Troy RuthsFounder and CEO, Petro.ai
Troy Ruths, Rice CS Ph.D. alumnus and Houston entrepreneur (Ruths.ai), had finished his bachelor’s degree in computer science at Washington University in St. Louis and knew two things: “I wanted to continue to grad school, and I wanted an entrepreneurship opportunity.”
He had not decided which direction to explore for entrepreneurship, but his graduate school choice was easy. “My brother Derek was already working on his Ph.D. at Rice with Luay Nakhleh and we’re very close, so Rice was one of my top choices.”
In 2008, genomes were just being sequenced and Ruths said Nakhleh was doing a lot of exciting research in bioinformatics. “It was a burgeoning field, and the ramp-up was huge. The computational perspective was a big draw for me,” said Ruths.
He decided to focus on bioinformatics with Nakhleh and felt that the Ph.D. process was good preparation for his career. “Luay was a great mentor for me,” he said. “He’s a very methodical and rigorous thinker, which I am not. I learned to adopt his habits.”
Applying the techniques he was developing in bioinformatics for the energy industry came naturally to Ruths. “My dad worked for Chevron –I actually grew up in Indonesia and we moved to Houston when I was in elementary– so oil and gas (O&G) was part of my history. As luck would have it, it was only recently that the O&G industry has generated a huge demand for data science.”
Ruths said, “Our first problems were reference and search problems, just like we’d worked on in Luay’s group. ‘Can I find access to the information I need?’ We focused on reservoir surveillance solutions. Hydrocarbons are held underneath the ground in reservoirs, so a company’s reservoir is like their bank account. They needed ways to manage their bank account without knowing exactly what was in it or what was happening to it down there in the dark.”
But launching an O&G data science company meant creating demand for an unfamiliar solution. The young entrepreneur said the analytics market had not yet expanded to the petroleum industry and his startup, Ruths Analytics & Innovation (Ruths.ai) opened about three years before their target audience recognized a need for their product. Last year, Ruths.ai was selected by Gartner as one of five Cool Vendors in the Oil & Gas tech market.
The breakthrough for Ruths.ai came in the form of a market crash in 2014 when large and small organizations across the petroleum industry had to optimize deep drivers for improving performance. Ruths said, “They had to significantly reduce headcount while still increasing productivity. When you have that kind of headcount gap, you have to fill it with technology, and data analytics was ranked one of the top seven innovative key initiatives for the industry by the Society for Petroleum Engineers.”
Analyzing huge data sets for their O&G clients felt remarkably similar to the projects Ruths had tackled in Nakhleh’s bioinformatics group. Both require physics-based system approaches. He said, “In biology, cellular systems are so complex that we need both statistics and machine learning to understand the elaborate patterns we observe. The issues of data dimensionality and quality are similar in O&G, and also require a computational approach.
“And you have to question all the data because you don’t know if it is good or not. Unlike machine-acquired data that can be expertly cleaned by Facebook or Google, the data we are mining is natural and it is noisy both in terms of the sensors and the processes.”
Another challenge Ruths.ai decided to tackle was sharing information. “Privately-funded O&G data is not shared,” said Ruths, “but we decided to begin sharing our algorithms. Typically these kinds of solutions are super expensive, but sharing our algorithms meant we reduced the entry cost and we’ve been able to improve access. For the first time, you can buy analytics with a credit card.”
While working in computational biology, Ruths realized that having a community was necessary for growth. So he helped encourage the birth and development of the new community with an open marketplace that includes solutions designed by Ruths.ai engineers as well as independent developers. As the community of application developers and application customers grows, the members continue sharing their expertise and the challenges they hope to solve, which in turn provides a steady stream of expansion in terms of new and improved tools and solutions.
Ruths said, “We have grown a community of O&G people using the same tools to work on similar projects. Now, we are THE data science company for oil and gas, and the majority of our business comes through subscriptions. If our marketplace is like the app store, our subscriptions are like Netflix.”
The growth of the marketplace and demand for Ruths.ai solutions could easily overwhelm the small startup, but Ruths drew on lessons he’d learned as a college basketball player to help keep his team fresh and focused on their priorities.
“We created our own sprint schedule,” he said. “We work in 90-minute sprints, four times a day. We sprint for 90 minutes and take 30 minutes off, then sprint for 90 and take an hour off, usually around lunch. We come back to a 90-minute sprint, take 30 off, and finish with a 90-minute sprint. You end up working six hours in an eight hour day, and we adhere to it rigorously.”
His team has successfully used the sprint schedule for almost two years and found they became more productive by working less.
“There is a lot of balance,” said Ruths. “And there are rules like no personal work or conversation during sprints. You can’t ask how the kids are or what someone did for the weekend, no personal email during that time, no personal calls unless it is an emergency. Then on the break, we are just as serious about no work conversation or tasks. That is when we relax, recharge, and connect with colleagues.”
He said when new employees start, they may feel the need to get back to work but the seasoned members of the team have realized that the disengagement was critical for consistent quality work.
“We all need to unplug, get out of the rabbit hole, rethink the project,” said Ruths. “That flow is one of the most important things we’ve discovered here. Working the same duration at the same time, you set yourself up mentally and biologically. It’s very easy to drop into the flow because you are doing the same thing each day.”
This article was originally written by Carlyn Chatfield on the Rice University Department of Computer Science website.