December 14, 2016

Catalytic’s Sacane Chose Charleston Using Data, Spreadsheet

Ashley Fletcher Frampton  /  Charleston Digital News
Catalytic CEO, Scott SacaneCatalytic CEO, Scott Sacane
Catalytic CEO, Scott SacaneCatalytic CEO, Scott Sacane
Catalytic CEO, Scott SacaneCatalytic CEO, Scott Sacane
Catalytic CEO, Scott SacaneCatalytic CEO, Scott Sacane

The Charleston Digital Corridor's Leadership Profile series is focused on the individuals who are driving Charleston tech scene forward. This series is brought to you with support from Charleston Southern University.

Scott Sacane is co-founder and CEO of Catalytic Data Science, a 10-person company based in Charleston that integrates life sciences data and research onto a platform accessible to other life scientists. Sacane lives in Connecticut. 

Where did you grow up? What was life like and your memories from there?

New Jersey, the Jersey shore. It was an interesting town to grow up in because it was right on the coast, so it was very easy to get to and from the shore. Life for me in the 70s was playing sports and going to the beach. It was pretty easy going. Mostly a blue-collar community.

How did your company come to be in Charleston?

My co-founder and I – he's an evolutionary biologist, I'm a molecular biologist – we tend to be very data driven. Our whole lives are governed by the scientific method, from freshman year in college on. And so when we were looking for a location, we just did what you would think: We created an Excel spreadsheet and made a list of characteristics that we thought were attractive to locate the company. They were cost of living, competition for engineering talent, ability to relocate, ability to recruit locally, those kinds of things.

What we initially thought was we were going to be in San Francisco or in Boston, because that's where our customers are. What we ended up realizing pretty quickly was the cost of living in the major tech hubs was pretty significant. The competition for engineering talent for startups was pretty stiff. So, we started to look around to some of the second-tier cities like Austin or Boulder, Colorado, Portland, and Seattle. And Charleston was in that list.

As we collected all of the data on the characteristics we thought were important, we'd have a composite ranking that came out at the bottom of the spreadsheet. Charleston continued to come out at the top of the list. It was a real methodical, quantitative approach to trying to find the right location for building a company and building an engineering team.

In your own words, what does your company do?

It's a company that's sole mission is to aggregate all of the information resources and analytics that a life scientist would use in their daily workflows and have them all integrated into one platform so that they can easily move from data source to data source, from analytic to analytic, without having six or seven disparate tools.

What inspired you to start your current business?

As far back as 1988, when I started my career as a scientist, I had been struggling with this exact same problem that Catalytic is trying to solve. Which is, as a scientist there is often a lot of information that's available, whether it's in unstructured text or it's in actual structured data sets, that you can use to bring to bear on the decision you are trying to make or the experiment you are trying to conduct or the task that you are trying to complete. But that information is really, really hard to locate, and it's scattered in disparate repositories across the globe. And it's rarely in a form that can be used at scale and in a computable format that will actually fit the way scientists work. So it gets very difficult to quickly learn from others who have done similar things to you.

In one of my first jobs, I was assigned with cloning a particular gene and then figuring out which protein was being expressed by that gene. That's super easy to do today, but back in the 80s it was kind of hard. This gene belonged to a class, a family of a larger set of genes. I knew those genes had been cloned. If I could have just easily found the research and the work that others had done on those genes, it would have dramatically accelerated my ability to clone that gene. I would have just used the same process, the same protocols and everything that they used. But it was really hard to locate, it was really difficult to aggregate. And that process is still going on today. It's just massively amplified.

I started Catalytic to solve a problem that I had for 20 years and I know all of my colleagues have had for 20 years, which is using information at scale, and having it available and usable at the time you are making the decision. That will hopefully transform the speed and productivity and accuracy of decision-making in life sciences.

What was your first job, or most memorable early job? What did you learn from it?

My first job was washing dishes at a diner on the Jersey shore. And it was memorable because I did not want to ever do it again. When that summer was over, I thought, "You know what, this school thing is probably important and I should probably pay attention." It was a tough job, and the only reason I stuck with it was because I wanted a moped, and I needed like $500 to buy my moped so I could get around the Jersey shore.

Did you have an entrepreneurial drive early on, or did you acquire it through experiences?

It developed. I definitely wasn't sitting around in high school thinking about starting companies, or even in college. I am a molecular biology major.

Where it really started to take root was my first job. I was the 11th or 12th employee. That company grew to 125 and then it went public, and then it was acquired by a larger company. I was part of the corporate formation process, from the scientific side, and part of the growth of the company, and it was just a really exciting experience. It wasn't something that I had ever expected as a scientist that I would experience. But this was a really cool, really interesting experience, and that's what set the entrepreneurial wheels turning.

How would you describe your organization's culture?

Evolving. Everybody at an individual level and a group level needs to commit to the decision-making process. Once decisions are made, everybody's got to commit to accountability of meeting those decisions, meeting the timelines.

We are single-mindedly focused on the mission, which is improving the speed and efficiency and productivity of the life sciences research process. That's kind of our guiding North Star. We don't get up every day and think long and hard about revenues or earnings. We think long and hard about aligning all of our activities and all of our work around how do you make life sciences research better for the people who are doing it through the deployment of IT.

What is your management style? Why is that your approach? Has it changed over time?

My management style is probably unintentional. I don't think a lot about it. But I have learned lessons along the way – I've never had a bad boss. Every boss I've ever worked for has been amazing. Just amazing mentors. What they all had in common was they tried to hire the very smartest people they could find and then they enabled those people to do their jobs. They didn't try to micromanage them. I try to do the same thing. I try to find the most talented people possible and just evangelize for them, try to knock down any barriers.

What lessons have you learned from good bosses? Bad bosses?

I just have not had a bad one. One of the things I have learned from the good bosses – the amount of time they would spend with me and the amount of mentoring that they provided, even though they were super busy people that had accomplished a lot in their career, meant a lot to me. I try to do the same thing.

What's the hardest or most important lesson you've learned in business?

If you're too early with an idea, you are wrong. You can actually have exceptionally important ideas that can create a lot of value, but if you're just too early with that idea, executing on it becomes impossible. So timing matters. And then executing matters.

What's the biggest misconception about being an entrepreneur?

The misconception is, if I have an idea and I make a PowerPoint, I can go raise money and I can be my own boss and I can have my own company. It does not work like that. It's always about grinding it out and being able to deal with a lot of no's and a lot of doors closed in your face.

Do you have a routine that's important to your day?

The only thing that I try to do is I'll try to get in a workout around 2 o'clock in the afternoon. I'm somewhat early to work. I take my daughter to school. I have a 16-year-old who is still in Connecticut. By the time I hit the office, it's like 7:30, 7:45, and I'll work all the way up to about 2 o'clock and try to get a workout in. But I don't have a super structured day. What I've found is when you're at a startup and it's still early, the day changes every single day, so it's hard to have much of a routine.

What obstacles have you faced building your business? How have you overcome them?

A lot of the traditional obstacles. The biggest for me is always recruiting. Finding the great engineers and the great employees that are going to enable the vision. It's always tough to map out a specific recruitment process that fits the company. Overcoming it is a long-term process. Just a lot of grinding and consistency on trying to see more and more candidates and have them move through the pipeline. Then once you have the team, getting the culture right is typically a challenge.

With a background in biology, how do you build an engineering team?

Biologists are not coders, and they don't want to be. If they did, they would have gone to school to do coding. And coders are not biologists, and if they wanted to be, they would have become biologists. They are both really, really smart groups of people, but they are completely incompatible in their thought processes. So they don't talk to each other.

Biologists know that they want software to do the following five things, but they can't make it. Software engineers are like, "Well, I can just make this software that biologists would want to use." But by the time the biologists see it, they are like, "What is this? I can't even use it. It's awful." So, having domain expertise in the life sciences living under the same roof with professional software developers is the only way to get this right.

To this day, I still struggle with understanding what coders do for a living and the terminology that they use and how they think about things. The way to overcome it is, in our case, finding other senior tech leadership to bring into the company that has been around long enough that they can communicate with me in a particular way, and then they can communicate to the engineering team. Because if it was me running the engineering team, it would be a disaster.

What do you look for in the people you hire?

Technical competency is probably 25 percent of what we look for. What we are far more interested in is engineers that are really motivated by the mission of trying to change the pace and the efficiency and the productivity of life sciences research. Because if they are not super passionate about the problem, then it becomes hard to stay motivated at work and fight through all the challenges that you are going to inevitably fight through in a startup. And then we want a group of people that have behavior characteristics that fit as a team.

What is your biggest pet peeve in business or amongst colleagues?

The overuse of jargon is one. And celebrating non-events.

What advice would you give aspiring entrepreneurs?

Fall in love with the problem, not the solution, because the solution is always going to change. If you are really passionate about solving an important problem and you are myopically focused on that for very long periods of time, you will be successful.

What advice would you give new graduates seeking to work in the tech industry?

Think long and hard about your career. There is definitely always going to be the Mark Zuckerberg or Bill Gates or the story of the college dropout who actually makes it big, but that is so rare. Most startups fail.

So if you are a young computer science or equivalent graduate and you want to be an entrepreneur, you want to join a startup, do it with the mindset of there's a 100 percent probability that it will fail. Then have a career path in the eventual realization of that failure.

If you're not ready for that, then maybe the best thing to do would be to go to an established company, get some experience with systems that actually work, with mentors that are smart, do a few years, and then go take your risk.

What do you see as the future of your company?

Hopefully it's going to end up being the platform that dramatically changes the way that life scientists use information to inform their decision-making.

What one person has been the biggest influence on your business life? And why?

The biggest influence start to finish has been my dad. He's an electrical engineer. That methodical thought process – how to deconstruct a problem and then reconstruct a solution and think through critically how you can problem solve – I've carried with me.

The other one – I've never met him, but every time I hear Jeff Bezos, Amazon.com founder and CEO, speak, he just makes a lot of sense to me. The way he thinks about what you want to build a business around. Oftentimes he gets asked the question, "Where is online commerce going to be five years from now and how do you build a business around where it's going to be?" He always says, "That's the wrong question. You should be asking what won't change, because you can build businesses around things that won't change."

Are you a Mac or a PC? iPhone or Android?

Mac all day. Mac, iPhone. As scientists, even from college, we were Apple IIe users in the lab.

What is your usual Starbucks order?

I'm just a venti dark roast.

Outside of work what keeps you busy?

For a really long time, and it's winding down now, it was my kids. All of their activities, and I coached all of their teams growing up. Fly fishing and skiing now are the things that, if I'm not working, I'll be doing.

What has it been like building your technical team in Charleston?

It's been good. We were a little bit worried about that when we selected this city. But we felt like, inevitably if the company grows, it's going to have to be a mix of local talent and talent from the outside that's willing to relocate to Charleston. We've been really happy with the conversations and the actual relocations that we've had, with how easy it is to get good engineers to come here. If they believe in the mission, then Charleston is a big selling point. They love coming here.

Do you see any challenges recruiting tech talent to Charleston?

There are challenges for sure. The challenges tend to be more from the perspective of the specific individual. If there is an individual who is either single or they don't have kids, who is living in San Francisco or New York or Boston – that isn't terribly challenging. Where you tend to get a recruiting challenge is when people have to relocate families. Then the question becomes, well, Charleston is a great place, but if we move to Charleston and this startup doesn't work out, it's not like San Francisco where there's thousands of companies and you can probably get a job by lunch. That challenge is a real challenge, but it'll get better with the more successes that occur in Charleston.

What are your thoughts on how Charleston's technical landscape has grown?

I think it's really encouraging. I haven't spent a whole lot of time really diving into what type of corporate formation is happening here and how the funding is coming together, which are two critical components. We are financed by investors in San Francisco and New York, so we don't have any local investors. But just being around FS1 and FS2, there are some pretty interesting companies, some pretty interesting people. It looks like it's getting to that critical mass where we'll start to get some acceleration in corporate formation.