“Adapt or die” is Brad Pitt’s mission as Billy Beane in the Oscar-nominated film Moneyball, which – it turns out – isn’t just a story about baseball; it’s about change management.
The message is one that healthcare is facing with physician recruiting, a make-or-break area for every organization. Doctors are disappearing across the country, leaving for retirement and other jobs. They’re vanishing faster than recruiters can replace them.
It’s a simple, dire problem: no doctors, no business. And if you fill roles out of desperation with misaligned physicians, the cycle keeps spinning.
Organizations have to get a whole lot smarter about how they’re assembling their physician teams. Healthcare needs its own moneyball.
Adapt or die.
Actual quote from A physician recruiter:
“We’re all looking at the same active candidates, and boy does it get costly when you’re competing for only a few providers against the guys across the street. I want candidates they don’t know about.” – Physician recruiter
Scene from the film “Moneyball”:
“You don’t put a team together with a computer, Billy.” – Oakland A’s scout
“Adapt or die.” – Billy Beane
If you’ve seen the movie or read the bestselling book by Michael Lewis, (and who hasn’t), you know that Moneyball unspools the riveting chapter of sports history when Oakland A’s general manager Beane changed the game of baseball by reinventing sports recruiting.
With its lean budget to build a roster, the A’s had a huge competitive disadvantage. So Beane was open to disruption when sports analytics legend Paul DePodesta started talking to him about sabermetrics. As Brand put it, “Your goal shouldn’t be to buy players, it should be to buy wins.” By using computer-generated analysis to identify the best undervalued players for each position, Beane could outsmart the bloated old ways of big-money baseball.
The strategy shook the industry and faced ridicule. But it worked. And it disrupted baseball forever, with other sports borrowing moneyball techniques to this day.
Today, moneyball is a term of art. Broadly, the concept connotes the competitive advantage of innovation, which applies to any field. Specifically, moneyball revealed the value of statistical models to source talent that can elude the naked eye. Moneyball doesn’t replace actual baseball scouts and human judgment, but it can help those humans source opportunities, upend conventional wisdom, and back or buck gut instinct with scientific grounding.
So why not create a new kind of moneyball with other forms of recruiting? Like the physician kind.
That’s exactly what a group of us thought when we began applying AI to the entrenched challenge of physician recruiting.
Actual quote from a physician recruitER:
“There has to be a better way. Our current sourcing methods feel redundant and only lead to a small subset of the candidate population. I pay recruitment firms handsomely just to try to extend our reach, and it still feels like we fall short.” – Physician recruiter
Scene from “Moneyball”:
“Baseball thinking is medieval, and they are asking all the wrong questions, and if I say it to anybody, I’m ostracized. I’m a rebel, so that’s why I’m cagey about this.” – Peter Brand
It’s not just old baseball thinking that’s medieval; so is the thinking behind traditional physician recruiting.
The provider shortage across America is acute and getting worse, at terrible cost to patients. More than 100 million people, or nearly one-third of the nation, have trouble accessing primary care, according to a recent study published by the National Association of Community Health Centers.
But traditional physician recruiting can’t help because it’s broken, and everyone knows it. Above all, the doctors on the frontlines know it. They feel the brokenness directly when they’re doing more work than they should be handling because their organizations are understaffed, staffed with the wrong people for the job, or both.
For decades, recruiters have used the same approach of cold calls, email blasts, posting and praying. The recruiting “solutions” that have popped up over the years do little to help because they all focus on the 10% of candidates who are actively searching for a job at a given moment in time, overlooking entirely the 72% of passive candidates who aren’t looking but are interested in a new opportunity.
Traditional sourcing doesn’t produce enough interested candidates for each job, which forces organizations to sift through resumes and hire the first candidate who checks a limited number of boxes. So even when recruiters do (finally) fill vacancies, they’re often signing hires who aren’t aligned with the organization and end up leaving within a year. Anyone who thinks that this outdated approach is enough to meet the Defcon 1 emergency in healthcare today isn’t paying attention.
The fallout is immense.
Patients suffer. Work satisfaction suffers. And organizations suffer when burnt out physicians leave, which creates a deepening hole to fill. This leaves companies heavily dependent on more and more recruiters; or they need to bring in premium labor through locum tenens.
Organizations don’t want Band-Aids; they want long-term, sustainable solutions.
Physician recruiters are bearing the brunt of the pressure to solve the provider shortage for their organizations. But the problem is much bigger than them. The old way of recruiting simply can’t meet the needs of a historic crisis in the digital era.
That’s why we started Winnow.
Actual quote from A physician recruiter:
“I have the greenlight on any tool or resource that can improve our cost to hire and time to hire. We are desperate to find new ways to improve our metrics and stay ahead of our competition.” – Physician recruiter
Scene from the film “Moneyball”:
“We got to think differently.” – Billy Beane
A couple of years ago, I teamed up with a group of brilliant data scientists and business minds to bring machine learning to the problem of physician recruiting.
How, we wondered, could we use AI to fix the broken old roulette wheel of physician recruiting and more efficiently build high-performing physician teams? How could AI transform the business of physician recruiting from a scramble for bodies to fill roles into a scientific, data-driven process that is designed to place the exact right person for each position.
When you prioritize finding these better aligned matches, you get longer-term and higher-quality hires. But to do this, you have to go beyond the small pool of candidates who are actively looking.
Tapping into the passive candidate pool is the holy grail that eludes most recruiters. Context matters, relationships matter, and timing matters. Many recruiters skim the surface through networking and referrals, but this is an intricate long-game that gets underplayed.
How could we scale a solution with a software platform to reduce the inadequacies of traditional physician recruiting in the modern age amidst an acute provider shortage? How could we find a better way?
What we developed is Winnow, an AI-enabled recruiting platform that uses thousands of datapoints to identify the best aligned candidates for long-term placement, then finds the connections between those candidates and the physicians within an organization’s own staff.
Suddenly, recruiters not only understand the small pool of candidates they should be focusing on, they can also engage their own physicians in the referral process. And CMOs are paying attention; we’re finding that they’re even more curious to dive in than recruiters themselves.
Winnow is unlike any existing physician recruiting tool currently on the market. We are not a job board, nor are we supplementing an existing recruiting team with more human capital resources for tasks like cold calling. After all, why pay for someone else to spend countless hours calling on candidates who aren’t good fits?
And why assume that sourcing is enough? Engagement is the second part of sourcing, and the perfect candidate is far more likely to engage with your organization if they have a warm referral through someone they know.
Winnow changes the game for physician recruiting by powering a strategic and targeted process. Its AI-enabled talent search identifies and helps engage referrals for the best active and/or passive candidates to recruit for each role and location.
Today, successfully building a physician team that sticks means saying goodbye to status quo recruiting that isn’t working. It means leveraging science to help guide the way.
Moneyball seemed crazy when Billy Beane implemented it – until his team started winning. Physician recruiting needs its own moneyball pivot, with a new mindset around what actually works. That includes not just the AI tool of Winnow, but organization-wide buy-in around the referral process. Turns out that physician recruiting is a team sport.
Actual quote from A physician recruiter:
“Our referrals are our greatest source of candidates; They already know about us and have a contact at the facility. They tend to lead to a hire. Any way that we can squeeze more referrals from our provider base is critical to our sustained growth. Any tool that is able to increase referral rates is worth its weight in gold.” – Physician recruiter
Scene from the film “Moneyball”:
“If we win with this team, we change the game for good.” – Billy Beane
The only thing more uncomfortable than innovating is failing. When it comes to physician recruiting, healthcare must adapt or die.
