Our guest today is Taylor Brown, COO and Co-Founder of Fivetran.
Taylor is passionate about helping good humans build awesome products. He draws inspiration from his time as a liberal arts student at Amherst College, experience as a designer at North Social, and lifelong athletic endeavors. Most recently he has built Fivetran, a fully managed automated data integration provider, from an idea to a rapidly growing global business valued at more than $1.2 billion. He believes that magic happens when you can build a simple yet powerful product that is truly innovative and helps users solve a hard problem.
Taylor understands this is only possible with an amazing team and is privileged to work with the best in the business.
In This Conversation We Discuss:
- How the PITA factor been beneficial for feedback
- How to decide what metrics the team needs to keep track of and what market dashboards are set to maintain them
- How Fivetran was founded and funded
- What changes Fivetran went through as they were growing in their fundraising
- How to work with the board where there’s a balance for advice and for taking a risk
Connect with Taylor Brown: LinkedIn
Fivetran – https://fivetran.com
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Our guest is Taylor Brown, the COO and Cofounder of Fivetran. Taylor is passionate about helping good humans build awesome products. He draws inspiration from his time as a Liberal Arts student at Amherst College, Experiences Designer at North Social and a lifelong athletic endeavors. He has built Fivetran, a fully managed automated data integration provider from an idea to a rapidly growing global business valued at more than $1.2 billion.
He believes that magic happens when you can build a simple, yet powerful product that is truly innovative and helps users solve a hard problem. Taylor understands this is not only possible with an amazing team and is privileged to work with the best in the business. Taylor, welcome to the Second in Command Podcast.
Cameron, thanks for having me.
I appreciate it. Just put it in layman’s terms for us, what does Fivetran really do? Explain to a girl in a bar.
Fivetran is an automated data integration provider. What that actually means in layman’s terms is when you’re a company, a business, you’re leveraging all these different software tools, whether it’s for your ad systems, your marketing systems, your sales systems, payment systems, all these different tools are available to you.
The thing is, each of these tools is collecting a ton of data and a certain size that data becomes quite valuable to you. It’s valuable to you outside of each of those systems when it’s combined together. For example, you may send 10,000 emails a month and you want to know which of those emails actually converted into a payment. You have to have your email data, you have to have your payment data. What Fivetran does is we connect to all your disparate systems and we replicate that data into a centralized data warehouse, like a Snowflake or a BigQuery. There’s a fair amount of heavy lifting and automation and work that has to be done to get that data out. We do all that and then it’s in that central place. Our customers can then query directly against that data and make sense of their business from it.
Are you guys more of a consulting company than a SaaS company or is there a bit of the product in there as well? The product is there, but is the real work, the consulting side or the people side of the business?
It’s an amazing question. The way this is done traditionally was that pipeline was a custom pipeline. The tools that you leverage for that were generally some sort of workflow tool that you would have to set up and configure and the things break and everything else. You sort of on you or the consulting firm that you hired to do that.
Fivetran’s innovation is that we’re 100% product. We have zero services team. We do everything through an automation system and it’s all software. When you go in and you set up like AdWords to Big Query integration, every single one of our customers setting up the exact same integration, our system’s smart enough to go in and figure out what do you have that’s custom within there, move it over, load it to the warehouse, and then continue to keep it up-to-date. Anything changes in the source, we’re going to automatically change the warehouse for you. It’s all done through the system.
That’s huge. That’s what’s given you scale.
Yes, exactly. It’s standardized. If you go to one company and you’re head of data and you’re like, “I want to use this for all my advertising systems.” I’m going to like, “Pull it all in.” You’ve taken all the time to then build all these models and everything on top of it. You leave that company, go to a different company, you can set it up and you’re going to get all the same stuff. You’re like, “Cool, I know exactly how this works. I can just build on top of this again because it’s extremely standardized in that way.”
Don’t companies use the data in different ways or does that matter?
Absolutely. I think a lot of companies like to believe they use it in different ways. I think if you actually look at it, probably like 75% the same and 25% unique to that business from, again, I’m kind of guessing on this one. The thing that we replace or change from the previous generation of tools was that what we found is a lot of the folks who should have been spending time analyzing. They’re spending 50% of their time just getting the data out, just making sure that it’s there, auditing it. They’re only spending 10- 20% of the time actually analyzing it and not analyzing it, spending the time. That’s like the most important thing, I think, that the companies should be spending their time on.
Do you guys just say no more often than you say yes then? Do you tell these big companies, “No, it doesn’t do that, can’t do that or you don’t need that?” Or have you been able to build it all out because you’ve got so many customers that now it does it as well?
Early on, there were a lot of noes. It’s been more of the reframing for these customers because a lot of them are used to like, “I’m usually just building all this stuff myself and then loading it in.” A lot of times they would do what’s called ETL, Extract, Transform, and Load. You’re in the way, along the journey you’re transforming this data.
The reason for that is because the old warehouses that were on premise were not. They were constrained by the size of them or the amount of memory or power or whatever and now, the new warehouses are much larger. You can have infinite scale. The idea is that you just take everything, you move it over. We do a little bit of cleaning, but then you do a lot of your actual modeling logic within the warehouse itself.
Closer to the folks who know how to do all that stuff within SQL, within the analyst layer there. We’ve had to teach that over and over again like, “You don’t need to do this transformation, all this extra heavy lifting.” Because a lot of that transformation was honestly around trying to make your warehouse more performant.
Now, these cloud warehouses are ridiculously performance. 50% of the complexity just goes away. We just reframe the, “Here’s how to rethink about it.” Then the big question is, “Cool, cool, cool. You have 100 connections. I have 6,000 connections that I need. There are 40 or 50 different ones that you don’t currently have. How do we get those?” We have to build a roadmap to go build out these additional connections, but we do not have a single connection that’s unique to only one customer. This connection works for every customer.
Do you sell based on the number of connections as well? Is that like an additional fee?
We used to sell based on connections and there was a price for connection. We’ve shifted to just being priced on monthly active rows. Essentially, unique rows that get passed through our system each month.
What’s a row? Like a row of data?
Yes, if you look at Excel, if you have a table, each one of those is a row. If you’re moving to each one of those that gets passed through, unique. If you have one row that goes like 50 times in one month, rolling an accountant is one.
Do you guys have much churn in terms of customers or is it pretty low? I think that your customers would be pretty sticky once they’re in. They’re not going anywhere.
We’ve got relatively low churn compared to benchmarks. We’re in the less than 10% per year and even lower than that. I think some of the churn we’ve seen is we’ve shift to do a self-service model for the smaller companies in the last year. There are companies that come on and come off and come on and trying stuff out. It’s a little bit hard to understand and look at that super closely.
The larger customers, once you build infrastructure on top of it, so long as it’s reliable, so long as it’s delivering, it’s better than anything you can build internally. It’s better than anything and more reliable than anything you could buy before through the informatic is to the world. Because those are essentially tools where it’s, “Here’s a toolkit, go build what you need. If something breaks, call your own team.” We’re like, “We’ll promise you data delivery day in and day out, from point A to point B. If something breaks, it’s on us. We are going to go fix it. We have international team on 24/7 that’s basically sitting and watching your pipelines.”
Has the pain in the ass of the smaller customers been worth it for you?
I would say yes.
They call it the Peter Factor, is it?
Yes. We’ve only recently introduced the ability to come on, and they’re pleased to have a minimum of $10,000, $12,000. Going lower has actually helped the customers who are like, “I only want to try this for one thing.” We see it as more of like a try-before-you-buy. The other side of it is that there’s not much configuration. I think in a tool that’s highly configurable, you have a lot of smaller customers who come in, they don’t have the resources, set it up, they get frustrated, then they make a lot of noise.
Fivetran’s product is as simple as like you go in, authenticate your warehouse, authenticate whatever sources you want in a matter of clicks, and then that’s it. You let it go and we do everything else. We set it up in such a way in which you can’t configure it because we don’t want people to screw it up because then that ruins their ability to actually work and do the things that we’ve promised them.
Are you guys at a critical mass size now, where you don’t need to add people or add as many people? Can you double the size of the company but only add 10% more employees?
We’re not quite there, I think, that’s partially because we still have a lot of R&D that we’re doing. We’re innovating a ton right now, both in terms of new connectors as well as in terms of a couple new products that we’ll be releasing later this year 2021. On top of that, our go-to-market has spread globally a lot, and so there are a lot of areas that aren’t as efficient.
AMEA is not as efficient as the US. APAC is not quite as efficient as the US. As we’re building those out, everybody is not quite as efficient, but we are starting to slow down that. Every year, we get a little bit more efficient, so our revenue per head count continues to rise. I think, by the time we go public, we’ll be in a very good place in the next two to three years.
I was speaking to somebody, and I gave them four data points they need to start measuring in their growth. It was revenue per employee, gross margin per employee, profit per employee, and then salaries as a percentage of revenue. Do you track any numbers like that per efficiency, or are you worried about efficiency yet?
Yes, we talk about those. We look at Rule of 40. We look at CAC, and CAC by segment, CAC by region. We are looking at a bunch of those. We’ve set up a global scorecard. I think of it as like the gaslight for the vehicle. We’ve set up a scorecard of 10 or 12 metrics for the whole company. We have one for each function as well. It’s like, “Here are the key things we’re looking at. For marketing, it’s stage ones. It’s cost for stage ones, it’s cost for stage zeros.” It’s like, “How are we doing Ansys? Did you hit that number? Are you within the cost for that, that we were expecting?” Those just help to say, “You’re in the right realm here,” or “No, something is wildly off.” We’re looking at that every quarter and saying, “You’ve got nine are good and three are off. Let’s take a look at those three.”
You just said something that I wrote about in my first book, Double Double, big on dashboards, and I talked about it. The leadership team needs their one dashboard with 10 or 12 metrics. Then, each business area needs their own dashboard. Kind of like a car, like I don’t need to see all 10,000 data points that the computers tracking. I need to see the speed right in front of me and then the gas can just light up when I’m less than an eighth. How did you decide which metrics the leadership team would be looking at, and when did you start putting those dashboards in place?
We’ve had dashboards a long time. This last year 2020, we shifted to a consumption-based pricing model in February of last year 2020. We had our go-to-market dashboards, but we weren’t closely watching some of the cost metrics and things like that. Certain things tanked because there was this big shift, and I don’t think we were keeping a close eye on it.
As a result, it was like, “We need to sit down and really look at this.” It was a combination of our leadership team and a couple operations folks on my team and our finance head. We sat down and said, “What are the most important things for us to be looking at?” Checked with the board, then went back and then we proposed things. Then the leaders of each functional group came back and said, “No, I want this or no, I want that or I want this.”
Some of those things were like, “We can’t actually measure that. We don’t have the data.” It’s like a bit of a horse-trading thing. Then we end up with, “These are the things that we have.” These are not necessarily, I would say, operating metrics. We’re not using these to help drive performance per se. These are the things we’re expecting of you. If they drop below this, that’s a red light, but then we have a whole set of dashboards that are more operating metrics. Here’s the number our sales team needs to hit, or here’s the number that each of these functional areas needs to hit for marketing. Then they have to have it cascade down from there. Each of the leaders of those functional groups have built each of those out with our analytics team over the last few years as well.
Let’s go back to the beginning. You and a childhood friend started this together. Is that the story that I understand?
Basically, yes, a long-time family friend. George, my Cofounder, our CEO, he and I have a set of cabins up on this land up in Northern Wisconsin that’s been in each of our families and 10 other families collectively for a hundred years. Growing up, he’s from New York, I’m from Colorado, but we spent some time up there every summer together. Our parents knew each other and grandparents, and so on and so forth.
When we both moved to San Francisco around the same time, I was working for a startup company. He was working for a startup company. I think at some point we realized we both want to start our own company. I was just like, “This person is extremely smart. I’ve got a lot of trust in this person and I’ve known them for a long time.” I was very lucky that I felt we’re able to come to together and start this company.
You had the idea, was there an idea together? Did you go through a few different rounds of coming up with ideas? How did you start? How did you fund it?
We’re actually up at our cabins in Wisconsin, and George was like, “Things are a little dysfunctional where I am, and I would love to start my own company.” At that point, I was doing MBA program plus working at my previous startup. I was like, “Just leave and start your own thing.” He quit and spent a few months working on this idea, which is a Numerix platform like MATLAB and the cloud.
His whole thesis came from the time when he was at his PhD lab. He was helping a lot of the scientists who didn’t really know how to program to work with data. He was helping them learn how to program because he had an undergrad in Computer Science, and then he went to a biotech startup company after that. He was, again, helping all these other folks, all these other scientists worked with data.
His a-ha moment was, “There’s obviously a disconnect here. There are a lot of people who in science need to work data that don’t know how to, how can I help them with this?” His idea was, “Let’s take one of these numeric platforms like MATLAB or Mathematica, and let’s just put it into the cloud and let’s build the infrastructure around it so that folks can come in and just work with it.” That was his idea.
At the same time, I was working for a company. I was building applications for Facebook and whatever. I was doing a lot of design and I got some of the development. One of the challenges we had, which actually I hired an intern to help with getting all this data together around our customers and collating it and understanding, “Who should we charge more money?” For example, we had Usher using this $26 per month offering of ours and he should have been paying us $1,000 a month. We’re like, “How did Usher? This isn’t right.” I knew that we needed something like this.
George and I just started to join forces. We applied the Y Combinator, we got accepted by Y Combinator which was its own crazy story. I think they let us in partially just because they liked the combination of an engineer and a designer who knew each other very well. Paul Graham really liked the idea of MATLAB or Mathematica in the cloud. We got in with that and within about a month, I spent a lot of time just, I didn’t know anything about Numerix platform, I’m just calling everyone.
What I realized is the Numerix platform world was largely shifting too. People didn’t want to pay for it. There was like a $4 billion or $5 billion market cap industry. The people shifted saying, “I would rather just use free tools like Python or R, or whatever.” We decided, “Why don’t we shift our thinking to businesses? Why don’t we focus on helping analysts at businesses? Because we’re surrounded by all these businesses now within Silicon Valley. They probably need help with data, too.” That was the iteration that happened and we launched with big spreadsheets for big data. That was our initial launch and we raised a little bit of money.
We raised about $750,000 on a hope and a dream. Then we spent the next two years iterating on that idea of spreadsheets. We were looking at it as like 40% of analyst’s time was spent just getting data together. 10%, 15% of the time was spent actually analyzing it, and the last 30%, 40% was evangelizing and sharing it. We were like, “Let’s focus on the spreadsheet thing. I think we can make this better.” That led to just because we built this very performant spreadsheet with 200 million rows or whatever more, that didn’t make it easier to work with. It was like, “That doesn’t make it easier.”
Then we learned about pivot tables and then we started with some customers like, “This is a great spreadsheet, but then how do I get data into these?” We put it on top of Redshift. Redshift was a new data warehouse at the time. Then we’re like, “Cool.” People are like, “How do I get data to that?” Then we built some integrations, and we basically built a poor-man’s BI tool, and then we essentially ran out of money in around 2015.
We went out and were like, “Let’s go sell what we can.” What happened from that was that a couple folks that we knew in Silicon Valley came to us and said, “I already have my own Redshift. Your pivot table thing is cool, but I really need the integrations into the Redshift. I need to get my data into my Redshift.” We’re like, “I think we could do that. That makes sense. Will you pay us for it?” They’re like, “We’ll pay you a lot of money for it.” That was like the a-ha moment of, “We will do this.” Within about a week, we changed the whole company to then being like integrations for Redshift, and that’s basically the same product that we have today.
Crazy amount of iteration and brain power behind this. You couldn’t have done it without the Y Combinator and raising cash. You couldn’t have bootstrapped this thing. How much did you raise?
We initially raised about $750,000. That got us about 2 years with 3 people, and then we started to run out of money. Maybe we could probably not, like that time, that two years was really valuable because the two of us and our first hire, Mel is our CTO, it was a really good time for us to bond and learn how to work with each other and build that trust and understanding of the space.
Actually, fundraising was really hard when you just have an idea and you’re two people. I hated fundraising. A friend was like, “The best time to fundraise is when you can go in with your fingers up saying like, “I don’t need your money. Basically, let’s talk about partnership.” When we got our first customer, we decided, “Let’s not fundraise. Let’s just run on revenue.” We spent the next eighteen months running on revenue. I switched to doing all the sales and marketing and partnerships. We started hiring more engineers and we built out like that for the next 14 or 15 months. That was probably the most stressful time because we had to pay salaries. We had to hit a number every single month in order to pay salaries.
You had to run a real business.
Exactly, but as a result of it, we had a really good business and so then we raised some more capital. In 2017, we raised another $800,000 or so. We immediately then started a team in India. We were about 12 or 13 people. Started an office in India because we just knew that the type of work that we’re doing, this integration work was not the type of work that someone from AWS or GCP or Stanford or Harvard or Yale would want to do. We needed to find a group of folks who were interested in this and how can we make it interesting. We scaled from there.
How much have you raised to date? $1.5 million?
We have $163 million raised now. At some point after those tiers, we raised about $800,000. Then we raised another $1.2 million about a year later, and then a year later we raised $15,000, and then we raised $35,000, then we raised $100,000 this last year 2020.
How much equity have the two of you guys got now? Between the two of you?
I think it’s somewhere on 25% still, so decent. Because we had this first few years of raising, we didn’t dilute a whole lot.
I think that’s probably one of the smartest things you did, isn’t it?
For sure, absolutely.
There are probably hundreds of smart things, but like that, I think that’s… I used to coach the, well I didn’t coach them. I led the strategic planning for Hootsuite about eight years ago and I got Ryan and the leadership team at Hootsuite to drive towards profitability because that’s the only way you’re going to build a real business is to build a real business. You can’t just build a bus. At some point, you need to have revenue and gross margin and profitability. You guys doing that in early days would have given you some of the rigor that has allowed you to really scale today. What changed when you were doing the funding rounds? By the way, do you know a company called InfoTrust at all or a data analytics company?
I don’t know them. It’s a relatively large space, so there are a lot of folks in it.
Do the analytics companies use your tools?
Absolutely. A lot of the ones that we partner with are more of the general purpose analytics companies like Tableau or Looker or Sisense.
These guys do analytics for some of the big brands. I’ll ping them and see if they know you or if they should be introduced, but I used to coach them. I wrote 80 employees. They’re the number one company to work for in Cincinnati, but they just do analytics work for big brands. I’m curious whether this would be helpful for them.
One of the areas we’ve actually started building is an OEM offering for specifically that, and for a lot of the bigger brands and a lot of times they work with other companies. We’ve definitely started to grow that. I’d love an introduction.
I’ll ping them. I coached them for a couple years and then their COOs and the COO Alliance too. I’ll find out if they know you guys or should be introduced. What changed for you guys as a company, as you started to raise money and what were some of the lessons that you learned that maybe you would’ve done differently as you were raising the first couple rounds?
Early on, we were like, “Let’s just keep driving this,” trying to be a profitable company. Then we raised a little bit, we’re like, “Let’s see if we can make this efficient.” I think we had this weird belief that we’ve seen a lot of companies around this work. People just raised tons of money and were like, “The profits will come and we’ll figure it out.” They never did. We were always scared like, “Any amount of money we raised, we want to be able to make up for it and get back to profitability.” That was every round.
When we raised our A, it’s like, “We’re still at a place where we could pull back growth and we could get profitability.” At every round, it was like, “There’s an opportunity for us to continue to grow really fast and we should probably go hire more people. If we do, I’m sure we can actually get the revenue from it.” We got a little bit more confidence with taking on a little bit of cash, and then we took a little bit more and then we took a little bit more. I think it was really the last round that we felt like, “At this point, we are committed to going public fully.”
Now, it’s just about how do we have the right partners? How do we make sure we capitalize the business correctly? Not overdilute, not over-raise, and still drive the business to a place where also we can get back to profitability because we’re going to have to at some point especially, if we go towards public.
I’ve looked at other companies where they raise a ton of money, they get really bloated, they over hire and then they have to do this crazy swing to get back to public. They hire a bunch of people and there’s a bunch of access swung and culture goes to hell and it’s a bit tough. We’re really trying to be thoughtful about the path towards public from here.
One other thing that I think is interesting is when we raised our A, we had a number of other offers that came in much higher. We had a couple that were super high and we had a couple that were low and we had a couple in the middle. We really optimized for adding a human that could add to our board that would help us through that phase of our business. We added Ilya from Matrix Partners and he’s just a really great cultural fit for us at that time of the business and today.
We had one other earlier board member who we brought in through the seed who is a little bit frustrated like, “We could get a much higher valuation. What are we doing?” We said, “Look, we’re not on the treadmill, yet. We don’t really want to fully try and go and maximize value and put ourselves on this really high expectation. We want to raise capital and get the right partner so that we can make sure we’re getting the R&D part of our business in place and really getting the right foundation and another great person to just give us advice, a mentor.” That worked and the same thing actually happened.
The next one with ACZZ. There have always been people who have come in at higher valuations, but it’s like, “We really wanted a partner who knew enterprise super well.” We brought in Martin from ACZZ, again, super helpful. That whole ACZZ has been extremely helpful for us as a company with their operating team. I think every round, you have to think through, it’s more than just capital. You have to think through exactly what it is that you want in those. I think as we get to larger and larger sizes, it does become more about capital, about valuation, as well. Every single round we’ve had a very different strategy or tactic.
It’s interesting that you guys were aware of that, but I think it’s also interesting that you even explained it to some of your early board members, like, why we’re doing some of these things. Because the reality is opinions are like assholes. We’ve all got one and we can get that advice and opinions, but if it’s not directed in the vision of where you’re going or why we’re doing stuff, it can often just pull you off track. Sometimes they’re not doing it out of malice or if they’re not clear on the direction, they’re going to give you advice with the direction they think you’re going in. I assume that’s the Board of Directors now versus Advisory Board, or is it more Advisory?
We have a full Board of Directors now. We have a couple observers, and we have two independents and two VCs, and then George and I and a couple.
How do you work with the board where there’s a balance of getting some advice and there’s a balance of the compliance and regulatory and risk? Do you go the Board of Directors for advice and for strategic or do you go to them offline for that?
The board that we put together, our strategy was to try and put a bunch of very bright people who will help us on the board. Everyone that we have on the board was an operator at some point. Most of them were all CEOs before at some point. We optimized very heavily for that because we wanted to be able to use them as mentors and as folks to be advisors for us. Largely, we’ve done that. I would say we’re very transparent with everyone on our board about everything.
I’ve heard about companies that have problems and they hide it, and then they try and hide it and eventually it shows up, and it’s like this big problem. We’ve been maybe almost overly transparent about these things. We have a lot of trust, and we get a lot of feedback. It has been very helpful for us. I think at some point, once we go towards a public offering everything else, we’ll have to move more towards compliance and then politics groups in and there’s all that stuff that probably ensues from there.
We’ve tried to not have any of that be part of it. We even do like a board offsite every year and we went skiing two years ago before COVID. It was like, “It’s great to get to know humans.” Then they all have great networks. For me personally, the thing that has been valuable for that network is whenever I don’t know how to do something, it’s like, “Let me go talk to 3 or 4 subject matter experts who are the experts in that thing.” Then they’re like, “This is the progression you’re going to go through and here’s the things to do and here’s the things not to do and here’s the teams to talk to and whatever.” That’s been crazy valuable at this point for me.
When you talk to the people that have done it a hundred times before it’s just so simple. I love the board offsite idea, as well. I think that’s amazing because you actually do get to humanize everything. For you and George, considering you’ve been friends, I’m actually going to our family cottage. We’ve had this same place for not quite a hundred, but we’re about 60 years right now. I’m going back there with my kids in about 10 days. You and George childhood friends, I guess, it’s all been easy, this whole eight years, no arguments? Just everything’s been.
We are childhood friends. I was actually closer with his little brother. His little brother and I used to get all kinds of trouble, and he was a little bit more tame. He read more books and did more fishing. We were taking the golf cart and crashing it, speedboat, and stuff.
I wonder if the gas on the fire will work as good as last summer.
The last few years have been amazing. I think early on, that first two years really get to know each other and I learned a ton from him and I continued to learn a ton from him, especially around the technology pieces of it. Then I can push a little bit on the operating pieces. It’s been great. I think naturally I really like to do a lot of the operating stuff. He really likes to do a lot of the deep thinking, product visionary pieces and he’s extremely good at it.
We have a natural yin and yang, but I also think we look and pick different things and we’re just always a little bit in each other’s business and it’s okay. It works for each other. There have certainly been times when we’ve argued over stuff, but an argument doesn’t go past. It’s not like, “F*** you for this.” There are no hard feelings felt from that. That’s been something for me that’s been really great because we just have such a deep trust in each other.
When you’re debating for the growth of the organization, you’re not fighting with each other because you don’t like each other. Have you had disagreements or debates around stuff in front of the team or do you try to keep those debates as the CEO and COO separate from the team? Maybe not so much the leadership team, like the rest of the employees.
I don’t know that we have a strong conflict meeting culture. I think we’d have okay debates in our means. We’re not like dead out, like everyone’s yelling sort of thing. There’s certainly been times when George and I have been in conflict in conversations with folks who are outside the leadership team who felt like there’s two titans throwing rocks at each other. We’re like, “Let’s pause this and talk about it later.”
The funny thing is in these conversations it seems like really intense and everyone is like, “The two founders are yelling at each other.” Then we’re like, “We got a call. We’re laughing about it.” We’re like, “I still don’t agree with you on this point, but whatever.” We just keep going. We talk about something else. It’s created some friction for sure with the organization.
How have you grown as a COO? Eight years in building this company and literally from the startup co-founder to today with 570ish employees. How have you had to evolve and where have you evolved as a leader?
There are many different areas. Early on, I was like, “I had to learn how to build.” I actually learned how to code. I coded all the front end. I got really deep into that. Then, I switched to becoming a sales leader and just doing all the sales. I did all that and then it was like marketing and I started hiring and then it became this thing where I’d be like, “We need this. Let me go learn how to do it.” Then like, “Let me hire someone to do it,” then grow from there.
In reflecting, I think there are a lot of founders who realize they don’t like the operating piece that much. At some point they’re like, “I’m out. I’m either going to leave. I’m going to go start something else because that’s what’s exciting to me or whatever.” I think I’ve been fortunate that I actually really like the operating piece. The things that I enjoy are, I like competition, I like people, and I like building stuff. I was actually a Sculpture Major in college and I had played a lot of sports. It was the combination of sports and sculpture. Were like, “Great.” Now it’s like, “I’m building not just the product, but I get to help build teams or we’re building structures or processes or I’m helping build careers and also with people and we’re all competing altogether like one big team.” I get a lot of that.
Your parents must have been shaking their heads and going, “Where did we f*** up when our kids did a Sculpture Major in college with, I imagine, the other four people who chose that same major in the entire planet?”
It was just me. It was a fine arts buzz, the only one who did a thesis and sculpture. Well, it’s kind of funny because my mom’s actually an artist, but she was always like, “I can make much money doing this.” My dad’s a lawyer. He was like, “Do whatever you want.” I think I realized over time that art wasn’t competitive enough, nor did it deal with people enough for me to be a long-term career. Then I looked at architecture and that wasn’t quite right. I looked at industrial design and that wasn’t quite right. Then I got a text somehow and I was like, “This is freaking amazing. How did I not know about this earlier?”
You are building something. Have you ever read the book, The Agony and The Ecstasy?
I have not.
Read it. It’s about Michelangelo. It’s the story of Michelangelo and all of the sculptures that he did and the paintings and the design. Him and Leonardo going into hospitals and stealing bodies to understand the human body so he could carve the Michelangelo and the Pietà. When I toured Italy many years ago, I went and saw as many of his sculptures as I could see after reading this book. It’s a fantastic story.
I will definitely read it. In college, I did study a bunch of Michelangelo. He’s such an interesting human, but very amazing.
I had no idea he was a sculpture. I thought he was just a painter. I found out in the book, I’ll do this and we’ll go back to the interview here, but, Leonardo and Michelangelo competed to see who was going to paint the Sistine Chapel. Leonardo painted one wall of the Sistine Chapel, Michaelangelo painted the other as a competition. Leonardo used a heater to try to get his glaze to seal faster and he burned the bottom of his painting, which is why he lost out to Michaelangelo. That’s how Michaelangelo painted. I’m like, “That’s so cool.” I don’t know this shit.
Speaking of amazing.
Also, so stupid. They had a contest to see who’s going to win. Really? Anyway, let’s go back to the 22-year-old Taylor who’s graduating from college. He’s going to start off on his career. What advice would you give yourself back then?
That was a tough time for me because I was like, I don’t know if I should go do art and live in New York. I don’t know, otherwise I should maybe go try and do industrial design. I think for me, the advice that I got at that point from my college football professor was just like, “Go as hard as you can. Go a million miles an hour, just pick something. Even if you don’t know if it’s perfect, just go a million miles an hour at it until you either like it or you don’t. Then you go a million miles to something else.”
PG basically said the same thing when we started Fivetran. He was just like, “Go a million miles an hour until it’s the wrong thing, and then go a million miles an hour at something else.” I think that was the thing that eventually got with you. I decided, “I’m just going to take a bunch of classes in Industrial Design, I’m going to go a million miles an hour at that. At night I’m going to start learning how to build websites because that seems like I could make money doing that.”
Then someone called me, a friend from college, “Why don’t you come join my startup that we just started. Here’s a one-way ticket to fly out to San Francisco.” I was like, “This is awesome. This sounds great.” This whole thing is working. When I got there, I was like, “This is awesome.” The million miles an hour and I just haven’t really looked back. I definitely got lucky.
There are a lot of folks that I’ve talked to. I’ve talked to a lot of folks in college in the last year or two because they asked like, “How did you get here?” I think I got lucky but I also, I picked something and went hard at it and then picked something that I thought for my life I would be excited about. That’s the thing that I think a lot of people don’t always think about. When I’m 50, if I’m still doing this thing, am I going to be happy? It’s like, “Pick that, then go hard at it and you’ll find out very quickly whether you do or not.”
I love that. By the way, one of my kids is twenty, and he’s in that stage of trying to figure it out. I told him that, but not really in the same wording. I’m going to go back to him and say, “Just pick it and run with it, and go a million miles an hour. If it works, great. If it doesn’t, who cares? Just pick the next thing. Go. The key is to drive hard and have fun while you’re doing it. Then pick something else to drive hard on.” Taylor Brown, the COO from Fivetran, I really appreciate the time today. Thanks for sharing with us on the Second in Command Podcast.
Cameron, thanks so much for having me.
I appreciate it.