Bobby Pinero is the CEO and Co-Founder of Equals, a next-generation spreadsheet. He has worked in Finance, Analytics, and Data generally for the last few years. Previously he was the head of Finance and early employee number 8 at Intercom.
Equals is hiring across Engineering, Design, Growth, and an Executive Assistant. Reach out to Bobby if you are interested!
Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe.
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Here are the highlights from my conversation with Bobby:
St. Albans was incredibly formative for me. I was insanely fortunate to go there. To this day, it is probably by far the best academic experience and environment I was in - even though I went to Stanford for college after that. I learned 100x more at St. Albans than at Stanford, which speaks to what an incredible academic place it was.
At the same time, St. Albans was a strange place to spend such formative years. I never fully fit in there. The type of kids who went there came from the top and wealthiest families in the country, such as politicians and lobbyists. We used to have car shows in the parking lot at the school, where parents would bring their cars in and show them off. Every year, there is a tradition at St. Albans where parents and students would open their homes to the public. The students would have to show them off and give tours of the houses. It was pretty insane.
I did not come from any of that. I commuted an hour each way to get to St. Albans on the metro. I came from a squarely middle-class family. My mom was an accountant, and my dad worked for the government. I was not wearing Burberry ties to school like many other students. As a result, I always felt like an outsider.
Going to a school like that gave me a huge chip on my shoulder. Being in that type of environment made me want to prove myself. It gave me a hunger and a desire to achieve things and be successful. Whether that is healthy or not, it was undoubtedly formative.
I met incredible people at Stanford. Some of my closest friends to this day came from Stanford. Whether I like it or not, having a stamp of Stanford on my resume was insanely valuable. However, Stanford is academically meh for me personally. It is probably more on me than on Stanford. I probably could have done more to get the most out of that experience. But that also is a reflection of where I was in my own life. I did not want to be in school. My philosophy was that: I never wanted to go back to school. I was ready to get going and do things in the real world. I was so over being in class, doing problem sets, and taking tests that led to nothing. It just all felt so impractical and pointless.
But to Stanford's credit, the most important thing it did for me was a class called "Engineering Entrepreneurship." When I was there, it was taught by a guy named Steve Blank. Over 13 weeks, students had to start a company and pitch it to real venture capitalists in the last week. I loved it. I was really in my element and did well in the class. The class opened my eyes to how much I would love to start my own company someday. After I left Stanford, the class was still bouncing around my head all the time. In that way, it sparked something in me.
My main lesson from IBM was that I never wanted to work for a 400,000-person company again. I felt so small, insignificant, and powerless. For me, the draw towards startups and young companies is that I get to do so much more and see the impact of my work. But IBM was a great place to start my career and learn how to be a professional. There are spaces in these big companies to learn the basics: how to write an email, create a presentation, or use Excel. At IBM, I met the person who ultimately introduced me to Intercom, which was one of the most meaningful steps in my career. The idea for Equals was seated or sparked by some of the tools I used at IBM. In many ways, that experience shaped my career onwards.
Inflection was my first step into the startup world. It was a 150-person company when I joined. I learned the basics of how web companies work there. I learned how to write SQL, which was incredibly important to me. I learned how to measure a SaaS business and metrics like retention, LTV, and conversion rates. In many ways, I would not have succeeded in my role at Intercom without that experience from Inflection.
The way I approached my career with these two roles has been getting closer and closer to that engineering entrepreneurship class - like going to smaller companies and eventually starting my own thing.
Intercom specifically called to me because I was not looking to leave the role at Inflection, but a friend of mine said they were looking for somebody to run finance. When I learned more about the company, a few things stood out to me:
From there on, I decided to make the leap. My parents and other folks told me: "Hey Bobby, isn't it a bit crazy to join such an early-stage company? What if it does not work out? This is pretty risky." For me, that just never even crossed my mind. I saw it as zero risk. Either this works, and I can take a career leap. If it does not work, I will also learn a lot and make all sorts of connections to find another opportunity. I encourage folks to make that leap and join something early because you learn so much.
I gave this talk six years ago, so it was more insightful back then than it is now. But the main message of the talk was: The biggest mistake I made at Intercom regarding my analytics journey was not hiring a data engineer early enough. Today, that could be a data engineer, an analytics engineer, or someone who can play both roles. But my background before Intercom was primarily in finance. I was not a data person. Especially 6 or 7 years ago, there were not all of these modern data tools that there are today. There was not much conversation about how to build a data warehouse, how to transform data, how to consolidate at all, how to plug the data into different tools, and how to make the data operational within the company. I totally did not know how to do that.
We were too late hiring a data engineer, making it a lot more painful. I wish we had done it much sooner. I had hacky ways to hack around that myself with Python scripts and my own little databases that I spot up and maintain for Intercom. But the main message was that you should build a data infrastructure as soon as possible. It is a little bit more well-understood today, but it 100% still holds for any scaling startup.
The analytics journey went through many different stages at Intercom. We centralize the team and then decentralize them later. Especially in the beginning of Intercom, I was a big proponent of combining finance and analytics teams. There was just so much overlap between what those two teams needed to do in the early phase of the startup journey.
Many folks think about finance as the team putting the budget in place, building a plan and headcount, doing accounts payable and receivable, etc. But that is different from strategic finance at an early-stage company. Most of those tasks can be outsourced, especially accounting. Finance at an early-stage company is about unpacking the business. It is about understanding: How does ARR come to be? What are all the levers? What happens from the time somebody first visits your website all the way down to being a power user? What steps do they take, and how can you maximize those things?
Finance needs to be involved in that conversation and helps unpack the analytics. The more those two teams overlap, the more powerful it is if they are together. As you get to bigger scales, there are different arguments in which you might need more specialized teams. Maybe the analytics team needs to be decentralized and sit next to the teams they support. But it was super valuable to Intercom to have those two teams together from the get-go.
There is no one-size-fits-all metric that a startup should measure at any particular stage. There are different types of businesses: SaaS, e-commerce, marketplace, social media, Web3, etc. Each of them has its own set of metrics. Every business is unique in its strategy, opinion about the world, and stories. Force-fitting metrics and benchmarks to companies can be a trap. Investors obviously love to do this because their whole job is to look from the outside in, compare companies, and try to find the winners. They try to benchmark and put where you are relative to others. But it is the role of a great finance, analytics, or data person to tell a company's unique story as compelling as possible, so I try not to dictate which metrics folks should use.
The role of finance, analytics, and data people is to explain how the business works. That comes from how people get value from the product. Some folks do not like talking about revenue as much. They like other North Star metrics. But I like revenue. I like unpacking what drives revenue because revenue is the actual enumeration of what value people get from your product. Our role is to unpack and dissect where that revenue and value come from.
At Intercom, everything was about net retention, which is an indicator of the lifetime value of a customer or a cohort. If you understand how to acquire customers and continue to drive the lifetime value of those customers, then you can make really insightful decisions about how to prioritize across your business. One of the most impactful analyses we did was to drive an understanding by customer segments - from the tiny startups to the mid-size startups to the enterprises. What was their net retention? What was the lifetime value of those customers? Was each segment growing? Which segment did we want to invest heavily in? That is the magic of a SaaS business.
Equals is a tool I wish I had had as an analyst for the past decade. The seed idea for Equals was planted during my time at IBM. We had this tool called Essbase, an Oracle product that plugs into Excel that automatically connects to a database. It is structured as an OLAP cube. It was magic. You could pull any data from the database directly into Excel. It made my job so easy. It also made it easy to know and verify how others have built their analyses. At IBM, we had probably 100 engineers building and maintaining Essbase.
When I left IBM and joined Inflection/Intercom, we obviously did not have that. I learned how to write SQL and Python. I tried every BI tool on the planet (Mode, Tableau, Periscope, Superset, Metabase, etc.), yet none fit the way I knew and wanted to work. That is because I wanted to be in a spreadsheet. There is something really powerful about how a spreadsheet lets you work with data. It is this canvas where you can touch and feel data, move it around, and build compounding formulas without even knowing it.
As I was leaving Intercom, I looked at what everybody else was building in the market. Folks kept trying to take me out of the spreadsheet - whether a BI tool, a dashboarding tool, a notebook, or a low-code/no-code spreadsheet replacement. I was honestly tired of it. That is where the idea for Equals came from: Can we build a modern spreadsheet to get the modern analysis done? Today's equivalent to those 100 Essbase data admins and engineers are all the analytics engineers and data engineers who are building these SQL data warehouses with robust transformations.
The story behind actually founding it is very serendipitous. While wrapping up my time at Intercom, I was thinking about what to do next. Obviously, a big part of me wanted to start a company and keep getting closer to the point of origination. I have kept a list for a while of different ideas that I had, and Equals was one of them. I was actually in the process of talking to another company and joining them as the Head of Finance, doing the same thing I had done at Intercom. As fate would have it and the universe would make it work, I got to the very final stage of that process. They did a backchannel reference on me and ended up calling my cofounder-to-be Ben. We worked together at Intercom in the early days, but I had not talked to Ben for a year or two. When he got that backchannel reference, he reached out to catch up. It happened that he was experimenting with something new in the spreadsheet-type space called Equals. It was a different concept where we ultimately landed, but we just started talking, and the whole idea of Equals came out of us. It clicked, and we were off to the races.
Ben is probably in the top 1% of product people on the planet. He had a strong product mind when we reconnected and started working through the idea. He is the best partner I could have imagined building a company with. The decision became easier because we have worked together: He was Intercom's first employee and was there when I joined. We worked very closely together and helped take Intercom from $1M to $50M in ARR in less than three years. I was doing analyses, and he was building different funnel flows in the product. We knew we could work really well together.
After leaving Intercom, Ben started his own company. That experience had just been insanely invaluable for the Equals' journey. We were able to learn from things they did well and mistakes they made in that experience. Ben and I talked about that all the time, and he has just been an incredible partner to have as we build Equals - particularly for me as a first-time co-founder.
There are different pulls toward the spreadsheet. One is that it is fully customizable. I describe it as a canvas on which you can do almost anything. In fact, you can go down a rabbit hole of finding all sorts of wild things that people do with spreadsheets beyond your imagination. The big appeal of the spreadsheet is that it is infinitely flexible to match business needs. In that way, I am always drawn back to the spreadsheet because I can solve any modeling problems or questions in it.
Then there is also the inertia: Why do we always end up back in the spreadsheet? It is because people have been trained in using spreadsheets. The vast majority of executive folks, who would not even call themselves analysts, are comfortable in this environment. So there is just inertia around spreadsheets that will not go anywhere.
There has been a lot of unbundling of the spreadsheet by building different vertical uses cases:
Yet the foundations of how companies do analysis and the best practices of how to collaborate have changed over the last decade. Equals is our attempt at building that third-generation spreadsheet, which incorporates everything we have learned over the last decade. Equals is unbelievably simple to describe and impossibly obvious of a product.
The spreadsheet is the fundamental missing piece of the modern data stack. We can just talk about the consumption layer of the data stack because the stack goes pretty deep. Even on the front end of the stack, there has been an explosion of new tools.
The vast majority of analysis still happens in spreadsheets. I do not mean this flippantly, but one of the biggest reflections from my time at Intercom is that every meaningful business decision we made was out of a spreadsheet.
Think about all the weird workflows that exist in most companies: You have finance, RevOps, accountants, growth marketers, salespeople, functional analysts, and all sorts of people pinging a data team to write them a query so that they log into Tableau to download a CSV in order to get the latest data into their spreadsheets. But they then find out that the Tableau dashboard has changed, so they cannot get that report they once were able to get. You just have innumerable spreadsheets flying around a company with rough data in them. People will ask: Where did you pull that data? How did they pull it? Is it right? How do you reproduce it? There are all these broken workflows around the fact that the most important tool (aka the spreadsheet) for analysis is completely disconnected from the data stack.
Our grand vision at Equals is to meet folks in the way they like working with the powerful paradigm of a spreadsheet. Equals is the tool that gives the vast majority of people access to the data stack.
Hiring is insanely hard for a startup. The thing that Ben and I look for the most when talking to folks is genuine excitement, curiosity, and passion for what we are building. We have been in a position where we were going after an engineer who was choosing between five different startups and us. They were choosing based on compensation and a few other things. That is not to say that we do not put together strong offers in front of people. But we look for folks who are fired up and excited about what we are building, understand and resonate with our story, and choose to work on this almost above anything else. It is particularly important for us because what we are building is really difficult. Building a spreadsheet in the browser is not an easy thing.
A practical lesson I learned from hiring at our current stage is that I just have stopped talking to folks at big companies (Facebook, Google, Uber, etc.) No doubt there are many great people there. Many of them say they want to join a startup. But I found that a startup for them usually means a 400-person company, like a Series-B, C, or D company, not a 10-person scrappy startup. I have wasted many cycles trying to get someone from those big companies to join us at five people and only to have them accept an opportunity at a Series B, 400-person startup.
Ben and I talked a lot about our culture. When we started Equals, the opportunity in front of Equals was as big of a business opportunity as it exists on the planet. We are rebuilding the next generation of a fundamental building block for every single company. What we are going after is huge. We want folks who are excited and motivated by that. We ask folks to enjoy their work, work hard, and take the opportunity seriously.
Before Ben and I wrote a single line of code, I was out talking to hundreds of folks like me and trying to understand: Do they have the same problem as I do? Do they share the same worldview as I do? A big part of this is just hustling. It is getting out into the world and talking to people. Some will say no. Some will have a different worldview from you. It is just putting your nose down and doing the hard work. From those customer discovery calls, I started to see who was excited, who got a problem, and who would totally use the product. Then I pulled those folks into design conversations and started building/iterating the product for them.
Our ideal users have wide-ranging backgrounds: finance, RevOps, accounting, growth marketing, digital marketing, etc. Users and customers of Equals are in diverse sectors, from consulting to weather patterns to mechanical engineering. The use cases are countless, which is exciting when you start to pair a data warehouse and a spreadsheet together.
One of the biggest mistakes I made in hiring my team at Intercom is that: More people do not mean more output. More people, in some cases, can mean more work - especially when these folks are more junior than you.
The other lesson I will offer here is that finance folks have a bias to be frugal. Finance people want to spend less money and have less headcount. At Intercom, I died on the hill trying to show how lean and efficiently I run my department. I would save the company so much money. Guess what? Nobody cared except for finance. We fell behind as a team. We were swamped. The team was burned out. It was not until we made a concerted effort to go beyond that again. So the big lesson here is to avoid being a superhero and running the leanest team in the company.
I have one strategy that helped me in my finance career, which I call the overheard list. The idea is simple:
That was my strategy and mentality as somebody wanting to have an impact.
The foundation upon which I built Equals came from all these things that I have learned in my journey and all the experiences that I have had. My high-level takeaway is to continue trusting the process that you are on and follow things that excite you. You may have some concept of where you want to be at the end, but the journey is not necessarily linear.
I am way more effective as a founder now as somebody who has been working for ten years. I learned how to prioritize, recruit, interview, manage, etc. These are essential things I needed to learn before starting a company. For some people, it might be a different path. But for me, those were critical lessons and steps along the journey.
In terms of mindset, it is more of: How do I keep building on the skills I have had? How do I keep learning and growing? How do I continue to push myself to be better? I have been doing that all my career and will continue to do so.