It’s an understatement to say that recruiters and talent acquisition managers have had it tough over the last four-odd years. The pressures have compounded like a line of falling dominoes: First it was the COVID-19 pandemic; then came the mass talent migration; then the advent of new concepts like ‘quiet quitting’ and ‘acting your wage’, which, like them or not, seem to be the manifestations of a tired and existentially anxious workforce.
Now, in 2024, it’s likely that we’ll have to contend with a global recession.
Hiring is tougher. Candidates are wary and they expect more. Duh.
So do companies and their CEOs. However – and somewhat counter-productively – many companies have sought to cut recruitment budgets, lay off recruiters and talent acquisition managers en masse, and deprioritize long-term recruitment marketing strategies. We’re facing troubled times, and recruitment (and perhaps HR, more generally) is being treated as a cost center.
This misunderstanding of HR as a money sink is nothing new. It happens during every trough in the market. But, if we don’t make efforts to change this perception, 2024 will be a particularly painful valley to climb out of.
Why is recruitment treated as a cost center?
CEOs have been keen on talent strategy for years, but are struggling to quantify the effects of recruitment and talent acquisition activities. They cannot see the A to B journey, the action and its result. When the market is good, talent is in abundance, and you’re hiring effectively, nobody cares. But when times are hard, nebulous processes are put under harsh light.
Relatedly, recruitment and talent acquisition leaders are struggling to prove that the outcomes of their work are driving revenue. This is primarily an issue of data capture and analysis, in our experience: When companies come to us to help with hiring quality talent, the number one issue they have is to do with metrics and KPIs. Most do not know how to reliably measure quality of hire, nor time-to-hire, nor the effectiveness of their recruitment marketing channels. Many know that their processes are plagued with inefficiencies, but are not sure how to go about fixing them.
(To be clear, totally understandable. This stuff is hard.)
The big and unmanageable HR tech stack
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.
These technologies cost big money. As a result, the question CFOs and CEOs will be constantly asking of HR is this: Is it adding real value? Can you prove it? Or are we simply stuck to a system that tackles old problems with insufficient solutions?
The bottom line is this: Enterprise companies are overstacked, overworked, and need to adopt different solutions to old problems. It doesn’t mean less tech, necessarily, although it can; it means the right tech.
Focus first on areas of lost productivity.
Easier, perhaps, than it sounds. It’s always better to iterate than to completely restructure your hiring function. So get your team together and examine your processes. How much time is spent:
- Sourcing and reviewing candidates (including, importantly, reading through resumes and cover letters)?
- Screening?
- Scheduling, rescheduling, and conducting interviews?
- Organizing and corralling hiring managers?
- Gathering, collating, and providing feedback to candidates?
- Communicating with candidates, more generally?
- Onboarding?
Ideally, you have baseline data in your ATS to help you arrive at some indicative numbers. But let’s assume that you don’t: calculating rough person-hours is enough to see where time may be spent more effectively.
In our experience, sourcing and screening are the stages in which quick wins might be gotten. As time-honored research (and our Smart Interviewer product) shows, resumes and cover letters are not useful indicators of candidate quality or potential. They can be easily falsified. What’s more, Sapia and Aptitude research from 2022 discovered that 22% of candidates drop out at the application stage and 24% at the screening stage.
The biggest companies are starting to focus more on this. According to the Wall Street Journal, employers like Google, Delta and IBM are combatting the tight labor market by easing strict needs for college degrees.
Interviews are another huge cause of inefficiency. Structured interviews are the best explainer (at 26%) of an employee’s performance, but many companies allow recruiters and hiring managers to conduct interviews haphazardly, causing a misidentification and loss of talent that can be hard (if not impossible) to measure. If you’re interviewing badly, how can you know if you’re capable of finding good candidates? What’s the associated cost of such a problem?
It’s no surprise, then, that according to our research, 50% of companies say they’ve lost talent due to the way they interview. Big costs involved there.
Next, focus on measurable metrics
Don’t worry: We’re not going to lay out a massive and exhaustive list of metrics you should be tracking. Not feasible; you’re overworked as it is.
Instead, we’ll prescribe three good places to start, including links to helpful blog posts explaining how you measure them effectively:
- Candidate abandonment rate
- Candidate source attribution (or where candidates actually come from)
- Candidate experience baseline
Each of these metrics can help you improve efficiencies, and in turn, start to prove that your recruitment function is having a positive effect on business outcomes.
Layer on tech that can help you drastically improve hiring efficiency, while giving you time to focus on big picture stuff
At a certain point, we must realize that force-multiplying technology is the only way to win in the unfolding ‘now’ of work. We’re spending way too much time with processes that can be repeated and automated – often out of some sense of duty to uphold 1:1 human connection (as if technology completely removes that, which it doesn’t).
And, because we do this, we weaken our position at an executive level: CEOs care about what is scalable, and the average recruitment function, traditionally speaking, does not.
In a recent episode of our Pink Squirrels! podcast, Sapia CEO and founder Barb Hyman had a chat with expert HR change management leader, Kyle Lagunas, about this very topic.
The one foolproof way to elevate recruitment in your company
We exist to help you hire better, faster, and with fewer headaches. Our Smart Interviewer takes care of the scheduling, interviewing, and assessment stages of your process – saving upwards of 2,000 recruitment hours (av.) per month, and enabling you to offer jobs to candidates within 24 hours of application.
It’s delivered in a chat-based format (hello, Gen Z!), and candidate responses are assessed according to science-backed personality models. This means you can be sure you’re getting top talent, and you can prove it with measurable, repeatable data.
That’s not all: Our tech is blind, which means it natively disrupts bias and maximizes the size of your talent pool. Everyone gets an interview, and everyone gets personalized coaching tips whether or not they get the job. Our application completion rate, for all customers, sits at around 85% on average; our candidate satisfaction rate is well over 90%!
(And, if you need a second stage interview, you can use our Video Interview tool.)
Everything you do with our platform is pulled through to comprehensive data dashboards, allowing you to see hiring efficiency, quality, time, diversity, and other metrics. CEOs love this kind of transparency.
There you go: time saved NOT having to screen, review resumes and cover letters, compile candidate feedback, communicate with candidates, or improve hiring manager interview techniques.
When you’re saving that much time and money, your recruitment (or HR) function has more bandwidth to focus on long-term talent acquisition and people initiatives.
Don’t struggle in 2024 – speak to our team today about how we can solve your hiring challenges.
Related
Blog
Humanising hiring: the largest study of AI candidate experience ever
This is the state of hiring in 2025. Too often, candidates are ghosted, ignored, and reduced to a CV. Recruiters are forced to make decisions in data poverty, with scraps of information like grades, job titles, or where someone has worked before. Privilege gets rewarded; potential gets overlooked.
For the first time, we now have evidence that AI, when designed responsibly, brings humanity back to hiring.
The largest research study of its kind
Sapia.ai has released the Humanising Hiring report. The largest analysis ever conducted into candidate experience with AI interviews. The study draws on more than 1 million interviews and 11 million words of candidate feedback across 30+ countries.
Unlike surveys or anecdotal reviews, this research is grounded in what candidates themselves chose to share at one of the most stressful moments of their lives: applying for a job.
The findings are bold and unprecedented
- 9.05/10 average candidate satisfaction across all groups and industries
- 81.8% of candidates left written feedback — engagement at this scale has never been seen before in hiring research
- 8 in 10 candidates would recommend an employer just because of the interview
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30% more women apply when told AI will assess them, resulting in a 36% closure of the gender gap
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98% hiring equity for people with disabilities through a blind, untimed, mobile-first interview design
Candidate voices
Here’s what candidates themselves revealed:
“None of the other companies I’ve applied to do this sort of thing. It’s so unique and wonderful to give this sort of insight to people… whether we get the job or not, we can take away something very valuable out of the process.”
“That felt so personal, as if the person genuinely took the time to read my answers and send me a summary of myself… that was pretty amazing.”
Expert validation
“This study stands out as one of the most comprehensive examinations of candidate experience to date. Analysing over a million interviews and 11 million words of candidate feedback, the findings make clear that responsibly designed AI has the potential to fundamentally improve hiring — not just by increasing speed, but by advancing fairness, enhancing the human aspect, and leading to stronger job matches.”
— Kathi Enderes, SVP Research & Global Industry Analyst, The Josh Bersin Company
Proof that AI can be human
The research challenges the idea that AI dehumanises the hiring process. In fact, it proves the opposite: when thoughtfully designed, AI can restore dignity to candidates by giving them a real interview from the very first interaction, giving them space to share their story, and giving them timely feedback.
With Sapia.ai’s Chat Interview:
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Every candidate gets the same structured, role-relevant questions.
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Interviews are untimed, so candidates can answer at their own pace.
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Bias is monitored continuously under our FAIR™ framework.
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Every candidate receives personalised feedback.
This isn’t automation for the sake of speed. It’s intelligence that puts people first, and it works. Leading global brands, including Qantas, Joe & the Juice, BT Group, Holland & Barrett, and Woolworths, have all transformed their hiring outcomes while enhancing the candidate experience.
Why it matters now
Applicant volumes are exploding. Boards are demanding ROI on people decisions. And candidates expect fairness and agency. Sticking with the status quo — ghosting, inconsistent interviews, CV screening — comes at a real cost in brand equity, lost talent, and wasted time.
It’s time to move from data poverty to data richness, from broken processes to brilliant hiring.
Download the report
This is the first time candidate feedback on AI interviews has been analysed at such scale. The insights are clear: hiring can be brilliant.
👉 Download the Humanising Hiring report now to see the full findings.
Blog
What’s More Ethical: Measuring Skills or Guessing Them?
Barb Hyman, CEO & Founder, Sapia.ai
Why skills data matters for HR and CHROs
Every CHRO I speak to wants clarity on skills:
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What skills do we have today?
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What skills do we need tomorrow?
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How do we close the gap?
The skills-based organisation has become HR’s holy grail. But not all skills data is created equal. The way you capture it has ethical consequences.
Two very different approaches to skills analysis
1. Skills inference from digital traces
Some vendors mine employees’ “digital exhaust” by scanning emails, CRM activity, project tickets and Slack messages to guess what skills someone has.
It is broad and fast, but fairness is a real concern.
2. Skills measurement through structured conversations
The alternative is to measure skills directly. Structured, science-backed conversations reveal behaviours, competencies and potential. This data is transparent, explainable and given with consent.
It takes longer to build, but it is grounded in reality.
The risks of skills inference HR leaders must confront
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Surveillance and trust: Do your people know their digital trails are being mined? What happens when they find out?
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Bias: Who writes more Slack updates, introverts or extroverts? Who logs more Jira tickets, engineers or managers? Behaviour is not the same as skills.
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Explainability: If an algorithm says, “You are good at negotiation” because you sent lots of emails, how can you validate that?
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Agency: If a system builds a skills profile without consent, do employees have control over their own career data?
A more human approach: skills measurement
Skills define careers. They shape mobility, pay and opportunity. That makes how you measure them an ethical choice as well as a technical one.
At Sapia.ai, we have shown that structured, untimed, conversational AI interviews restore dignity in hiring and skills measurement. Over 8 million interviews across 50+ languages prove that candidates prefer transparent and fair processes that let them share who they are, in their own words.
Skills measurement is about trust, fairness and people’s futures.
Questions every HR and CHRO should ask
When evaluating skills solutions, ask:
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Is this system measuring real skills, or only inferring them from proxies?
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Would I be comfortable if employees knew exactly how their skills profile was created?
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Does this process give people agency over their data, or take it away?
The real test of ethics in the skills-based organisation
The choice is between skills data that is guessed from digital traces and skills data that is earned through evidence, reflection and dialogue.
If you want trust in your people decisions, choose measurement over inference.
To see how candidates really feel about ethical skills measurement, check out our latest research report: Humanising Hiring, the largest scale analysis of candidate experience of AI interviews – ever.
FAQs
What is the most ethical way to measure skills?
The most ethical method is to use structured, science-backed conversations that assess behaviours, competencies and potential with consent and transparency.
Why is skills inference problematic?
Skills inference relies on digital traces such as emails or Slack activity, which can introduce bias, raise privacy concerns and reduce employee trust.
How does ethical AI help with skills measurement?
Ethical AI, such as structured conversational interviews, ensures fairness by using consistent data, removing demographic bias and giving every candidate or employee a voice.
What should HR leaders look for in a skills platform?
Look for transparency, explainability, inclusivity and evidence that the platform measures skills directly rather than guessing from digital behaviour.
How does Sapia.ai support ethical skills measurement?
Sapia.ai uses structured, untimed chat interviews in over 50 languages. Every candidate receives
Blog
Mirrored diversity: why retail teams should look like their customers
Walk into any store this festive season and you’ll see it instantly. The lights, the displays, the products are all crafted to draw people in. Retailers spend millions on campaigns to bring customers through the door.
But the real moment of truth isn’t the emotional TV ad, or the shimmering window display. It’s the human standing behind the counter. That person is the brand.
The missing link in retail hiring
Most retailers know this, yet their hiring processes tell a different story. Candidates are often screened by rigid CV reviews or psychometric tests that force them into boxes. Neurodiverse candidates, career changers, and people from different cultural or educational backgrounds are often the ones who fall through the cracks.
And yet, these are the very people who may best understand your customers. If your store colleagues don’t reflect the diversity of the communities you serve, you create distance where there should be connection. You lose loyalty. You lose growth.
We call this gap the diversity mirror.
What mirrored diversity looks like
When retailers achieve mirrored diversity, their teams look like their customers:
- A grocery store team that reflects the cultural mix of its neighbourhood.
- A fashion store with colleagues who understand both style and accessibility.
- A beauty retailer whose teams reflect every skin tone, gender, and background that walks through the door.
Customers buy where they feel seen – making this a commercial imperative.
How to recruit seasonal employees with mirrored diversity
The challenge for HR leaders is that most hiring systems are biased by design. CVs privilege pedigree over potential. Multiple-choice tests reduce people to stereotypes. And rushed festive hiring campaigns only compound the problem.
That’s where Sapia.ai changes the equation: Every candidate is interviewed automatically, fairly, and in their own words.
- Bias is measured and monitored using Sapia.ai’s FAIR™ framework.
- Outcomes are validated at scale: 7+ million candidates, 52 countries, average candidate satisfaction 9.2/10.
- Diversity can be measured: with the Diversity Dashboard, you can track DEI capture rates, candidate engagement, and diversity hiring outcomes across every stage of the funnel.
With the right HR hiring tools, mirrored diversity becomes a data point you can track, prove, and deliver on. It’s no longer just a slogan.
Retail recruiting strategies in action: the David Jones example
David Jones, Australia’s premium department store, put this into practice:
- 40,000 festive applicants screened automatically
- 80% of final hires recommended by Sapia.ai
- Recruiters freed up 4,000 hours in screening time
- Candidate experience rated 9.1/10
The result? Store teams that belong with the brand and reflect the customers they serve.
Read the David Jones Case Study here 👇
Recruiting ideas for retail leaders this festive season
As you prepare for festive hiring in the UK and Europe, ask yourself:
- How much will you spend on marketing this Christmas?
- And how much will you invest in ensuring the colleagues who deliver that brand promise reflect the people you want in your stores?
Because when your colleagues mirror your customers, you achieve growth, and by design, you’ll achieve inclusion.
See how Sapia.ai can help you achieve mirrored diversity this festive season. Book a demo with our team here.
FAQs on retail recruitment and mirrored diversity
What is mirrored diversity in retail?
Mirrored diversity means that store teams reflect the diversity of their customer base, helping create stronger connections and loyalty.
Why is diversity important in seasonal retail hiring?
Seasonal employees often provide the first impression of a brand. Inclusive teams make customers feel seen, improving both experience and sales.
How can retailers improve their hiring strategies?
Adopting tools like AI structured interviews, bias monitoring, and data dashboards helps retailers hire fairly, reduce screening time, and build more diverse teams.