Your Hiring Pulse report for April 2023
In March’s Hiring Pulse, we focused on the rocket-like growth in the Candidates per Hire trend which has everyone teetering and wondering what’s coming up next.
Now, as if all the drama of the last few years in the form of COVID-19, the Great Resignation, the Ukraine invasion, a looming recession, inflation, yadda yadda yadda, wasn’t enough – we’re now dealing with yet another destabilizer and disrupter in the landscape. This is catastrophic for the pessimists among us, but ameliorative for the optimistics among us.
That’s, of course, the emergence of ChatGPT, generative AI and LLM AI (large language model AI) and all their many offshoots.
How this will change our landscape is really a huge amount of fodder for another large-scale discussion, but let’s keep it in mind as we dive into the latest data because it will change how we hire.
Let’s get started!
How we’re looking at data
We’ve adopted two methodologies in how we look at the Hiring Pulse dataset. For Time to Fill and Candidates per Hire, we’re measuring each month using the average of 2019, the last “normal” year, as a baseline index of 100.
For job openings, we’re taking a different route – simply, the average number of job postings per company. This gives us the opportunity to gauge overall recruitment activity and whether that’s going up or down.
Want a more detailed methodology? Jump to the end and check it out.
As always, we look at the worldwide trends for three common SMB hiring metrics:
- Time to Fill (TTF)
- Total Job Openings (JO)
- Candidates per Hire (CPH)
Let’s start analyzing!
The three main highlights for this month’s Hiring Pulse are:
- Job activity continues to be high for small businesses
- TTF is continuing to decline sharply – but at what cost?
- CPH is finally ‘stabilizing’ – sort of
1. Time to Fill
For this report, Workable defines “Time to Fill” as the number of days from when a new job is opened to when that job opening is filled. It’s important to understand that definition: jobs that are still open as of the end of March are not included in this graph as they don’t yet have an “end date”. Only the jobs that are filled are included here.
Quick clarification, because people are asking: the data in this chart shows the trendline against the 2019 average as an index of 100, not the actual number of days in TTF.
Got that? Good. Let’s have a look at the monthly TTF trend throughout 2022 against the average of 2019, based on jobs that have been filled:
Again, we see a decrease in the TTF trend. This is the third consecutive month of decline – and it now stands at 81 for March 2023, down from 87.1 in February and 90.6 in January.
This shortening TTF may initially seem a good thing for both employers and jobseekers. For hiring teams, of course it means you’re finding candidates to fill your much-needed positions quicker than before. For jobseekers, it means you’re getting jobs quicker than before.
There are downsides, too. It may be a sign of a need to fill urgent roles ahead of a looming recession, either for that hire to provide the stopgap that’s needed to carry a company through the downturn. It could also signal a rush to get ahead of potential budget cuts and hiring freezes before they happen. Not inherently a problem, but rather, signals of problems.
But we’re already in April and we’ve been talking about that downturn for a long time now (and in multiple Hiring Pulses). It’s highly likely that the shorter TTF is due to a larger candidate pool – when a job is opened, applications start flooding in and it’s easier to lock in on someone who fits the bill.
All the same, there are caveats to this shorter TTF. Companies may not be taking the opportunity to properly evaluate candidates which means a higher risk of bad hires. That can be expensive down the line and you don’t want that.
So, consider slowing down, even in the face of increased urgency to fill roles.
Or – more apropos – consider better, more optimized ways to evaluate candidates so you can vet them more thoroughly, and quickly too. Like, for instance, incorporating (ahem) AI tech in your hiring process.
Now, let’s move on to job openings.
2. Total Job Openings
Total job openings represent the total number of job openings activated across the entire Workable network.
As stated above, we’re displaying this as an average of job postings per company in the network. And because this is not contingent on job opened/filled dates like TTF and Candidates per Hire, we can simply look at the raw job open numbers up to the end of March.
Well, look at that. Steady growth across the board. Those lines at the bottom of the chart look like a group of airplanes taking off together from November 2022 at different speeds and cadences, and then ultimately falling into line with one another into March.
We’ll get into the specific details in a second, but first, the main takeaway is that the overall average jobs opened per company in March in our dataset is 7.6, up from 6.7 in February and 6.6 in January. At this time last year, we didn’t see such a consistent increase in job openings.
We’ve talked about this in previous Hiring Pulses: a downturn doesn’t necessarily mean hiring freezes for new jobs. It can also mean a recalibration – for instance, let’s look at the restructuring of teams with the objective of producing with 10 FTEs where 15 were able to do so previously.
In such a reworking, job requirements change as a result and new skill sets are discovered to be needed. Some team members can learn and grow, some get promoted, some are disgruntled and leave for other opportunities, some are let go, and finally, entire new jobs are created to fill important gaps in these new team structures.
In times of affluence, these things do happen and they are an opportunity to scale. But in times of fiscal stress, they come up as necessities as businesses clamor to find more efficient ways to carry out processes.
Anyway, interesting discussion and we’ll come back to it. Now let’s look at the company size buckets.
Larger companies still anomalous
Job activity for companies of 200 or more employees saw a roughly 10% increase from February to March. This is interesting compared with previous years, where larger companies saw averages of 15.2/15.9/19.5 for the first three months of 2021 and 21.3/21.3/23.8 for the first three months of 2022.
Yet, this year, instead of a spike in March after a roughly stable Jan-Feb trend, we’re seeing a dip from January to February and then an almost identical recovery from February to March.
Perhaps we’re splitting hairs by looking at the data like this, and perhaps it’s just one of those anomalies, but it’s still interesting to look at.
Medium is steady as she goes
For companies with 51-200 employees, we see a jump in the average job postings for March to 6.2 after a relatively stable January (5.7) and February (5.6).
We noted it last month and the insight remains the same – this is not wholly anomalous. Job activity trends for the first three months of the year is again pretty normal this year for medium-sized businesses.
Small and vibrant
Now, here’s where the interesting stuff is. Small-sized businesses with 50 or fewer employees are continuing to rise in terms of job activity. Last month, we saw a jump from 4.1 to 4.7 jobs per company from January to February, and that growth has accelerated to 5.5 in March.
We’ve talked extensively about agility in small businesses rapidly adapting to evolving economies and shifts in market trends. We’re definitely keeping an eye on this one.
Now, on to the candidates.
3. Candidates per Hire
Workable defines the number of candidates per hire (CPH) as, succinctly, the number of applicants for a job up to the point of that job being filled. Again, remember, this is a trendline using the 2019 CPH average as a baseline of 100, not the actual number of candidates per hire.
Now that Let’s look at what’s going on here through March:
We’ve talked for months about a prominent spike in the number of applicants per job dating back to July 2022. Ultimately, a 56% increase in CPH from July 2022 to February 2023.
But now, apart from a moderate slowdown from November to December (understandable given that December is slow all around), we finally see the CPH trend coming in lower than the previous month.
Not really by a lot, but it’s there: March’s 136.6 is a drop from February’s 141.5.
We discussed the Great Resurgence in last month’s Hiring Pulse – that’s still happening, of course, but the candidate pool is not a bottomless one. Are we finally reaching the crux of this data point? Or is this just a hiccup and more are on the way? We shall see.
What’s going on here?
As the hiring landscape continues to shift and adapt to the ever-changing job market, one thing we know for sure: the use of AI in the hiring process is growing exponentially. While generative AI tools like ChatGPT can provide significant benefits to hiring teams in terms of time and efficiency, they also come with potential risks and drawbacks.
OK, full disclosure: ChatGPT was used to help write that paragraph above with some minor tweaks. However, it’s on point. We’re in a time where we’re now dealing with yet another earth-shattering development on the heels of previous ones – that being the rise of artificial intelligence in the everyday zeitgeist and lexicon. Sure, we’ve been talking about AI for years but until ChatGPT, we hadn’t really thought collectively about how AI fits into our everyday lives at work and at play.
Now, we’re exploring all the ways in which ChatGPT can be used in human resources, and all the ways in which technology can boost hiring processes. At the core of these conversations is optimization of workflow.
So, let’s go back to this month’s data analysis. We’re seeing a shorter time to fill. We’re seeing more job activity. And we’re (still) seeing a lot of candidates for each of those jobs. Combine all three, and understaffed and underfunded hiring teams are just scrambling to get it all done.
ChatGPT is a real boon for those teams, obviously. You no longer have to write those job descriptions (not from scratch, at least). You no longer need to craft lists of interview questions designed to get what you need to know from the candidate. Yes, we have templates for both and more, but that can only go so far. In these rapidly evolving times, we need something that can keep with the times and meet our current needs immediately. Generative AI tech can do that for us.
But (and of course there’s always a but) as teams grapple with these surging trends and developments in the hiring process, it’s crucial to strike that balance between speed and quality. You know the saying, “He/she who hesitates is lost”? And the other, pretty much opposite saying: “Slow and steady wins the race.”
It’s about finding a balance between both. Speed serves a purpose, and so does quality.
Now, we asked ChatGPT what actionable tips it has based on all of the above. It presented the following (without any edits):
Focus on targeted outreach: Instead of simply casting a wide net with job postings, consider a more targeted approach that identifies and reaches out to qualified candidates directly. This can help ensure a higher quality of candidates and reduce the need for rushed hiring decisions.
Implement AI tools thoughtfully: While AI tools like ChatGPT can provide significant benefits, it is important to implement them thoughtfully and carefully, with an eye toward potential risks and biases. Consider involving human oversight in the AI hiring process to ensure that the best possible candidates are being selected.
Prioritize candidate experience: In a competitive hiring landscape, it is important to prioritize the candidate experience, from the application process to the interview and beyond. By providing a positive experience, you can attract and retain top talent, even in uncertain times.
Good work, bot. And ChatGPT even has the insight to recommend caution on using itself. Ultimately, it’s a great tool to help you in your work, but only if you steer it properly and that you maintain that all-important human touch at the end.
As for how AI will change the working world – it will, in absolute, countless spades. It’s not a coincidence or an accident that everyone is talking about it right now. Jobs will change. Workflows will change. The overall interaction of society will probably change.
And will it impact the economy and in turn our three trends of time to fill, job openings and candidates per hire? Yes, it probably will. Let’s watch and find out.
Until next month…
Thoughts, comments, disagreements? Send them to [email protected], with “Hiring Pulse” in the subject heading. We’ll share the best feedback in an upcoming report. Watch for our next Hiring Pulse in February!
The Hiring Pulse: Methodology
Because one of the three metrics (Job Openings) is different from the other two metrics (Time to Fill and Candidates per Hire), we’re adopting two very distinct methodologies.
To bring the best insights to small and medium (and enterprise-level) businesses worldwide, here’s what we’re doing with the Job Openings metric: we’re taking the number of job openings in a given month and dividing that by the number of active companies in our dataset, and posting that as an average. For example, if July 2022 shows the average Job Openings per company as 7.7, that simply means each company posted an average of 7.7 jobs that month.
For the Time to Fill and Candidates per Hire metrics, we’re comparing a specific month’s trend against the full average of 2019, and we show the result using that 2019 average as a baseline index of 100. For example, if July 2022 shows an average Time to Fill of 30 days for all jobs, and the monthly average for all of 2019 is 28, we present the result for July 2022 as 107.1 – in other words, 7.1% higher than the average of 2019.
And we chose 2019 as the baseline because, frankly, that’s the last normal year before the pandemic started to present challenges to data analysis among other things.
The majority of the data is sourced from businesses across the Workable network, making it a powerful resource for SMBs when planning their own hiring strategy.