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
You can try out Sapia’s Chat Interview right now, or leave us your details here to get a personalised demo.
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:
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.
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.
Barb Hyman, CEO Sapia
Madeline Laurano , Researcher Aptitude Research
Sapia, which uses text-based communication to interview candidates, has uncovered a correlation between candidate language and job churn that is “stronger than what you would find normally in traditional psychometric testing of job-hopping”, says CEO Barbara Hyman.
Similar to its recent study measuring candidate personality traits, researchers used data from 46,000 job applicants who completed an online chat interview and used the six-factor HEXACO personality model to analyse responses.
The HEXACO traits are honesty-humility, emotionality, extraversion, agreeableness (versus anger), conscientiousness, and openness to experience.
The ‘openness to experience’ trait has long been considered in organisational psychology circles as an indicator of job-hopping, and this has been reinforced by Sapia’s research, says Hyman
“Low agreeableness also correlates with people who may move and look for better opportunities,” she adds.
Analysing candidates’ responses to determine their job-hopping likelihood is especially useful for many entry-level roles, where people do not have prior experience on their CV.
“We know ‘flight risk’ or staff churn is a really big problem for our customers, particularly those who hire at volume into low-skilled roles. For them to be able to identify this upfront and avoid or minimise it was really valuable,” Hyman says.
And, from the candidate’s point of view, “we’re seeing a real craving and an appetite for understanding yourself and understanding where your strengths are best placed”, she adds.
The researchers also note further work is required to assess the true predictive validity of the outcome – that is, establishing the correlation between inferred job-hopping likelihood and actual job-hopping behaviour.
Sapia has also incorporated the job-hopping measurement into its algorithms to provide this additional information to recruiters, says Hyman.
Importantly, however, “we don’t automatically discount someone who has a high job-hopping likelihood; it’s just another data point you get to look at”.
For some employers and roles, the ‘openness to experience’ trait is generally desirable, Hyman says.
“In investment banking, you want people who are comfortable with looking outside of the box and being really curious and questioning,” she says by way of example.
She stresses the intention is to allow recruitment decision-makers to use the technology as a “co-pilot, not an autopilot”.
Barbara Hyman, Shortlist, Thursday 27 August 2020 2:20 pm
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Finally, you can try out Sapia’s Chat Interview right now, or leave us your details here to get a personalised demo.
An average time-to-hire of 40 days. Hiring costs in excess of $2,000 per candidate. An average turnover rate of 60-70%.
The challenges of hourly recruitment in the retail industry have been well-documented.
Despite this, many of the largest companies persist with old-school recruitment processes.
Given the break-neck pace and scale of the industry, it’s hard to diagnose and fix the problem.
Understandably, many HR leaders have been quick to layer on technology solutions that seem to make things easier; in actuality, these tech solutions have added complexity, making efficiency gains difficult and actionable insights hard to find.
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.
This stack is implemented across a decentralized system – hundreds of stores across the country – resulting in a situation where hiring managers are forced to use systems they don’t understand and don’t like.
The bottom line is this: Retail companies are overstacked, overworked, and need to adopt different solutions to old problems.
One of the biggest challenges with recruitment at major retail companies is high turnover rates. Retail staff members move fast and often, and have a high likelihood of migrating to competing businesses.
This is partially a nature-of-the-beast problem, but if we better understand what makes people tick, we can better match them to the roles at which they’re likely to succeed, and therefore keep them longer.
For example, we know that the best retail cashiers are high in extraversion. They’re energized by being around people, have good interpersonal skills, and have a lower likelihood of experiencing negative emotion while on the job.
It makes sense, then, to prioritize extraversion when matching candidates to the role of cashier. That’s a personality trait – with attendant soft skills – that will predict success for that role.
When people are matched to the job for which they are best suited, they’ll experience higher levels of purpose and satisfaction. It’s obvious why – the daily activities will invigorate rather than drain them. People who have purpose stay longer.
Therefore, if you accurately match soft skills to roles, you’ll reduce churn. Our AI Smart Chat Interviewer is really good at this: Across the board, our skill-matching power reduces non-regrettable churn by a minimum of 25%.
If you’re keen to get started measuring soft skills, download our HEXACO job interview rubric. It features more than 20 interview questions designed by our personality psychologists to assess the skills of candidates that come your way. It will even help you figure out what soft skills are best for you based on the needs and values of your organization.
Chances are, when your employees or candidates leave, they’re probably staying within the industry – and that means they’re likely going to your competitors. It’s 2023, and the stock-standard advice would be to offer higher wages and perks.
That’s not always feasible, and besides, there’s no guarantee that doing so will markedly reduce the threat of poaching and abandonment. Money is important, but it doesn’t trump purpose and belonging.
The key to better employer branding is a system for active listening. Find out what your people, be they employees or candidates, think. Ask them often. It’s important to do this at the onboarding stage, but it should continue through to the point of highest churn – the six-month mark.
Our joint report with Aptitude Research uncovered some interesting data on the importance of two-way feedback between candidates and employers.
Gathering and acting on mutual feedback:
An NPS (Net Performer Score) framework is a good place to start. How likely are you to recommend our company to a friend or colleague?
The NPS tracking question is easily configurable and embeddable into automated emails, meaning it can be set up through your ATS with little additional work.
When you begin to analyze the data, keep things simple: Dump the data into a spreadsheet, and look at your average numbers. If your score is below 0, you’ve got work to do – if it’s 0 to +30, you’re doing well. 30+ and over, well done!
(If you’re reading this, it’s probably not likely that you’ll get a 30+ score on the first go-round. That’s okay – the goal is to find out how much work you’ve got to do.)
The benefit of benchmarking NPS is that it gives your business a single, easy-to-understand proxy for employee engagement. Once you’ve got the number, you can start to make small changes and see how that affects the overall number.
We hear it all the time: Sourcing is a big problem. When we ask customers about their current processes, however, a common problem emerges: We don’t really know how many people we’re losing from our recruitment funnel, and why.
This presents a great opportunity: Often, improving an application process means removing things, rather than adding them.
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:
Let’s say 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.
Is the page too long? Does it have too much text? Is the ‘apply’ button clearly shown? Is the form too long, requiring too much information to fill out? Are your perks/EVP attributes clearly displayed?
We’ve got an in-depth guide for measuring and improving your abandonment rate here.