In partnership with 12twenty.
Before you can make a quality hire, you need a quality talent pool, and quality talent pools don’t happen by accident.
They are built through referrals, alumni, former employees, university partnerships, professional communities, and other trusted relationships that give employers something an application alone can’t: context.
Yet most organizations measure quality at the other end of the funnel. We look at performance, retention, time to productivity, and hiring manager satisfaction, often 30, 60, or 90 days after the hire.
Those measures matter. But they’re lagging indicators. By the time they tell us something went wrong, we’ve already made the investment.
I believe we need to move the quality conversation upstream.
Alongside Quality of Hire, Talent Acquisition should be thinking about Quality of Source: not just where a candidate came from, but how much we knew about them before they entered the hiring funnel.
That’s where a Trusted Talent Network becomes strategically important. Relationships with employees, alumni, former employees, universities, and professional communities can create a richer signal than an application alone and give recruiters a better starting point when a role opens.
That matters even more today because the candidate pool itself is changing.
AI is making it easier to create polished applications, tailor resumes, and apply at scale. As candidate-generated information becomes easier to manufacture, trusted relationships and independently established signals become more valuable.
And that brings us to a fundamental question:
Where did this candidate come from, and what did we know about them before they applied?
The candidate pool has changed
For years, more applicants generally felt like a good thing and it gave us confidence in our sourcing strategy. As technology has evolved, TA teams found it even easier to distribute jobs and reach candidates and even easier for candidates to find the jobs and apply.
Today, AI has taken that dynamic to another level. Candidates can now generate highly polished application materials in seconds. They can tailor those materials to individual job descriptions, and they can even automate the act of applying itself.
Greenhouse’s 2025 Workforce & Hiring Report found that 22% of candidates use bots to automatically apply for roles, increasing to 31% among Gen Z candidates. Source: Greenhouse 2025 Workforce & Hiring Report
Using AI to help with a job search isn’t inherently a problem. Plenty of legitimate candidates use it to improve a resume, prepare for an interview, or communicate more effectively. The problem for employers is signal.
A polished application used to tell us something about the person who created it. Today, we have to be more careful about making that assumption.
And the problem extends beyond embellished resumes. Gartner has predicted that by 2028, one in four candidate profiles worldwide could be fake. Source: HR Dive reporting on Gartner research
Today is a very different recruiting environment, and much of our response has been to add more screening after the application arrives. More assessments. More verification. More interviews. More technology designed to determine which candidates in an increasingly large stack are actually who and what they say they are.
Those things have a role, but they don’t answer a more fundamental question: Where did this candidate come from, and what did we know about them before they applied?
We need to look upstream
This is where the quality-of-hire conversation needs to change.
If we only measure what happens after someone enters the funnel, we miss one of the earliest decisions that can influence the eventual outcome: where we sourced that candidate in the first place.
Not all candidate pools begin with the same information. Think about an employee referral. A former employee. Someone you’ve engaged with through a university relationship. An alumnus. A member of a professional community where there is a credential, relationship, or history that exists independently of their application. You know something about those people before they tell you about themselves.
That’s different from an applicant whose first interaction with your organization is clicking “apply.”
It doesn’t mean someone from an open job board can’t be an exceptional hire. Of course they can. And it doesn’t mean a referral or known candidate is automatically a good one. It means the starting signal is different.
That distinction is becoming much more important as candidate-generated information becomes easier to manufacture.
Screening can’t be the whole strategy
There is a temptation right now to treat the AI application problem primarily as a technology problem.
If AI creates more applications, use AI to screen them. If candidates use AI to optimize resumes, build better assessments. If identity becomes harder to establish, add another verification step. Some of these tactics and solutions will be necessary, but we shouldn’t confuse a better filter with a better candidate pool.
You can’t screen your way out of a sourcing problem.
For TA leaders, that means quality of source deserves a place alongside quality of hire. Start connecting eventual hiring outcomes back to where those relationships began.
Which sources produce employees who ramp faster? Which produce people who stay? Where are your strongest performers coming from? Which sources give recruiters useful information about a candidate before the formal hiring process even begins? And which sources consistently leave the team starting from zero?
Those questions turn sourcing from a volume exercise into a quality decision.
Trust is becoming a recruiting advantage
None of the sources I’m describing are new.
Companies have relied on employee referrals, internships, alumni, university partnerships, former employees, and professional communities for decades. What’s changing is their strategic value.
In a market where candidate information is abundant but increasingly difficult to verify, relationships and independent signals become more valuable, not less. The strongest recruiting organizations won’t necessarily be the ones with access to the largest number of profiles. Instead, they’ll be the ones with access to the highest concentration of trusted relationships.
This realization requires a different approach to sourcing. Instead of waiting for a requisition to open and then beginning the search, organizations have to maintain relationships with talent before the need exists. That work isn’t always easy to attribute to this quarter’s hires. But that’s also the point.
A trusted talent network compounds.
Every internship, alumni relationship, referral, university partnership, professional connection, and former employee can add context that doesn’t disappear when a requisition closes. Then, when the next role opens, the recruiting team isn’t necessarily starting with a blank search box and an anonymous stack of applications.
They’re starting with people they know something about.
Move the quality conversation forward
Talent Acquisition doesn’t need another complicated quality-of-hire formula.
Instead, we need to connect the measures we already care about to decisions that happen earlier. Keep measuring performance; keep measuring retention; and keep asking hiring managers whether the people hired are delivering what the business needs.
But now when a great hire is found, it is imperative that sourcing teams trace that outcome backward. “Where did this hire come from? What did we know about them before they applied?”
And do the same thing when a hire doesn’t work out.
Over time, this commitment to quality improvement gives TA leaders something a 90-day score alone cannot: information they can use to change where the next search begins. That’s the shift we need to make.
Quality of hire doesn’t start 90 days after someone joins the company. It doesn’t start at the interview. It doesn’t even start at screening.
Quality is already being shaped by the talent pool chosen for recruiting. And in today’s hiring market, that may be one of the most important quality decisions we make.
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