Jake Aaron Villarreal: I'm Jake Villarreal, born and raised in Silicon Valley and here to take you behind the scenes to share what it's like to be a startup founder, the journey they're on, the problems they face, and the products they build as they transform industries. I'm excited to have with us today Logan Havern, founder and CEO of Datalogs. Logan, welcome to the show.
Logan Havern: Thanks, Jake. Excited to be here.
Jake Aaron Villarreal: Great. A little bit more about Logan. He is an innovator in the analytics space solving the biggest challenges with enterprise data management in Business Intelligence (BI). He studied engineering at Texas A&M focused on analytics and went on to work for well-known companies like JetBlue where he experienced data challenges early in his career, which inspired him to solve the problems he encountered. He's not just the CEO but an engineer who built their first version of Datalogs on his own and their vision is to create the BI Ops category. So, I guess as we dive in here a little bit, Logan, before we do that, where are you... where are you calling in from today?
Logan Havern: I'm in our office in New York City today.
Jake Aaron Villarreal: Great. I love New York. I spent a number of years there. In fact, uh, interesting qu- uh, sort of interaction between why I was there. I was there working for Oracle Corporation, and a few weeks back you invited me to come out to one of your events which was being hosted by Ray Lane, [who] at the time was the President of Oracle and I had never met him. So it was a privilege to not only meet you and your team but also to meet Ray Lane and just really understand his growth over life and it was really fun to, to meet him. So thanks for that invite. It uh meant a lot to me.
Logan Havern: Yeah, of course. Uh we're glad you able to, were able to make it out. And then yeah, also Ray Lane has been a great... as an investor in us and we're super excited to have him as part of our team and on the cap table.
Jake Aaron Villarreal: Yeah, what a great investor. And it just goes to show the type of company you're building and the product you're bringing to market, that you know he's a smart guy and if he's going to take funds and put it into a company that you're building, I know you're on to something big. So let's, let's kind of talk a little bit about you. Give us your background, uh, a little bit more of your origin story. How did you get into technology and kind of growing up, what were some of the things that led you to be an entrepreneur?
Logan Havern: Yeah, growing up I was always interested in entrepreneurship. I guess very early on kind of watching Shark Tank, other kind of classic entrepreneurship shows. And then when I went to university at Texas A&M, I think that kind of kicked off my entrepreneurship journey. Not to the level of [what] it is today, but I tried and kind of failed on a few different startup ideas then. And then after graduating, I ended up working at JetBlue for about four years in aviation there, and then saw some challenges around the data space that I ultimately wanted to solve.
Jake Aaron Villarreal: Yeah, really cool. Well, it seems like a very linear approach. You studied in engineering and then you went on to work for an enterprise company and kind of found some areas you thought you could solve. You know business is really about solving a problem in a market, and you know, when you do that hopefully companies will pay you for it. What problem are you working on solving today with Data Logic... Datalogs?
Logan Havern: Yeah, today at Datalogs what we're doing is going into the largest analytics, BI, and data products in the world, and uh, with this we ingest logs, other information from these tools. But the challenges that our clients have is really around BI and data sprawl. So this normally results in... as you get more and more users creating different dashboards, reports, analytics and insights, it creates chaos within [an] enterprise where there's duplication, unused assets, wasted compute. And Datalogs sits on top of any analytics environment to monitor for cost, security, and risk problems in an enterprise.
Jake Aaron Villarreal: Yeah, makes sense. For the listeners, you know, when you talk about dashboards and business intelligence, if you're a small company, it might not necessarily ring a bell. But if you're a big organization like an Oracle or you have thousands of employees, you know, getting reports out of your data is important. And depending on what tools you use, it could be multiple vendors, multiple tools, and there's also some inherent risks about the data you're pulling and who gets access to it. And um, give us kind of a lay of the land of typically when you go into a company, what size are they? What are you getting into? What, what's like a good target for you when you're pitching your product?
Logan Havern: Yeah, it's a good question. So, we're focusing mainly on Fortune 2000s and the Department of Defense, and we need at least 2,000 reports, dashboards, data insights for us to actually be able to create measurable value. And when I say measurable value, that's really around: can we save our clients money, improve performance in analytics, and identify risk? And it requires this critical mass of BI reports and dashboards in the environment. And then when we go in, we're typically selling into kind of CIOs or CDOs. So a C-level executive who ultimately owns data and decisions at a large enterprise. And we build a business case for them based on: "Hey, what is the measurable cost impact that Datalogs can have? What percentage can we speed up getting data into the hands of end users?" And then also on the governance and risk side, identifying where there's problems. And our clients range from, I'd say our largest one today has about 140,000 dashboards in a single BI platform, and then we have all the way to smaller ones with around 2,000 to 3,000. But the same problem exists at both of these types of companies where it's unmanageable. They're wasting money, wasting time, and can rely on a software product like ours to help manage the environment effectively and efficiently.
Jake Aaron Villarreal: Wow. Sounds like a tough problem to solve, but you've built a platform. It sounds like it's doing that. Um, why is this important to you?
Logan Havern: Yeah, so I guess one of the big kind of impact areas that we're creating at Datalogs is really driving the future of how data is being used. And for any business, this is going to help them create better insights, uh, create better decisions and also build a better company. And as a founder and entrepreneur, it's always been a passion of mine is the data space and understanding it. And for me, being able to impact uh the bottom line at different organizations has always been kind of a motivating factor, is how can we help uh different organizations be faster, stronger, and more effective. And uh that motivation keeps us uh on the right track at Datalogs.
Jake Aaron Villarreal: Yeah. You know, there's a lot of CIOs out there that might listen to this. Walk us through what the product looks like and, and as you're providing that to them, like what are they getting into? You touched on what it does, but walk us through the tool or the product a little bit more.
Logan Havern: Yeah. So, what we're doing on the product side is connecting to any analytics or BI platforms. So, take for example Power BI. So a client of ours might have 12,000 reports in Power BI, and as soon as data touches this BI and analytics world, there's another wave of transformation that happens. There's business users who start uh manipulating data and it becomes very, very messy very quickly as your volume increases. So at Datalogs, we touch the backend APIs and logs behind these different BI platforms, ingest it into our platform, and then automate the insights. So answering questions like: what exists, who's using what, what are access patterns across the org, who has authorized access, where are their endorsed data sets or unused data sets? And then we set up alerts and monitoring. So this is flagging any kind of critical issue.
And so take for example a duplicate data set. So two different business users brought in the same data set and you're spending 2x the compute when it could be half of that. Our system would alert of that, give you context around the problem and then assign it to an end user or write back to the system to actually fix it. So, we're running in the background cleaning up these cost issues, performance issues, risk issues, but it's all through data insights from the logs and APIs behind these uh analytics tools, centralizing them, and then identifying and solving and monitoring problems in these environments.
Jake Aaron Villarreal: When a CIO goes to the CTO or goes to the CEO of this enterprise company and says, "Hey, we need to allocate more money for a new product that's going to help us, you know, improve our business at some level or give us a bigger benefit." What benefit are they telling that CEO that your product's going to give them?
Logan Havern: Yeah, I'd say our clients really fall into two categories. One is on the cost and reduction of spend. So in these large analytics environments, there's tons of wasted compute. So you could be refreshing thousands of dashboards that are... you're paying for that data refresh, that data pipeline, but no one's actually consuming those insights. So by cleaning that up, identifying these and either getting rid of them or archiving them, we're instantly saving money that impacts uh your spend in the data world.
And then the second is around risk and security. So, how do you ensure that we have the right information to the right people at the right times, that you're not reporting out the same thing differently? And most companies, when they come to us, there's been some sort of critical event in their environment, like a security leak or there was four different reports that went to the CEO that were all saying the same thing but had different numbers. And that triggers this, "Hey, we need something like Datalogs to clean, manage, and monitor these tools because we have this proliferation of reports."
Jake Aaron Villarreal: That's really good to hear. You know, when you talk about providing a benefit to a company, oftentimes there's an ROI you have to show them, or you got to give them a value proposition they can really dig into to say, "I'm going to spend X. I need to understand why." Um, what's the value proposition? Or more specifically, can you provide them detailed numbers that they can look at and say, "Oh, this is what I'm going to save or this is how I'm going to benefit"?
Logan Havern: So for all of our companies that we're going live early in the sales process, we start with what we call an "analytics diagnostic." So we plug into all of their BI systems and create a business case that shows an exact dollar of savings opportunity of what you'll achieve with Datalogs. And typically we're in about the 30 to 40% reduction of compute and licenses. And then we're also flagging these risks. So when we go to the, that meeting with the CIO or sometimes the CEO of these larger companies, we have the data, the insights to prove: "Hey, we plugged in, we ran an early test and we found these issues already." We quantify that and it becomes a very clear business case and then we're charging only about 5 to 10% of that total value and we quantify it either on the cost savings, labor savings or the risk side of things there.
Jake Aaron Villarreal: Wow. It makes it a no-brainer not to at least look at the product if you can see the numbers and the savings. So, that's about as good as it's going to get in terms of making a business decision. You know, when I went out and met with you and Ray Lane and the whole group there up in San Francisco, it was really fun to hear all the ideas around where AI was impacting the industry and, you know, every sector. It seemed like there was a real value proposition for how AI could optimize or be a co-pilot or an assistant to some industry. Um, talk to me a little bit about how AI is impacting the analytics space.
Logan Havern: Yeah, it's a really good question. I guess I'll give kind of a two-part answer. One about AI and our product, and then the second of how we kind of view it in the analytics space. So for us at Datalogs, we've integrated with AI to actually write back to systems and solve problems. So, we're using different LLMs that allow basically what would have been a human in the loop to help expedite that, almost like a co-pilot for your admin type feature in the BI world. And on the analytics space, which I think was kind of the bigger part of your question, is we're seeing that within the BI tools themselves, which is still the largest access point of data, they've added in kind of chat-like features to generate instant data insights. So, there's more business users, the skill level goes down to actually start creating new reports, dashboards, insights, or you ask a question and get an instant data answer. This is great in terms of improving data literacy at enterprises. But it also creates a problem of what's going to happen if this is the wrong answer, wrong data, wrong insight? And as part of our product positioning, we want to be on kind of that monitoring side of insights created by AI. And also just beyond the BI wave itself, we're seeing that there's more and more data products out there that companies are using to create different insights powered by AI. So being able to load this data into your chatbot kind of GPT type features and get instant answers, I think we're going to continue to see throughout enterprise.
Jake Aaron Villarreal: Yeah, great. Thanks for sharing that. As a company, you know, what drives large organizations to purchase your product?
Logan Havern: Yeah, I think uh kind of what we talked about earlier, of creating a very clear business case of showing "this is the value, this is how we're measuring it and this is the impact it's going to have for you all." And uh it took us I'd say about two years to really get down positioning, where at first we were trying to sell mainly kind of an efficiency play, but when it came time to have that business case, it was very hard to tie it to real dollars and we faced a lot of rejection there. And so I think really being able to quantify the value that we're creating and getting through uh quite a few iterations to where it's actually measurable from a product perspective, but that ultimately drives the decision is: "how are we impacting the bottom line?"
Jake Aaron Villarreal: Yeah, makes sense. What's the biggest, what's the biggest challenge you're facing currently as a company?
Logan Havern: Yeah, in terms of challenges, I think right now we're at a kind of inflection point of where we're starting to hit scale where as we're adding in more and more customers, having bigger contracts, even working kind of on the federal DoD side of things, is that the complexity of customers continues to rise. And with that, we're working on kind of thinking through a larger strategy of how do we build out and scale our customer success org for our company and how do we ensure that every client has the same experience that our first 10 clients did? And uh so that's something we're constantly working on and really trying to think through of how do we build this longer term with that scalability and customer success in mind.
Jake Aaron Villarreal: Yeah, great. You know, every company goes through shifts and pivots. You hope you don't have to do too many, but you know, for younger companies, maybe there isn't a ton of that that's already happened or occurred at this point. But for your company, maybe even if they're micro shifts, what, what's been one or two you can share that might be helpful for others to hear?
Logan Havern: Yeah, so I guess going back to kind of our founding journey of Datalogs, the original concept, we were doing something slightly differently, different than what we are doing today. Uh so originally the first kind of version of the product I built was really around how do we help people find reports and dashboards. And I built it kind of part-time when I was at JetBlue as a side project, and coincidentally it went viral on Reddit. And I was super excited and quit my job the next day expecting to make a bunch of money. And then we went through... I think we had like 500 signups, and zero converted to actual revenue or users beyond that signup point. And it was kind of this "uh-oh" moment of, "Okay, I quit my job, I thought [I] was going to generate a bunch of revenue, have this kind of overnight successful startup journey." And in reality it was nowhere near that of what actually happened.
So we ended up going back and interviewing as many of those people that would talk to us, and I'm still in, friends and kind of contact with a lot of them today. But we were able to kind of listen and hear the bigger pain points in the market of managing from this administration standpoint versus originally we were focused on discovery. And it's still like the same domain and just like a kind of slight shift in how we design the product, who's the end user and our positioning and messaging. But if we didn't go through that kind of big pivot or aha moment and stuck to what we were originally doing, I think we would have kept trying and ran out of cash very quickly. And we got close a few times where we were down to a week or two weeks left on kind of payroll and moments that were kind of tricky there, but ultimately it worked out.
Jake Aaron Villarreal: Yeah. God, I think we've all been through those moments where you're looking into the abyss going, "Hm, what are we going to do now?" And you figure it out somehow, the universe helps. Um, what's, what's the biggest breakthrough so far for the company or for you personally since you've been building Datalogs?
Logan Havern: Yeah, I think for us was really the... we had a first kind of pilot where going back to that pivot story. So, we ended up getting like a little bit of revenue, not a ton, and then we decided to pivot our messaging and try something slightly different with this new product. And we spent a year building out the original version. It worked, thought it was great, but no one was adopting and using it. The next thing we built was literally just a Python script that exported data to Excel, and a company agreed to purchase it for $20,000. And that was more revenue than we had the entire time of doing this original product. So, I'd say that was kind of the big learning moment for us where we got this new version of the platform out and really set us on a different direction.
Jake Aaron Villarreal: Yeah, that's great. Wow, what a number, too. $20,000 off of a spreadsheet. Really good to, to know that's kind of sometimes where you start. Um, you know, if you look at your company now, going back to the beginning, if someone would have told you something that would have been helpful or, or you would have known then what you, or know now what you wish you would have known then, what would that have been?
Logan Havern: Yeah, I think the biggest kind of shock to me in this enterprise software world is just how long deals take to close. Is that a week in startup time or like someone says, "Hey, this is urgent. I need this ASAP." And I'm like, "Okay, perfect. Let's set the next meeting tomorrow." In the corporate enterprise world, that next meeting could be four weeks away. And to them, that is a fast turnaround. And so, we've kind of always been in this high pressure sales environment where like, "Hey, you said you need it tomorrow. Let's do our best, deliver it, get it out there tomorrow." Uh but it took me a long time to kind of learn, okay, it doesn't mean that that client or prospect isn't happy with us, isn't interested anymore. That's just kind of the reality that these things take a little bit more time.
And then yeah, I think the other kind of learning, and it's in a lot of kind of entrepreneurship and startup books out there, but to sell software at [the] enterprise level, you either need to make someone money, save them money, or deal with risk and regulations. And those are kind of the three reasons why people buy enterprise software. And as soon as we tied our value props over to those areas, we started seeing this kind of massive uptick in interest, even though [with] small tweaks on the product, but people really only buy for three reasons.
Jake Aaron Villarreal: Yeah, really good to know and hopefully a lot of listeners hear that and can use that as in their journey. Um, what's on the roadmap for you as you, you know, we're halfway through 2024 going forward?
Logan Havern: Yeah. So, as a company, I think, I mean roadmap means a ton of things for us from a product roadmap, kind of team, fundraising, and there's a lot of stuff on the horizon on all three. I'd say from a product perspective, we're doing this big shift where today, and kind of on our first version of the platform that we've been able to implement with companies, it's very rigid and not flexible in terms of: hey, a client wants to build out a new monitor for a specific rule in a BI environment, it's a little bit of effort to go in and make those changes. But we've built out this new version over the last six months where they can create their own monitors in place rather than our team doing it. So, it's this kind of fundamental shift in how we're delivering the product to the customer and the experience they have. So, from that side, very exciting.
And then from a fundraising perspective, we're getting kind of ready and planning to do another fundraising round later this year. So, prepping for that. And then from a team and sales perspective, we're kind of expanding our presence in the Department of Defense and going after the federal market which has been a journey, just learning kind of the language, how to talk about it, how to ultimately work with teams there. But I've been fortunate to bring on a recently retired Lieutenant Colonel from the Air Force who built out a lot of the kind of data projects and insights there who's joined us to help scale in the DoD and on the federal side.
Jake Aaron Villarreal: Oh wow, that's amazing. Really cool. I'd love to check back in and see how that goes. I know there's a lot of opportunities in that space if you can get it right and have the right connections, too. So, really cool. Um, if companies want to find you or find Datalogs, where do they go?
Logan Havern: Yeah, I think the best spot to find me is to connect with me on LinkedIn just under my name, Logan Havern. And for our company, our website's just datalogs.io and that's Datalogs.
Jake Aaron Villarreal: Cool. Logan, I want to thank you for coming on and sharing your story and having the courage to do that, and also for the listeners for listening. It means a lot to me that you spent your time with us today. I'm your host Jake Villarreal signing off for now, but can't wait to catch up with you all on the next episode. Until then, take care.
Before we wrap up, I want to give a big shout out to all the entrepreneurs that are joining to make this podcast possible. And from all the listeners for listening, it means the world to me if you chose to spend your time with us today. I'm your host Jake Villarreal. Signing off for now, but can't wait to connect with you all soon on the next episode. Take care.
This show is sponsored by Match Relevant, a company that helps venture-backed startups find the best people in the market. And they do it in three simple steps. First, they sit down with founders to understand their story. Second, they tell their story into multiple candidate channels. And third, they schedule interviews within 48 hours. Find us at matchrelevant.com to learn more about how we do it.
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