have been keen on talent strategy for years, but are struggling to quantify the effects of recruitment and talent acquisition activities. They cannot see the A to B journey, the action and its result. When the market is good, talent is in abundance, and you’re hiring effectively, nobody cares. But when times are hard, nebulous processes are put under harsh light.
Relatedly, recruitment and talent acquisition leaders are struggling to prove that the outcomes of their work are driving revenue. This is primarily an issue of data capture and analysis, in our experience: When companies come to us to help with hiring quality talent, the number one issue they have is to do with metrics and KPIs. Most do not know how to reliably measure quality of hire, nor time-to-hire, nor the effectiveness of their recruitment marketing channels. Many know that their processes are plagued with inefficiencies, but are not sure how to go about fixing them.
(To be clear, totally understandable. This stuff is hard.)
Where recruitment is concerned, a HR tech stack tends to look like this: an unwieldy ATS, often coupled with a conversational AI or scheduling tool.
These technologies cost big money. As a result, the question CFOs and CEOs will be constantly asking of HR is this: Is it adding real value? Can you prove it? Or are we simply stuck to a system that tackles old problems with insufficient solutions?
The bottom line is this: Enterprise companies are overstacked, overworked, and need to adopt different solutions to old problems. It doesn’t mean less tech, necessarily, although it can; it means the right tech.
Easier, perhaps, than it sounds. It’s always better to iterate than to completely restructure your hiring function. So get your team together and examine your processes. How much time is spent:
Ideally, you have baseline data in your ATS to help you arrive at some indicative numbers. But let’s assume that you don’t: calculating rough person-hours is enough to see where time may be spent more effectively.
In our experience, sourcing and screening are the stages in which quick wins might be gotten. As time-honored research (and our Smart Interviewer product) shows, resumes and cover letters are not useful indicators of candidate quality or potential. They can be easily falsified. What’s more, Sapia and Aptitude research from 2022 discovered that 22% of candidates drop out at the application stage and 24% at the screening stage.
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.
Interviews are another huge cause of inefficiency. Structured interviews are the best explainer (at 26%) of an employee’s performance, but many companies allow recruiters and hiring managers to conduct interviews haphazardly, causing a misidentification and loss of talent that can be hard (if not impossible) to measure. If you’re interviewing badly, how can you know if you’re capable of finding good candidates? What’s the associated cost of such a problem?
It’s no surprise, then, that according to our research, 50% of companies say they’ve lost talent due to the way they interview. Big costs involved there.
Don’t worry: We’re not going to lay out a massive and exhaustive list of metrics you should be tracking. Not feasible; you’re overworked as it is.
Instead, we’ll prescribe three good places to start, including links to helpful blog posts explaining how you measure them effectively:
Each of these metrics can help you improve efficiencies, and in turn, start to prove that your recruitment function is having a positive effect on business outcomes.
At a certain point, we must realize that force-multiplying technology is the only way to win in the unfolding ‘now’ of work. We’re spending way too much time with processes that can be repeated and automated – often out of some sense of duty to uphold 1:1 human connection (as if technology completely removes that, which it doesn’t).
And, because we do this, we weaken our position at an executive level: CEOs care about what is scalable, and the average recruitment function, traditionally speaking, does not.
In a recent episode of our Pink Squirrels! podcast, Sapia CEO and founder Barb Hyman had a chat with expert HR change management leader, Kyle Lagunas, about this very topic.
We exist to help you hire better, faster, and with fewer headaches. Our Smart Interviewer takes care of the scheduling, interviewing, and assessment stages of your process – saving upwards of 2,000 recruitment hours (av.) per month, and enabling you to offer jobs to candidates within 24 hours of application.
It’s delivered in a chat-based format (hello, Gen Z!), and candidate responses are assessed according to science-backed personality models. This means you can be sure you’re getting top talent, and you can prove it with measurable, repeatable data.
That’s not all: Our tech is blind, which means it natively disrupts bias and maximizes the size of your talent pool. Everyone gets an interview, and everyone gets personalized coaching tips whether or not they get the job. Our application completion rate, for all customers, sits at around 85% on average; our candidate satisfaction rate is well over 90%!
(And, if you need a second stage interview, you can use our Video Interview tool.)
Everything you do with our platform is pulled through to comprehensive data dashboards, allowing you to see hiring efficiency, quality, time, diversity, and other metrics. CEOs love this kind of transparency.
There you go: 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.