Datacast Episode 105: Building The Next-Generation Spreadsheet, Being A Curious Analyst, and Engineering Entrepreneurship with Bobby Pinero

The 105th episode of Datacast is my conversation with Bobby Pinero, the CEO/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.

Our wide-ranging conversation touches on his early interest in entrepreneurship at Stanford, his early career as a financial analyst, his time at Intercom as the Head of Finance scaling their analytics, his current journey with Equals building the next-generation spreadsheet, lessons learned from hiring analysts, advice for finance operators in startups, and much more.

Please enjoy my conversation with Bobby!

Listen to the show on (1) Spotify, (2) Google Podcasts, (3) Apple Podcasts, (4) iHeartRadio, (5) Stitcher, (6) RadioPublic, and (7) TuneIn

Key Takeaways

Here are the highlights from my conversation with Bobby:

On His Education at St. Albans School

Source: https://www.stalbansschool.org

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.

On His Academic Experience at Stanford

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.

Source: https://ecorner.stanford.edu/contributor/steve-blank/

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.

On Early-Career Lessons at IBM and Inflection

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.

On Joining Intercom As The First Finance Hire

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:

  1. I wanted to be at a product-first company. Inflection was a marketing-first company. It was excellent at acquiring customers. We knew our LTV down to the cent. Our acquisition was a machine. But while I was there, the market started getting more competitive. CPC started to go up, which meant the margins on acquiring customers became thinner. Sometimes, we had to turn channels off because they were no longer profitable. The only way to fight against that is to increase LTV, which means improving retention and how people use the product. But we did not know how to do that. It was not in the DNA of the company. I wanted to be somewhere where the product was in the DNA of the founders. So when I met Owen and Des, I immediately saw that in them.

  2. The thing that sold me the most was Twitter. I remember going on Twitter and searching for Intercom. Many folks were talking about how much they loved Intercom and how it was a game changer for them. That was exactly what I was looking for.

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.

On Scaling Analytics at Intercom

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.

On Combining Finance and Analytics

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.

On Key Startup Metrics

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.

Source: https://www.intercom.com/blog/saas-metrics-for-fundraising/

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.

On Founding Equals

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.

On Choosing Ben McRedmond As His Co-Founder

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.

On The Appeal of Spreadsheets

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.

On The Equals Product

There has been a lot of unbundling of the spreadsheet by building different vertical uses cases:

  1. There are the Airtables of the world, where a spreadsheet is a database or a mini application.

  2. There are the Smartsheets, where a spreadsheet is a project management or workflow tool.

  3. There are also spreadsheets-meeting-docs, like Notion or Coda.

  4. In terms of spreadsheets for doing analysis, it has not changed much. It is Google Sheets and Excel.

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.

  • It works just like Excel functions, formulas, and features down to the keyboard shortcuts.

  • It natively connects to any data warehouse. You can write SQL right there alongside your spreadsheet and access the SQL database without writing SQL through its visual editor.

  • It seamlessly integrates with various other places you want to get data (Salesforce, Hubspot, Quickbooks, NetSuite, etc.)

  • Every time you pull the data, it is versioned and snap-shotted. You can restore it with the click of a button.

  • It is also fully collaborative and web-based.

On Spreadsheet For The Modern Data Stack

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.

  • On one end of the spectrum, there are a ton of BI and dashboard tools that basically do the same thing: pulling data, charting it, and throwing them up on the dashboard. It is useful but also insanely limited with what you can do there.

  • On the other end of the spectrum, there are notebooks where you write SQL, Python, and R. These are the Jupyter notebooks and Hexes of the world. They are awesome but serve a tiny fraction of the population. There is still a tiny number of folks who can use those tools effectively.

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.

On Hiring

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.

On Finding Design Partners

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.

On Lessons Learned From Hiring Financial Analysts

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 most uncomfortable but fruitful thing I did for myself at Intercom was hiring folks with many more years of experience than I did. It sounds obvious and simple, but it is really uncomfortable when you have to do it. I needed to hire somebody who has five more years of experience than I do in FP&A, accounting, or analytics. All of a sudden, that challenged my authority. It challenged who I am and my value to the company.

  • My biggest lesson is that it is the only way to scale. You have to have trust and confidence in yourself that there are other ways you can add value. You want to delegate the things you are doing today to those people with more experience. You should give them context on the business, connect them within the organization, show them your experience within the company, unlock them, and partner with them to build a highly impactful organization. That will be the biggest leverage for 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.

On Advice for Finance Operators In A Startup Environment

I have one strategy that helped me in my finance career, which I call the overheard list. The idea is simple:

  • Typically, when you start in a new company, you do not necessarily have the confidence, ideas, or context to come up with things you might want to investigate, analyses you might want to do, and ways you can be impactful to the business. I kept a notebook with a list of everything I would overhear people talking about — in a meeting, over lunch or happy hour, in water-cooler conversations. I look for areas where somebody said something that was not backed by data, there was a conflict, and somebody guessed something about the business. I would write them down.

  • If you do that long enough, you will start seeing some patterns emerge. You want to tally some ideas or concepts brought up more frequently than others. That is your list to start investigating. Once you have the overheard list, you should pick one idea and do an analysis on it.

  • You should act as if you are the CEO who will make the decision. You are not a contributor. You should make the decision that needs to consider different factors and how other teams will respond. You have to do other parts of the analysis to make the best possible decision.

  • Things will compound from there. If you provide stakeholders with relevant analyses, they will insert you into meetings that you would not have been inserted to. Now you will get more context, your overheard list starts to grow, and you can do another analysis based on those.

That was my strategy and mentality as somebody wanting to have an impact.

On Learnings From His Analyst Career

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.

Show Notes

  • (01:33) Bobby shared his upbringing in DC and high-school experience at St. Albans School.

  • (04:10) Bobby described his academic experience at Stanford studying Management Science and Engineering.

  • (07:39) Bobby recalled valuable career lessons learned working as a Finance Analyst at IBM and Inflection.

  • (09:56) Bobby reflected on his rationale for joining Intercom as one of the company’s early employees right after its Series A financing in 2013.

  • (14:16) Bobby unpacked his 2016 talk “Scaling Analytics at Intercom,” which explained the analytics journey at Intercom.

  • (18:46) Bobby shared a few metrics that are fundamental to the health of a startup across its growth stages (read his Intercom blog about the data points that startups should measure).

  • (22:50) Bobby shared the founding story of Equals.

  • (27:33) Bobby explained his decision to choose Ben McRedmond as his co-founder.

  • (29:35) Bobby expanded on the appealing traits of using spreadsheets.

  • (31:54) Bobby described the evolution of spreadsheet-like products and how the Equals product works at a high level.

  • (34:35) Bobby gave his take on how the concept of a next-generation spreadsheet fits into the quickly evolving modern data stack.

  • (38:31) Bobby shared valuable hiring lessons to attract the right people who are excited about Equals’ mission.

  • (44:34) Bobby shared the challenges of finding Equals’ early design partners and lighthouse customers.

  • (47:17) Bobby recapped key lessons about hiring financial analysts at Intercom.

  • (51:45) Bobby shared advice to a smart, driven finance operator looking to get more influence within a startup environment.

  • (56:26) Bobby emphasized the valuable skills acquired from his analyst career for his current founder journey.

  • (58:45) Closing segment.

Bobby’s Contact Info

Equals Resources

Equals is hiring across Engineering, Design, Growth, and an Executive Assistant. Reach out to Bobby if you are interested!

About the show

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.

Datacast is produced and edited by James Le. Get in touch with feedback or guest suggestions by emailing khanhle.1013@gmail.com.

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