Fixing The Pipeline Problem Starts With Killing The 'Talent Surplus' Mindset

Most business leaders still run on a basic assumption inherited from a different era: that talent is plentiful, that enough people will apply, and that the job of TA is to move those applicants efficiently through screens, interviews, and offers. That assumption breaks the moment the talent a business actually needs is scarce. Measuring applications comes too late to answer the question that matters most, which is how much of the talent the business needs it can actually reach.

Working to arrive at the answer sooner is Michael Peterson, Senior Director of Global Talent Acquisition for Talent Sourcing, Intelligence and Innovation at Edwards Lifesciences. Over more than two decades in the field he's built TA functions across healthcare, technology, and manufacturing, hired at high volume, and turned around teams under pressure. His current work reflects his assertion that TA has to stop measuring its own process and start measuring whether it can deliver the talent a business needs, when and where it needs it.

"We need to shift our teams and more importantly the business to a talent scarcity mindset. That means we need to understand the market. Looking at who's applied is such a narrow view of the true funnel," he says.

The surplus mindset is the thing that's broken

Peterson traces most of TA's problems to a mentality that no longer matches reality. "I think we're really still the victim of this past talent surplus mentality," he says. "The default was that talent is readily available, and as long as we can get people to apply, and plenty of people should apply because there's plenty of talent, then we can move through the rest of the funnel." In his view, that framing keeps TA stuck as a process rather than positioning it as a strategic partner or, more importantly, strategic leader within the business.

The correction is understanding the market before a requisition is ever opened. A raw headcount number for a given skill in a given city tells you almost nothing on its own. "Not just the top line of, 'There's a thousand engineers in a given city.' It's 'How many of those engineers have this mix of skill set and experience and would be interested in what our value proposition is?'" he says.

From there, the practical constraints like on-site requirements, travel expectations, and specific skill combinations start narrowing the pool fast. "A lot of companies fall into this trap of saying, 'Oh there's a thousand engineers there, we shouldn't have a problem.' Your thousand can become 10 with just a few bullet points," Peterson notes.

Measure the outcome, not the machine

If the market is the real starting point, then the metrics TA has traditionally lived by are measuring the wrong thing. Peterson wants TA to look beyond time to fill, time to hire, and cost per hire toward an outcome that matters more directly to the business. "Let's focus on being a reliable source of high-quality talent for the business by shifting from measuring the process to measuring the outcome," he says. "To me, that's on-time talent delivery. We get you the talent you need when you need it."

Getting there requires TA to know three things well, and Peterson is precise about them. "A healthy TA function has good visibility into the market so we can make good decisions. We have a good workforce plan so we know where we're going on behalf of the business. And we have good information about ourselves so that we understand that process." The process knowledge doesn't disappear under this model. It gets repurposed, so that understanding notice periods, onboarding, and sourcing timelines becomes the basis for telling the business when to open a role.

Available is not the same as reachable

One distinction sits underneath Peterson's whole argument: a market can be full of workers, while the specific talent an organization needs stays out of reach. Part of that is candidate behavior, and right now he sees two camps in the market that look similar from the outside.

One group is actively looking because of personal circumstances or uncertainty about their current employer. The other is staying put. The trouble is that the two aren't easy to tell apart. "It's not obvious who's who," Peterson says.

Risk tolerance also clusters in ways that shape reachability. “Some talent segments may be more deliberate and risk-conscious in considering a move. For example, it may be harder to attract an experienced quality engineer from a stable organization than someone working in a role where career movement is more common,” Peterson points out. An outreach campaign that hits a risk-averse pocket of a market will underperform for reasons that have nothing to do with the offer.

Intelligence is what you do with the data

The function Peterson is building turns that market knowledge into decisions, and he's quick to say the hard part is not collecting data. It's the surplus mindset once again, this time making people discount what the data tells them. "People say, 'I know your job's hard,' but many are still planning around expectations formed in a very different labor market, expecting scarce talent to be found in timelines that don't reflect today's reality."

Sometimes the fix is simply information, delivered early. He describes managers opening a plant overseas who wanted engineers in a time frame the local notice period alone made impossible. "The notice period alone is 90 days," he informed them. In the better cases, business leaders now come to his team ahead of time. "There are business leaders that will come to my intelligence team first, and say, 'We have this role, and we can put it in any one of these five locations. You tell us what order those five should be in, and if any of them have critical failure points.'" That input has moved entire functions to different locations than originally planned.

What he wants to measure upstream is the thing a standard funnel dashboard omits entirely: whether the business's plan is achievable in the market before it commits. "Take the workforce plan, run the market intelligence against it for at least critical roles, assess the labor markets, and then inform the business early on what our likelihood of success is," he explains. That means catching the expensive mistakes early, like a location chosen on cost alone. "Yes, there's a lot of talent there, but you layer on just one or two requirements and that talent evaporates completely," he says, describing an example where a long commute and a four-day in-office rule shrank the funnel on contact.

Assessments as a two-way test

Where assessments come in, Peterson treats them as one input in a larger read. He describes the evaluation as a three-legged stool: how a candidate does on the assessment, whether the role is right for the person, and whether the environment is right for them, too. The same score can mean different things depending on timing and fit, and the discipline is in weighing all three rather than letting one number decide. "When those assessments are appropriately validated, well deployed, well tracked, and can tie back to meaningful outcomes," he says, meaning the people who score well genuinely outperform, "that should be feeding back into the intelligence function to narrow down that field from 1,000 engineers to the 10 that really are relevant for us in the market."

The part most teams miss, he says, is that the feedback loop can run in reverse, as well. "People will die on a certain hill about what's important for a role, and then you A/B test it and take it out and realize it's making absolutely no difference," he says. "How many people did we pass on because we're so indexed on this requirement?" An assessment, in other words, can build the case to drop a requirement as easily as to add one. He's equally careful not to overload candidates. When a company says half its candidates abandon a long assessment partway through, "I think that's telling you something."

Changing TA for the better

For all the talk of markets and metrics, Peterson lands somewhere human. He tells a story from his hospital days, when a consultant asked which hospital everyone wanted to be the best. The obvious answer, the hospital everyone worked at, was wrong. "The hospital you want to be the best in the world is the one that your loved one's in. Doesn't matter if it's yours or not."

He applies the same logic to the work. The cardiovascular care that Edwards' work supports matters enormously, and so does every other company's mission to the people it serves. With this in mind, his goal is not to fix TA at Edwards, or in medical devices, or in one country. "One of the things I'm really trying to do is change TA, period, to a more predictive model, using the intelligence, using data, and shifting mindsets away from surplus to scarcity," he says. Start the conversation about what TA is for, and hold it to the outcome that actually matters.