It’s a cliché, but nonetheless true, that as time passes all processes become dated.
Some might need to be thrown out completely. Many more need to be adjusted and refined to keep up as workplaces and ways of working change.
I’m not old enough to remember the recruitment days of Rolodex and faxed documents. But I’ve heard the stories. Paper mountains of resumes teetering on desks. Consultants queuing at the one office fax machine to send their applicants’ profiles to clients.
Who knew that today we’d be communicating almost instantly by email, on our own computers, or sifting through resumes using Applicant Tracking Systems? In the 1980s that would have sounded like something from Doctor Who.
Since then, it’s all slowed down a bit.
Sure, ATSs take a lot of the legwork out of choosing who to interview. But they’ve also led to Resume Optimisation tools to help applicants beat our filters.
How can we avoid picking only the people who are best at gaming the system? How do we know we’re not missing our perfect applicants?
Now AI is taking the hiring process another leap forward. It’s speeding up the more process-driven elements and helping us select interviewees who are more likely to fit into our businesses.
And that means we need to re-examine two elements of that hiring process – the resume and the interview.
First, let’s tackle the resume.
Here’s a challenge for you. Find five well-known businesses that don’t ask for a resume on their careers page. Difficult, isn’t it?
Now think about the resumes you’ve seen recently.
I’ve seen resumes that are well-constructed, professionally crafted prose. And others that are complete works of fiction.
You’re as likely to find glaring spelling mistakes, a messy layout, and a shameless plea to be considered as you are a concise summary, an attractive photo and carefully chosen keywords. If you’re really unlucky you get all of these in one “super-resume”.
A quick search on “How are resumes used?” reveals the astounding advice that applicants should “know the facts in detail, as they may be questioned” about them. That just confirms my suspicion that these documents are more like scripts than records of facts.
And, there’s one more thing that recruiters know about resumes, even if they don’t all admit it …
According to research by the Cambridge Network, some recruiters give CVs a six-second speed-read and many recruiters spend just under 20% of their time on a profile … looking at the picture!
Resumes are rarely used correctly or understood properly, by applicants or recruiters. They most certainly do not predict how successful an applicant is likely to be in a role. Instead, they’re a minefield of potential bias: year of graduation (age bias), name (racial / gender/identity bias), experience in a similar business (confirmation bias), and so on.
So isn’t it better to put some truly intelligent AI for HR to work instead?
I was astonished to see that 96 per cent of senior HR leaders understand the benefits of using artificial intelligence in their HR and talent functions. But there’s a big gap between recognising the benefits and reaping them.
The canny HR leaders who are already adopting AI techniques will have a head start on their slower rivals.
Some more traditional HR tech providers have evolved their recruitment tools, presenting them as predictive. However, they’re more likely to be creating profiles of your better staff and matching these profiles to the external candidate market, not predicting how they will perform.
Instead, the new wave of HR tech uses well-constructed algorithms, created using a business’s performance data, to provide an unbiased shortlist of candidates far more likely to succeed within the business once hired.
The algorithm can’t be misled by optimisation techniques, personal feelings or prejudice. Instead, it uses objective data, science and evidence to find the people who are most likely to be a good fit and perform. For this role, in this business. And it will help uncover applicants we might have otherwise overlooked when their resume didn’t match our expectations.
The better solutions work by identifying the defining characteristics of the whole performance group within a business (superstars through to under-performers) and then predicts where external applicants will sit on your performance scale once/if hired.
These advanced solutions then go further via validation reports to prove their better predictions are turning into better new hires. They then use Machine Learning to ensure each unique model continues to learn more about the performance of each business, further improving its predictive power over time.
These two additional steps mean that whilst us humans are still required to make the final hiring decision, we will get better results for our applicants and our businesses. Maybe that’s where the resume might still have a role – as the frame for some reasonable high-level questions to help us understand the person in front of us in more depth, once they’ve got through the first stage.
The most sophisticated algorithms are already outperforming humans in the selection and identification of suitable candidates – and by that I mean candidates who go on to become productive, valuable and loyal employees.
So, what would you rather have?
– A shortlist of candidates chosen because of what they’ve selected to include in (and omit from) their resume?
– A shortlist of candidates you know are likely to do well in your workforce, because they’ve been chosen using statistically-proven, company-specific performance drivers validated by behavioural science?
Not that tricky a question, is it?
And very easy to see how, with the advent of AI for HR, resumes will soon be as much a part of recruitment as faxes and Rolodex.
When I was leading the People & Culture team at the REA Group, my new CEO was passionate about Values, and the central role they play in defining your culture. Following a successful change program to evolve new Values that mirrored the desired Culture, one that would set the business up for continued growth and as a talent magnet, she asked me how we were going to embed those Values through our people processes – who we hire, who we promote, who we reward etc.
It couldn’t be a screen saver pop up or posters on a wall. The values had to be really heard and felt. At the same time, we also had a business that was hiring in the hundreds each year so scaling culture means getting this right.
These are two distinct notions when it comes to hiring: hiring for values and for culture. One should stay pretty fixed, and the other should be dynamic as your business context is always changing. If a company’s values are its bedrock, then a company’s culture is the shifting landscape on top of it. Hiring purely for culture is a recipe for self-reinforcing hiring, aka hiring that is biased. As we all know, innovation comes from the diversity of background/thought/etc, so by hiring only for the culture you can decrease, or even stifle innovation.
Celebrate that just as your product is always evolving, so will your culture. That means people who were great when you were a team of 50 may not be the right person for when you get to 500.
At Sapia we work with our customers to ensure their values are embedded right from the chat interview. This takes many forms, including
No recruiter could ever get that feedback data at the scale and speed to improve their recruitment process. But using Sapia we make a hard decision easier, meaning you can focus on hiring the right people to grow your business, at scale, without sacrificing the candidate experience. And if the VP for a global business focused on connecting people to opportunity can’t recognise bias, it’s a sure sign we need to pay more attention to who, and how, we hire.
“Talent is really distributed very evenly in the world, and opportunity is not.”
So, what do you think? Is your hiring values-driven, or based on the ever-intangible ‘culture-fit’? How do you scale hiring based on values? And how can we in HR, Talent Acquisition and Recruitment support hiring managers to grow innovative, diverse teams?
You can try out Sapia’s Chat Interview right now, or leave us your details to book a demo
In the current world, websites like LinkedIn have become a great platform for people to seek out new job opportunities. Same for organisations.
Given the current COVID-19 crisis, almost daily I come across 2 or 3 posts of people seeking to find a job as their company let them go, due to the economic situation.
Such posts are very popular. The power of social media is really unravelled in these times with a clear case multiple strangers coming to rescue to the person who starts the post. This help is extended either in case of connecting for an opportunity or by simply commenting so that more and more see in their personal feeds and the post goes viral.
I am sure many prospective candidates or affected people may have found their job of choice or compulsion with this. Great effort indeed!
But this also brings out the fact that many people (and companies) may be little hasty in making the job decision.
Given that hiring is an expensive process, HR leaders and hiring managers have often struggled with the possibility of the candidate leaving the job in a few months or years from joining.
Problems become more complex with the fact that the current breed of young workers rate company loyalty relatively lower in their ranking of traits of a dream job. A better brand, a better culture or better compensation can sway them to the other side of the door.
Another study found that in some sectors, the average stay in the company is reducing rapidly due to the high attrition.
People who move from one job to the other very often are popularly known as ‘Job Hoppers’.
One study says that in 2018, the turnover cost was $680 Billion in the US economy. Here is the link to the study.
As a phenomenon, job-hopping has been an area of significant interest for both industry and academia.
Now a new study may have found the solution to this problem with the help of Artificial Intelligence techniques.
The study titled ‘Predicting job-hopping likelihood using answers to open-ended interview questions’ scanned through over 45,000+ interview responses to correlate them with personality types using multiple AI techniques to lead to conclusion.
The correlation models used for assessment of the personality types derived from the interview responses with the propensity of job-hopping are below –
The conclusion of the study is –
The full study with details of the future work prospects in the area can be found here.
Amitesh Tyagi, Grow Daily, 25/07/2020
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Tristan Harris, the ex-Googler, now an evangelist for humane Ai and featured in The Social Dilemma shares the stunning fact that 70% of the videos we watch on YouTube, on average 60 minutes a day, come from the recommendation of algorithms.
His point? That choice is illusory.
When a machine can understand you better than you can understand yourself you lose your power. You also loose choice.
The now-famous historian Yuval Noah Harari has written and spoken about the threat to humanity from the type of artificial intelligence that knows us better than we know ourselves.
This is the worst kind of Ai.
When you think that you are in control of those choices, but you can’t see it to even know it’s happening. Google and Facebook and many other Silicon Valley behemoths have mastered this. They own this space.
Not all Ai can be weaponised against you.
The predictive technology that underpins tools like Spotify, Netflix do enrich peoples’ enjoyment in music and movies.
Not to weaponize your choices. Not to be used against you.
We, humans, move from being hacked to hacking ourselves.
Finally, Ai that gives you back your human agency.
300,000 candidates for jobs ranging from retail, sales, call centres, carers, graduates, HR managers, … this is how they feel about the use of Ai that is designed for their benefit.
Imagine what the world would look like if the whole world had better self-awareness.
Today not knowing yourself carries an even greater cost.
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Finally, you can try out Sapia’s Chat Interview right now, or leave us your details to get a personalised demo