In the candidate short market we’re in, it’s absolutely critical to keep talent engaged throughout the entire application process. You simply cannot afford to lose the talent that you’ve spent time and money attracting.
This sounds obvious, of course, but abandonment is a key problem – and few companies know where, when, and why it is happening.
Let’s start with the metric, and then talk about how we apply it to your wider talent acquisition journey.
Overall candidate abandonment rate = number of candidates still in the process at shortlist stage, minus the total number of candidates who landed on your careers page, divided by that total number again. Or:
At the very minimum, this is the metric you need to start tracking, because it is a generalized diagnostic for the health of your recruitment process.
If you know that you had 100 visitors to your careers (or job ad) page, but your shortlist has only 10 candidates in it, you’ve lost 90% of your possible talent pool at one stage or another.
Simple math, yes, but in our experience, many recruiters and talent acquisition managers don’t look at what their starting pool of candidate interest was – and therefore, what their theoretical talent pool might have been – and look only at actual applicants.
This poses another, related question: How do I know what my abandonment rate is at each stage of the application process?
Let’s say, like the example above, that you had 100 visitors to your careers (or job ad) page, and 20 of them completed the first-step application form on that page. You’ve lost 80% of your possible pool right there.
Not great, but at least you know – now you can examine that page to uncover possible issues preventing conversion.
Without examining stage progression in isolation, you might never know why people aren’t sticking around.
To reiterate: As well as an overall abandonment rate, you need to measure the drop out rates at each of the stages of your talent acquisition journey. The next section can help show you what to focus on.
Conventional wisdom tells us that the longer your application and interview process goes on, the higher your dropout rate will be.
But that’s a generalized issue – it tells you nothing about how to fix the problem, beyond simply making it shorter. You need specific, localized data to diagnose and fix your leakage spots.
Data from a 2022 Aptitude Research report on key interviewing trends found that candidates tend to drop out at the following stages, in the following proportions:
Good to know, right? If you audit your own journey, looking at these stages and using these numbers as benchmarks, you can quickly identify your weak areas.
For example: You might be proud of your four-step culture-building interview process, in which candidates have a coffee meet-and-greet with the team they’re hoping to join.
But if it’s cumbersome for the applicant and relies on several stakeholders to orchestrate, it may be dragging your process out unnecessarily, and doing more harm than good.
25% of candidates drop out here. Shouldn’t really be a surprise, should it? Job interviews are long, numerous, and in many cases, ineffective. According to Aptitude Research, 33% of companies aren’t confident in how they interview; 50% believe they’ve lost talent due to poor interviewing.
When asked about their top interviewing challenges, surveyed HR and TA leaders responded:
Let’s focus on that second-last challenge: lack of objective data. Almost a third of companies are approaching their interview and application process with assumptions and gut feelings; and half of them believe their interview process is too long.
Despite this, 68% of companies say they have not made any improvements surrounding candidate experience this year. How many, then, are looking seriously at their entire talent acquisition journey to see where it’s failing?
This is why we’re focusing on candidate abandonment rate in this post: It is a simple metric to show the health of your application process, easier to measure than many of the other recruitment metrics for which you’re responsible (the ever-nebulous quality-of-hire being a prime example). As the saying goes, what gets measured, gets managed.
Start here today, and see what you learn.
(P.S. Sapia’s Ai Smart Chat Interviewer combines the first four stages of your process – application, screening, interviewing, and assessment – together, resulting in an application process that can secure top talent in as little as 24 hours.
Because it’s a chat-based interview with a smart little AI, your team doesn’t need to do anything – everyone who applies gets an interview, immediately. That maximizes your talent pool right from the get-go.
What’s more, our candidate dropout rate is just 15%, on average. That means that 85% of your starting talent pool will stick around.
Why do our candidates stick around? More than 90% of them love the experience. See how we can help you here, today.)
It’s now well established that a wider talent pool means more opportunities for recruiting diverse candidates and this results in higher returns, increased productivity, and creativity benefit companies with a diverse workforce. The issue isn’t that we need these thighs to be proven anymore, but rather that nothing we’ve been doing to create the change we need has worked.
Though well-intentioned, DEI has not delivered. Companies have been motivated by the optics of their DEI programmes rather than taking consequential actions to bring about change. Unconscious bias training has been proven ineffective because it cannot address the systemic issues that lead to bias in the first place.
Companies have also spent large sums of money and resources improving their cultures that celebrate belonging, but neglecting their recruitment metrics because they excuse lack of diverse talent as a ‘pipeline problem’.
To address this we need to do something radical. Because what we are doing just isn’t working.
This is where Ai is, where the power of technology can really have a positive impact on the world.
You need to find undiscovered talent.
Undiscovered talent is the talent that you overlook when using traditional hiring practices that rely on CVs, which are limited in communicating real skills, and job interviews, which are beset with bias and limited in their insight. By using radical new talent intelligence that uncovers people for their job fit, based on science-backed insights, you start to uncover undiscovered talent. These are people who might have been dismissed because of things like age, past experience, ethnicity, gender or other preconceptions and biases that we have about who we think is a good fit for a job.
Our technology has uncovered some amazing talent for the companies that we work with, that they would have otherwise missed out on. This is a massive advantage when it comes to making an impact on this issue.
This is how we start to move the dial on Diversity, Equity and Inclusion.
Want to know if technology can give everyone a fair go?
Hiring with heart has always been important. A recruitment process is often a customer’s closest contact with your brand promise.
The COVID-19 pandemic and its resulting economic damage will result in [double] your potential customers applying for roles and straining your already stretched recruitment teams. Many organisations are asking themselves are our hiring practices costing us, customers?
Maybe a better question would be how many customers did we lose from that hiring round?
Here are interesting findings noted by Ph. Attraction in 2016:
There’s a great read on Virgin Media in the 2020 Candidate Experience Playbook.
In Australia, just one of Sapia’s clients received over 150,000 applications for 10,000 roles in a single year. Unfortunately rejecting over 140,000 potential customers. A poor hiring process could cost them 35,000 customers a year.
This became a catalyst for change. Investing in Sapia:
How many customers are you losing in bulk-hiring?
Here are the two big reasons to prioritise improving candidates’ experience in 2020.
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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. Download it here.
A few weeks ago, I had the privilege to attend Sir Ken Robinson’s opening keynote speech – ‘The Pulse of Innovation’ – at HR Tech World Congress in London.
(You might recognise Sir Ken Robinson from his Ted Talk, ‘Do schools kill creativity?’, which has been viewed almost 45 million times so far.)
As expected, Sir Ken’s speech was filled with equal parts of humour, inspiring stories and thought-provoking ideas around creativity and innovation at work.
Sir Ken opened by highlighting that the average lifespan of organisations is now shorter than it ever has been, and he stressed the importance of continuous innovation and adaptation to external factors in order for organisations to survive – quoting the famous example of Kodak as a company that failed to do so.
Given the context of his speech, it came as little surprise that he stressed the importance of HR’s role in facilitating innovation by identifying and refining talent, and he brought forward one key point which I found particularly interesting – human talent is often buried.
Sir Ken’s point is that talent is not something that we can easily identify, it is something that is hidden within individuals, and it is HR’s role to ‘mine’ for that talent.
“Human talent is highly diverse and it’s often buried. Human resources are like natural resources, you have to go and find them, cultivate them, refine them. If you do this you find that people are capable of extraordinary things.” Sir Ken Robinson
Everyone has potential but it can be quite difficult to see it amongst all the noise and stereotypes we bring with us.
To illustrate this point, Sir Ken cited his own experience interviewing Sir Paul McCartney and George Harrison, both members of a band I think you might know the name of.
During the interview, Sir Ken was surprised to find out that neither of these immensely talented musicians was recognised by their music teacher as ‘top of the class’ – yes, they happened to have the same music teacher in school.
This truly highlights the limitations of our ability to be able to determine what talent looks like (the poor music teacher must really have had to re-evaluate his assessment protocol!).
One of the reasons for this is that we are all inherently bias. While this bias is not conscious, it does affect decisions we make every day.
The ability to categorise or stereotype is an important developmental and evolutionary process that helps humans make sense of the world.
Stereotypes help us make judgements quickly without having to source all pieces of information, but it is detrimental when applied to identifying human talent and hiring decisions.
A basic example; in recruitment and talent acquisition, if successful salespeople in our organisation have all previously had red hair, we might decide that we should only hire red-haired sales assistants.
As human beings, when we try to identify what good ‘looks like’ we concentrate on a few aspects of an individual, and may end up ignoring other important factors that lead to success.
This was further highlighted in a recent Harvard Business Review article, where it was found that 40% of individuals in their study of 1,964 ‘high potentials’ (employees in the top 5% of the organisation) were incorrectly classified as belonging in that category.
In other words, almost half of those identified by managers were not high potentials at all.
42% were below average, with 12% actually being in the bottom ranks with regards to leadership effectiveness.
The point clearly illustrated here is the inability of managers to correctly identify high potentials by not concentrating on the right traits and skills of an individual – they are only human after all.
Sir Ken Robinson spoke in detail about the success of the Beatles and how it was due to the diversity within their group – something that is almost impossible to achieve when allowing subjectivity to guide hiring decisions.
One way of addressing subjectivity and unconscious biases in the hiring process is to make use of data-driven technologies.
Using data to inform hiring decisions means HR can take into account the traits and skills that actually lead to performance, rather than keep focusing on hiring based on subjective stereotypes of success.
At Sapia, we develop predictive models, powered by artificial intelligence, that can predict the likelihood of candidates performing well in organisations based on their behaviour – not on the stereotype they fit into.
Our algorithms and questions are created so that everyone is given an equal opportunity to succeed and be considered, based on what actually drives performance – regardless of age, gender or nationality.
Through adopting AI and data science in the HR field, we can get one step closer to bias-free hiring and increased diversity within organisations.
Whilst AI does take the human out of some part of the hiring decision, the outcomes ensure the human is at the forefront with more opportunities for all.