Volume hiring on a tight timeline can strike fear into even the most experienced recruiter! More often than not, the fallout of failing to hire enough people causes real pain to the business, managers, and you.
So, how can you tackle high volume recruiting and get better with a high volume recruiting strategy each time? Here are our pro tips.
What is high volume hiring?
High volume hiring, often termed high-volume recruiting, is the process of recruiting for many positions (50 or more) concurrently or in a very limited period of time. Often the 50+ roles will be of the same job type. It also implies high volumes of applicants coming through for recruiter’s review, making high volume recruiting tools crucial.
Volume hiring in recruitment, also known as volume recruitment or bulk recruitment process, is common in retail and hospitality, where many people have to be hired quickly for busy periods, events, and new store or restaurant openings. Graduate recruitment in large organizations often falls under high volume recruitment, as does hiring for nurses, other health workers, and call centre staff. A proper high volume hiring strategy is pivotal in these sectors.
During C-19, we saw the emergence of surge hiring – again, another form of high-volume hiring where thousands of people are needed in-store or in the contact-centre within days.
High volume recruiting challenges to overcome
Apart from the sheer logistical challenges, there are five major high volume recruiting challenges organisations face.
- Time invested in high-volume hiring
Roles filled by high volume recruitment often have a highly sensitive empty chair impact. A restaurant with too few servers, a shop with too few attendants, a call centre with too few people answering the phone, or a hospital ward with too few nurses, all are scenarios that underscore the importance of volume hiring.
In a perfect world, recruitment requirements can be anticipated and planned for using the right high volume recruiting tools, but that’s not always the case. That’s why a scalable, repeatable high volume recruiting strategy is essential.
- Cost invested in high-volume hiring
When you’re attracting, screening, selecting and hiring 250+ people at once using the bulk recruitment process, it’s not just timelines that can blow out.
The cost can easily go over budget too. This is where scalable processes, talent pooling, and high volume recruiting tools are your allies.
- Poor candidate experience during high-volume hiring drives
In many industries that need high volume recruitment, your candidate is also your customer. Often people are applying for a position because they love your brand. If they have a bad experience, you’ll not only probably lose them as a customer, they’ll tell their friends and family too.
Getting the candidate experience right at scale isn’t easy, but it’s essential. Otherwise, your marketing department will be asking some serious questions, and you’ll find it much harder to find good applicants in the future.
- Communicating employee value proposition (EVP) during a high-volume recruitment drive
Speaking of reputation, your employer brand and employee value proposition play a huge role in attracting the right candidates. You may also find that candidates in certain industries (like retail and hospitality) are easily swayed to join a competitor who tells a better story.
Sometimes a candidate’s decision whether or not to take a role is related to their hourly rate. But more and more often, candidates want to work for a company that aligns with their values and offers learning and development opportunities. Make sure you articulate your EVP well using an effective high volume recruiting strategy. Your competitors will be using their EVP to try and snaffle your candidates.
- Balancing diversity in your hiring pool across high-volume roles
High volume hiring strategy demands that diversity be a cornerstone. Hiring for diversity when you’re under time and cost pressure can feel overwhelming. But it’s essential that you embed diverse hiring practices in all of the hiring you do. Building a diverse team will result in better decision-making, better customer service, and a healthier bottom line.
Volume hiring strategies
Now you know the major high volume recruiting challenges, it’s time to put together the right volume hiring strategies to help you overcome the challenges, and attract and hire the best people.
Bulk hiring techniques have come a long way over the years, from Applicant Tracking Systems scanning and scoring CVs, to the explosion of recruitment Ai now available. Let’s take a look at the volume hiring best practices you can use to make each stage of the bulk recruitment process scalable, fast and fair.
Six major milestones of the bulk recruitment process
There are six major milestones in the bulk-hiring process. Discover, engage, assess, interview, decide and validate. Each stage is equally important, and most stages of the bulk-hiring process can be streamlined so that they’re highly scalable. (The Interview and Decide stages are the most time and resource-intensive, but they’re well worth the investment.)
Discover
Ensuring the right potential applicants find you is the first step in getting volume hiring in recruitment right.
Remember:
Lean into your Applicant Tracking System (ATS). Spend your time writing a great ad highlighting your EVP and let the ATS do the heavy lifting of shipping to multiple job boards.
Think about how applicants from underrepresented backgrounds can find your ad, and make it clear everyone’s welcome.
For retail and hospitality, don’t forget walk-in applicants. Check if you can use a ‘kiosk mode’ or similar with your ATS so applicants can fill in their details on an iPad rather than having paper applications pile up on manager’s desks (and get lost!).
Check previous applicant pools and ask for employee referrals.
Measure:
Performance of each advertising channel (ideally by how many successful candidates the channel attracts)
The diversity of your applicant pool
Pro tip:
People want to know what it’s like to work at your organisation. Ideally, have a video on the ad with people in a similar role explaining what it’s like. If you’re in a hurry – include quotes from an employee or two.
Engage
Once you’ve got an applicant’s attention, you need to make sure they stay interested.
Remember:
Applicants are applying for multiple positions, and the organisation who delivers the best candidate experience wins. Make communications look as 1:1 as possible.
Measure:
Application completion rate. This will tell you if the process is working, or if there’s something putting potential applicants off. This could be the length of the form, a confusing requirement, or even a technical glitch.
Pro tip:
Put some character into your application received responders. Write as you talk rather than like a bureaucrat. And don’t say: we can’t get back to everyone if you don’t hear from us you’ve been unsuccessful (or similar). If you expect candidates to put energy into applying, put energy into replying.
Assess
Now you’ve got a pool of candidates; you need to assess them.
Remember:
Sadly, CVs have proven themselves to not be a good way to assess future performance, and they only reinforce biases. This is an opportunity to disrupt the usual bulk-hiring techniques with something that delights candidates and hiring managers.
Measure:
Candidate satisfaction. This will tell you how candidates find the experience. It’s is a good indicator that offer acceptance should be healthy, and that you won’t lose customers who are candidates. Some recruiting platforms offer candidate satisfaction surveys, or you can choose to use your employee engagement platform.
Pro tip:
We created Smart Interviewer, our conversational chat technology so that every candidate could have an interview. Not only do you get detailed responses to questions, but the answers also reveal more about the candidate’s personality than any CV ever could. Using natural language processing, we’re able to build an accurate personality profile. Every single candidate receives automated, personalised feedback, and they love it. One supermarket client, Iceland, interviewed 50,000 candidates and received a 100% candidate satisfaction score.
Interview
Once you have the results of Ai chat assessments, you’ll want to interview the candidates whose scores and profiles appear to match your requirements.
Remember:
Have a diverse selection panel (especially if you have a diverse talent pool).
Be consistent in how you interview and assess each candidate. Especially in group interviews, don’t be tempted to hire extroverts. You need a mix of personalities to build a successful team.
Measure:
Attendance. If there’s a significant drop-off, look into why.
Pro tip:
We created Talent Insights so you can easily see each candidate’s score and psychometric profile informed by their Ai chat responses before you speak with them. We designed our Live Interview platform to make collecting and recording consistent data easy, so you can ensure everyone gets a fair go (and you don’t have to sort through impossible to interpret notes after your meetings).
Decide
Now you’ve got a list of fantastic candidates, you’ve met them, and you’re ready to invite some of them to join you.
Remember:
Now is not the time to fall back on ‘gut feeling’ or ‘culture fit’. Use the data you’ve collected to make informed, unbiased bulk-hiring decisions.
Know in advance if you’ll accept a candidate with minor flags in background checks or character references in place of professional ones. Stick to the decisions when you’re in those situations.
Measure:
Offer acceptance rate – to uncover any underlying issues with how attractive your EVP or employer brand is.
Applicants to hire rate – to understand if you could advertise less or in fewer channels in future.
Candidates to hire rate – to understand if you can optimise the size of your interviewed candidate pool.
Pro tip:
Start onboarding the moment an employee signs. Invite them to your learning platform, or simply send them a video from their manager or the CEO welcoming them on board and saying how excited you are to have them.
Validate
To ensure your process is working, it’s essential to measure your success.
Remember:
Book in an hour or two a week or so after the end of each bulk recruitment process to analyse the data.
Take a look at the list of challenges above, and any goals you had at the start of the process and see how you tracked against them.
Measure:
Candidate satisfaction
This will come from surveys sent to all candidates. It’s built into Sapia and most other recruitment software.
Time to hire
The elapsed between when a candidate is first contacted (in these volume hiring strategies, the assess stage) and when they’re hired.
Cost per hire
All of the hiring costs, divided by how many candidates were hired.
Offer acceptance rate
The number of offers accepted, divided by the number of offers made, multiplied by 100. If this is low, consider any issues with your EVP or the time it takes to make an offer after an interview.
Diversity
At Sapia we don’t collect attributes which could attract bias. We build an understanding of diversity by using Namsor (www.namsor.com) in order to validate the effectiveness of our platform. Namsor takes names of applicants and derives gender and ethnicity, and we use that data to understand how effective we have been at achieving diversity at each step of the path.
Pro tip:
Measure, learn and optimise your high volume recruiting strategies every single time you complete a project, and you’ll find you improve each time. This will save time and money, and increase diversity.
Bulk hiring tools that are perfect for high-volume recruiting
Technology is your friend when it comes to building scalable volume hiring strategies and embracing high volume recruiting tools. Here are four key pieces of technology to consider for high volume recruiting. There are plenty of tools out there, so this is by no means an exhaustive list.
Applicant tracking system
Your ATS will help you post ads, screen resumes, bulk communicate with applicants, and collect data. When working within a high volume recruiting strategy, you should also use it to build talent pools and pipelines for future roles.
Interview automation
An Ai assessment like Sapia means you can give every single applicant a conversational chat interview. The quickest payback you will get on volume hiring is an investment in interview automation. Interview automation can truly enhance your high volume recruitment process and help you make it more efficient (and pleasant) for everyone involved. This will help you get your time back quickly and release the budget for automation in other areas of recruiting. Embracing such high volume recruiting tools ensures efficiency.
Sapia meets the needs that challenge many of my clients today – how do they manage high volume recruitment processes in a streamlined and cost-effective way, while still delivering a great candidate experience and quality hiring decisions. With Sapia, you leverage the latest in data analytics and tech to maximize efficiency & effectiveness; and the candidate experience is fresh and engaging, with great feedback! The product is great and constantly evolving!
It’s worth considering a candidate engagement survey for your high volume recruiting strategy. In this survey, you can ask questions to reveal how well your EVP is resonating. Then you can compare candidate engagement scores with new employee engagement scores and exit interviews to understand if you’re delivering on your EVP as part of your bulk recruitment process.
Onboarding
Integrating your onboarding software with your ATS (or choosing one with onboarding included) allows you to start onboarding and engaging candidates as soon as they sign their (automated) contract. This is a dream for high volume hiring, getting workplace health and safety, and even procedural training done before a new employee walks in the door.
Good news: It’s only going to get easier
It’s easy to feel overwhelmed when you’re doing high volume hiring in an environment where there’s elevated unemployment or other challenging factors. The good news is that as much as the world may be getting more complicated, and as much as candidate expectations are soaring, the technology to support recruiters in high volume recruiting has never been faster, fairer, or more scalable.
Establish your own volume hiring best practices and keep optimizing your volume hiring strategies. It takes some time to set up, but the rewards are well worth the effort.
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Skills Measurement vs Skills Inference – What’s the Difference and Why Does It Matter?
There’s growing interest in AI-driven tools that infer skills from CVs, LinkedIn profiles, and other passive data sources. These systems claim to map someone’s capability based on the words they use, the jobs they’ve held, and patterns derived from millions of similar profiles. In theory, it’s efficient. But when inference becomes the primary basis for hiring or promotion, we need to scrutinise what’s actually being measured and what’s not.
Let’s be clear: the technology isn’t the problem. Modern inference engines use advanced natural language processing, embeddings, and knowledge graphs. The science behind them is genuinely impressive. And when they’re used alongside richer sources of data, such as internal project contributions, validated assessments, or behavioural evidence, they can offer valuable insight for workforce planning and development.
But we need to separate the two ideas:
- Skills Measurement: Directly observing or quantifying a skill based on evidence of actual performance.
- Skills Inference: Estimating the likelihood that someone has a skill, based on indirect signals or patterns in their data.
The risk lies in conflating the two.
The Problem Isn’t Inference of Skills. It’s the Data Feeding It
CVs and LinkedIn profiles are riddled with bias, inconsistency, and omission. They’re self-authored, unverified, and often written strategically – for example, to enhance certain experiences or downplay others in response to a job ad.
And different groups represent themselves in different ways. Ahuja (2024) showed, for example, that male MBA graduates in India tend to self-promote more than their female peers. Something as simple as a longer LinkedIn ‘About’ section becomes a proxy for perceived competence.
Job titles are vague. Skill descriptions vary. Proficiency is rarely signposted. Even where systems draw on internal performance data, the quality is often questionable. Ratings tend to cluster (remember the year everyone got a ‘3’ at your org?) and can often reflect manager bias or company culture more than actual output.
Sophisticated ≠ Objective
The most advanced skill inference platforms use layered data: open web sources like job ads and bios, public databases like O*NET and ESCO, internal frameworks, even anonymised behavioural signals from platform users. This breadth gives a more complete picture, and the models powering it are undeniably sophisticated.
But sophistication doesn’t equal accuracy.
These systems rely heavily on proxies and correlations, rather than observed behaviour. They estimate presence, not proficiency. And when used in high-stakes decisions, that distinction matters.
Transparency (or Lack Thereof)
In many inference systems, it’s hard to trace where a skill came from. Was it picked up from a keyword? Assumed from a job title? Correlated with others in similar roles? The logic is rarely visible, and that’s a problem, especially when decisions based on these inferences affect access to jobs, development, or promotion.
Presence ≠ Proficiency
Inferred skills suggest someone might have a capability. But hiring isn’t about possibility. It’s about evidence of capability. Saying you’ve led a team isn’t the same as doing it well. Collecting or observing actual examples of behaviour allows you to evaluate someone’s true competence at a claimed skill.
Some platforms try to infer proficiency, too, but this is still inference, not measurement. No matter how smart the model, it’s still drawing conclusions from indirect data.
By contrast, validated assessments like structured interviews, simulations, and psychometric tools are designed to measure. They observe behaviour against defined criteria, use consistent scoring frameworks (like Behaviourally Anchored Rating Scales, or BARS), and provide a transparent, defensible basis for decision-making. In doing this, the level or proficiency of a skill can be placed on a properly calibrated scale.
But here’s the thing: we don’t have to choose one over the other.
A Smarter Way Forward: The Hybrid Model
The real opportunity lies in combining the rigour of measurement with the scalability of inference.
Start with measurement
Define the skills that matter. Use structured tools to capture behavioural evidence. Set a clear standard for what good looks like. For example, define Behaviourally Anchored Rating Scales (BARS) when assessing interviews for skills. Using a framework like Sapia.ai’s Competency Framework is critical for defining what you want to measure.
Layer in inference
Apply AI to scale scoring, add contextual nuance, and detect deeper patterns that human assessors might miss, especially when reviewing large volumes of data.
Anchor the whole system in transparency and validation
Ensure people understand how inferences are made by providing clear explanations. Continuously test for fairness. Keep human oversight in the loop, especially where the stakes are high. More information on ensuring AI systems are transparent can be found in this paper.
This hybrid model respects the strengths and limits of both approaches. It recognises that AI can’t replace human judgement, but it can enhance it. That inference can extend reach, but only measurement can give you higher confidence in the results.
The Bottom Line
Inference can support and guide, but only measurement can prove. And when people’s futures are on the line, proof should always win.
References
Ahuja, A. (2024). LinkedIn profile analysis reveals gender-based differences in self-presentation among Indian MBA graduates. Journal of Business and Psychology.
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Making Healthcare Hiring Human with Ethical AI
Hiring for care is unlike any other sector. Recruiters are looking for people who can bring empathy, resilience, and energy to the most demanding human roles. Whether it’s dental care, mental health, or aged care, new hires are charged with looking after others when they’re most vulnerable. The stakes are high.
Hiring for care is exactly where leveraging ethical AI can make the biggest impact.
Hiring for the traits that matter
The best carers don’t always have the best CVs.
That’s why our chat-based AI interview doesn’t screen for qualifications. It screens for the the skills that matter when caring for others. The traits that define a brilliant care worker, things like:
Empathy, Self-awareness, Accountability, Teamwork, and Energy.
The best way to uncover these traits is through structured behavioural science, delivered through an experience that allows candidates to open up. Giving candidates space to give real-life, open-text answers. With no time pressure or video stress. Then, our AI picks up the signals that matter, free from any demographic data or bias-inducing signals.
Candidates’ answers to our structured interview questions aren’t simply ticking boxes. They’re a window into how someone shows up under pressure. And they’re helping leading care organisations hire people who belong in care and those who stay.
Inclusion, built in
Inclusivity should be a core foundation of any talent assessment, and it’s a fundamental requirement for hirers in the care industry.
When healthcare hirers use chat-based AI interviews, designed to be inclusive for all groups, candidates complete their interviews when and where they choose, without the bias traps of face-to-face or phone screening. There are no accents to judge, no assumptions, just their words and their story.
And it works:
- 91.8% of carer candidates complete their interviews
- Carer candidates report 9/10 Candidate Satisfaction with their interview experience
- 80% of candidates would recommend others to apply
- Every candidate receives personalised feedback, regardless of the outcome
Drop-offs are reduced, and engagement & employer brand advocacy go up. Building a brand that candidates want to work for includes providing a hiring experience that candidates want to complete.
Real outcomes in care hiring
Our smart chat already works for some of the most respected names in healthcare and community services. Here’s a sample of the outcomes that are possible by leveraging ethical AI, a validated scientific assessment, wrapped in an experience that candidates love:
Anglicare – a leading provider of aged care services
- Time-to-offer dropped from 40+ days to just 14
- Candidate pool grew by 30%
- Turnover dropped by 63%
Abano Healthcare – Australasia’s largest dental support organisation
- 1,213 recruiter hours saved in the first month (67 hours per individual hiring team member)
- $25,000 saved in screening and interviewing time
Berry Street – a not for profit family & child services organisation
- Time-to-hire down from 22 to 7 days
- 95.4% of candidates completed their chat interviews
A smarter way to hire
The case study tells the full story of how Sapia.ai helped Anglicare, Abano Healthcare, and Berry Street transform their hiring processes by scaling up, reducing burnout, and hiring with heart.
Download it here:
Blog
New Research Proves the Value of AI Hiring
A new study has just confirmed what many in HR have long suspected: traditional psychometric tests are no longer the gold standard for hiring.
Published in Frontiers in Psychology, the research compared AI-powered, chat-based interviews to traditional assessments, finding that structured, conversational AI interviews significantly reduce social desirability bias, deliver a better candidate experience, and offer a fairer path to talent discovery.
We’ve always believed hiring should be about understanding people and their potential, rather than reducing them to static scores. This latest research validates that approach, signalling to employers what modern, fair and inclusive hiring should look like.
The problem with traditional psychometric tests
While used for many decades in the absence of a more candidate-first approach, psychometric testing has some fatal flaws.
For starters, these tests rely heavily on self-reporting. Candidates are expected to assess their own traits. Could you truly and honestly rate how conscientious you are, how well you manage stress, or how likely you are to follow rules? Human beings are nuanced, and in high-stakes situations like job applications, most people are answering to impress, which can lead to less-than-honest self-evaluations.
This is known as social desirability bias: a tendency to respond in ways that are perceived as more favourable or acceptable, even if they don’t reflect reality. In other words, traditional assessments often capture a version of the candidate that’s curated for the test, not the person who will show up to work.
Worse still, these assessments can feel cold, transactional, even intimidating. They do little to surface communication skills, adaptability, or real-world problem solving, the things that make someone great at a job. And for many candidates, especially those from underrepresented backgrounds, the format itself can feel exclusionary.
The Rise of Chat-Based Interviews
Enter conversational AI.
Organisations have been using chat-based interviews to assess talent since before 2018, and they offer a distinctly different approach.
Rather than asking candidates to rate themselves on abstract traits, they invite them into a structured, open-ended conversation. This creates space for candidates to share stories, explain their thinking, and demonstrate how they communicate and solve problems.
The format reduces stress and pressure because it feels more like messaging than testing. Candidates can be more authentic, and their responses have been proven to reveal personality traits, values, and competencies in a context that mirrors honest workplace communication.
Importantly, every candidate receives the same questions, evaluated against the same objective, explainable framework. These interviews are structured by design, evaluated by AI models like Sapia.ai’s InterviewBERT, and built on deep language analysis. That means better data, richer insights, and a process that works at scale without compromising fairness.
Key Findings from the Latest Research
The new study, published in Frontiers in Psychology, put AI-powered, chat-based interviews head-to-head with traditional psychometric assessments, and the results were striking.
One of the most significant takeaways was that candidates are less likely to “fake good” in chat interviews. The study found that AI-led conversations reduce social desirability bias, giving a more honest, unfiltered view of how people think and express themselves. That’s because, unlike multiple-choice questionnaires, chat-based assessments don’t offer obvious “right” answers – it’s on the candidate to express themselves authentically and not guess teh answer they think they would be rewarded for.
The research also confirmed what our candidate feedback has shown for years: people actually enjoy this kind of assessment. Participants rated the chat interviews as more engaging, less stressful, and more respectful of their individuality. In a hiring landscape where candidate experience is make-or-break, this matters.
And while traditional psychometric tests still show higher predictive validity in isolated lab conditions, the researchers were clear: real-world hiring decisions can’t be reduced to prediction alone. Fairness, transparency, and experience matter just as much, often more, when building trust and attracting top talent.
Sapia.ai was spotlighted in the study as a leader in this space, with our InterviewBERT model recognised for its ability to interpret candidate responses in a way that’s explainable, responsible, and grounded in science.
Why Trust and Candidate Agency Win
Today, hiring has to be about earning trust and empowering candidates to show up as their full selves, and having a voice in the process.
Traditional assessments often strip candidates of agency. They’re asked to conform, perform, and second-guess what the “right” answer might be. Chat-based interviews flip that dynamic. By inviting candidates into an open conversation, they offer something rare in hiring: autonomy. Candidates can tell their story, explain their thinking, and share how they approach real-world challenges, all in their own words.
This signals respect from the employer. It says: We trust you to show us who you are.
Hiring should be a two-way street – a long-held belief we’ve had, now backed by peer-reviewed science. The new research confirms that AI-led interviews can reduce bias, enhance fairness, and give candidates control over how they’re seen and evaluated.