Written by Nathan Hewitt
The new kind of battle in the war for talent
Before COVID, the conversations I was having with HR executives were about how Sapia might help them with the volume of candidates they were receiving for job openings. For every job posted there were often over a thousand candidates, and it doesn’t take much of a stretch of the imagination to understand how overwhelmed many big organisations were. Our Ai was seen as the solution to automate dealing with candidate volume in a way that found the best people, but also touched base with everyone who applied as part of their brand building. In a nutshell, before the pandemic, efficiency was the key driver in looking for automated hiring solutions like ours.
Now that we’re emerging from the disruption of COVID, no one is talking to me about needing help with the volume of candidates they receive. In fact, they are asking how we might help them get any candidates in the first place! All around the globe, and across multiple industries, there is a need for candidates. It’s certainly been an abrupt change that has left many scratching their heads, but there is almost no time to wrap your head around it if you want to stay in the game. This is a new war for talent unlike any we’ve seen before, and candidates have the upper hand. It’s created a need for a solution to solve two things: firstly, to identify skills in candidates that traditional ways of hiring failed to identify (I call this cohort “undiscovered talent”) and a strong candidate experience (you are the one being interviewed from the moment they hit “apply”).
I thought it was worth looking at how the “war of talent” has evolved since it was first coined by Steven Hankin at McKinsey & Company in 1997. At that time there was a shift in the way that companies valued their talent, and it became seen as important to attract the best in order to have a successful organisation. It’s hard to think about this now, but at that time the whole idea of cultivating company cultures that aimed to elevate and value employees was new. At this stage though the “war” was largely for executive talent with recruiters focusing on building their brand by poaching star C-Suite talent off competitors, wooing them with big sign-up bonuses and lavish overtures like unexpected gifts and trips.
As tech companies started to become the big players in the market, the focus turned from business acumen to the need for the best digital and technical talent. Recruiting became less about material perks (though many engineers still commanded high salaries) but also about giving talent things they wanted besides just money. Flexibility, free lunches, unlimited holidays and creating cultures that were about “working hard and having fun” were how the war for technical talent was won. This was really a time of culture wars between companies, but also meant that many companies hired only for culture-fit. This resulted in fairly homogenous teams that were largely white male techbros, and eventually many large tech companies were called out on it. Beyond tech, corporates were also waking up to the fact that they had some serious diversity issues that needed to be addressed. This led to a new war. The war for diverse talent.
Pre-COVID, hiring more diversely was a strong focus for companies to find the best talent. We all know that diverse teams result in better business outcomes and anyone who had a “pale, male and stale” executive team was seen as minted in the past. Coupled with Black Lives Matter, which became a global movement to address racial inequality from the C-suite down, finding more diverse talent through reducing bias in hiring, was where the war was being fought. This is not a won battle by the way, and remains a large focus for many companies that we work with and help. Importantly, finding diverse talent is still a key part of this new and emerging next phase of the “war on talent” … the one where workers have the upper hand. The one where candidates are in short supply, and people want jobs that suit them just as much as whether they are seen as just suited to the job.
Recruiters have been forced to look at people differently – and this is not a bad thing. Factors like age, ethnicity, education, gender and even past experience that obscured our understanding of someone’s ability to do a job have all been cancelled as qualifying factors. Soft skills, or human skills, have become the focus on what we need to understand in order to assess someone’s suitability to do a job. Are they a team player? Do they like to problem solve? How aligned are they to our company values? Are they self-aware and in touch with their emotions? Can they put stress aside to achieve outcomes?
“What we recruit for” has significantly shifted for many already, but there is still some catching up to do on the “how we recruit”. To be blunt, CV’s and cover letters begging recruiters to “pick me!” serve no purpose in this new battle. They ask too much of candidates from the outset, serve no valuable purpose in the information they provide, confirm our biases and just create work on the HR manager’s side.
We need to walk in a candidate’s shoes and make sure that our recruiting process puts them first, treats them fairly and without bias, meets them where they are at, and is both friendly and informative. And, HR teams need to do this all while working efficiently and fast. Speed is crucial when talent is in short supply.
Impossible? No, not at all. Recruiters need to understand that Ai platforms like ours exist to solve all these problems. We’re not a “technical” solution, but a human one, in that we can accurately identify soft skills immediately and engage with candidates in a one-on-one way, at scale.
You cannot win this war on talent without chat-driven Ai technology. Technology like ours is the only way you can quickly understand the real human skills that every candidate brings to the table, without dismissing anyone upfront.
I can’t help but think that these issues we’re facing as recruiters and HR managers right now, where workers have the upper hand, while unchartered territory, will only serve our industry for the better. It’s a chance to give everyone a fair go, truly understand them, treat them with the dignity they deserve … and still hire better teams.
Maybe it’s not a battle after all. Maybe it’s a win-win.
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For more on how to improve candidate experience using recruitment automation, we have a great eBook on candidate experience.
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Does diversity start with the way you hire?
To find out how to interpret bias in recruitment, we also have a great eBook on inclusive hiring.
In the last month alone, four well-known consumer brands, including Netflix and Hubspot, have published their glossy self-assessments of their progress against Diversity and Inclusion.
If you look at the hard data, though, there is still so little real progress despite so many initiatives and positive intent.
The recent Bersin report shows that, surprisingly, diversity in the U.S work context is going backwards.
That’s because it has to involve some discomfort that cannot be avoided.
One of the first things companies need to do to improve Diversity and Inclusion is to scrutinise their hiring and promotion process.
- Are you relying 100% on human judgement? Decades of research has proved we are biased, especially in hiring.
- Is there any objective data captured about the candidate to ensure a fairer and smarter decision? CV data does not count as objective data; neither does having five subjective viewpoints on a candidate from 5 different interviewees.
- Are you using screening tools or assessments like video interviews? These exclude large chunks of the candidate pool, i.e. introverts, people with autism, people of colour, people who don’t like playing games.
A recent post about the impact of non-inclusive hiring on a 21-year-old job-seeker attracted 35k views and countless efforts to help him find a job. 
It was great to see, but what about the other few million candidates out there who haven’t had the benefit of a social media post to get a job?
Unless we solve the root of the problem, the post achieved little.
Inclusiveness is often a journey, but the most immediate thing we can all control is removing bias from hiring and promotion.
This is literally something that you can start doing tomorrow. Addressing systemic bias is more complex but removing unconscious bias is something we can solve for now.
Get me out of here!
From a candidate’s perspective, applying for a job is demoralising and exclusive. It often involves playing a game, glamping up for a video interview, mind-numbing multi-choice questions, only to be ghosted 99% of the time.
We have been speaking about candidate-first for a decade, now is the time to do it.
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PredictiveHire finalist for In-House Innovation in Recruitment Award at UK’s Recruiter Awards
PredictiveHire and Iceland Foods are finalists in the 2021 Recruiter Awards for the category In-House Innovation in Recruitment.
Established in 2002, the Recruiter Awards are the UK’s most prestigious honours in recruitment.
The awards recognise best practice and celebrate achievement by agencies and in-house recruiters during the prior 12 months, also throwing a spotlight on marketing and technology. The In-House Innovation in Recruitment category recognises outstanding innovation by an in-house recruitment team that has led to the achievement of strategic business goals.
The success story PredictiveHire has been nominated for starts with 2020 creating a crisis for Iceland, as it did for many. Increased trade and COVID-19 absences meant store leaders were massively drained of time, yet there was a surge in both the need to hire and the number of applicants. As it stood, the recruitment process was 100% manual, and all done at store level by store managers.
PredictiveHire’s contribution to In-House Innovation in Recruitment
Iceland had to innovate. Hiring needed to be centralised and automated.
Iceland developed a set of ‘non-negotiable’ criteria for an automated platform and began looking. They ultimately chose PredictiveHire as their interview automation partner – they loved the notion of ‘hiring with heart’.
Once PredictiveHire was selected, we had integrated with their API (Kallidus) and the applications started rolling in within four weeks. Iceland estimated in the first 4 months they saw 5x payback, 8,000 hours freed up for their time-poor store managers across the organisation, and over 50,000 applications were processed every month. They also found that 97% of candidates who followed the link to apply completed the application process and 99% of candidates reported a positive experience.
You can read the full Iceland Foods + Kallidus + PredictiveHire story here.
The award will be presented at the annual Gala in London on September 23, 2021.
The rigorous judging process is done by a judging panel of 33 credible and experienced industry professionals including Rob McCargow, Director of Artificial Intelligence at PwC UK, James Fieldhouse, M&A Managing Director at BDO, and Karolina Minczuk, Relationship Director at Natwest Bank.
Other nominees are BDO in partnership with Amberjack, BUPA, GQR, and Virgin Media in partnership with Amberjack.
About PredictiveHire
PredictiveHire is a frontier interview automation solution that solves three pain points in recruiting – bias, candidate experience, and efficiency. Customers are typically those that receive an enormous number of applications and are dissatisfied with how much collective time is spent hiring. Unlike other forms of assessments which can feel confrontational, PredictiveHire’s FirstInterview™ is built on a text-based conversation – totally familiar because text is central to our everyday lives
Every candidate gets a chance at an interview by answering five relatable questions. Every candidate also receives personalised feedback (99% CSAT). Ai then reads candidates’ answers for best-fit, translating assessments into personality readings, work-based traits and communication skills. Candidates are scored and ranked in real-time, making screening 90% faster. PredictiveHire fits seamlessly into your HR tech-stack and with it you will get off the Richter efficiency, reduce bias and humanise the application process. We call it ‘hiring with heart.’
You can try PredictiveHire here (you’ll receive real personality insights), or leave us your details for one of our team to show you through the whole product
If you’d like to stay up to date with PredictiveHire, you can subscribe to our newsletter here.
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Why HR should implement predictive hiring – and how to get started
You know the common definition of insanity? The one where the same thing gets done over and over again, but the end result doesn’t change? It might not be a big deal when talking about your daily commute, but taking the same old approach to hire key personnel could be an expensive mistake.
Industry studies estimate bad hires cost up to 2.5 times the dollar amount of that person’s salary – and the damage doesn’t end there. Mismatched employees disrupt workplace chemistry, productivity, and profitability.
In response to poor hiring decisions, a growing number of companies now employ predictive screening and hiring models. Engaging predictive analytics and artificial intelligence (AI) – or algorithms that ‘think’ like humans – to help with the legwork historically performed by recruiters.
AI and predictive analytics look at historical data and then apply the learnings to new data to predict future outcomes. So, predictive hiring models can predict who will make it through the interview process, outperform their peers and still be around a few years down the road.
Progressive HR professionals have realised the potential of predictive and data-driven hiring, and hiring managers seem to agree.
“Today, HR has a seat at the table, and in order to maintain that business partnership, you need to have an analytics framework.”
Andy Kaslow, CHRO, Cerberus
A 2016 survey revealed a strong desire to drive talent acquisition through data and analytics. Two hundred executives at large U.S. firms want technology to play a bigger part in the hiring process. And the clamour for analytics isn’t confined to a younger crowd. Two-thirds of decision-makers who desire data-driven solutions fell between the ages of 45-64.
So, why isn’t everyone doing it?
Although there is a general consensus that data-driven and predictive hiring will make hiring decisions more accurate, many HR professionals still view it as cumbersome and costly to implement.
And it can be true.
Understanding the data needed to make an impact, and figuring out the best techniques and algorithms to use is difficult.
And it can be expensive to hire data scientists, and other key technical personnel needed to implement a full scale HR analytics system.
But, there’s no need to go it alone or to do it all at once.
Rather than setting up in-house HR analytics teams, most companies opt to engage a vendor who specialises in custom predictive screening and hiring models. Finding a vendor that works with you to solve your hiring challenges will significantly cut cost and time to implement.
So, if you are considering implementing predictive hiring, we have put together a few tips to ensure you get off to a great start.
1. Define what you want to improve
The crucial first step of any successful project is to define what that success looks like. And implementing predictive hiring isn’t any different.
Have a think about the biggest issue your organisation is facing at the moment that better hiring decisions will solve.
For example, you might have the issue that a lot of new hires are leaving your organisation after a few months. Or you might have a company culture in need of strengthening, and need to hire people who fit with your ideal culture.
When you have honed in on the issue you want to solve, you also need to start thinking about the data that will be required to solve your challenge.
To give you an indication of the type of data you might need, consider these examples;
- If you have an issue with turnover, the data needed would be employees’ start and end date.
- Or, if you were looking to improve your customer service level at a call centre, you would need some sort of customer service KPI data – for example NPS.
(These indications are based on the data required if you were working with us at PredictiveHire)
2. Find a shortlist of vendors
After defining the issue you want to address with predictive hiring, it is time to find a shortlist of vendors that can help you achieve your goal.
Make sure you look for vendors who are able to build predictive hiring models focused on your specific issues, whilst making sure the candidate experience isn’t compromised.
3. Perform your due diligence
When you have your shortlist of vendors narrowed down, make sure you perform your due diligence. Some vendors will be a better fit for the challenge you wish to solve with your predictive hiring model.
Make sure your shortlisted vendors address these key questions;
- What are they basing their predictions on? Predictive hiring experts should be able to tell you the scientific basis of their predictions.
- How do they address the potential of existing biases being incorporated into the algorithms?
- How do they fit in with your current hiring process? Can they fit in without causing too much disruption/change?
- What is the user experience of their product like? How about the candidate experience? For a predictive hiring solution to be useful it should be easier to use than not to use.
- How do they support you during implementation, on-boarding and roll-out of the tool?
- What is required from you in order to maximise the project outcome?
Ai for Hiring – Buyers Guide: The 8 Questions You Must Ask
All of these questions are important to address to ensure the project’s success.
Implementing new software and processes will always require some level of change management, for example; following the ADKAR or Kotter change management approaches. Make sure you are comfortable with the level of support the vendor will offer you during the roll-out.
Following these three steps will ensure you are off to a good start with your predictive hiring project – and can start reaping the rewards quickly.
Predictive HR analytics is here to stay.
Resisting this change may put your company at a distinct disadvantage in the marketplace.
A recent MGI study found that AI can significantly improve the bottom line for businesses willing to incorporate them into their core functions. And the time really is now. Early adopters will enjoy a significant data-advantage in only a few years.
“[Leading businesses] use multiple AI technologies across multiple functions. As these firms expand AI adoption and acquire more data, laggards will find it harder to catch up.”
McKinsey Global Institute, June 2017
In the words of Gartner Research’s senior vice president Peter Sondergaard, “Information is the oil of the 21st century, and analytics is the combustion engine.”
You can try out Sapia’s Chat Interview right now, or leave us your details to book a demo