Meet the Team — Kevin Boehm, Head of Product
Meet the Team is our ongoing series of employee profiles. It’s an opportunity for our users and partners to get to know us a little better. As a remote company with employees around the world — from the U.S. to Slovenia to Spain to New Zealand — it’s also an opportunity for our team to get to know each other a little better.
We’re thrilled to introduce Kevin Boehm, Head of Product at GlobaliD. Kevin’s an MIT-trained engineer who cut his teeth in consumer finance before moving to Amazon and ended up as an early team member on a little project called Alexa.
Now, he’s helping us build the future of digital identity. In our wide spanning conversation, Kevin talks about the thread that connects everything he’s worked on so far, the core principles he abides by, and what makes GlobaliD different from anywhere else.
Introducing Kevin Boehm
Kevin: I’m Kevin Boehm, Head of Product. The best way to summarize my role is that I look at the universe of opportunities and the portfolio of products that we can build and ultimately make sure that we’re making progress to deliver digital identity that people, businesses, and developers want to use.
On the themes that drive him — including rocket science
There’s a couple themes that jump out in terms of the work I’ve done or the jobs I’ve found myself in. They’ve all typically been related to technology or some sort of large scale or optimization problems. They almost always involve multiple stakeholders, whether that’s developers and end users, buyers and sellers, or advertisers and publishers.
I studied mechanical engineering at MIT. I just enjoy tinkering, taking things apart — learning how really, really complex systems like heat exchangers for a nuclear reactor work, and then breaking it down into: Here’s the 12 sub-problems that allow this to function. How do we figure out how to optimize each part, and which part should we start optimizing first?
Some of the research work I did in college was around non-destructive testing of aerospace components, including figuring out how well new technologies can identify defects in parts like engine blades. It allowed me to zoom in really, really deep and optimize a single process that has life or death consequences. By learning to work at both breadth and depth, I got comfortable that no problem is too large or difficult to approach.
What the credit card game taught him about data and feedback loops
I ended up at my first job at Capital One — I don’t want to say by happenstance — but I didn’t know that much about credit cards or lending coming out of school. The big thing there that was interesting and shaped the way I think: Capital One actually invented the concept of credit cards with tiered pricing. Up until the late 80’s, almost everyone got the same interest rate around 20%. Capital One was the first company to say, Hey, let’s start looking at users differently, A/B testing, and optimizing.
The big thing I learned at the bank was: How do I take billions of rows of data around hundreds of millions of users and figure out a hypothesis that we can test.
Here’s someone who we can give a 10% rate or 25% rate. Their whole culture and DNA was around: Test, segment, optimize — all the way down to the mail that you receive:
What envelope?
What color is it?
What’s the call to action?
What are the product terms?
What’s the signup incentive?
All of that is something they test; they learn. They have a feedback loop. I developed this assumption after two years working at the bank that everyone in the world has measurements, goals, and success criteria.
The big thing I learned at the bank was — I hate the term big data so I try to actively not say it : How do I take billions of rows of data around hundreds of millions of users and figure out a hypothesis that we can test? I like to joke that it was kind of like being a private investigator. You had all the evidence and clues in front of you. It was just a matter of putting together your business hypothesis.
How Amazon’s culture showed him the big picture
I moved to Amazon after two years at the bank, and I went from owning a really narrow piece of how credit cards work to owning an end-to-end credit program.
What was really exciting was that I got to transition from just trying to understand how credit cards work — and being a nerd and having dozens of credit cards — to understanding how I can leverage the assets that Amazon has. There’s so many users. It’s like a giant Petri dish, having the ability to carve that up and say, I’m going to run this test on 5% of Amazon users. I had millions of opportunities to test something.
That feedback loop between having an idea, implementing it, and seeing how much money you’re making was 15 or 30 minutes — not days or weeks.
There was one really cool experience I had at Amazon. I was working on a new program, kind of an internal startup, that was on pace to make hundreds million a year. We shut it down — what, at a normal company, would have been a crazy, irrational decision — because there was a competing opportunity we could focus on with the potential to make billions of dollars a year in profit.
We looked at it and said, Here’s an opportunity that’s 10X bigger than the other. Let’s shut it down right now. Yes it hurts, but once the decision is made, there’s no second thought. You just move on and focus on the big thing. That was something that was ingrained in the culture; everything is constantly changing, and it’s your job to adapt and evolve and solve the biggest problems for the business overall.
Joining the Alexa team early on
The last role that I had at Amazon was working on Alexa. I got to join early on, about a year after the first Echo device launch. At the time, Amazon had invested several years into developing Alexa, solving the science and engineering problems to make a smart speaker work and figuring out: How do we build this into a business?
Back in 2015 or 2016 — there were a limited number of things a user could do with Alexa. But in the long term, we had all these aspirations about how to make an operating system that is everywhere — in people’s homes, computers, hotels and cars. How do we use this to drive long term value of the company?
Amazon’s very long term focused and specifically focused on driving value for end users. This was even taking that to an extreme and saying, 10 years from now, we might start making a profit off of this. What are the things that matter most between now and then?
When I think about GlobaliD, we have some use cases now, where it’s like: Let’s make this work so users understand digital identity. Even if all the partners and players aren’t there yet, let’s deliver value to users today wherever we can do better than the current solutions.
On building for the future — lessons from Alexa
In terms of things that shaped my thinking and are valuable at GlobaliD, this lesson stands out: You need to provide and illustrate value to users as quickly as possible.
For Alexa, some of our first use cases we supported were prominent features like ordering a Domino’s pizza or an Uber. While we didn’t necessarily think these would be the killer app, we believed that users, developers, and businesses could understand, get excited, and start imagining how they could incorporate it into their lives in the future.
It was on us as a company to figure out: What are the five or six cases that people will get — even if it’s not something they’ll do all the time. Otherwise, they’ll use it for a day, unplug it, and throw it into the closet.
When I think about GlobaliD, we have some use cases now, where it’s like: Let’s make this work so users understand digital identity. Even if all the partners and players aren’t there yet, let’s deliver value to users today wherever we can do better than the current solutions.
Another piece that was really instrumental was building things in the scrappiest and cheapest way possible. One of the benefits we had at Amazon — because we were spending probably about a billion dollars a year on the program — was that we would have three or four teams building competing solutions for the same problem. They were building in different ways.
More often than not, the team that was most successful was not the one that started off using the latest and coolest forms of machine learning and data science; it was a team that did things really scrappy to test and continuously iterative solutions to solve user problems.
Core principles #1: Focus on the end user
The first principle is always being focused on the end user.
Knowing what they care about.
If they’re going to wake up and want to engage with us, then we need to know what they wake up and think about in terms of their biggest problems.
That customer focus — whether that’s when we’re building, designing, or selling — that’s number one.
Core principles #2: Moving fast or slow
Number two is realizing — and I’m going to sound like such a shill for Amazon here — but realizing what we call one-way door versus two-way door decisions.
When something is easy to change, let’s not spend a lot of time talking about it. Let’s make the best decision and move fast. We can always go back through the door and change our decision.
When something is going to be expensive or impossible to change, that’s when it’s worth us spending time to get it right.
There are so many decisions we have to make every single day, it’s about figuring out which ones are worth the extra cognitive burden.
Moving fast when it’s smart, and then taking time where the stakes are higher..
Core principles #3: What matters most
The third is just being willing to say — I don’t want to say throw stuff away — but ruthlessly prioritizing what matters most now.
The predominant belief of, I want to keep doing this instead of admitting defeat, is counterproductive. You are losing if you’re letting your less valuable ideas get in the way of the more important ones.
If a scientist or an investor sticks with 100% of their hypotheses in the face of contradictory evidence, they’re likely not in the top of their field. As a business, if you’re not throwing away your worst ideas, you’re either a genius and correct 100% of the time, or you’re unintentionally starving your best ideas from succeeding. In my experience, it’s usually the latter.
The road to blockchain is paved in economic incentives
I went down the Bitcoin and blockchain rabbit hole in — was it 2017? It was one of the Super Bowls where the Patriots won, and I actually had some money to cash out. I had previously read about Bitcoin, and once I used it, it piqued my curiosity. How does this actually work? This led me to start reading white papers, learning about encryption, protocols, and projects.
What I really, really appreciated was — I don’t want to just overuse the term decentralization: The ability to build a functioning system resistant to participants who are actively trying to screw each other over. That’s about as close to perfection as it gets when people are trying to collude, trying to steal — and the system aligns economic incentives accordingly.
As soon as I saw the potential value there, I became interested in exploring and identifying where future business applications could be.
“Anything that I care about in the next 10 years is going to be bolstered by identity.”
Outside of payments, I did a lot of research into projects and took a course through MIT’s executive education program. Some of the use cases that were covered included some early identity providers. None of them are still around today because they were a bit too early or they pivoted since then. But having learned about the concept, I was intrigued. Intrigued but also skeptical. It’s a tough nut to crack.
What ultimately led me back here when I was looking at my next opportunity: I landed on identity because I couldn’t choose.
I was really interested in payments, fintech, and the crypto space. I knew I was going to do something adjacent to that. I was also exploring companies in insurtech and insurance, which ultimately comes back to identity. The third was a lot of stuff in advertising and data — but the data optimization space.
All of these revolve around individuals, their data, and the ability to connect products and goods to those individuals. I could say this in two ways. One, I figured out that identity was at the hub of all the things I cared about. Another way to put it is, I was too indecisive to pick a single field.
So I said, Why don’t I pick the one that has the most applications? I thought to myself, Anything that I care about in the next 10 years is going to be bolstered by identity. So why not go solve something that heavily shaped my mind?
The GlobaliD difference
When I think about where we stand and the other players in the space, I think about the common themes that exist beyond GlobaliD. As a human race or as users of technology, we definitely want to have as much control as possible.
What I think is different about our approach is not just that we’re taking this long term focus — lots of people can say they’re taking a long term focus. But it’s us starting with the most meaningful and high stakes problems (in terms of overall reach) that ultimately revolve around money (and as a result, put us into a highly regulated, highly inspected space).
Where I see us coming into play along with a lot of our competitors is providing users a new way of doing things, a new way of interacting with other individuals, online businesses, peers, enterprises — and doing so in a privacy-preserving manner.
These are going to be the table stakes terms.
What is different about our approach and what ultimately led me to pick GlobaliD versus any of these other competitors is the time horizon that we’re looking at.
The kinds of problems that we’re looking at solving require a certain long term focus but also a certain type of stubbornness. It’s not necessarily looking at a one-off problem we can solve. It’s looking at what we would seek to change on a 10-year time horizon. What are the big biggest problems for us to solve in order to do that?
What I think is different about our approach is not just that we’re taking this long term focus — lots of people can say they’re taking a long term focus. But it’s us starting with the most meaningful and high stakes problems (in terms of overall reach) that ultimately revolve around money (and as a result, put us into a highly regulated, highly inspected space).
And it’s not just our focus around payments. (Most of the identity companies I’ve seen that have picked a lane to start in have chosen payments or healthcare.) It’s the combined focus on solving an immediate problem today, while knowing that if we continue to solve the second, third, and fourth problem — if we connect these four or five pieces together — we can actually fundamentally change the way that commerce happens, the way that people bank, and the way that people interact.
It comes down to having the long term approach, having the regulatory focus, and constantly seeking out where there’s immediate end-user value. If it’s just the first two, I’m not as excited. With the third, that’s where we’re going to be successful.
What we’re most excited about
The huge opportunity for us is if we can make this ability for people to share info in a privacy-preserving manner intuitive. It’s our best shot at becoming a verb.
There’s two areas I’m really excited about. They’re related but pretty different.
What I’m really, really, really excited about is making digital identity accessible and understandable to a mass market audience. When I talk to people — my friends, my family, people I grew up with — I tell them that the general idea of what we’re trying to solve is how they can interact with someone or a business and prove information about themselves without revealing their identity.
Every single person I talk to is like, Sign me up. This sounds like a better way. How do we do it?
The challenge for us is that at no point in solving this for the user do they need to understand hashing encryption, zero-knowledge proofs, or credentials standards. In the same way, when I look at jokes on the Reddit homepage, I don’t need to understand what protocols are happening in the background.
It’s just: I want to do this thing, and it’s as simple as possible.
The huge opportunity for us is if we can make this ability for people to share info in a privacy-preserving manner intuitive. It’s our best shot at becoming a verb. You don’t search for things, you Google things. What would it mean if you were to GlobaliD someone? It’s not to say the overarching goal is to become a verb — but it’s the ultimate sign that you’ve solved a problem in an intuitive way.
That’s our biggest end-user-facing or consumer-facing opportunity. The bigger one for us as a business is figuring out how we can start solving problems for developers in this growing web3 space. There’s nothing but problems and opportunities in any emerging market.
It comes down to knowing the end user, knowing what their problems are, and then it’s our job to solve them now while looking ahead and deliver solutions to problems they don’t even know they have yet.
GlobaliD’s biggest challenge
Our biggest challenge is that the areas we can add the most value today and the areas we want to be providing value in the long term are related but not necessarily translating one-to-one to each other.
Specifically, if we believe we can make these new financial instruments with regulatory compliance in a privacy-preserving way, the problem is that developers and users won’t wake up and say, How can I be more compliant today? It’s just not top of mind for them.
So today, if all we’re doing is trying to sell them compliance, compliance, compliance, it’s kind of like saying, eat your vegetables. Vegetables come great as a side dish for a lot of people. It’s on us to figure out what the main protein or entrée is. How do we gradually introduce these vegetables, and before they know it, it’s part of their diet?
It comes down to knowing the end user, knowing what their problems are, and then it’s our job to solve them now while looking ahead and deliver solutions to problems they don’t even know they have yet.
