Like “innovation,” machine learning and artificial intelligence are commonplace terms that provide very little context for what they actually signify. AI/ML spans dozens of different fields of research, covering all kinds of different problems and alternative and often incompatible ways to solve them.
One robust area of research here that has antecedents going back to the mid-20th century is what is known as stochastic optimization — decision-making under uncertainty where an entity wants to optimize for a particular objective. A classic problem is how to optimize an airline’s schedule to maximize profit. Airlines need to commit to schedules months in advance without knowing what the weather will be like or what the specific demand for a route will be (or, whether a pandemic will wipe out travel demand entirely). It’s a vibrant field, and these days, basically runs most of modern life.
Warren B. Powell has been exploring this problem for decades as a researcher at Princeton, where he has operated the Castle Lab. He has researched how to bring disparate areas of stochastic optimization together under one framework that he has dubbed “sequential decision analytics” to optimize problems where each decision in a series places constraints on future decisions. Such problems are common in areas like logistics, scheduling and other key areas of business.
The Castle Lab has long had industry partners, and it has raised tens of millions of dollars in grants from industry over its history. But after decades of research, Powell teamed up with his son, Daniel Powell, to spin out his collective body of research and productize it into a startup called Optimal Dynamics. Father Powell has now retired full-time from Princeton to become Chief Analytics Officer, while son Powell became CEO.
The company raised $18.4 million in new funding last week from Bessemer led by Mike Droesch, who recently was promoted to partner earlier this year with the firm’s newest $3.3 billion fundraise. The company now has 25 employees and is centered in New York City.
So what does Optimal Dynamics actually do? CEO Powell said that it’s been a long road since the company’s founding in mid-2017 when it first raised a $450,000 pre-seed round. We were “drunkenly walking in finding product-market fit,” Powell said. This is “not an easy technology to get right.”
What the company ultimately zoomed in on was the trucking industry, which has precisely the kind of sequential decision-making that father Powell had been working on his entire career. “Within truckload, you have a whole series of uncertain variables,” CEO Powell described. “We are the first company that can learn and plan for an uncertain future.”
There’s been a lot of investment in logistics and trucking from VCs in recent years as more and more investors see the potential to completely disrupt the massive and fragmented market. Yet, rather than building a whole new trucking marketplace or approaching it as a vertically-integrated solution, Optimal Dynamics decided to go with the much simpler enterprise SaaS route to offer better optimization to existing companies.
One early customer, which owned 120 power units, saved $4 million using the company’s software, according to Powell. That was a result of better utilization of equipment and more efficient operations. They “sold off about 20 vehicles that they didn’t need anymore due to the underlying efficiency,” he said. In addition, the company was able to replace a team of ten who used to manage trucking logistics down to one, and “they are just managing exceptions” to the normal course of business. As an example of an exception, Powell said that “a guy drove half way and then decided he wanted to quit,” leaving a load stranded. “Trying to train a computer on weird edge events [like that] is hard,” he said.
Better efficiency for equipment usage and then saving money on employee costs by…