Data-Driven Work Cultures: DeVaris Brown of Meroxa On How To Effectively Leverage Data To Take Your Company To The Next Level
An Interview With Pierre Brunelle
I believe it’s important to have a data-first and an archival mindset. If I do something, how can I report on the success or failure of that thing? I think that most teams, or companies for that matter, really don’t have a culture for data standardization. The biggest problem is teams only think about data in their own silo, they don’t think about providing data out to the broader company to solve any problem. I feel strongly that you really want to create a data culture that thinks about the 360-degree view of the organization and where data fits in and how we can standardize it so everyone is able to make a decision based on a single source of truth.
As part of our series about “How To Effectively Leverage Data To Take Your Company To The Next Level”, I had the pleasure of interviewing DeVaris Brown.
DeVaris is the CEO and co-founder of Meroxa, a VC backed data application platform that empowers developers to build data products by using their existing infrastructure, tooling, and workflows.. Prior to founding Meroxa, DeVaris was a product leader at Twitter, Heroku, VSCO, and Zendesk. When he’s not sitting in front of a computer, you can find DeVaris behind a camera capturing moments in time, at the stove whipping up the finest delicacies, or behind a set of turntables, moving a sea of people through music.
Can you tell us a bit about your ‘backstory’ and how you got started?
I’ll start at the point where Meroxa became a spark in the back of my mind. I had been a product leader at several companies and at each stop, I was tasked with the same three projects — building an internal developer platform, building an internal admin panel, or building a data platform. Along that journey, I met my co-founder, Ali Hamidi. We were often sent out on customer calls and came across the same problem each time. The data platform is an unwieldy beast and companies were having serious issues with it. They would ask us when is XYZ company (my then employer) going to build the Heroku for data? We heard it so much we pitched it, but it landed on deaf ears. So, we said, you know what? This is something we should build. This is something we need to do for the future. There were a few years between that moment and the birth of Meroxa and I made a few more stops. At the first stop, the team I was on worked on an internal developer platform. The second project was a data platform. At that point, I was like, you know what? This is God talking to me. Let me go ahead and see if there’s a market and a need for this. And by golly, there was, so that’s where I got started and how Meroxa was born.
Can you share a story about the funniest mistake you made when you were first starting? Can you tell us what lessons or ‘takeaways’ you learned from that?
I would say the biggest mistake that I made was I was still giving people series seed equity after we raised our series A. We started off with a very small option pool and that’s how we modeled everyone’s options. However, as we grew — and grew super fast — I realized quickly we were running out of options. We’re okay now. But at that point in time, it was like, yeah, I should have adjusted how we were granting options. And it got to a point where it was like, oh man, I think we’re about to run out. (laugh) We’re all good now. For me, the takeaway was we need to do better at modeling out our hiring plan and spread things out when hiring. There was definitely good and bad though. A lot of companies have been complaining about how it’s difficult to hire people, knock on wood at Meroxa we haven’t had that issue. We embrace our differences and encourage team members to come as they are, and I think that’s one of the key reasons we have such a great team.
Is there a particular book, podcast, or film that made a significant impact on you? Can you share a story or explain why it resonated with you so much?
There are a couple of books. One is Think and Grow Rich by Neopolitan Hills. It’s about manifesting the life you want and the things that you want out of life. I took the learnings from that book and put them into practice so that I could become a better CEO. Actually, build the type of company I wanted to build. So far it’s working.
The second is a book by Reginal F. Lewis, Watch All the White Guys Have All The Fun. That was a good book that influenced me. It showed black excellence and how we’re able to participate and be wildly successful in the largest of arenas. It was a big motivation for me to push on in a space where there aren’t a lot of folks that look like me.
Are you working on any new, exciting projects now? How do you think that might help people?
Yes, we certainly are. We’re currently developing a fascinating, fun way for developers to create data applications using the Meroxa platform. It’s a departure from the status quo of low-code drag and drop dashboards, and really puts the power into the hands of the software engineers to do more DataOps type work. We believe it’s going to revolutionize the data landscape and is a true game-changer in data development. I’m really, really excited about it. And then on the open-source side, we have a project called Conduit which is a data integration tool. We recently opened it up so that people can write integrations and the like. So, we’re working to build a community around those two initiates. I’m really excited about what the team at Meroxa is doing and our plans to revolutionize access to data.
Thank you for all that. Let’s now turn to the main focus of our discussion about empowering organizations to be more “data-driven.” My work centers on the value of data visualization and data collaboration at all levels of an organization. So I’m particularly interested in this topic. For the benefit of our readers, can you help explain what exactly it means to be data-driven? On a practical level, what does it look like to use data to make decisions?
My personal thoughts about being “data-driven” are sometimes a little controversial. I think people rely on data so much that it takes the art out of finding ways to overdeliver for our customers. The definition of data-driven that makes the most sense to me is knowing enough about the customer and their behavior so that you can offer them a highly personalized contextualized experience. People aren’t static individuals. Therefore, having enough information about their behavior as it pertains to your product or your service is vital. That allows you to provide them with a better experience. I think that’s what it means to be data-driven.
However, a lot of folks think that running AB experiments — testing experiments all day is being data-driven — — that’s not right. I don’t think we ask “why” enough. Nobody’s really doing that. They’re just doing work for the sake of doing work, to be honest, because the reality is people are not converting more, interacting more or engaging more. They’re just being bombarded with ads that aren’t super personalized. So, for me, being data-driven means asking what information is at my disposal to build a more personal relationship with my customers.
Which companies can most benefit from tools that empower data collaboration?
Every company and any entity that’s customer-facing. Hospitality, retail, gaming, finance, insurance…literally every company. That’s the problem. It’s apparent nobody’s really doing effective data collaboration. Therefore, we don’t really know what the ceiling is. I don’t necessarily think data collaboration is company-driven. It’s more of a behavior or a mindset. Literally, every company needs to collaborate around data in some way, shape, or form. If you’re serving a customer, whether internal or external, every company needs to be focused on data collaboration. It’s not just useful for a certain type of company.
Say I’m working at an Amazon facility and my team is responsible for pulling widgets. I need to know things like shift schedules, when the widgets are expected to arrive at the facility, the committed delivery date to the customer, etc… Everything is collaborative around data. If I don’t have that information it impacts my revenue and profit margins. There’s literally no place where data doesn’t impact the experience. The problem is, people don’t have the ethos to know how to effectively collect, transfer and manage the information they need to make relevant business decisions.
We’d love to hear about your experiences using data to drive decisions. In your experience, how has data analytics and data collaboration helped improve operations, processes, and customer experiences? We’d love to hear some stories if possible.
Yes, it’s one of those dangers. The world is increasingly becoming more interconnected, therefore we need better interfaces. Back to my Amazon example, reliable data should be at the center of every decision. Making one decision based on bad data will have a negative effect on the entire supply chain. This goes for every industry. If I’m a hotel and I know that 90% of my revenue comes from 10% of my guests, I want to know when those guests check into the hotel so I can offer them a personal experience. I want to know what they’re buying. I want to know what they’re ordering, what time they wake up, what time they leave the hotel to go shopping and when they return. I want to be able to build a map of their activity around my hotel so that I can offer them a personalized experience during their current stay and enhance that experience during future stays to incentivize them to keep coming back. That’s the holy grail. We have all this information, but at the end of the day, what are we really doing with all this data? I’ve personally worked on projects that have collectively cost companies trillions of dollars to build systems that still aren’t able to provide a super personalized real-time profile of their customers. Imagine what the world and the commerce opportunities could be if teams had the tools to better collaborate and truly uncover the messages in the data.
Has the shift towards becoming more data-driven been challenging for some teams or organizations from your vantage point? What are the challenges? How can organizations solve these challenges?
Yes. The issue is the data landscape is not standard. A lot of times the information isn’t easily accessible. You go into any organization, you have a mixture of the size of the tools, a mixture of the operational data stores being used — just a mixture of things being used to emit data. People tend to optimize for their local issues and don’t really think about the broader picture. For example, a marketing team has a certain way of looking at data. They’re likely using visualization tools, probably Excel, etc. and pulling the data from let’s say a SAS tool, in an attempt to extract more insights into their customer outreach efforts. However, it’s super hard for their data teams to pull that information and maintain its freshness. For this reason, teams tend to work in silos because the data sources aren’t centralized and nobody really wants to manage them. The other part is that on a larger scale no one has established an overall vision for what being a “data-driven” company really means. They didn’t ask the 5-Ws. Therefore, there will be major gaps and later down the line the team realizes they should have been collecting information they aren’t. Those issues compound over time and it becomes a giant snowball that keeps rolling. There’s going to be a variety of things they should have been collecting. So, I believe, if you compound those issues over time, it becomes this giant snowball that keeps rolling downhill and it’s hard to stop.
Ok. Thank you. Here is the primary question of our discussion. Based on your experience and success, what are “Five Ways a Company Can Effectively Leverage Data to Take It To The Next Level”? Please share a story or an example for each.
Five is specific and quite a lot! I would say first and foremost, have a data plan. As I mentioned earlier, the stakeholders need to sit down and ask some key questions before trying to tackle any data problem. Questions like, what information can help me solve this problem, where is the information coming from and what interval do I need to receive it, what’s the best way for me to consume the information. There are more questions, but you get the point. If every organization did that — — just sat down and really took the time to map out the problem and all the components they need to get to the solution, they would be able to kick off their projects with a solid understanding of what they are ultimately trying to achieve in the long-term. If teams would start there, they would be able to solve 90% of their problems and significantly reduce costs.
Number two, from a technical aspect, I believe having a platform that allows you to centrally manage resources and data sources and pushes the execution out to whoever’s solving the issues with stakeholders is key. Some folks will call this data, measured data domains or something like that. But, I’m a firm believer that the people closest to the problem know how to ask the questions the best. Therefore, we should put tools in their hands that allow them to do just that…answer the questions. However, the central problem is that the tool or platforms companies decide to implement rarely play nice with each other, therefore a lot of time and effort is spent trying to get that information into a semblance of a standard format. So, essentially I’m saying the key is finding a more efficient way of standardizing data. In other words, centralized resources but decentralized execution. Automate as much as possible. Pick a platform that allows you to do that with minimal maintenance, so you can free your teams up to focus on delivering value.
These are just two of the ways a company can effectively leverage data and take it to the next level, and the two that I think are the most important as companies look to leverage data into the future.
The name of this series is “Data-Driven Work Cultures”. Changing a culture is hard. What would you suggest is needed to change a work culture to become more Data-Driven?
I believe it’s important to have a data-first and an archival mindset. If I do something, how can I report on the success or failure of that thing? I think that most teams, or companies for that matter, really don’t have a culture for data standardization. The biggest problem is teams only think about data in their own silo, they don’t think about providing data out to the broader company to solve any problem. I feel strongly that you really want to create a data culture that thinks about the 360-degree view of the organization and where data fits in and how we can standardize it so everyone is able to make a decision based on a single source of truth.
The future of work has recently become very fluid. Based on your experience, how do you think the needs for data will evolve and change over the next five years?
That’s kind of a softball question for me, because I believe the world is probably about 2–3% real-time data right now, and it’s going to be much more of that in the near future. Right now, the world runs on batch, people are making decisions on 24-hour old data. The world is operating off of that right now. However, the world is demanding better information quicker, so I anticipate real-time is going to become the status quo soon. I also think the balance between openness and privacy will play a significant role in the evolution of data availability. In the U.S., more states are introducing their own privacy laws and there are 60 or 70 privacy agreements around the world. It will be challenging for people to navigate that space. How do you navigate that space? There are entire industries built on personalization. So, if browsers and phones stop allowing companies to access that information, how are they going to target and retarget buyers. Therefore, there has to be more fidelity to the information that we’re capturing in a way that’s not going to violate compliance or regulatory standards. That’s huge.
Those two things are huge bellwethers for the future of work and data. It’s funny to think about the proliferation of job titles in the data space. I made an analogy, it’s kind of like house music: House music started off as just house music. Then it went to the UK. Now it’s grime and tribal and all these things. We’re going to see more and more sub-genres of the data worker to reflect the evolving nature of the toolset. Right now, we just say data engineer, data scientist, data analyst, but there’s going to be more and more as tools and needs evolve. I don’t know necessarily if that’s a good thing, but I just know that’s where it’s headed.
Does your organization have any exciting goals for the near future? What challenges will you need to tackle to reach them? How do you think data analytics can best help you?
Yes, we want to bring real-time data to everybody that needs it within an organization. We’re focused on software engineers and making their experience great. However, other parts of the organization need that too, so we’re being very methodical and thoughtful around the end-to-end experience. We are focused on removing silos, we aren’t just solving problems for an individual we want to solve problems for the team — the company and offer best practices for delivering data as a product. Spread out, they’re siloed. So, how do we make sure that we’re not just solving for the team, but for the individual, and also make sure that we’re installing or instilling best practices around them delivering data as a product? It’s all about changing the game and facilitating rapid innovation, and Meroxa is best suited for the changing data needs of our world.
Thank you so much for sharing these important insights. We wish you continued success and good health!
