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10 October 2022 | Topics: Datavant Culture
Why and How to Hire for Potential
An approach to finding “10Xers” with the will and the skill to grow
Recently, Chris Abbass invited me to join him on Hiring on All Cylinders podcast where I had the opportunity to discuss my own journey into the People space, the opportunities I see today, and how we’ve scaled culture through a period of disruption and uncertainty. Chris’ insightful questions prompted me to expand this conversation into a 3-part series for the blog. Below is part 2 of 3. Part 1 is here.
Why hiring for high-potential is a differentiator
I compare it to the Compounding Effect in finance. I’ve written about this since 2018.
I think personal growth is very similar to compound interest: it tends to be exponential. A lot of people in the first half of their career journey have the capacity to increase their personal skills at a rate of 2 or 3 times a year.
Here’s an example: If you take someone who’s been in the workforce for three or four years, give them another year, along with the right environment and coaching, they could become twice as impactful or capable.
But most organizations in tech, in professional services, and the investment community don’t have easy paths for people in the first half of their career to accomplish 2X and 3X scaling per year in their capabilities. It’s more like 20%, or 50%, if you’re lucky to be in a learning-rich environment.
When you look at the difference between someone growing at 50% expansion of skills year-over-year or 2X expansion of skills year-over-year, and you think of it compounding like interest on investments, after a few years you get people with really divergent levels of impact, performance, and capability.
We’ve always had a view, especially as an early-stage company, that we’re not sure what the future holds (in terms of the unique opportunities and puzzles we’ll be solving). The problems we’re solving today and the problems we will be solving in 18 months might be really different from one another, so why don’t we bring in people who have the ability of 2, 3, or 5Xing their capabilities year-over-year?
We call that “potential” — that will and skill to grow.
Even now, as a scaled organization (with ~1200 salaried staff and 8,000+ hourly staff), the premise is still true: we’re building something that’s never been done before — connecting the world’s health data to improve patient outcomes, which today requires cutting edge technology innovation and human-powered operational excellence — which means all across the org, the challenges of today and the challenges of tomorrow will be different.
So, investing to hire high-growth, high-potential talent helps us have optionality and a range of skills for the future.
What it looks like to evaluate and hire for potential
Aspiring to attract and hire high-potential employees is relatively easy.
The “how” is tricky.
We do a lot of interviewer shadowing and training in the company today, standard tools like structured, criteria-based interviewing and question banks.
I’ve probably conducted 1000+ interviews (I love it), and a few of the traits I focus on that are predictive of success here are:
- Learning & curiosity
- Resilience & grit
First, I think learning and curiosity are really critical dimensions. In an interview, I’ll ask questions like, “Tell me something you’ve learned in the last few years.” It could be personal or professional. It could be, “I picked up woodworking during COVID,” or, “I learned a new coding language in my last job.” But the “how” is so much more important than the “what.”
I push a lot on how people learn. I look for signals like:
- Are you a hands-on learner?
- Do you want to read a lot of books or blogs?
- Do you want to go to events and learn from practitioners?
- Do you want to hit every obstacle you encounter and then ask experts for help?
I believe a calibrated interviewer can tell in an interview how innately curious someone is by spending a lot of time on the candidate’s questions — spend more than 5 minutes of a 30 minute interview on this.
Assess the questions they bring to you. One tactic I use is simply to flip the interview and start with the candidate’s questions first. It can throw some people off, which is not the goal, but the super curious folks will have a list of questions and show excitement instantly. I’ve even seen candidates say, “Oh wow, I’ve never started with questions, this is awesome…”. That’s a great sign.
Second, I also like to push on resilience and grit. “Tell me about a time that you struggled.” Or, “When have you gotten really hard feedback and bounced back from it?”, questions that put the candidate in a place of, “This thing I did was really trying. How did I move through it? Did I react with a teachable spirit and mine the experience for lessons learned, and get better, or did I get beaten down, burned out, and disappointed?”
One of my favorite articles on interview questions is from First Round Review, here.
There is no best or worst way to learn, though understanding the ‘dark shadow’ of each style is helpful
While no one of the learning styles above is better or worse, I do think there are certain styles that fit better with different managers and different organizations at different moments in time.
If you, as a learner, say in an interview “I want to do it myself,” (I see this a lot with early career software engineers, for example), I will go deep with followup questions, such as:
“Here’s a scenario: you’ve gotten a challenge from your manager. You’re not really sure how to solve it and you don’t know where to start. What do you do? How long do you work alone on your own? When do you start to post in the team Slack channel for guidance? When do you ask your manager for help?”
A lot of different learning models can work, but if someone says, “I don’t want to bother my team and managers, I want to do a lot of reading. I’m going to take an academic approach to it. I’m going to test and fail.” I will ask, “When do you know that you’re wasting your time?” Building a business is a team sport. It’s not individuals doing problem sets in college where you’re not supposed to share.
On the flip side, if someone says, “I learn best being an apprentice. I want to watch someone do it,” that can work fine too in a lot of different forums. If you do pair programming as an engineering team, or you have a sales model where junior sales people supporting pitches and witnessing a more tenured person working. But then as an interviewer, I want to find out if they work individually enough before they ask for help. If they like to be in an apprentice model and we don’t have a formalized mentorship or shadow program, will the candidate have enough capability and will to do some research on their own? You want people to work independently and autonomously before they tap on their colleagues or their manager for help.
So, there is not a perfect or wrong answer to the question of how a candidate likes to learn best. Yet, I like to vet the worst case scenario or the dark shadow for each type of learning style to make sure that someone’s not going to spend a week alone working on a coding problem when half a day would have been fine, and then they could have asked for help on Monday afternoon instead of waiting until Friday afternoon.
Hiring for potential is only the first step — intentional investment in cultural infrastructure is needed to nourish the potential
There’s no easy answer or playbook here. Three areas I recommend:
- Intentionality — don’t wing it, be thoughtful
- Investment — it takes time, people, and money to do this — it won’t happen organically
- Clarity — know what you are as a company and what you aren’t, what you will do and won’t do. Be explicit. Write things down. Train on it.
You have to keep the right balance of experienced and not-yet-experienced folks with high potential.
First, you have to understand and have a perspective on which types of roles benefit from potential as a primary capability, and which benefit from specialization or expertise. It’s not one-size-fits-all.
For the typical company of a hundred people — for example, tech companies and startups at series A, B, or C fundraising — conventional wisdom might say only a handful of roles should be filled with high potential generalists.
I see it differently. Many more roles than conventional wisdom would suggest can be high-impact if they’re hired for potential.
For this to work, a company needs to have intentional focus and resources. Here are some of the ingredients we’ve found helpful at Datavant over the last 5 years:
- An emphasis on coaching and feedback (e.g., part of your cultural values or leadership principles) as well as innovation and experimentation (can’t be afraid to fail)
- Clear expectations for managers (leaders of teams) to include (a) giving written feedback X times a year and (b) doing one-on-ones on at X frequency, which should include feedback or coaching
- Providing training (from in-house People team, or external trainers like LifeLabs etc) on how to do 1:1s, how to coach, etc
This can range from informal to highly structured. If you don’t have these in place today for a team of 100, you can start a MVP (minimum viable product) approach with 1–2 person-days of effort — it doesn’t have to be a major lift to start.
In part 1, I talked about a few of our principle-based guiding documents. One of them was, “What are the expectations of a leader of this company?”
When we had only ~10 people-managers, we wrote a document. It had four categories:
- strategy / setting a vision
- managing execution
- growing & enabling the team
There were tenets that said, “We believe in feedback and coaching as a critical ingredient to this environment.” If you have high-potential team members that you bring in, but you don’t pair that with an environment that facilitates learning, an environment that is okay with making mistakes, you’ll never have people unleash that potential.
We tried to be clear that it’s an expectation we have for every leader, to invest in coaching and to make it okay to make mistakes.
In the second year of the company, a new junior engineer checked-in code that broke Production. Our response? That engineer and a few others fixed it quickly. We tell the story and we joke about it today. Everyone knew who it was, and we tried to make that lore and celebrate it. That new hire engineer didn’t get in trouble for breaking the Production environment. There was no penalty or discipline for it. It was a great hands-on learning moment to fix it. And ultimately we tell stories like that because it shows you do work that matters.
We take off the guardrails. We trust you. And we hire people who seek and thrive with this level of autonomy and judgement.
People will make mistakes and will recover from them. So by setting that norm of, “experimentation and mistake-making is okay as long as we learn from it in appropriate ways,” and then setting expectations for managers and leaders to invest in coaching and feedback, we hope to use those things as fertilizer for the potential so it can really grow and be unlocked.
Considering joining the team? Check out our careers page and see us listed on the 2022 Forbes top startup employers in America. We’re currently hiring remotely across teams and would love to speak with any new potential Datvanters who are nice, smart, get things done, and want to build the future tools for securely connecting health data and improving patient outcomes.