Rachel Olney - Founder & CEO of Geosite: Selling to Large Organizations, Obsessing Over the Problem, and Finding Your Strengths

Rachel Olney  00:00

What we'll do is we'll write down like, here are all of our stakeholders. Here's what they care about. Here's the way that we interact or don't interact with that. And here's the path forward to find something that's going to create value inside their organization.

Callan Harrington  00:13

You're listening to That Worked, a show that breaks down the careers of top founders and executives, and pulls out those key items that led to their success. I'm your host, Callan Harrington, founder of Flashgrowth, and I couldn't be more excited that you're here. Welcome back, everyone, to another episode of That Worked. This week, I'm joined by Rachel Olney. Rachel is the founder and CEO of Geosite. Geosite is a Y Combinator backed startup working to build the geospatial marketplace. Their platform sources, visualizes, and analyzes the relevant geospatial data so their customers can make informed business decisions. Rachel is also completing her PhD in mechanical engineering at Stanford and was listed on the Forbes Top 30 Under 30 list. If geospatial data sounds super complicated to you, you're not alone. She gives a great explanation in the episode. And it's really interesting, what can be done with it and the impact that it can have. She also talked us through her approach to selling to large bureaucratic organizations, and it was a great enterprise sales playbook. We also had a great conversation on how to find your strengths. I've started focusing on my strengths a lot more lately. And I could already say in a short period of time, it's made a significant difference. And Rachel gave excellent advice for anyone trying to turn their strengths into superpowers. And one thing of note, Rachel's getting her PhD in mechanical engineering, which has nothing to do with geospatial engineering. I loved hearing the reason behind this, and she broke it all down in the conversation. In short, she is obsessed with the problem. And being obsessed with the problem was a common theme throughout the episode. And we jump into it right from the start. So with that, let's get to the show. Rachel, super excited to have you on the show today. Tell us about being obsessed with the problem.

Rachel Olney  02:41

Yeah, I go back to this all the time when I'm talking to, you know, potential founders or people that are getting into startups is, it's really important to be deeply, deeply, deeply obsessed with the problem that you're solving. For me, finding that problem was really circuitous and unexpected. So my technical background. So really quick, I know you did a quick Geosite overview, but Geosite makes geospatial data usable for non geospatial users. As like a top contour of that. But I'm not from the geospatial industry, or the industries that we currently serve.

Callan Harrington  03:19

Before you continue to go into that. Can you explain to that what you just said, like I'm five?

Rachel Olney  03:25

Like, you're five? (laughs)

Callan Harrington  03:26

Like I'm five, like I'm five. (laughs)

Rachel Olney  03:27

Lots of satellites, lots of airplanes, lots of drones, they make tons of data. On top of that you have these brilliant people making climate models, taking geospatial data, and turning that into property characteristics, flood risk, fire risk, you name it, the amount of stuff we know about Earth is astounding. Using that data is really, really hard. So from a technical integration standpoint, the data is tricky to work with. And then from a knowing what to use standpoint. So if you today were like I want to know everything about this place that I'm deciding whether or not to live in Washington, I need to know if my house is gonna burn down, whether or not it's in good shape, you know, what climate risks are going to be there, you know, etc. Whatever your questions are, figuring out the right data sources to answer your questions is really difficult. So Geosite is the plumbing to do all of that. We suck all the data in, we suck all the analysis in, all the geospatial models, all of that. You can take all of this really rich data, right? And then fuse it together and put it into other systems that people are already using or even visualize it for them. Right. So what we do is we just make geospatial data more useful. That's our core thesis. And the whole reason that I started the company is because I'm obsessed with the problem, to come back to your question. So I did my bachelor's, master's and my PhD, have not turned in my dissertation yet, so I'm not a doctor yet, all in mechanical engineering. So that's my expertise, is really thinking about systems-wide engineering, and how things come together, and industrial IoT, as part of that. And at the same time, I did a big space study for the Air Force, just, you know, grad students have to make money, right. And the Air Force needed somebody to research the future of space. And I was like, great, I'm happy to do an overview analysis of the entire industry. And so between an understanding of industrial IoT, an understanding of the future of the space industry, and then some work I was doing with special operations, what I started to realize was, even though there was all this rich data, everybody was struggling to use it. And I didn't necessarily understand the data either, right, I wasn't some amazing geospatial practitioner, I didn't know the first thing about doing geospatial analysis. But what I really understood was, there are people with problems that needed geospatial data. And then there was data out there and the plumbing didn't exist, the only way to get access to that data was to have the expertise to know where to look and to know how to vet those data sources, how to combine them, how to actually extract the value from them. And you know, I'm literally laying there in bed at night, this is back in 2016, 2017. Just like mind blown that there are real world situations where people are injured or killed, or there are major problems, because people can't access data that already exists. It's already there. The analysis is there, the data is there, It all exists. But for bureaucratic and technical reasons, is too hard to access. And I just became totally obsessed with it. And also obsessed with how much brilliant data there was out there. And so even though I wasn't coming at it with a deep technical understanding, it was that understanding of the user and their problem that really drove me to start the company.

Callan Harrington  06:53

So I have a follow up question on this.

Rachel Olney  06:57

Yeah.

Callan Harrington  06:57

Was this a problem you cared about enough that if a company was solving this you would work for that company? Or did you have to lead the charge on this?

Rachel Olney  07:05

That's such a good question. So like I mentioned, I was doing that big space study for the Air Force. So this was before Space Force was the thing. And Air Force was doing a big study of every piece of the commercial space industry from launch providers all the way through communication, space based communication, space based imagery, analysis, you name it. And as part of that, I ended up really well connected in the industry. So I knew most of the geospatial companies out there. And so after I became obsessed with this problem, I reached out to everybody, was like, what are you doing? They'd be like, we're doing geospatial AI. By geospatial AI, what I mean is, people taking satellite imagery, and then telling you from that imagery, hey, there's vegetation encroachment issues, or there's roof condition issues, or, you know, X, Y, or Z property or terrain characteristics. And everybody was so excited about geospatial AI in 2018. This was the hot thing. So everybody would call me like, oh, no, we're doing this, we're doing that. And I'd be like, well, have you considered this? And we're like, well, that's not really our part of the market. So I genuinely tried. I tried to convince a bunch of different companies to focus on this part of the problem, the data integration and translation part of the problem. But because machine vision was so cool, that's really what everybody wanted to focus on. And I would have been happy to join a team doing it.

Callan Harrington  08:28

I think that's so interesting. And, well, here's what I'm curious about is, if- so, a lot of people were working on the AI component of this. And also just speak from like, the sales side. When you're selling AI, it's an easier sell, because people hear the name they know.

Rachel Olney  08:42

Yeah, it's shiny.

Callan Harrington  08:42

Yeah. Exactly. Right.

Rachel Olney  08:43

It's super shiny.

Callan Harrington  08:44

And sometimes it is- like it could do some, I mean, as we all know, generative AI can do some really, really, really cool stuff. What I'm curious about is, did you have any issues in some of those early sales because you weren't pitching AI? And you were selling something that was very practical, like this is something that can be used right away? Or did that end up helping?

Rachel Olney  09:04

Yeah, it takes a mechanical engineer to be like, forget the AI. We're doing plumbing, you know? Yeah. I had an advisor early on in my career. His name's Banny Banerjee. He's at the design school at Stanford. And he would always say, "pick the unsexy problem." We definitely picked, you know, the unsexy problem. Although now it's very shiny, because people have realized you can't use just one geospatial AI algorithm to solve all your problems, if you're a global company. You need a lot of different models, and a lot of different datasets, and they've started to realize that, but yeah, definitely in the beginning. And even now, what we look for is customers who already have enough experience with AI, and enough experience with leveraging this kind of data, that they know that there's no silver bullet. Right? When we talk to a potential customer, and they've never touched geospatial AI, they've never touched getting property characteristics, or parallel data, or anything from- or post catastrophe data even, from the use of remote sensing data. Usually we don't prioritize them, because they're gonna go chase those shiny objects. And so that's what they do. The good news is in terms of market timing, a lot of major companies were chasing those shiny objects in 2016 through 2018. And it takes a while for those cycles for them to come back. So right now we're at this really interesting moment, especially in the insurance industry, where most of the major carriers and reinsurers have leveraged a lot of this new cool data and realized, yes, this is very powerful for X geography and Y property type, right. And they know that, okay, this solves this piece of the problem. But we also have this problem, and this problem, and this problem, and this problem. And then they get really overwhelmed by the integration and procurement problem that they're faced with, to pull in all the different datasets that they need. And those are the people that we tend to talk to. So that way then we avoid the "oh, well, what's the AI?" Right? Because these are more sophisticated buyers, that understand the need for data normalization and integration, before it hits their systems. And so that's where we focus. What I would say is a lot of the insurance industry is there. I would say the utilities and infrastructure market, which is one of my favorites. That's my bread and butter. I cannot wait till the day we get to do infrastructure and utilities. You know, just go from big bureaucracy to big bureaucracy.

Callan Harrington  11:20

You love it. No question about it?

Rachel Olney  11:35

I don't mind it. It doesn't intimidate me like some founders, you know. I think bureaucracy is just process. That's all it is. You just have to be able to understand the process, and how the organization fits together, and each of its components. And that's fine. You just have to deal with it.

Callan Harrington  11:50

Can we talk about that a minute? Can we talk about like what you just said specifically? Because this is a huge thing, and especially if you're selling new tech to very, very large enterprises, ones where multiple decision makers have to be in there. How do you do that? What is your process for doing that specifically?

Rachel Olney  12:07

Yeah. So the first thing I would say is show some patience for the organization. I think it's easy to get really frustrated as a founder, because your timelines are so different than theirs. And so it can be really infuriating with how slow they are. When I first started working with the DoD, I was on an absolute tirade that the slowness of the Department of Defense is just pure problem. There's nothing good about it. Right. And the more I started to understand the DoD, which is one of the world's biggest bureaucracies, the more I understood the importance of inertia for organizations that people rely on. And so a lot of times in these really big industries, think utilities, or insurance. These are industries that people rely on. Like utilities is life or death. Like think of the mismanagement of electricity in Texas during the Big Freeze, people died, right? Like, there's a reason for some of these huge, huge industries, to have certain processes in place to ensure stability. And if you're a huge company, your fiduciary responsibility to shareholders is also a reason for stability, right? Like you need to be meticulous about things. So I think my advice to founders dealing with bureaucracies is first be sympathetic to why bureaucracy exists. Now, it's perfectly valid to be frustrated with outdated policy and rule sets that don't make sense, given modern technology. Like those, absolutely help people, you know, find those and uproot them. But the overall understanding that there's a reason for the slowness, and that reason is stability, gives you the equanimity to even approach the situation. From there, you know, if you're going to do sales to these bureaucracies, understanding that, okay, a bureaucracy has a lot of different parts. And those different parts have different reasons that they exist. And because they have different reasons that they exist, they're gonna have different things they need, right? So in insurance, you're going to have the IT and security team. There's certain things they need, things they need to see from your business, how you handle data, whether you have certifications, what are your qualifications to be handling data on their customers, right? If you're going to have that. Or on the locations of their customers, those sorts of things. You're going to have your business unit owner, who, they have a certain budget for data, or a certain budget for technology, or certain budget for whatever, and they have certain ROI that they're looking for. And so you have to understand what they need. And then you have to understand what the people they're reporting to need, right, and what the actual users need. And so I think the ability to sit there and understand all of the different competing demands within an organization is what's necessary to do those sales.

Callan Harrington  14:56

And I'm curious to how are you doing that? I mean, and of course, we've had conversations in the past in the insurance industry. And I totally agree with you. I love going after those-

Rachel Olney  15:07

Whales.

Callan Harrington  15:07

Yeah. And especially if they have a high barrier of entry, right? Insurance is a great example, because the procurement process might be a year long. And what you're describing is exactly how you shorten the procurement process. You're getting the goals of all the different stakeholders that you can essentially circle back to.

Rachel Olney  15:22

Exactly.

Callan Harrington  15:23

I'm curious, are you setting up one-on-ones with each of those different stakeholders? What's your process for doing that?

Rachel Olney  15:29

Yeah, so that really depends on the organization, right? Like no sale looks the same when you're in enterprise sales, because every organization is different. So it may be that you're leveraging the budget of that individual business unit. Great. Your number of stakeholders just went down. You have to make sure that you've bought in everybody in that business unit, and that you understand the other people that are gonna have to check off that you're okay, the procurement teams, the security teams, all of that stuff, those are your stakeholders, and that's simpler, right? If you're talking about a contract that's more complex, and you're gonna have multiple parties in it, there's a couple different options. At the end of the day, I think it's good to find the time to sit down with each of the people in the organization, and make sure that they understand that you understand that they have things they need, right? That's thing number one is, I'd be like, here's this engagement that we're planning on with this business unit owner who's bought in. They've introduced me to you, because here's what I understand you do as part of the organization. Let them explain whether you're right or wrong. People love expanding on things, it's harder to come in cold. So you sit down with them, here's what you do. And then you say, here's what we're planning to work on with this business unit owner. Our question is, are there ways that we can leverage what we're doing with them to help with anything you're working on? Right? Like, what are your current priorities, and I'm really blunt with people about, hey, if one of the things we're doing is not a part of one of your current priorities, let's make sure not to waste your time, like just achieving your current priorities, probably has you and your team at capacity. If what we're doing is not your current priority, let's punt by six months, right? There are other people that we can talk to, we have this project with the other business unit owner, we'll keep you informed of what we're doing. Within six months, we'll circle back, and we'll see if you're ready for these next steps. Right. And this is the case with one of our current customers that we've done, we've been really successful with, where we have a bunch of activity with certain parts of the business, and then other parts of the business, we're keeping informed as we go, right. And that's how you start to do it. So that's if you have one business unit. If you're trying to enter with a bunch of different stakeholders, you have to make sure that you have high level organizational buy in on the vision. So an example of that would be, we work with carriers who, like I said, have dabbled in using geospatial data, right. They've used property characteristics from a geospatial AI company. Maybe they've used a few new post catastrophe models, especially to look at damage, you know. They've dabbled in the industry, and what they buy into is the overall vision of, by working with Geosite, we have future-proofed our need for geospatial data. Because Geosite can continually bring in whatever the latest greatest is, whatever it is we need, select from all of that and feed it into our process. So there has to be some sort of deep organizational buy in that where they want to go, maps with what you do, and that you're going to help them get there. And then it becomes a really fun, nightmarish exercise with the rest of the organization, to good idea fairy all the different ways to first engage. And then it's your job as a salesperson, or as a founder, to figure out which of those do you engage in first, and which of them have the most organizational impact get you in on the right foot. Hopefully, you have an internal stakeholder who cares enough about the long term vision that they're willing to help you select those, so you don't get distracted by the like- I think one of the carriers we're speaking to, there's basically twenty-five different possible projects to work on, right off the bat. But you're not gonna work on all twenty-five. First, you have to pick the right the right ones to engage in.

Callan Harrington  19:19

One of the things that you said, right, in particular, you talked about when you're talking to a different business unit that you got referred into, and you find out it's not a top priority. 98% of people won't punt that. 98% of people will try to sell why it is a top priority.

Rachel Olney  19:39

Yeah.

Callan Harrington  19:39

And that will kill a deal really fast.

Rachel Olney  19:42

It'll kill the deal, because what it shows is you don't respect their time, and you don't respect that they do know their priorities. Like one thing we'll do is say, hey, here are things that we've seen in the past are good to think about before we do X, right? Like let's say X is the engagement that you would have with that customer, we're gonna provide you with this service, or this piece of technology, or this data. Ahead of that, what we've seen be helpful is these things. Are you ready to start those things, or are those also down the line, right? And we've had that conversation. So that's why like, in the case of Geosite, we can't just throw people in the deep end with all of the data that's in the world, and everything that they can possibly want. That's too much. And so one thing that we've learned to do is to preempt that with a value engineering process where we say, let's make sure we understand how your actual unit economics work. And we understand what the price point is for the things that you might need. And that way, then, once you are ready, we know exactly what blend of data is going to be valuable to your underwriting process, or to your claims process, or to your whatever. And usually they're like, oh, yeah, that's gonna take time to figure out. Okay, actually, I can connect you with so and so on our team whose job it is to figure that out first, before we get to implementation, right. And so if it's a big enterprise deal, where there's a lot of moving pieces in that deal, what you can sometimes do is bring forward that, let's start figuring things out part of it without trying to pressure them to start using the data or start using the tech.

Callan Harrington  21:18

Yeah, so this is gonna be a little bit of a pivot.  But I wanted to dovetail on this, one of the things that I've heard you said in the past, and I thought was really, really, really interesting was, you said, to turn strengths into superpowers, as opposed to focusing on weaknesses. And you mentioned, and this is why I kind of said it was kind of linked to this, that one of your superpowers is wrangling and wrangling these different pieces together.

Rachel Olney  21:20

Yeah. Yeah.

Callan Harrington  21:40

One of the things I'm curious about is, because this is pulled from interview you did a few years ago, is that still your main belief in turning strengths into superpowers as opposed to focusing on those weaknesses?

Rachel Olney  21:52

Yeah, it's a good question. I think it came in the context of, if you're going to start a business, you're gonna do anything really hard, like think of an Olympic athlete. They're not going to pick a sport that they're not really, really, really strong at, right? It's the same with profession, like any profession. And so for Geosite, it's necessary to understand the needs of a bunch of different people, and be able to weave that into one specific initial engagement. That holds true. And in geospatial. I'm not a geospatial analyst. That's my weakness, right? Like, we're a geospatial company. But I've brilliant, brilliant, brilliant, geospatial experts across my company who do that. In insurance, you have to wrangle these people, you have to hold all that complexity in your mind. Hopefully not your mind, your documentation sometimes, too. I'm really notorious about this actually, don't do what I do do what I say, you know. What is that old adage? Because there are tools out there for mapping these kinds of things, especially for sales teams, that can be really helpful. What we'll do is we'll write down like here are all of our stakeholders, here's what they care about, here's the way that we interact or don't interact with that. And here's the path forward to find something that's going to create value inside their organization. So I don't know if that answers your question. But yeah, wrangling is a huge skill set that you have to have if you're doing enterprise sales.

Callan Harrington  23:16

Well, I'm curious, how do you find your superpowers? How do you find your strengths? I'm going through an exercise right now. So this is very, very top of mind. Because actually, I will say, different a little bit than what you mentioned, I would pick positions to help round my skill set out as opposed to just go- I'll give you an example. I really wanted to be CEO, and I was talking to a mentor of mine. And he goes, I said, yeah, I think I need to go to COO before going to CEO, because I was a VP of sales. He goes no, get a bigger sales job, and then crush it there, and then go take the CEO role.

Rachel Olney  23:50

Yeah.

Callan Harrington  23:50

That didn't even cross my mind at that time.  But now it's hitting me. So I'm curious, how do you figure that out? How do you figure your strengths out?

Rachel Olney  23:53

Interesting. Well, I think specific roles and titles is one piece of it. I was actually talking to a close friend about this the other day. My COO and my CTO are the perfect COO and CTO for me as a CEO. Right? So I think in any executive team, it's really about the matching of skills. And so a job as a CEO can be many different things. When we hired our CTO, Daniela, it was this moment when I realized, I think this person might love what we do as much as I do. It was the first time I had met someone who is maniacally obsessed with making geospatial data more usable. And so what that did was it complemented my need for somebody who could help lead our product. Because to lead product in any sort of early stage company, you have to be obsessed with the problem. Back to that beginning thing, right? And so the CEO role can differ, but the thing that you have to know before you do anything is, like you said, what are your strengths? One of the most elucidating things can be asking other people. That's definitely a step I would recommend. It might be very uncomfortable. But asking other people, where do you think my strengths are, can be helpful. And pick people who are going to be blunt with you, not ones who are just going to inflate your ego. Hopefully you have good enough, close enough professional and personal friends, that they will be honest with you, and tell you, hey, you're really good at this, you're not really good at this. Right? And inside of even our own company, we're very open about those sorts of things. And we laugh at our weaknesses, right? So even the other day, I was talking to her head of customer success, and she was like, well, you're gonna do this Rachel thing, you know, like this thing that I do that disrupts her ability to do her job. But she and I balance each other in terms of, you know, certain ways that we engage with customers. And it's good to know your flaws and your skill sets. What I would also say is, there's a difference between what you're good at and what you enjoy. And being able to differentiate between those, very honestly with yourself, is important. I'll give a very clear example. Most people think I'm an extrovert. They're like, wow, Rachel's so good at peopling. Right? And I am. I can extrovert with the best of them. I can, you know, you and I see each other at conferences. I can go to conferences, I can meet with everybody, I can talk to people about my passion for my company. But I'm actually I'm just barely over on the introverted side. And so it's very exhausting for me, right. And so, with understanding that about myself, I've created ways to surround myself with people who can compliment me. My CTO is unstoppable. She can go from one thing to the next thing, to the next thing, to the next thing, and be like, what's next. And she's just- her energy for engaging with people, and really deeply engaging with people, not like niceties, like asking people, where's the future of this piece of the industry, that piece, what's happening with this technology, whatever. Her ability to, like, rapidly absorb information is astounding. And so she's very complimentary to me, right? Public speaking, I have no fear of public speaking. And I just do it very effortlessly. So my team will go behind my back and sign me up for speaking opportunities. Because I myself won't opt in, to be like, oh, I want to go to this place where there's lots of people. But they'll be like, hey, Rachel, you're on this panel. And I'm like, okay, that's fine, easy. So it's important to understand the little nuances of things where you're like, I'm good at this, but I don't enjoy it, so it's going to be de-energizing. This other thing, I'm very good at it, and it's very energizing. And then finding the right balance there, including what's valuable, right? It's important.

Callan Harrington  27:45

Well, and it's the number one thing on my mind right now.

Rachel Olney  27:48

Yeah.

Callan Harrington  27:48

And what you just described is hitting home, because I heard this described by Matt Mochary, in the Mochary Method, he put this in there. I think this was based on research from the author, Gay Hendricks, and there's these four zones, you've got the zone of incompetence, zone of competence, zone of excellence, and zone of genius. And one of the things that you just described, I thought was really interesting was the zone of excellence is something that you're above average at, but you really don't like doing very much. And zone of genius is something that is a strength, and you can do it all day.

Rachel Olney  28:23

Yeah.

Callan Harrington  28:23

It's basically how do you spend 80% of more of your time in that zone of genius?

Rachel Olney  28:29

Yeah.

Callan Harrington  28:29

And then the other thing that you mentioned, which I think is dead on, and this is what I struggled with, because I was trying to think of, it's hard to label your own strengths. It's hard to say, oh, I'm really good at this.

Rachel Olney  28:39

Yeah.

Callan Harrington  28:39

Unless you're a total narcissist, then you've got a million strengths.

Rachel Olney  28:42

But there's a difference between just creating a laundry list to make yourself feel good, and being like, here are the places where every single time, like you have empirical data, like, there have been times where you've done a thing, and people are like, wow, what? How did you do that? Right? Or where did that come from? And then you can sit back and go, oh, that was unexpectedly well done. And then you can reflect on that. And what that takes is, to your point earlier about taking on roles that were helping you expand experimentation, so I'm really big on people prototyping their lives. This is a very, very Stanford thing. There's like an entire course on prototyping your own life, and trying out, in small ways, different careers. So I, when I was in grad school, you know, almost became a patent agent. I love- patents are so clever. Like to create a truly powerful patent, it's very narrow and very simple. But its simplicity is what makes it powerful. So there's this very beautiful world of like trying to figure out what is the core of some piece of technology, what's the truly valuable bit, and I loved it. And I was like, but I don't know that this is a career I would want. So I convinced a patent agent firm to take me on for two weeks, give me one patent to work on or a couple of patents to work on. And I would work for them for free, do a bunch of work. And I would come to the office every day. And I would just kind of prototype for a few weeks, like, what would this look like as an actual job. And I hated it. Oh, my God, I hated it. It was not for me. But before I had that experience, there were parts of that that I loved. Right? But there were much bigger parts of it that I didn't. And I would, you know, I think I could have figured that out, but it was much faster to just spend a couple of weeks trying it out. And so I think, especially when people are early in their career, or even while they're in school, if they have the time to moonlight doing some things, that experimentation is really powerful. And that's really where you find, you know, what are your superpowers. And I realized one of the superpowers was holding all that complexity in my head. I can understand what fifteen different people in an organization need in order for a project to be successful. And I can create a single path forward, right? I can get a roomful of people that are each talking about their own little bubble, and totally talking past each other, I have a skill of being like, okay, if I talk about this in this way, and not in this way, and I bring this in, I'm gonna be able to get everybody in one direction. Right. And that's a specific skill set. Like you said, the wrangling is a skill set. And I wouldn't have known I was good at that unless I was put in situations where I tried it. So yeah, got to try a bunch of different stuff. And then you have to actually be introspective, like, sit with yourself and think, what do I actually enjoy? Which is, most people don't give themselves the time to do that.

Callan Harrington  31:31

Oh, yeah. And they underestimate. One of the things I think, so I'm going through this exercise now, it's called the reflective best self exercise. And it's exactly what you described.

Rachel Olney  31:39

Yeah.

Callan Harrington  31:39

You ask former co workers, friends, family, those are the best ones. They're the most blunt. And you put together, they give a couple of stories when you were at your best self, and then they share what characteristics, what skills and stuff, are there. And I just got them all. I reviewed them all yesterday. And I was like, man, one of the things I was blown away is the things that you think are very non important, and how much other people value those things, and why that's so hard to come up with some of those strengths. And you were just talking about pretty much all of it.

Rachel Olney  32:09

Well, it's because you're with yourself all the time, you don't notice them. Right? Like when you walk from your house to your car, you don't notice the sky is blue. It's always blue. You're not gonna like-

Callan Harrington  32:19

Not in Columbus, it's not. (laughs)

Rachel Olney  32:21

Well, that's fair. Right now, actually, outside, it's pretty gray here right now. But either way, you know what I'm saying? You've been in those things for so long, of course you devalue them. But one of the important things, and I don't know that process that you're going through, is I would emphasize the need for lots of different viewpoints. Because what you're looking for is, if you're a data scientist, you don't want none of one, you want a large sample set, and then you see what rises from that sample set. What are the commonalities across all of those where it's like, oh, there's pretty good consensus that I'm good at this thing. Crazy.

Callan Harrington  32:52

Yeah. And you'll appreciate this. It was the University of Michigan, Stanford, and Harvard that created this.

Rachel Olney  32:58

Nice.

Callan Harrington  32:59

And yeah, you need fifteen minimum, twenty is ideal. And I think I had like twenty-two. And it was really, really interesting.

Rachel Olney  33:05

So informative. And one of my advisors, they also made us go through this exercise of- This was early in our career, like doing a bunch of different things that I'm really curious as far as process. One was just writing down everything you like, and everything you don't like, like literally just sitting there and brainstorming a giant list. I like coffee with cream. I don't really prefer, you know, black coffee. I like- it can be like the silliest things. And then, like, what is the perfect day? What does it look like? What is your dream job? Like if you could actually have any job on the planet, what would it be? And it's a harder question than you think, having to think through like, what is my actual dream job? And so I think that it's worth spending that time.

Callan Harrington  33:51

Yeah. I love that. I could talk about this all day. But one of the things that I want to move to is, you know, we talked a lot about this, we talked about how the strengths impacted and a lot of the positives that have gone on with founding Geosite. What have been those challenges? I would say in particular, what have been the unexpected challenges that you had? And let's start with kind of the in the earliest stages.

Rachel Olney  34:12

Yeah, I think. So, I'm a solo founder, which is unusual. There aren't that many solo founders. The reason I chose to be a solo founder was one of the number one reasons that startups don't succeed in the first two years is co founder conflict. And I think people underestimate how important picking the right partners is. And I knew that the speed with which the company would start moving, versus me being able to find exactly the right people to start the company with, were in opposition. I knew the industry. We already had interest from special operations to get going on some research and development, and I could manage contractors or just engineers or teammates myself. But what I couldn't do is magically make the perfect co founder appear. And that was, in the very early days, the most stressful part of starting the company was finding the right people to start the company with. Because again, you want people who complement your skill set, who complement your demeanor, honestly, who in every way make you a better founder, and you make them a better founder, right in the same way that you look for life partner, right. And if you're running a startup, especially enterprise SaaS, you're looking at a ten year commitment to this person, like you're going to be working with this person every single day for ten years. You better really like and trust and want to be around that person. And I think it's easy now. Like, I love my team, oh my gosh, like, I love my team, so much every single one of them. And I'm so proud. And so humbled. It's the first time I've had impostor syndrome, is when I think about my team. Like, they're so amazing. They're so amazing. But it was a long road to get to there. And my first CTO, he was phenomenal, and exactly the CTO that we needed, but he wasn't maniacally in love with the problem we solve. He believed in me as a CEO, he believed in our tech, he believed in our market positioning, and was excellent, right. But he had excellence, but not genius, right? Like, excellence in the role, versus our new CTO has that genius, right? She lives and breathes this industry. It is her entire brain is dedicated to what is the future of spatial data use across every industry. She loves that, right? So finding those people, I think it's okay to also accept, okay, this person isn't perfect. But here are their gaps. Here's the way I fill them. Right. So with my first CTO, you know, I filled the gap of passion for the problem and what we're doing, and he filled the gap of technical expertise and ability to execute. I can't build a geospatial software system. I don't know how to do that. Right. So we were perfectly complementary. So I think that's the big first hurdle. The second one is, it can come in two different ways. Depending on why you founded the company, I recommend back to the beginning point, start a company because there's a market or user problem that exists and is valuable to solve, like, people are willing to pay money to solve the problem. Not just that would be a nice to have. But there's an actual, viable reason for why this problem should be solved. And there's an ROI to it being solved. If you start from there, the problem becomes what's the right exact product or solution. That's much easier. That's the landscape we were in. We went through, I think, three different major iterations of what our solution on the market was. But the problem we solve stayed the same. That's much easier than, there are a lot of founders that will start a company because they are obsessed with some new technology, or some new capability that they can build. And then they're searching for problems where there's an ROI for paying for that solution. That's much harder, because you're a hammer in search of a nail, versus being the person who's building something and having lots of different options for how to build that. Right?

Callan Harrington  38:18

Yeah, I love how you just put that. I actually hadn't thought about it that way. I'm personally very problem focused as well. And I get obsessed with certain problems. But you are right, right, because so much technology will go out of style. It'll come in, because technology is just it evolves so quickly, that so much of that is going to be outdated at that point. And you are right, it is very much a hammer looking for a nail.

Rachel Olney  38:41

Yeah.

Callan Harrington  38:42

As opposed to having the nail. That's a great way of putting it.

Rachel Olney  38:44

Yeah. I watch a lot of foundersnd , and, you know, early startup operators, struggling to figure out where to implement their technology or who will pay for it. Versus starting with, hey, there's this huge problem. If we have a solution to it, people will pay for it.

Callan Harrington  39:01

I love that. So what comes next? What's next for you? What's next for Geosite on this journey?

Rachel Olney  39:05

Yeah. We never expected to get into the insurance industry. I honestly didn't know anything about insurance.

Callan Harrington  39:10

Nobody ever does, ever.

Rachel Olney  39:12

I know. I know. That's the cliche. Right.

Callan Harrington  39:15

But it's so accurate.

Rachel Olney  39:17

It's so accurate. I mean, we started in defense. So our biggest defense contract currently is for civilian search and rescue. So someone who gets lost at Yosemite, or in Alaska, or anywhere in the continental US or Alaska. There's a team called the Air Force Rescue Coordination Center. They triage search and rescue at the federal level. Before using our platform, search and rescue was actually done using Excel spreadsheets. So yeah, they'd copy paste some lat-longs, and call some people, and I mean, what I want to do is give credit to the airmen and women who did it. Like phenomenal, truly phenomenal, triaging all search and rescue using Excel spreadsheets is crazy.

Callan Harrington  40:05

It's pretty insane when you describe it like that.

Rachel Olney  40:07

It's insane.

Callan Harrington  40:08

Yeah, absolutely.

Rachel Olney  40:08

It's so impressive. So on government hardware, you know, these computers can only open one Excel spreadsheet at a time.

Callan Harrington  40:15

Yeah, Windows, Windows XP. I gotcha.

Rachel Olney  40:18

Yeah. I mean, phenomenal from a like personnel perspective, like what they were able to do. But anyways, so we hold that contract now. So, you know, not Excel spreadsheets anymore. And that's 11,000 Search and Rescue incidents, and 370 of those are life saving operations per year. So that's really the world we started in, was government and security. And so we'll continue our work there. Insurance we really entered about two years ago. And it's been bananas. So what's next for us is just continuing to scale in insurance, it's absorbing, you know, most of our capacity for growth right now. Because, you know, with the increase in frequency and severity of natural catastrophes, and the rise of more accurate data and models, we're really at this inflection point where the way that risk and mitigation of risk is handled across the insurance industry is rapidly changing. And it's a lot of fun for us to be in the market right now. Because the use of new data sources is skyrocketing. And we've actually been able to have real world impact with our platform already. Even having just stepped into the industry. Like there was massive flooding in southern Australia. And there was a Australian insurer that we were working with, to take all the flooding data, incorporate that with all of their policy, location data updated, geocoding, etc. And they were doing automatic payouts to people who were evacuated. So while you're evacuated, even if you are going to get your claim paid out on your property, at some point, a lot of people end up in bankruptcy or financial ruin during that evacuation period. And one of the largest defaults for mortgage payments is actually natural catastrophes. Because even if you get that claims payout from an insurance company, the financial damage of going through an event like that is so astounding. And so their ability to step in and start helping people during the crisis, rather than after, was huge. And so, and not just huge from a human impact perspective, but from an actual dollar perspective. If you look at the customer acquisition cost for an insurance carrier, keeping people happy during the catastrophe is really important. And then you getting to insure that freshly built home with a new roof is great. You want to keep that customer. If you're gonna keep any customer in that region, you want it to be the one that you've just repaired everything for, because they're going to be a lower risk overall. And so there's all of these financial reasons that align with doing good, that we've loved in insurance. And I think there's just more interesting stuff to come.

Callan Harrington  43:11

It's funny, I didn't even think about this, but it literally ties back to exactly what we did when we started this and the obsession with the problem. And what you just described, I think is really interesting, because I don't know that the majority of people would say, oh, geospatial data, and then automatically associate it with the impact that you just mentioned. I think that's really, really cool. Rachel, last question I have for you is, if you can have a conversation with your younger self, age totally up to you, what would that conversation be? What advice would you give them?

Rachel Olney  43:40

That's a really funny question. I used to be a big planner. I love a plan. Back to like I don't mind bureaucracies. I don't think I, you know, thrive in them. But I don't mind them, because I understand them. I was always that kid with like a ten year plan. Mind you, nothing goes according to plan. Did I think I was a startup company? Absolutely not. Like did I- especially a geospatial company? No.There's so much that didn't go according to plan. I think what I would tell my younger self is, pick something you love and don't try to over stress about it. And I think I was so stressed about figuring out every single step. And the best advice I've gotten on the right amount of planning actually comes from that same advisor who said to pick the unsexy problems. He actually has a TED talk on- I don't know what his TED talk is on. I'll have to look it up. You'll have to look it up.

Callan Harrington  44:33

I'll take a look.

Rachel Olney  44:34

His name is Banny Banerjee, like I said, but his advice when it came to planning your life was, it's a lot like climbing a mountain. You know which mountain you're trying to climb, right? Like you know yourself and what you care about enough that you know what the big rocks are. You know what matters to you. More so than like where you'll end up right? But you know what matters to you. And you can see maybe the next 100 meters in front of you. So you can plan for those 100 meters. You can look at the near future. And you can think about where you want to end up. And don't worry about what's in between. Like, at the end of the day, if you know overall, where you're going and what matters to you, and you're being smart about what you're doing now, it's gonna be fine. For younger me, that would be a really hard thing to buy into. I think. So I'd try to tell her, you don't have to plan everything.

Callan Harrington  45:21

I love that. I think that's such excellent advice. If I would have took my advice on my ten year plan in high school, I know this because I got one of those letters that you wrote to yourself, and it said that I'm going to be an attorney that has an Escalade on twenty-two inch spinning rims. And I'm very happy that I went in a different direction.

Rachel Olney  45:40

Exactly, exactly like. Well, and, I mean, think of like my dedication to my plan. Like I almost, and will eventually, finish the paper to have a PhD in mechanical engineering. I do no mechanical engineering, like other than hobbies around the house, right? I specialized in manufacturing, I was fluent in Mandarin. I was 100% sure I was gonna go into the world of, you know, the future of manufacturing. And that was that, but it took a total different turn.

Callan Harrington  46:09

Rachel, what are the hobbies around the house where you are using mechanical engineering? (laughs)

Rachel Olney  46:16

(laughs) So just this weekend, my partner and I were welding a new part for a Jeep, to where if we get stuck in a ravine, we can pull the Jeep out back. So we have a winch on the front, you need to pull the Jeep up out of a ravine. But if you're going backwards, you need a winch going around to the other side. So he's also a mechanical engineer. So in any given weekend, there's probably some welding, or power tools, or all sorts of things.

Callan Harrington  46:43

If there's one thing I've taken from this interview, it is you have a considerably more interesting life than I do.

Rachel Olney  46:50

I think people should be handy. I think it's a nice skill.

Callan Harrington  46:54

I love it. Rachel, this has been a blast. Thank you so much for coming on. I really enjoyed this.

Rachel Olney  46:58

Yeah. Thanks, Callan.

Callan Harrington  46:59

Absolutely.  I hope you enjoyed Rachel and I's conversation. If there's one thing I took away from this episode, it's how important it is to be obsessed with the problem you're solving. If you want to learn more about Rachel, you could find her on LinkedIn in the show notes. Also, if you liked this episode, you find me on LinkedIn to let me know. And if you really want to support the show, a review on Apple Podcasts, or Spotify is very much appreciated. Thanks for listening, everybody, and I'll see you next week.