A good candidate experience doesn’t cut it in the current recruitment climate. It’s the most basic thing that hiring managers need to fulfil, but if that’s all you are delivering you are going to miss out on talent.
You need to hire fast (interview-to-offer in 24 hours) and your process needs to be frictionless – ie. you can’t be asking candidates to jump through hoops to prove themselves to you. No games, no CVs, no third interviews, no asking them to make time for an interview when you are free.
Those days are over. The global talent shortage is being felt across every industry and recruitment needs to be re-imagined.
And, there’s only one solution: automation.
Yes, it can be hard to cut through a lot of hype around automation, but it is possible that leaders can develop a clear-eyed way to think about how these technologies will improve their organizations.
This is not about replacing jobs of HR managers, but giving them the tools to help them grapple with the challenges in the current hiring environment. It’s about empowering HR teams to be able to do the seemingly impossible – and be good at it. Or to put it another way, help them create a human-centric organization with super-human intelligence.
This was the challenge that Woolworths Group brought to us. Even before the pandemic, the Group was realising that they needed to invest in more efficient processes to keep up with the recruitment demands of the company. But remaining fair about who they hired and treating candidates with respect was not up for compromise.
They had just recovered from surge hiring needs brought on by COVID and wanted to make sure they never had to go through that as a team again. The task had been slow and manual, took too long to hire and the tech they had used was not reliable.
They were looking to redefine their whole approach and realised they could not deliver a positive experience to candidates without the help of technology.
Sapia’s current chat-based candidate assessment was chosen as a front-runner after an extensive search for tools, given the fact that it meant that bias was removed from reviewing candidates and because it also meant they could give every candidate constructive feedback – even if they didn’t get the job.
However, there was still an opportunity to solve for the sheer volume of video interviews that had to occur in the next step.
This made Woolworths a perfect candidate to roll out Sapia’s Video Interview product, a video interview delivered via conversational chat that candidates can do in their own time, and doesn’t require any scheduling input from hiring managers.
This means anyone can now run a fully automated hiring process that is both fair, candidate-friendly and insanely fast. Woolworths was the first customer to go live with Video Interview and as the largest private employer in Australia it was a true test of the effectiveness of the product.
Within one week of going live Smart Interviewer, our text chatbot, had interviewed more than 10k candidates, all without bias. The introduction of an end-to-end fully automated chat based assessment process where every candidate is interviewed and every candidate receives personalised feedback transformed their recruitment for candidates.
But, what was transformational for hiring managers was that the top candidates were then able to do Video Interviews through the platform by video recording answers to a set of questions on their phone. No-one had to schedule an interview and hiring managers could quickly assess the best candidates for the role by simply watching a video – also, in their own time.
Time-to-decision is as little as 24 hours in some cases with the Group achieving an NPS score of 8.8.
The issues that Woolworths faced are felt by most large companies hiring at scale.
With the introduction of Video Interview, Sapia can now create and deliver a solution that streamlines the Woolworths recruitment process and improves the efficiency of large-scale recruitment for other companies as well.
If you’d like to know more about Video Interview and how we have integrated video into our product suite without compromising fairness, please get in touch.
You can also download our Woolworths case study.
I am seeing organizations increasingly rely on AI that comes from social media or resume data. How do you see that? Does that bother you? Do you think we need to educate the market about the difference between first-party and third-party data and ask questions about how clean and unbiased the data is?
As a former HR leader, I couldn’t use technology that analyzes my candidate pool or my people based on what they do on social media. It horrifies me, and it kills trust. I feel like that kills trust, you know, because I’m on social media in my own personal way. What do you think about that trend, and how can we tackle it?
I think we need to educate people at the point of recruitment. We could let them know why they should feel safe using AI-based technology and that it doesn’t use third-party data or do anything unethical.
If we provide warnings and information, people will start to look for trustworthy AI. Remember how banks got everyone to feel safe about transferring money online? We need an education piece on how this AI is different from that one.
Imagine if we said, “Before you’re about to go through AI-based technology for this recruitment process, we’re going to let you know why you should feel safe in doing so. It doesn’t use third-party data, it doesn’t do anything unethical.”
Again, take internet banking: How did the banks get everyone to feel OK about transferring money online?
I mean, all of us used to go and check the money even got there, and you know, there’s some people that still don’t use it today. I’ve got a friend with a fantastic organic beauty products business. Another one who’s got a collagen business. Both are constantly having to say, “We look the same as other products – but let me tell you how we’re not.”
And I think there is an education piece on, let me tell you how we’re not.
I love that you’ve taken the candidate’s view on that. We need to protect them and our brand, and trust is crucial. We shouldn’t blindly trust AI; we should be able to trust it because it’s safe to do so. That’s a great call to action for all of us in that space.
Listen to the full episode of our podcast with Meahan Callaghan, CHRO of Redbubble, here:
It’s not every day or every job where you get to say you are changing the way the world works.
For 2+ years, the small team of incredibly dedicated data scientists led by the incredibly humble Buddhi Jayatilleke have tested and re-tested and experimented and re-experimented to find a new formula for assessing talent – one that is 100% inclusive and bias-free, but also human, using the combination of AI, machine learning and advances in NLP.
Apart from reading daily the thousands of comments of gratitude we receive from candidates for this new formula, which is globally unique! it is wonderful to see that team receive the industry acknowledgement at a global level.
Last week, at a Virtual CogX, the world’s largest Festival of AI and Emerging Technology, with top CEOs, Scientists, Technologists, Data Scientists in attendance, with over 30,000+ attendees from hundreds of countries, 6500 world leaders and 650 presenters across 17 forums, this team were awarded Top 3 For Best AI in HR technology.
For a team that has been tackling this problem for such a small amount of time, with limited resources but endless tenacity and commitment, we couldn’t be prouder to get to work with them every day.
The PredictiveHire Data Science Team:
Are you interested in using an award-winning solution in your business to recruit faster, better, fairer? Let’s chat
PredictiveHire is also a finalist in the Talent Tech Stars awards for best Candidate Experience Solution of the year
There are some steps we can take to eliminate bias in recruitment and it begins with not relying on CVs as a method of evaluating candidates.
CVs are full of information that is irrelevant to assessing a person’s suitability to do a job. They instead highlight things that we often use to confirm our biases, and draw our attention from other key attributes or aptitudes that might make someone especially suitable for a job.
For example, if a CV mentions a certain university it might pique our attention (a form of pedigree bias). This is problematic, as there may be socio- economic reasons why someone attended a certain university (or did not attend another) and CVs do little to reveal this. Situations like this confirm the bias that lead to it in the first place, compounding bias for these long-term systemic issues.
Additionally, CV data reduces a candidate pool in a way that is not optimising for better fits for the role, by relying on the wrong input data and criteria to find a candidate. Amazon discovered this when it abandoned its machine learning based recruiting engine that used CV data when it was discovered the engine did not like women.
Automation has been key to Amazon’s dominance, so the company created an experimental hiring tool that used artificial intelligence to give job candidates scores ranging from one to five stars.
The issue was not the use of Ai, but rather its application. Amazon’s computer models were trained to vet applicants by observing patterns in resumes submitted to the company over a 10-year period. Most came from men, a reflection of male dominance across the tech industry. As a result of being fed predominantly male resumes, Amazon’s system taught itself that male candidates were preferable. It penalised resumes that included the word ‘women’ as in “women’s chess club captain.” It also downgraded graduates of all-women’s colleges.
Studies have shown systemic unintended bias occurs when reviewing resumes that are identical apart from names that signify a racial background or gender, or a signifier of LGBTQIA+ status. The solution for this has been to remove names or any identifiable data from an interview or CV screening, but these have still experienced bias issues like those discussed earlier.
In order to be truly blind, any input data needs to be clean and objective. This means that it gives no insight into someone’s age, gender, ethnicity, socio-economic standing, education, or even past professional experience.
To truly disrupt bias, recruiters and hiring managers should utilise a new wave of HR tech tools such as Sapia, stepping away from using CV data as a way to determine job suitability.