Finding unicorns with a match-specific surplus.

So, it is PhD admissions season, and you might wonder: will I get in anywhere? Frankly, I don’t know whether you’ll get in. I didn’t at my first attempt.

Anyways, hopefully, I will see if I can create transparency in how PhD admissions decisions are made.

Of course, my views might be idiosyncratic—but I’ve been involved in PhD admissions for nearly 15 years and have managed PhD programs at two “top” institutions (Stanford OB in the past and Duke Strategy, which I currently manage). While my experience may not be representative, here’s what I’ve observed.

Share Research, Strategy: Way more fun than it sounds

We’re trying to solve a problem here.

What’s the problem?

First, I want to ask you: Do you know the acceptance rate for a paper at a top strategy or organization journal?

Note: You might be wondering what this has to do with PhD admissions. I promise I’ll get to that in a bit.1

Answer = 3-7% (let’s pick 5% for a nice simple number)

Second question: Do you know how many papers in top journals most good schools want someone to publish before they get tenure? 5 to 6 in about 8-10 years. Let’s, again, pick five as a simple number.

Let’s do some math. Assume you just wrote five papers during this time.

P(all 5 papers published)= p^n = .05^5 = 0.003125%

Yup, kind of like 0.

Put yourself in the shoes of a hiring committee: Do you think a school wants to hire an assistant professor they think has a 0% chance of meeting their tenure bar?

Of course not! This decision becomes even starker because the bet on the assistant professor isn’t a “free” bet but will cost the hiring school between 2 and 2.5 million dollars (assuming standard salaries, research budgets, benefits, office space, etc.) per assistant professor. They want this ultimate probability to be as high as possible.

What maximizes those probabilities? A very high p and large enough n.

Let's do some more calculations and move beyond these base rates. We should consider a high-quality researcher who gets 50% of their papers published (10x higher than the base rate). However, this person writes slowly (but well), so they still wrote only five papers in 8 years.

P(5 papers published if you wrote 5)= p^n = .5^5 = 3.125%

It's better, but sure as heck, not enough. Would you want a 3% chance that your 2.5 million bet paid off? I wouldn’t.

Ok, let’s bump up the number of papers you wrote, but keep the p = 50%. How about if you wrote 10 papers during those 8 years? Let’s plug our numbers into the binomial probability formula.

Ok, so what we have to calculate is:

So, if we do this, we get:

P(X >= 5) = 0.24609375 + 0.205078125 + 0.1171875 + 0.0439453125 + 0.009765625 + 0.0009765625 = 62.3%.

So ultimately, for this high p and large n person, P(X >= 5) = 62.3%.

This is a bet I’m willing to take as someone hiring an assistant professor.

I want someone well-trained and creative, produces high-quality work (high p), works hard, and will write papers (reasonably high n). In other words, they MUST write—high n, conditional on high p, is simply who they are.

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So, what’s the problem a PhD program is trying to solve?

Professors—especially research-active ones at top schools—have a simple goal: to make their ideas influential.

One key way they achieve this is by training PhD students who, along with the student’s own ideas, carry and spread the style and approach of the PhD program to the very top departments in their field. How will their students get top jobs? By convincing other departments to make the 2 million dollar bet on them. How do they do that? Signaling a high E[p] and a reasonably large E[n] by the time they graduate.

Like hiring an assistant professor, admitting a PhD student is costly. The financial costs are significant: $50k for a stipend, computers, office space, and a small conference travel budget, plus another $50k for tuition. A typical PhD takes about six years now, so we do the math and get a $300,000 investment in a PhD student (it's crazy that a cohort of three students poses nearly a $1 million outlay for an area!).

Moreover, as a PhD student, you are also getting lots of mentoring and development that is very 1:1 from faculty who could be doing something else with their time.

Given this, let’s work backward to the PhD admissions decision.

Programs want to admit people where the $300k investment pans out: you place the student at a top school. That is, we want students who will graduate with the largest E[p] (can they produce high-quality research that will get published in the top journals) and the largest E[n] (they will be productive). When the student goes on the job market and tries to become an assistant professor, these quantities should be clear to the hiring departments, who offer them a job.

Given the nature of the decision problem, PhD admissions committees are looking for two key factors that help them proxy for E[p] and E[n]: quality and fit.

What is quality? I think of it as the student's ability to excel in the Ph.D. program and eventually conduct high-quality, independent research with dedication and creativity (e.g., achieve a high E[p] and high E[n]).

You can think of two dimensions of quality: x1 and x2.

The x1 aspect of quality is what you bring into the PhD program (the selection effect). This is your “horsepower” (or “unicorn-power”)—your ability to learn new things, solve problems, write well, reason critically, show grit, be creative, and work hard. At a basic level, x1 also includes your interests — what motivates and drives your research goals.

The x2 aspect is your “coachability”—your capacity to take feedback, refine your approach, and maintain a relentless drive to improve, given the support of the faculty.

While x1 is much easier to measure than x2, I see x2 as the real key to unlocking the full potential of a PhD program. With strong coachability, the intense engagement and involvement of the program faculty can transform you, helping you grow far beyond what you came in with. It allows you to leave a different person.
What is fit? Fit refers to the alignment between a student’s research interests (x1), capabilities, and unique perspective with the research areas and distinct identity of a program and its faculty (y1). To succeed in publishing (e.g., to achieve a high p), you need more than generic ability—you need an “angle.” This is the style, approach, and unique perspective you bring, which must resonate with the program’s strengths to develop and refine your angle. There’s no universal high p; it’s always specific to a research area or approach. High fit means that your interests, skills, and aspirations align with the faculty’s distinctive approach—for example, the Duke PhD program in strategy is better suited for some students than others—f(x1;y1). This alignment ensures the program is uniquely positioned to maximize your potential and that the combination of you and the program creates the highest joint surplus.

Another element of a program that contributes to fit (y2) is how it’s structured to train students. At Fuqua, for example (I’ll write more about this later), our program emphasizes an apprenticeship model. From your first year, you collaborate closely with faculty, writing papers and gradually developing your own independent work. This approach differs from other PhD programs that are much more hands-off.

So, what are programs looking for:

So, this equation should tell you what we’re trying to figure out.

Essentially, PhD admissions come down to two things: quality and fit. We’re looking for students with the horsepower to do great research (x1) and the coachability to get even better (x2). But raw ability isn’t enough—you also need the right fit with the program you are applying to. That means your research interests and style (x1) align with what the faculty does best (y1), and the way you learn meshes with how the program trains students (y2). The goal? To admit people for whom the program will maximize their long-term potential—and who, in turn, will thrive and produce great work.

The admissions funnel

Ok, now let’s get down to the process.

During the admissions process, departments typically receive 50 to 150 applications, and the number of available slots varies across schools. Most strategy programs aim for an incoming class of 2 to 3 students each year (with around 4 to 5 admitted students each year). Depending on the number of applicants, admission rates range from 8% to 2.5%.

The first step in the admissions process involves sorting students into piles based on their academic achievements, such as their grades, GRE scores, and research experience (these are no longer literal piles but scores in a spreadsheet).

A pile:
- Top-tier students from elite universities with relevant research experience and letters from top scholars we know and trust.
B pile:
- Students with strong credentials from lesser-known schools.
- Students with weaker records from top schools and hard majors.
- Students with atypical majors.
C pile:
- Students with important discrepancies in their records (e.g., low grades, low GRE scores, etc.).
- May possess other qualities that make them suitable for research careers.
D pile:
- Students who would not be admitted to the program.

Faculty members then evaluate each candidate’s research fit and potential as a researcher. The admissions decision depends on the candidate’s ability and fit with the faculty's research areas.

You must signal your ability and fit convincingly to the faculty to increase your chances of getting into the best program.

Grades, GRE scores, and the rigor of your undergraduate curriculum are key indicators of ability—these are the x1’s. There’s not much you can change here unless you recognize weak x1’s early and take steps to strengthen them—by tackling more challenging coursework in a master’s program, improving your GRE scores, or gaining research experience that signals alignment with the program’s goals. But at the end of the day, your application reflects the x1’s you bring.
Fit can be demonstrated through relevant research experience, coursework, prior collaboration with faculty, taking a class with us, or working as a research assistant on a related project.

Students in the A pile are likely to be admitted to most top schools they apply to, while those in the B pile can improve their chances by working with relevant faculty and securing strong letters of recommendation—enhancing perceptions fit (x1 * y1), demonstrating high x2’s, or strengthening their x1’s (though this is typically more challenging).

For C-pile students, obtaining a master’s degree and using it to take challenging classes and conduct research can reduce the faculty committee's uncertainty and move them from the C to the B pile the next year.

The Winner’s Curse: How I Learned to Stop Worrying and Love the B pile

Ok, this was a long post, but hopefully, it clarified what’s happening behind the curtains of the PhD admissions process.

I want to close with one more observation (and yes, it’s obvious): a student can only matriculate into one program. So, it’s not clear that everyone should be admitting the exact same student if they want to attract the best fit for their program.

Frankly, if I’m recruiting for an nth-ranked program, I’d be concerned (maybe very concerned) if a student who, based on observables, looks like an A-piler ends up choosing my program. Why didn’t they get into a higher-ranked program? Did we miss something?2

Fortunately (?), I’ve usually had the opposite problem. I admit an A-pile student, they tell me we’re their first choice, beg me to take them off the waitlist, and I’m excited: “Wow,” I say to myself, “we could actually get this amazing candidate!” I give them an offer, and then—woosh—they ghost me. They pretend I don’t exist and use my offer as a bargaining chip with other programs (to those programs they ended up in: suckaz!). Meanwhile, I miss out on admitting students who would actually join my program, excel, and be happy to be here—all because some budding prestige chaser decides to create negative externalities for everyone.

So, if you’re that person—don’t do it. Please (please!), think about the ripple effects of your selfishness on others.

And for PhD programs—remember the winner’s curse. The B pile is your friend.

In summary, the key to being admitted to a top PhD program lies in reducing uncertainty about your ability (x1;x2) and fit (x1*y1;x2*y2) with the program.

PhD admissions are not just about finding the “best” student but identifying the student for whom the program can maximize long-term potential and who will thrive and make meaningful contributions to our knowledge of business and strategy.

What’s the problem?

https://en.wikipedia.org/wiki/Winner%27s_curse

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