Three numbers came out of PAC Solutions’ first full year on Recruiterflow, and the interesting thing is the order they fall in.<\/p>\n
Candidate pipeline grew 20%. Client submissions grew 189%. Placements doubled.<\/p>\n
Read those left to right and the conclusion is uncomfortable for the way most firms plan growth. A fifth more candidates produced nearly three times the submissions. The extra placements did not come from the top of the funnel. They came from the middle of it.<\/p>\n
This post covers what that shift actually required: why the ratio between those three numbers is the story, the four things that changed, and which parts a firm of any size can copy.<\/p>\n
PAC Solutions is a thirteen-person team led by founder Ryan Dunphy, working as an extension of their clients’ internal teams rather than as an outside supplier.<\/p>\n
They moved to Recruiterflow after outgrowing a previous system, looking for something that would evolve with them rather than something they had to work around.<\/p>\n
“Efficiency is being able to get more output without adding more effort.”<\/p><\/blockquote>\n
Ryan Dunphy, Founder, PAC Solutions<\/em><\/p>\n
<\/span>Why the ratio is the whole story<\/span><\/h2>\n
The instinct when placements are flat is to add candidates. It is the most visible lever, the easiest to measure, and the one every sourcing tool is sold on.<\/p>\n
It is also the wrong end of the funnel. Screening to client submission is the largest single leak in recruitment, with only 11.3% of screened candidates making it through, and the gap between the best firms and everyone else is wide: top-quartile firms convert that stage at 50.1% against 36.1% (Source: The Economics of Recruiting<\/a>)<\/em>.<\/p>\n
A 20% pipeline increase producing a 189% submission increase is that gap closing. More candidates reached the client because fewer of them stalled on the way, not because there were dramatically more of them to begin with.<\/p>\n
That distinction matters because the two routes cost completely different amounts. Adding 189% more candidates is a sourcing budget. Converting the ones you already have is a process change.<\/p>\n
<\/span>What actually changed<\/span><\/h2>\n
The data stopped living in people’s heads<\/h3>\n
Before the move, candidate detail went missing between follow-ups and team check-ins. Not lost exactly, just held in the wrong place: a recruiter’s memory, a thread nobody else could see, a note in a second system.<\/p>\n
Now communication syncs automatically and candidate data sits on one view everyone can open. Job and client pipelines are visible in real time, so bottlenecks show up while there is still time to act on them rather than in a month-end review.<\/p>\n
This sounds like a reporting improvement. It is really a conversion improvement, because most stalls at the submission stage are not decisions. They are candidates nobody got back to.<\/p>\n
The handoffs got triggered rather than remembered<\/h3>\n
Kimberly Borden, the firm’s TA and Technical Lead, set out to remove manual steps wherever the platform allowed it.<\/p>\n
The automations she built cluster around moments of transition, which is exactly where pipelines leak:<\/p>\n
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- When a job opens and applications start arriving, a task is assigned to the Account Manager so early candidates get engaged while they are still warm.<\/li>\n
- When a candidate reaches offer stage, stakeholders are notified without anyone remembering to send the message.<\/li>\n
- When a hire is made, the loop is closed automatically.<\/li>\n
- When a job closes, a client survey goes out to collect feedback.<\/li>\n<\/ul>\n
“I love recipes because they are really powerful, and I always tell everyone that if you have an idea to automate something, Recruiterflow can probably do that for you.”<\/p><\/blockquote>\n
Kimberly Borden, TA and Technical Lead, PAC Solutions<\/em><\/p>\n
The common thread is that none of these are tasks anyone would defend as valuable. They are the small obligations that get dropped first when a desk gets busy, and dropping them is what turns an active candidate into a cold one.<\/p>\n
Good candidates stopped depending on someone’s goodwill<\/h3>\n
Candidates marked as strong performers receive stay-in-touch follow-ups automatically, so a person who was excellent but not right for one role is still reachable when the right role appears.<\/p>\n
Around 71% of placements come from candidates already in the database before the job opened (Source: The Economics of Recruiting<\/a>)<\/em>, which makes this less of a courtesy than a pipeline strategy. The same logic runs on the client side, where job-specific drip campaigns market open roles and share candidates on a schedule rather than when someone has a quiet afternoon.<\/p>\n
AI removed the blank page, not the judgement<\/h3>\n
PAC Solutions uses AIRA to generate call summaries and draft interview questions across every role they work, and alternate job title searches to widen results when the obvious title returns too little.<\/p>\n
As a provider working across sectors rather than one niche, that matters more than it would for a specialist firm: recruiters need a credible starting point on unfamiliar roles fast. The AI produces the first version. The recruiter still decides.<\/p>\n
<\/span>The number nobody counts<\/span><\/h2>\n
Over 2024, the team saved more than 270 days of effort through automation.<\/p>\n
That figure is worth sitting with, because it is not a productivity statistic in the usual sense. Nobody worked 270 fewer days. That time went back into the part of the job that cannot be automated, which is the conversation with the candidate and the conversation with the client.<\/p>\n
Their clients rate them 9.6 out of 10. Those two numbers are connected.<\/p>\n
<\/span>What transfers<\/span><\/h2>\n
You do not need thirteen recruiters or a particular tool for the pattern to hold.<\/p>\n
Check your ratio before you check your volume.<\/strong> Pull submissions per hundred screened candidates for the last quarter. If it sits near the 11.3% industry figure, more sourcing will mostly produce more stalling. The constraint is downstream.<\/p>\n
Automate the transitions, not the tasks.<\/strong> The highest-value automations are not the big ones. They are the handoffs at stage changes, where work moves between people and things get dropped.<\/p>\n
Treat the follow-up on strong candidates as infrastructure.<\/strong> If staying in touch with your best people depends on someone having time, it will not happen in the months when it matters most.<\/p>\n
This is the same underlying point that showed up when Believe Resourcing raised capacity per recruiter<\/a>: work that lives only in someone’s head is a ceiling, and the ceiling is usually in the middle of the funnel rather than at the top. It is worth checking against your own recruiting metrics<\/a> before the next growth conversation.<\/p>\n
<\/span>Find your own leak<\/span><\/h2>\n
Take last quarter’s screened candidates and your submissions to clients over the same period, and divide one by the other.<\/p>\n
Bring that number to a demo and we will show you which of the stalls between those two figures a system can carry, and which ones still need a person.<\/p>\n
You can read the full PAC Solutions case study<\/a> for more detail, and the recruitment automation<\/a> guide for how these workflows get built.<\/p>\n
<\/span>FAQs<\/span><\/h2>\n
How do you increase placements without adding more candidates?<\/h3>\n
By improving conversion between screening and client submission, which is the largest leak in the recruitment funnel. Faster engagement of new applicants, automated handoffs at stage changes, and consistent follow-up on strong candidates all move that rate without changing sourcing volume.<\/p>\n
What is a good submission to placement ratio?<\/h3>\n
It varies by market and engagement type, so the useful benchmark is your own trend rather than an absolute figure. The one number worth comparing externally is screening to submission, where the industry average sits at 11.3% and top-quartile firms reach 50.1%.<\/p>\n
What should a recruitment firm automate first?<\/h3>\n
The transitions. Task assignment when a job opens, notifications at offer and hire, feedback requests when a job closes, and stay-in-touch sequences for strong candidates. These are dropped first under load and each one costs a live candidate when it is missed.<\/p>\n
Does recruitment automation reduce headcount?<\/h3>\n
In practice it changes what the existing team spends time on rather than reducing the team. PAC Solutions saved over 270 days of effort in a year with thirteen people and used the time on client and candidate conversations, which is where the placement growth came from.<\/p>\n
How long does it take to see results from recruiting automation?<\/h3>\n
The transition automations produce an effect almost immediately, because they act on candidates already in the process. Database re-engagement and drip campaigns take longer, since they depend on a cadence running for several months before the compounding shows up.<\/p>\n","protected":false},"excerpt":{"rendered":"