HackerNoon Reporter: Please tell us briefly about your background.
I grew up in New Jersey. I went to school at the University of Pennsylvania where I majored in systems engineering and played varsity volleyball. I spent several years working at Lockheed Martin specializing in simulation for the Navy before moving over to Zoomer and later Grubhub where I led decision engineering work for delivery planning and optimization.
What's your startup called? And in a sentence or two, what does it do?
Our company is called Nextmv. (We pronounce it "next move" but we're not picky about it.) Nextmv’s decision stack helps developers automate and optimize business decisions for routing, scheduling, and other operations.
What is the origin story?
If you go way back, Nextmv’s story is grounded in systems engineering, optimization research, ballistic missile simulation, and pizza delivery in the time of paper map directions and walkie-talkies.
More recently, I spent a few years leading decision engineering at Grubhub with my cofounder Ryan O’Neil, building automation and optimization solutions for food delivery. We saw a chance to better serve developers tackling these challenges and others like scheduling and packing in a new way.
And that’s how Nextmv started. Nextmv is delivering the power of decision science to every developer. We believe it’s the missing link between data science and operations. Where data science answers what's going on, the Nextmv Decision Stack tells you what to do about it.
What do you love about your team, and why are you the ones to solve this problem?
We’re a remote-first company that’s distributed all around the globe. Most of us come from the worlds of optimization, routing and delivery, warehousing robots, search, and software development — all relevant to the problem we’re looking to solve.
That said, I love the diversity of backgrounds, experiences, and tremendous thought that goes into everything we do. On a personal level, the team is a remarkable bunch with interesting lives outside of work, good senses of humor, and the Slack emoji/gif force is strong within our crew.
If you weren’t building your startup, what would you be doing?
If I wasn’t playing in the decision science space, I’d probably be doing a combination of coaching volleyball, traveling (ideally abroad), adventuring with my doggo, and cooking. I can’t really imagine working anywhere else since we started this thing.
At the moment, how do you measure success? What are your core metrics?
We look at traditional metrics like recurring revenue, customer health scores, and traffic to our online properties. At the next layer down, some of the metrics we look at include the number of daily active customers, API calls our customers make, and the number of decisions (e.g., routes assigned, schedules blocked) made.
What’s most exciting about your traction to date?
It’s been particularly exciting to see reactions to our content (on our website or HackerNews) and our product from people in the community. You see it in how people comment about how to think about optimization differently, applying it in new ways, learning more about decision science and engineering, or just getting really excited about the ways in which our team is building out and shipping features in our decision stack.
What technologies are you currently most excited about, and most worried about? And why?
I’m generally excited about all of the movement in the decision science tech space. For a long time, companies only had a few tech options to automate and optimize decisions for their operations. You typically only saw users in more legacy industries (manufacturing, defense, and supply chain) and academia. That’s changed in the last few years. You’re starting to see companies like Amazon, Walmart, Wayfair, Instacart, Grubhub, and others really have a presence at optimization conferences.
I worry about the challenge we have ahead of us. Optimization and decision science haven’t always been super accessible. A large part of our work will always be rethinking how we present complex ideas and systems to our users in a clear, concise manner. But you know what they say: "problems worthy of attack prove their worth by fighting back.”
What drew you to get published on HackerNoon? What do you like most about our platform?
HackerNoon has always been a known resource in my universe of reading materials. It’s certainly taken on new context for me now as a startup founder. I’m super interested in community building, and I think HackerNoon has an interesting place in that realm with the work done to create an accessible space for technologists to swap stories and learn from one another. It’s incredibly powerful and valuable.
What advice would you give to the 21-year-old version of yourself?
Two things: 1) What got you here doesn’t necessarily get you there. You always need to be growing, changing, and making new decisions based on what’s in front of you.
And 2) don’t assume everyone has it all figured out. We’re all doing 1 ^
What is something surprising you've learned this year that your contemporaries would benefit from knowing?
You can build a strong team that’s remote from the beginning. Nextmv grew from 2 to 3 employees at the start of the pandemic. We’re now 25+ people. Most folks haven’t met one another. (That will change in the future!) We span several time zones. Making it work takes work, of course, by being smart about meetings, building out really strong asynchronous communications, creating shared experience, not drowning in Slack messages (even if we are heavy Hey Taco users).
Don’t forget to vote for Nextmv as Startup of the Year in Philadelphia!