A Product Market Fit Show | Startup Podcast for Founders
00:06:56 · Pablo Srugo, Wardah Inam
[00:06:56] S1: I think that’s true. It’s a competitive landscape and it’s really not like there’s skill, and then there’s hard work, and there’s going to be people that do both. Obviously, if you’re not one of those people, your odds of success are probably lower than somebody that’s potentially competing with you and is equally skillful, but also just putting in a lot more work. There’s balances all these things. [00:07:14] S0: Pablo, I feel especially in the beginning, it’s all about learning. Again, there are no shortcuts to learning as well. You need to learn and you need to put yourself in different experiences. You need to understand different viewpoints. You need to understand your customers, and you have to have conversations. That’s just time that it takes to learn everything new. The faster you learn, the faster you execute, the faster you can make progress as well and learn from the mistakes, because everybody’s going to make mistakes. I think it’s almost inherit to – again, you could get very lucky with everything just working, but most things just don’t work. If they were that easy, then it would have been done before. [00:07:57] S1: Back to the storyline, you’re obsessed about dentistry. You’ve unlocked some potential, let’s say problems, which is that it’s more art than science. But do you have an actual startup idea at this point when you start thinking about, okay, maybe I need to get out of my day job because I’m just spending so much time over here?
00:08:15 · Wardah Inam
[00:08:15] S0: This is one I don’t recommend, which is I did not. I had a thesis, and my thesis was that if I did not do any – just to give you a sense. When I was understanding the field more, what I realized was that there was a challenge in terms of how dental data was being analyzed, how diagnosis was happening. The way the industry was with private equity entrance into the space, say 10, 15 years ago, with a lot of money coming into the space with consolidation happening, and not having ways of measuring clinical quality. There were ways of measuring financial performance. There was no way of measuring clinical quality in dental practices. I felt that if we did not do anything about it, we would head in a very wrong direction. This was the time that dental service organizations with this consolidation that was happening, I think everybody realized this was the future. This was going to continue. Earlier, there was a lot of resistance to the consolidation that was happening. But then I think at the time that I started looking into it, I think people started realizing, because of the economics, this is going to happen more and more. If this is the trend that we’re going to go on, these groups do need a way to measure clinical quality. If they cannot measure clinical performance and clinical quality, they cannot improve it. That’s where Overjet started, or at least the idea of Overjet started to form in my head. It was almost I had to do something about it, so I quit my job and started shadowing dentists. There was not a name for it. There was no formation that happened at that time. It was literally for me to understand more of the space, and I had to go and actually see what was happening in dental practices.
00:10:00 · Pablo Srugo, Wardah Inam
[00:10:00] S1: How did you do that? How did you let dentists let you into their practice just so you could watch? [00:10:05] S0: I did not have a good network there. I was trying to find dentists first. I think the first dentist connected with was in my building. The second dentist was literally, I was doing an Uber pool ride, and the person sitting next to me, I got talking. They asked me what I was doing. I told them I was exploring the dental space, and they introduced me to a dentist. That dentist ended up giving us our first tranche of data. I think it was more about just talking to anybody what I was working on and the problem that we were facing. [00:10:45] S1: What was in it for them? Were they just being nice or was it just like – did you give something in exchange? They would get the alpha version if you ended up building something? How did you even convince them to do that? [00:10:55] S0: No, I think they actually believed in the problem. I think for me, when I was stating the problem to them, I think they all saw the problem as the way I was seeing it. They didn’t know what the solution would look like, but they wanted to be part of the solving the problem. I will tell you this, the first time somebody shared that data with me, they actually said, no, thank you so much for working on this problem. That’s how they shared the information. It was a problem, I think, that people realized, and the fact that I was working on it.
00:10:55 · Wardah Inam, Pablo Srugo
[00:10:55] S0: No, I think they actually believed in the problem. I think for me, when I was stating the problem to them, I think they all saw the problem as the way I was seeing it. They didn’t know what the solution would look like, but they wanted to be part of the solving the problem. I will tell you this, the first time somebody shared that data with me, they actually said, no, thank you so much for working on this problem. That’s how they shared the information. It was a problem, I think, that people realized, and the fact that I was working on it. [00:11:27] S1: What were some of the key things that you discovered in those early days through the work you were doing, through the research you were doing?
00:11:34 · Wardah Inam
[00:11:34] S0: The way we started building this out was trying to understand the problem. We didn’t know that this could be done. We didn’t know what was possible and what was not possible. A lot of it was once we got the data in dental practices, we started just doing data analysis of and saying, okay, what is the prevalence of this disease? What does this look like? Why are people diagnosing a certain way? There was a lot of things that we found. For example, one of the things that’s key to Overjet even now is everybody thinks that there’s more overdiagnosis in dentistry than underdiagnosis. If I chat with most people, they will say, yes, there is an incentive for dentists to produce more. That is why telling you that there are conditions there, there’s the trust level suffers because of it. There is significant amount more underdiagnosis in dentistry and treatments that are not happening than overdiagnosis. That we found by actually analyzing the data and looking at the rates that CDC was saying in terms of prevalence of a certain disease, what we were finding, and how much it was getting diagnosed. I think there was a lot of interesting things that we found just from the data itself. Being in the chair, you can realize that dentist job might be tough. But if you are observing how they’re interacting with not only you, but other patients at the same time that you are in the practice, you start realizing how tough that job really is. Especially coming from the MRI side where radiologists are spending, a lot of time looking at x-rays and other MRI data, and usually in darker rooms, and with the right monitors, et cetera, that’s not what dentists are utilizing. They’re moving rooms. They’re changing lightning conditions. They’re having these old monitors that they’re making diagnosis on. There’s a lot of interesting learnings that I don’t think that the industry knew and had the belief in. But I think as we started to look at it from the data, and as a data problem, we started saying, the data quality is bad. The way things are being monitored is bad. The monitors that they have is bad. It’s not like dentists don’t want to do the right thing. The tools are not there, and we can do something about it.
00:13:54 · Pablo Srugo
[00:13:54] S1: What was that first solution that you conceived of? Because today, my understanding is you just automate that. You look at images and use AI to understand if there’s something wrong or make diagnoses. Was that the idea that you had at that point?