In this episode of Veteran Led, we talk with Dr. Andy Moye, a Veteran who has transitioned from military intelligence to pioneering AI applications in healthcare. Andy shares his journey of working alongside world-renowned doctors and his current mission to leverage AI in improving patient outcomes. He discusses the challenges and opportunities in applying artificial intelligence to complex medical decisions, particularly in oncology and cardiology. Andy explains how AI is being used to assist pathologists in cancer detection, potentially reducing misdiagnosis rates by up to 20%. He also dives into the development of AI tools that help doctors make informed decisions for complex patient cases by analyzing vast pools of medical data.
Connect with Dr. Moye on LinkedIn.
Learn more about Tempus_AI: https://www.tempus.com/​
Catch Andy at the Canada Healthcare Innovation Summit.
When you talk about artificial intelligence, typically what you’re talking about is machine learning. You’re essentially teaching the machine to learn something and then predict something. Ultimately, what AI is really very good at is pattern matching. It’s just very complex pattern matching.
Welcome to Veteran Led. Today’s guest is Dr. Andy Moye. In this episode, we’ll be talking about Artificial Intelligence startups, specifically in the medical technology space. Dr. Andy Moye is the SVP and GM of data products at Tempus AI, which includes pharmaceutical, biotech, and life science partners. Andy is a former naval aviator who has his MBA and a PhD in health economics and decision making. Welcome to the show, Dr. Moye.
You’re in an amazing space. You’re in the biotech space, in a time when people are extremely excited about artificial intelligence. How did you get involved in it?
Yeah, it wasn’t like when I was a kid. I can’t wait to get into biotech and pharma and AI. I wanted to be a soldier like my dad. I’m sure we’ll get into that. But yeah, it’s been a really wild ride. Fortunately for me, everything I’ve always wanted to do has been about service. How can I continue to make as big an impact on people as possible. Fortunately, after I got out of military, I got into this diagnostic space, started really understanding how cancer gets diagnosed in the U.S., which is not well, by the way. We’ll talk about that. The manual processes that go to that. Over the course of 20 years, I’ve really found myself at the forefront, the leading edge of all this technology where we’re really trying to drag doctors and pharmaceutical companies and researchers into the future, where the technology is able to help cancer patients get the right drug, help drug companies develop the right drugs so that they don’t fail in clinical trials. It’s been a little bit lucky in a lot of ways, but I think a lot of it just really came from like, Hey, I just want to serve.
How can I serve people? How can I continue to serve people?
Yeah, let’s get back to that service. As you said, you wanted to be a soldier, but you didn’t make it. Instead, you were a naval aviator. So, you flew in the Navy, but you got to help people, and you were there in service when 9/11 happened. Take us back to that time.
Yeah, I was deployed 9/11. I was a young… I was just out of flight school. You spend about a year and a half, two years in flight school. They send you off to a squadron. You don’t know anything, really. You think you do because you can fly a plane, but you go off. I was flying with a Korean. It’s funny. People forget. We were still engaged in the Kosovo Bosnia conflict even at the end of the ’90s. So, we were doing these. I flew an airplane called the P-3 Orion. The P-3 Orion was a hold over aircraft from the Cold War. It’s generally designed…It’s a crew-based aircraft, 11 people on the aircraft. They call them combat air crews. The airplane is designed to hunt subs. That’s what you do or naval boat. But after the fall of the Soviet Union, they had to repurpose the aircraft a little bit, and they ended up doing a lot of what they call ISR. Intelligence, surveillance, reconnaissance. We were doing a lot of that. We were deployed in Sigonella in Italy, and we were doing these missions up in the Adriatic and Kosovo, that stuff. We just happened to be off.
The crew just happened to be off that day. We’re over at the exchange, standing there looking at the TVs like a bunch of dummies and watching the towers fall. And fortunately, because I was young and dumb, didn’t know anything, my mission commander looked over at us and said, Guys, we got to go. What are we doing standing here? It’s funny because in Sig, there’s actually an Italian base and an American base, and we were over on the American base, but we were actually stationed on the Italian base. And so, we had to get off the American base, which was next to impossible. Some poor MP trying to kill us because she didn’t know what was going on. But we’re trying to explain to her we have to get off this base right now. We got off the base, go to the Italian base. That was another problem, to try and get back on to the Italian base. But we did, man. Then, like anybody else who served during that time, just no idea what’s happening. We stood down all flights for about four or five days until the orders could come in. We spent the rest of that deployment really doing terrorist hunting.
We spent a lot of time combing the Coast of Syria, things like that, looking for boats. We did a lot of what’s called maritime interdiction ops with the Seals, which was fun because you’d get over top of a boat and Seals would take the whole thing down. We got to watch it from 10,000 feet and those kind of things. We did that all during 9/11, and then I was deployed again right before we went into Iraq in 2003.
Now, you’re in the biotech space. I want to take you that because also you chose to go into the medical field to continue to help people and continue to give back, but you didn’t choose the easy route. I mean, the startup route, the startup space, the biotech space. I mean, at this point, you’re not going into a well-established organization. It’s much like you’re coming into something entirely new in some cases. In some cases, well, a little bit more established. But it’s much like, we would say, when we come into the set up a forward operating base, it’s like, this is new territory. And so why take on that challenge? Why not just say, Hey, I want to help people. I’m going to go in the med space. Why the innovation? Why the startups?
It’s funny. I love that really bleeding-edge technology piece. And it’s been something the past 20 years that I’ve been part of. You start to get a taste of it with innovators. I was very fortunate. As I got out of the military in that transition, a lot of us struggled. I got in with a company and didn’t really understand. I didn’t know anything about cancer. My mom had breast cancer when I was a kid, but didn’t really understand it. I didn’t know how this whole thing worked. I knew how to fly an airplane. I was getting a master’s degree at the time, trying to learn about business, trying to figure this stuff out. I was just fortunate to be exposed to some really smart people. One of those guys was this doctor named Dr. Raul Brayland. At the time, he was maybe this was 15 years, he was maybe in his late ’70s. He was world famous for inventing these diagnostic techniques for blood cancers. I got to get really close to him because he was just part of the company I was with. Now, I just shut the mouth off and let the ears open and just listen and just ask as many questions as possible.
We had another guy named Dr. Van Hof, Dr. Van Hof, is also well-renowned for his innovative approaches to cancer. If you have, particularly, pancreatic cancer, you have pancreatic cancer, you go see Dr. Van Hof. I had a chance to just spend time with him, just one-on-one with a young, dumb guy, asking really important questions. I think that just got me really motivated to say, Man, we really can make an impact, even outside military. You can go make an impact on people’s lives doing really cool stuff. The easy road is easy. It’s not for me. I think a lot of people can go do that, find a nice, cushy job with a big company somewhere and disappear, but that’s just never been the way I’ve been wired.
Well, it seems you have a pretty good grasp of it right now. I can think back to a while back, I saw you on CNN when you were the CEO of Paige AI, and you’re talking about the importance of artificial intelligence in detecting cancer and the patterns involved. So please take us to that. How is AI used to detect cancer today?
Obviously, AI is everywhere. People talk about AI. I’m sure if I went and took a poll of people on the street, do they really understand AI? Not really. And to back up a second, what is AI? If you talk about artificial intelligence, typically what you’re talking about is machine learning. You’re talking about using a variety of computer science techniques. Early days of these things called colluded neural networks or serial neural networks. Now you have some different architecture to these types of machine learning applications because you’re essentially teaching the machine to learn something and then predict something. Ultimately, what AI is really very good at is pattern matching. It’s just very complex pattern matching. AI has been around for years, actually. All the stuff in Amazon, when Netflix says, Hey, John, I think you’d like this movie versus that movie. That’s all AI. It’s taking learnings from what you’d like to look at and making a prediction about what you like. What’s been different over the past two or three years, particularly as the public has gotten really excited about things like ChatGPT and stuff, is the compute power, the ability for these really large models to come into existence have now happened.
It’s early start, people started to feel like it’s magic, this kind of stuff. But the company I was with was Paige, and Paige was founded by this guy, Tom Fuchs, who pioneered this way to sort of train the machine to look for cancer on a glass slide. To give just a very quick overview of that, what happens when you have cancer is you go to a doctor, they take a piece of tissue. If you have skin cancer or colon cancer or mammogram or whatever, they take that tissue, they cut it real thin, they lay it on a glass slide, they stain it, and a doctor, this person who’s a pathologist, looks at it. That’s the same process that’s been around for 100 years. They were doing this in literally 1905. They would take some tissue, cut it thin, no changes. Now, when you think about AI, now you’re able to apply. By the way, doctors suck at looking at patterns. People do, generally. It’s the old, how many jelly beans in a jar? If there’s like 20 jelly beans, you might be able to get pretty close. If there’s 2,564, you’re never going to get close. This is the problem.
When you’re looking at cells on a slide, there are millions of cells on that slide. Pathologists miss cancer. They’ll miss it up to 20% of the time, or if they do catch it, they may call it something that it’s not. That’s the problem, right? If you’re not getting the diagnosis right for cancer to start. So, Paige was founded in order to use AI to find cancer on a slide. Use it as a tool to help those pathologists get better at what they do. You see that in radiology, it’s pretty prevalent in radiology where you go get a mammogram, there’s a radiologist looks at that image. You can use AI to catch those things. You can use AI to look for lung nodules in our lungs, CT, all this kind of stuff. AI now is really good at pattern matching. It’s slowly permeating the clinical practice, but it’s slow. That’s the hardest thing about health care. It’s like all this amazing technology exists. It just takes forever to get into the actual use for where patients are taking advantage of it.
That’s because the pattern matching is more complex pattern matching than we would associate with most pattern matchings as humans. When we start to see this is a pattern here. This is much more complex. So, take us there. How much more complex is it?
Extremely. The other thing when you think about AI, the other group that’s been using AI for a long time is the government, Department of Defense, DARPA. You know what I mean? We’ve been using AI to look at satellite scans for a long time. In fact, it’s funny because our founder, Thomas, he was actually a JPL, and his first job was to develop AI algorithms for the Mars rovers. Because if you think about as you’re landing a Mars rover on the surface of Mars, there’s all these rocks, there’s all these valleys, there’s all this stuff going on. But it looks like, what is that? You see a camera coming down. Using AI to pick out, that’s a rock, that’s a valley, don’t land there, that kind of stuff. That’s what the initial stuff he did. He got to thinking about it like, well, this could be useful to say… Because cancer is just essentially cells that don’t look like normal cells. Your cells have gone haywire. That’s what cancer is. Tumors are basically cells that started to go nuts and mutated and don’t stop growing and they ultimately kill you. They look different. If they’re meaner and more aggressive, they look way different.
That’s how the AI is able to do that. It’s able to compare millions of these normal-looking cells from all the different cells you have in your body to the cancer cells. It’s just better at it than people are. It just it is. Even though no doctor wants to hear that because their whole livelihoods dependent on it, it really is better at finding those types of complex patterns.
How else is AI being used in health care?
Tempus is an interesting company, too. We have been collecting genomic information on cancer patients for a long time. The company was founded with this vision that not enough data is both available or being used to make the right decisions in health care, particularly in cancer, but now we’ve moved on to cardiology and urology in some other spaces. It really is true. I would say for the most part, cancer care in the United States is very much a recipe book. They have these things called guidelines. If you go, for example, with a certain type of cancer, they’re going to give a certain type of treatment based on the guidelines what they’ll pay for. They don’t really use a lot of data. In the beginning of this, to start to change has been the genomic revolutions. You have the AI revolution. You also have the genomic revolution. Twenty-five years ago, they did the Human Genome Project. Now, being able to sequence your tumor and understand what genes are driving your cancer is really, really important. We have 10 years ago or 15 years ago, it was maybe one or two drugs for that type of stuff. Now, there’s 100 or more that actually target a specific gene and have produced better results for the patient.
The problem is not every doctor uses that. We’ve been sequencing and doing all this genomics for a long time, and now we have this amazing… And we also get clinical information, John, which is really important. You take…If you’re a smoker or if you’re between ages of 50 and 60, and you took a certain type of drug, what happened to you? It’s important to understand that follow-up information and all the clinical information. It’s just really, really big data. Now that you have all that data, you can start to do really cool things with AI. One of the things we do at Tempus is we have a front door, we have this thing called Tempus One. We’re able now to interrogate this deep, deep pool of data to pull out insights that you’d never be able to pull out. There’s two reasons to want to do that. One, to help doctors make better informed decisions about certain types of patients. There are a lot of times they just don’t know what to do with a patient. I don’t know what to do with this guy. He’s got stage 4, non-small cell lung cancer. These genes aren’t right.
I don’t know. Let’s look at a cohort of patients that look like him and let’s pick a good treatment. AI can help enable them. The other thing that AI can help do, is start to do things like in cardiology. There’s, for example, you have a whole lot of patients who will go get an ECG, and about 2% or 3% of them will end up getting a stroke or have a heart attack a year later. Something happened. They get that ECG, the doctor says, You’re fine, and then six months later, they have some event. There’s AI that’s been trained on all of that data that is able to pick out those 2% or 3% of patients that may be at risk for some cardiac event. We launched that and really imagine a world where anytime you go get an ECG, you may go to the doctor, you get your ECG, doctor says, John, you’re looking great. You come home, we actually flag that doctor and say, Actually, the AI has found something here, you need to follow up with that patient. Then the doc calls you and says, John, I’m sorry, but actually we run this AI algorithm, and it actually has found something anomalous.
Come back in. You think you start to really prevent a lot a lot of deaths and heart attacks from that sort of thing. AI is starting to permeate a lot of different health care in clinical ways. Just some other AI, you know, makes the doctor’s lives easier. It’s good. It’ll listen in, it’ll summarize all the notes. It’s admin, and admin certainly kills doctors. It’s a big part of their burn out. But I think what really gets me excited is when you’re really impacting clinical care, you’re actually saving people’s lives using this technology, and that’s been super exciting.
You pointed out that you’re on the bleeding edge, so you’re seeing all this stuff happen. For a lot of us, this seems new, but you’ve been working on this stuff for years. Where do you see the future of AI and health care?
It’s a great question. The technology itself is far outpacing the market in the health care world, even the general world’s ability to use it, to understand it and to find the use case and that kind of stuff. If you get way, way out of the bleeding edge, the research on AI, the stuff that these guys are doing is really amazing. People talk a lot about AGI, Artificial General Intelligence. I think you’re still going to have their use case-driven AI, which means it needs to really understand that specific thing. We’re all not experts. I’m not a lawyer. I don’t pretend to be one. You can be generally intelligent, but you’re not going to be a lawyer. I think AI is going to be the same thing. It can generally have a good understanding of a space. But if you wanted to make clinical decisions about cardio events or cancer, it has to be trained on particular data. I should pause for a minute and talk about that because it’s really the most important thing. The thing that fuels AI is data. We collect data all over the place. Obviously, ChatGPT and Anthropic and these other groups are making large language models, they’re now getting sued because what they just went out is they just scraped the internet.
Let’s just take all the words and things that the internet has to say, we’re going to use that as our data and train it. That’s great, but what you get is all kinds of crazy stuff because we’re human beings and the internet’s crazy. So, the data really drives the output in a lot of ways. So, in the medical space, the data has to be really good. You have to know that no s***, sorry, but that patient actually had cancer or had that genomic mutation and died or responded to the drug, whatever. If you’re training it, if the data is not accurate, then you’re going to get crappy clinical decision reports. I think that’s going to cause problems because this looks like a really big industry, and it is. You’re going to have a lot of jokers and clowns who will come in and try to train algorithms. We see it already that are not really robust on the data. That’s going to cause trust issues with doctors, with patients, with hospitals. They’re going to say, Oh, I saw this AI, and it was wrong, all this time. Unless we really have some regulation to help with that, how was the data?
What is the data that you’re driving it on? It’s really going to be challenging to get good adoption in the next 10 years. I don’t know, like in 10 to 15 years, I certainly hope there’s a world where we see a lot more clinical decisions. That’s certainly the vision for Tempus, to make more decisions using data and using AI than what’s happening today.
Well, you bring up a great point because we’ve seen this in the legal sector as well, that there are a lot of jokers and clowns that have a rudimentary understanding of AI, and they’re going to try to apply it to their less than spectacular knowledge of how the legal system works. And so they come in and they… Garbage in is garbage out. And sometimes the data is unclean, the understanding is unclean, the command prompts are out of whack, and it’s garbage. And we’ve seen it happen, and we’re being sold this vapor, right? Oh, we’ve got this great AI product, and it’s crap. So how do you know? How do you know, Andy, whether it’s good or whether it’s garbage?
It’s a great question. I mean, just speaking specifically for health care, right? We’re getting into health care unlike some of these other areas, even in consumer, with ChatGPT stuff. Health care is at least very regulated, at least in the U.S., certainly in other countries. But the FDA, they’re really the ones responsible for making sure a medical device, a thing that you make a decision about or give to a patient or a drug or something, is safe and effective. That’s their role in government. Nothing more, that doesn’t mean it’s going to be better than the other thing. Is it safe and effective? I think at Paige, what we are really excited about, we’re most proud of is we developed an AI for detection of prostate cancer. So prostate cancer is an interesting thing. It’s one of those cancers where a lot of men die with prostate cancer. They don’t necessarily die of prostate cancer. The mortality rates in prostate cancer are very low, doesn’t mean men don’t die. It certainly can be lethal if you let it go. So don’t be my disclaimer. But generally speaking, compared to pancreatic or whatever, it’s not as lethal a disease. But if you have prostate cancer, you have to get it treated.
The way that you find out if you have prostate cancer is you can get a blood test called a PSA. Then you go and you get this thing called a biopsy. It’s miserable for men. I won’t even describe it because… And by the way, Veterans, this is a really huge deal. The Veteran population for prostate cancer is far out pacing the regular population. That’s for a lot of cancers, too, by the way. We’ll talk about that later. But we developed this AI system to find prostate cancers where a lot of times it gets missed because it’s a random biopsy and you may miss it. The prostate, we trained it on 70,000 patients working with Memorial Sloan Kettering in New York City. We submitted it all to the FDA, and the FDA took two years to really understand what the heck was going on here, what the data was, what the actual ground truth was. But we got it through, and it’s still today. It was over three years ago. Yeah, it was about three and a half years ago that it got approved, and no one else has been able to bring an FDA-approved product to the space.
It tells you something about the pain and rigor it takes, especially in health care, to get something FDA-approved. Then if it’s FDA-approved, you should at least be able to say, Okay, that’s a good checkmark. That’s something that says it’s safe and effective. It’s not full of crap. Does it work in the workflow? Does it work all the time? All that stuff you still have to sort out. But yeah, in legal space and finance tech, in general, consumer and retail, all that stuff, there’s no safeguard. There’s no guardrails and no really regulatory agency. Biden administration is starting to come out. This White House executive order about AI. It’s pretty toothless. There’s not a lot of teeth into anything in AI regulation right now. In Europe, they’ve gone the opposite way. They regulated the hack in of all things. It’s really hard to bring innovation there. There’s a combination that you have to help. I hate to rely on the government to help here, but it’s like, if they don’t at least give some input to whether AI is good, we’re all kind of screwed.
Why did you decide to go into the startup space as opposed to big biotech? Why startup?
I think you just find more innovation. I think when you start with an idea and say, Hey, here’s something that will help people. That’s really a lot of the startups I’ve been with, whether it’s Tempus or a Paige or any other company I’ve been with, it’s, Hey, here’s an idea that we think will help people. And bigger companies, for right or wrong, public or whatever. A lot of times there’s quarterly profit. A lot of times it’s just, Hey, we have a process here. There’s a lot of times big pharma companies, for example, will buy an asset just to bury it because they might have something competing. It becomes a challenge when you have a capitalistic health care system, which we do in the United States, the innovations that really, really, really, really help patients bubble up from the bottom. They don’t really start up there. I think a lot of innovative larger companies, we’re part of AstraZeneca as an example. I think they like to look at smaller biotechs as the engine of innovation for them. So come in and Hey, I like what you’re doing there. And either partner with you as they’ve done with Tempus or buy a company and bring it in.
But I think if you’re at that cutting edge, you’re really able to solve the hard problems. Why I get up every day right now is not only to help people because we know we’re doing good work to help people, but it’s just work on really hard problems. When you work with a lot of smart people who are also working on those hard problems, the day goes pretty fast, and it’s pretty rewarding.
What are the leadership skills necessary to be successful in a startup?
You know the other thing, John, as a Veteran, there’s this misperception, particularly among big companies, I would think for sure, but generally in the population, that if you’re in the military, you’re rigid, it’s impossible to deal with new situations. You were given a command and you followed that command. You didn’t think for yourself. There’s still that perception. I think there’s a lot of the general public like, Oh, military. Oh, he’s going to be real rigid and can’t think for himself or that stuff, which, as you know, could not be farther from the truth. I mean, generally, military members with the Army, wherever you were. The ability to work in ambiguous situations, that’s all we did. The ability to lead people where you have no idea what’s going to happen or what the outcomes are going to be, but you have training and you have some discipline to understand how to get there, that’s what you do every day. That leadership is the biggest piece. I tell people all the time, I have no idea what’s going to happen here. We have to be comfortable being uncomfortable. That’s the most important leadership skill, and you have to help people with that.
Not everybody in general population is okay with that. They don’t like that. But if you can get the right organization that says, Hey, I believe in this guy. He puts a little process, a little discipline, a little training around what we’re doing, but also understanding that we’re going to try stuff, it may not work. That may fail. But let’s fail fast, no blame, and let’s move on to the next thing. Those are really the big leadership skills. You have to be able to lead people in ambiguous situations. You have to be able to get them motivated, moving in one direction. You have to get them over the failures quickly because you’re going to get failures. You’re going to try something and it’s going to go, no one’s going to buy in or it’s going to fail disastrously or whatever. You have to get them over that quickly and say, First fail fast, and let’s move on. Those are really the biggest things I’ve seen in startups. I think most startups that don’t do well are the ones that… It’s an interesting statement, you’ve heard it, too, where it’s like people fall in love with their solution.
They don’t fall in love with the problem. Instead of solving the problem, they try to take their solution and force it. That doesn’t always work. You have to really understand the problem and tailor that solution to that problem. Startups that fail, the leadership that doesn’t help with ambiguous situations, that kind of stuff, I think the ones that would do well.
I think there’s a misconception, too, about startups that if you have an education, you come from a, well, let’s just put this in context of a conversation you and I had months ago where there was an individual from one of the top business schools in the country with zero experience, comes to you and says, I want to be your chief strategy officer. And you’re like, Yeah, but what have you done? So just because it’s a startup company doesn’t mean we’re starting with zero experience. So, talk us through that. How do you choose the team?
Yeah, great question. My career, John I’m sure you’ve seen it too, there’s a ton of value to that person you just described, that business school, younger person, because they see the world with fresh eyes. That’s a good thing. That’s not wrong, but it doesn’t necessarily mean they should be leading a strategy group in driving what you’re doing going forward. Because the ability to see around corners means you’ve been around the corner before. You know what I mean? It’s a rare person who understands what’s going to… Is there an ambush happening around the corner? If they’ve never been there. You don’t really get that from business school. You don’t get that. You have to be out in the world and do that. But I think there’s value in bringing those really smart people along. But it’s all about the role that you’re in. I think it’s a combination of having people who have been there a little bit, who have the technical skills, but maybe need some experience, all the way down to some of these younger folks who can start to dive in and want to be excited about what a startup or biotech is doing. At Tempus, we have a lot of that make up.
It’s really just smart people who don’t necessarily always understand health care, the health care system, or how this all works, or how doctors operate, those things. But they’re willing to have a great attitude and want to go and try to solve hard problems. Solving for attitude is number one. Solving for experience is maybe number two. Solving for education, maybe down the line a little bit. But I think if you look for those two things up front, you’re going to get a pretty good team.
Andy, that’s some great wisdom there. It’s always multidimensional. This takes us to the after-action review, the three examples of great leadership and the three examples of terrible leadership. If you could give us three examples of great leadership that you either experienced in the military or in the startup world.
Great leadership to me, was always about taking care of your people. Mission first, people always. I still use that line. I’m sure we all do. But it’s great. It means, Hey, you got to get the thing done. The only thing in the back of your mind as a leader, take care of your people. When we were in Iraq, we were flying missions, and this isn’t a complaint. We were flying a lot of hours. We’re not supposed to fly that many hours. The crew was dead. We were way over high time as far as flights go. Our commanding officer, even though he had a mandate to get missions completed, he recognized, Hey, these guys are going to die. If I don’t get them… He sent us off to some boondoggle for five days, I think an air show in UK, kind of thing. Get your heads right and then come back into the fray. I think about that a lot just from the perspective of, he didn’t have to do that. He could have just, Hey, suck it up, guys. Get out there. But I think that’s also seeing around a corner to say, If I keep these guys at it, there could be an incident.
These guys are worn out. Aircraft goes in, they make a mistake, they fly into Iran or something. That’s bad. Sometimes, not sometimes, I would say all the time, taking care of your people and making sure that you know where the limits are, and the lines are for them is a great example of good leadership. I remember that from my days, my old CO, Pat Buckley. In the civilian world over the past 20 years, I’ve just seen really good leaders in similar ways. I think it’s just about recognizing people’s strengths. I was fortunate enough as I just got out of the military, I had a leader, a mentor. Who’d been in health care his whole life, recognizing me, kind of what we were just talking about, Hey, here’s a really smart guy, good experience in the military, what does he know about health care? He’s a good operator. So, he pulled me in, made me an operator, and led to me becoming a VP very quickly just because he was like, This guy, let’s put him in the right role. I think that was really good leadership, too. It’s about recognizing people and saying, Hey, here’s somebody who may be not perfect over here, but man, if I put him in an operator role while he has experience in the military and that stuff, he’s going to kill it.
I did, and it really made a difference in the organization. Finding those types of roles, I think, are really important. Bad leadership. I think about a time, it was a training exercise. Just like in surgery, after you’re done with surgery, you have to count up all the tools. You don’t want to leave a clamp inside the patient. You count all the tools, you do inventory. Same thing before you go fly. You have to make sure if somebody came out to work on your airframe, whatever, all the tools are accounted for. Can’t fly if you’re missing a tool. We were missing a tool. This was a really high-visibility exercise. We called it in, Look, we can’t find this tool, whatever. The operations officer, who will go unnamed, came out of the aircraft and he said, What are you missing? We told him, he disappeared. He came back 10 minutes later, and he goes, Here it is. Go. We all knew damn well that wasn’t the tool. We all knew he went back inside; got I think it was like a crank or something. Got a crank, brought it out. This was a tough thing, man.
I remember, I was not the mission commander on that mission, but the MC just looked at it him and Hey can I talk to you and brought him aside, and they talked. You got to get this mission done, all that crap. We flew. I remember puckering up this tiny, the entire flight, praying that freaking tool went in the gear box. And number two wasn’t going to explode. Because this guy, he basically put the mission ahead of his people and blatantly broke rules. I think that leadership is just the worst. When you put your career, how you’re going to look, how people see you ahead of the people who are working for you, man, that’s just the worst kind of leadership. It’s funny, in the civilian world, I don’t see it, certainly really not as egregious as that. What you see is the same thing, people taking credit for your work, trying to climb the corporate ladder, just putting their foot on your head and getting up above you. Nothing really specific comes to mind from that perspective, but you see it. When you see it, you just know it’s just the worst kind of leadership.
Absolutely. Dr. Andy Moye, always been a good friend, always a smart, smart guy that can hold a great conversation just about anything, any topic, any subject, from leadership to science to literature. Love talking with you. How can people learn more about Dr. Andy Moye?
Tempus.com. Look at Tempus. You can find me on LinkedIn. Search Andy-Moye on LinkedIn. I typically do quite a few of these. Find me on stage. I’m speaking in Canada, actually, at the Health Innovation Summit in November. I’m giving a lecture at Stanford in December to their AI group. Find me at the Precision Medicine, various conferences and things like that going forward.
Great. Thanks so much for coming on the show and sharing your knowledge with your fellow Veterans on Veteran Led.
Thanks, John. It’s been great. Appreciate it.
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