The discipline of "operations research" (or "decision science") is relatively unknown in the startup and tech world. At its core, it is the application of mathematical models to business problems (often complex operations). While very complementary with data science and machine learning, it is an altogether different field.
The business world is full of the kind of problems that operations research is designed to solve. Automating the best delivery route for your food to arrive. Figuring out the best shift schedule for your medical staff, so you can support anticipated activity. Supply chain. Pricing. Project management. Basically, any area where you need to make an optimal choice based on available information.
So why isn't operations research more broadly used? A lot has to do with its underlying complexity. It is a deeply mathematical field. Currently available software solutions typically require PhDs from the field to operate successfully. And talent is rare. If you think it's hard to find a great data scientist, just try hiring an Operations Research expert. Historically, many graduates have been immediately snapped up by the defense industry.
My co-founder Ryan and I know this, because that's precisely our story. We started our careers in systems engineering and operations research on big government projects, including missile simulations and airport runway management. Thankfully, we found our way to the startup world, and a few years ago, met working on food delivery at Zoomer (YC S14) and later Grubhub.
It turned out that making on-demand pizza and taco delivery efficient and reliable required the same optimization and simulation techniques, but in real time. We felt the pain of having to choose from a small number of older-generation software tools and figured there had to be a better way.
So we decided to start nextmv, to solve our own problem, and build the kind of tools we wish we had. Easy-to-use decision science tools for optimization and simulation that are accessible to a broad range of software developers, and play nice with modern software infrastructure.
It's been an exciting ride ever since. We launched our optimization tool Hop in December, quickly added our first enterprise customers, and completed the YC W20 batch.
Today, we are thrilled to announce that we closed a $2.7M seed round of funding, led by FirstMark Capital and Dynamo Ventures, with participation from XFactor Ventures, Atypical Ventures, and additional funding from our existing investor 2048 VC.
Some thoughts from them:
Matt Turck, Partner at FirstMark: “We are thrilled to partner with nextmv. We spend a lot of time in the data and ML/AI world, and it has become clear that optimization is an area that's ripe for innovation and a key building block for the data-driven, automated enterprise. By offering optimization as a developer tool accessible to non-specialists, nextmv has the potential to unlock a very large market opportunity, starting with the world of logistics and expanding to other areas over time.”
Santosh Sankar, Partner, Dynamo Ventures: “Over the years, Dynamo has observed that there is a lack of consistency around data-driven decision making in the supply chain. While there is a desire and a need to be more data-driven, the existing systems (oftentimes siloed and patched together) and talent (lack of software engineers and data scientists) hold back real-time optimization and automation efforts. After meeting Carolyn and Ryan, it was abundantly clear that they were the right team to build nextmv.”
Allison Kopf, Partner at XFactor Ventures. "Optimization is critical infrastructure for dynamic supply chain businesses. Carolyn and the team at nextmv have built an incredible solution that puts the power of complex data science in the hands of every business. The future of logistics relies on real-time optimization and we believe nextmv is leading this transformation."
Alex Iskold, Managing Partner at 2048 Ventures: “2048 Ventures team is thrilled to be the earliest institutional backer of Carolyn, Ryan and the nextmv team. Decision Engines are rapidly becoming a centerpiece of business optimization infrastructure in delivery, logistics and schedules. Just like today where no business can operate at scale without data science, we believe that in 5 years no business will be able to scale without Decision Engines. We think the nextmv is well positioned to become a category leader here.”
We are a fully distributed team, but have our roots here in Philadelphia. A community we are so proud to represent. For more information on the company, the product, and our open roles, check out nextmv.io!
You have two vehicles and ten locations to visit. What's the best way to route your fleet? You have seconds to solve and Nextmv Cloud. Ready, set, go!
Transporting raw milk from farms to processing plants is a daily occurrence that seems simple at first glance. But it gets complex quickly when time is of the essence and milk volumes vary.
We've released Hop v0.7.0! This release introduces a cool new feature we call expanders into Hop to help customers manage time to first feasible solution and memory use as they scale their models.
Building decision models into binaries is a beautiful thing. It eliminates a lot of sticky deployment processes and gets you to production faster.
We're thrilled to have FirstMark Capital lead our Series A round, putting even more momentum behind our vision to bring the power of decision science to every developer.
Everyone talks about Santa's big night on his sleigh - a vision of efficiency with millions of chimneys traversed in a mere 24 hours
Launching Nextmv Cloud
Our quarantined world is even more on-demand than it used to be. We order groceries, gadgets and green goddess salad, and they all show up at our doors within minutes.
Routing, Packing, and Clustering - Optimization Fundamentals
We completed our seed round!
How does Hop make decisions?
What does nextmv do?