Revolutionizing Supply Chains and Leadership through AI with Michael Prokopis

The Human Code: Bridging Technology and Humanity with Michael Prokopis

In this episode of The Human Code, host Don Finley takes us on a journey through the intersection of technology, leadership, and personal growth with guest Michael Prokopis. They discuss autonomous driving, the evolution of AI, process mapping in supply chains, and developing future leaders adept at navigating both technology and human-centric roles. Michael delves into his background in technology and strategy consulting, and how he applied these insights to innovate in healthcare supply chain management at MD Anderson. This conversation is packed with insights on how technology not only solves today's challenges but also shapes the leaders of tomorrow.

00:00 Introduction to The Human Code 
00:49 Guest Introduction: Michael's Journey in Tech 
01:03 The Impact of Technology in Daily Life 
02:20 Autonomous Driving: The Future of Transportation 
04:14 AI's Evolution and Challenges 
06:39 Data Privacy and AI 
09:05 Future Leaders and Technology 
11:53 Supply Chain Leadership and Development 
16:01 Process Mapping and AI in Business 
22:38 Balancing Human and AI Collaboration 
27:25 Career Advice for the Future 
30:33 Conclusion and Contact Information

Transcript

Don Finley: 0:00

Welcome to The Human Code, the podcast where technology meets humanity, and the future is shaped by the leaders and innovators of today. I'm your host, Don Finley, inviting you on a journey through the fascinating world of tech, leadership, and personal growth. Here, we delve into the stories of visionary minds, Who are not only driving technological advancement, but also embodying the personal journeys and insights that inspire us all. Each episode, we explore the intersections where human ingenuity meets the cutting edge of technology, unpacking the experiences, challenges, and triumphs that define our era. So, whether you are a tech enthusiast, an inspiring entrepreneur, or simply curious about the human narratives behind the digital revolution, you're in the right place. Welcome to The Human Code. In this episode, we have the privilege of speaking with Michael per COPUS. Yes. A highly accomplished supply chain and operations, senior executive. Known for his innovative approach and transformative leadership. Michael brings a wealth of experience in managing organizational process and digital transformations, making him a thought leader in this field. Today, Michael and I will share the fascinating journey of AI in supply chain management and its transformative impact on the industry. How combining to AI technology with human experience can drive efficiency and innovation in unexpected ways. And the essential skills and mindsets future leaders need to thrive in an AI driven world and why continuous learning and adaptability are more important than ever. Join us as we dive into these insights and more with Michael per coppice. This episode is packed with valuable takeaways for anyone interested in the future of technology and leadership. You won't want to miss it. I'm here with Michael. I want to say that I am just so glad to have you here today. What got you here to this episode or like what brings you into this space of, wanting to talk about humanity and technology?

Michael Prokopis: 2:03

Sure. it's an interesting question because technology is all around us and we experience it in our daily lives. And we're certainly experiencing it in our work lives. And, from a personal experience, you turn on your TV and, you Netflix says here are 10 shows you ought to be thinking about watching next And that's all because of machine learning patterns and the way they think about their connection with each of us. At work, we do the exact same thing. And My background is steeped in technology, going all the way back to my MBA days at Dartmouth College, the Tuck School of Business. I spent the next five years doing strategy consulting in technology. and did interesting projects for Microsoft and GE when they were asking really exciting questions like, At what point in time will we be able to sell, essentially software over the internet? and in 1997, when we were still using dial up modems and maybe we had heard of DSL technologies, that was a really futuristic thought. and so here we are all those years later, and now we're asking questions like, when can my car drive down the road automatically, or autonomously? at what point in time can I push an enter button on my computer desktop and it'll actually make a decision for me or present me with three relevant options, to choose from. And so it's all around us all the time, and it's just a matter of how we're going to apply it, to continue to drive, performance and value and quite frankly, maybe even better quality of balance between work and our personal lives.

Don Finley: 3:21

What's the area of your own life that you want to see technology advancing?

Michael Prokopis: 3:26

Autonomous driving, please. we drive down the road and I talk all the time about all of us have to, literally million points of data. We have to process all of that almost instantaneously to be effective drivers. And some of us do that better than others. and some of us are more proud of our skills than others. And That mishmash creates a very interesting intersection where technology probably can help all of us, and maybe we can even then focus on things that we're better suited for or want to spend more time on while the mundane habit of driving itself can be taken, off the road. So I'm all about autonomous driving and it can't get here fast enough.

Don Finley: 4:02

I'm a hundred percent with you. There is one thing that I love. I love driving. And at the same time, there's so many other things that I could be better suited to do in that time. but then also just, thinking about parents and the coordination that it takes to bring kids to soccer and bring them back. And like how much more present we could be with each other.

Michael Prokopis: 4:23

well, and let's be honest, one of the things that we do where we have distracted driving, people are on, they're texting, they're, phone calls, all that stuff is going on all around us all the time. And maybe those are things that we want, really want to spend our time doing instead of sitting behind a wheel for whatever that commute length is.

Don Finley: 4:39

And I think that's what I love what you're saying here is let's use technology to do the things that like, to take care of the stuff that we don't want to be doing. But then at the same time, we can then focus on the things that we really want to be doing. And I have a personal philosophy around AI that like, That's how we go ahead and we implement it within our business as well as for our clients is let's take care of the things that take you away from that human experience and then allow you to drive into something that else is, more fulfilling for yourself, more aligned with your purpose as a person. how would you look at AI today or even over the last 20 years around how we've been looking at technology and the implementation of it across businesses, across our personal lives?

Michael Prokopis: 5:26

Yeah, it's an interesting question. And, the first thing I'll say is I had a very smart person tell me we're on AI 4. 0. Back in the early 80s, we had this thing called neural networks. And, neural networks, we're going to make all these predictions for us. And then we had 2. 0. And then we got into the early twos. And now here we are in 2024. And we're talking about 2024. Artificial intelligence again, but the reality is that it's actually been on a journey and it's not a light switch where you know One day you just flip the switch and it's all done for us And I think it's also demonstrated over that period of time the complexity of the human mind and how we process information If you all remember, you know the whole ibm watson experiment, you know It was going to replace medicine and doctors and it was going to make predictions about What was ailing you. And they quickly found out that even Watson, with all that horsepower behind it, still didn't have all of the neural network pathways, to make the correct diagnoses and actually led to some bad, diagnoses, which happens in the medical world as well. but you'd like to think that somehow with the human interaction that we have more ability to control. And for me it's this journey that we're on. There is no light switch to flip that says, okay, now we're in an AI world. And now we're not in an AI world. I think we're still discovering. And one of the things that I think we know is a kind of a true statement is that it takes a lot of data to form those, those connections and those pathways for an AI module software application to actually define a decision for us.

Don Finley: 6:50

And that is one of those, challenges with the neural network architecture that we see, right? Like it, and reinforcement learning where it requires a tremendous amount of horsepower and an amazing amount of data. I was looking at a report the other day that says basically our current models today are running out of data to train on, which is absolutely fascinating, but also I think it's a little short sighted, Because even on the internet, I think something like 90 percent of data is behind, either a paywall, a login, or in a private, resource. So there's still a ton more data available, but I think it shows the challenges that we have with AI architecture is that it does require a significant amount of let's say, practice tries in order to learn something.

Michael Prokopis: 7:36

Yeah,

Don Finley: 7:37

think about

Michael Prokopis: 7:37

it.

Don Finley: 7:37

yeah, go ahead.

Michael Prokopis: 7:39

I was just gonna make a comment. the other thing that we struggle with when we talk about data is, personal data and my, in the healthcare world, it's PHI. And what am I willing to share or not share? What sits behind a firewall or doesn't sit behind a firewall? Who's going to profit from the data? All those are considerations when we talk about data. And those are things that prevent us maybe from having a more rich pool of information. Think of that in a healthcare world. If we could take all of the information that's in every single EMR, in every single hospital, and combine it into one giant exchange. that would be a massive amount of data. And I think the predictions coming out of something like that, could move the AI platform forward. But the problem is that I, as a patient may not want all that information shared and people say, you can just change the math and you can make it, you can change the data. And so I say, all right, let's think about a zip code for a second. If I just give you my zip code and I take off the names and the addresses, but I leave the age and I say, man, and I say 80 years old, how many 80 year old men are going to be in a zip code? And so in very short period of time, You can now target an individual. And so until we can figure out how we're going to make those exchanges transparently without jeopardizing private information, I think that's some of the struggle we have when we talk about how we train these models.

Don Finley: 8:53

Oh, absolutely. And especially when we talk about this. It's a frequent conversation around what are we, what are you doing with AI? And are you giving your information over to another entity to use in their training data set, or even in, algorithms that are learning live? Are you actually just submitting that information for it then to be used with another one of their customers or not? So from a corporate perspective, it's the same type of like private information, but I think you hit on a really. Key point in this is we got to be careful about what information we actually want to contribute. Yet at the same time, there's amazing opportunities around what could be done when we figure out that challenge of like, how do we keep data private or Anonymize it to the point where you can't find out what street you live on because we've given you breadcrumbs back to the house. now what, how do you see the impact of AI and like what we're talking about changing what we see in future leaders or like how we get our leaders of tomorrow? what is the relationship that we're now creating with these tools that can make decisions for us?

Michael Prokopis: 10:06

one thing is I think our children are, We're developing them in a world that didn't exist for us. I can still remember when the first Atari, whatever it's set top TV box showed up and how dynamic it was to play something other than Pong on a television set. and so. But our children now do that on their telephones and they do that on these handheld devices. And they, there's, gaming, gamification of education that goes on. And so everything that they're immersed in is all of this experience, which none of us had, we all had to learn it on the fly. And, people joke, but it's the truth. I remember in 1975 at Christmas when I opened up Pong and I plugged it into my television set and we had two controllers and you could watch a white dot. Bounce across the screen. And maybe if you were good enough, you could get it to bounce back across the screen. and that was, literally the advent of, on online gaming, if you will. And but our children today are so steeped in technology and I watch three, four, five year olds, they walk over and they're like, you're not doing it right. And they push a button and you're like, oh, okay, I got it now. and w so we didn't have that development. It wasn't literally in our DNA. And I think the futures of the leader are going to come with a skill set that we don't possess today. And so we've got to constantly challenge ourselves. How do we take the, the real world that we've been indoctrinated in and give them enough of that subject matter expertise, and then let them take it and start applying some of these things that they know as part of their world. And then that ultimately evolves the model.

Don Finley: 11:33

is amazing to see younger generations and how quickly they have not accepted, but they're just that they know how these tools work, how they see how this is connected. They know the interface. I remember back when the iPad first came out, I was watching a two year old. Play with the iPad and she was, opening app. She was closing app. She was moving around. Like she kept on going back and forth and then, they swapped out the iPad for a magazine and she kept on trying to click on the images and it just, it was fascinating how. how intuitive that device was first off, but then secondly, like she had learned a way and come to expect the world to interact with her in that way that we just don't get that you and I didn't grow up with. absolutely fascinating. I think the other thing that I would love to, or that I recommend for people to look at is developing management. as a skill set earlier on in their career. And while you may not be managing a person, you're going to be managing tasks. And the way that you can interact with the, with an AI, that's a conversational UI is more of a management type approach to the work that's getting done.

Michael Prokopis: 12:49

Yeah, I think that's absolutely a great point. And just to comment real quick. Like one of the things that we've done, at MD Anderson that we're really focusing on is, what we're calling the Supply Chain Leadership Academy. And it's an organic program that we've built that says we're going to identify a group of high potential employees, and we're going to run them through a rigorous course. So they can at least have an overview of all the different areas that encompass supply chain. Because everyone from the pandemic remembers when toilet paper ran out, and therefore they're all supply chain experts. But the reality is there's all these functional silos inside of supply chain. In the old days, we said procurement, or resourcing, or warehousing, or, logistics, materials handling. And all those still exist today, and they have to have A subject matter expert in each one of them, but it's really the de layering, it's the umbrella that you put over the top of them and then take down the vertical wall so you actually become a horizontal alignment that becomes really important. And I think that the leaders of the future will have that embedded in them intuitively, that these barriers shouldn't exist. They exist in a physical process, but they don't exist in a data agnostic or in an AI world.

Don Finley: 13:59

there's so much to unpack in that, and I absolutely love it. And so I think I'm going to, The item that you really hit on was basically like an intuitive knowledge of being able to deconstruct processes, understanding what we've artificially placed there before, as well as understanding like how we could improve upon that. You're seeing this in Candidates that you're looking at for these leadership roles in the organization. that's cool. That is like a really well thought out way to describe that sort of stepping out of the tactical position of what needs to be done and looking at the system from a whole. how Have you been applying this for a while? Is this a new process or a new program that you've engineered or like, where does this fit within the organization?

Michael Prokopis: 14:47

Yeah, it's an evolution you get to, and it's probably been my entire career that's ultimately led to me this realization. Cause if I go back to the beginning of my career, whether it was in operations or, IT consulting, technology consulting, no one ever said the word supply chain. That's more of a recent construct where people started to recognize there's this umbrella that sits over the top of all of these functions. And if all these functions work correctly. We have an efficient supply chain. If any one of those functions break down, then you don't have efficiency. And so supply chain is a newer concept, but as I came to MD Anderson and I started asking questions about how are we developing our talent, how are we mentoring, how are we coaching, it became obvious to me that one of the things that was missing is that we were still so vertically aligned and you have to be, because you have to have procurement experts, you have to have material handling experts, and they don't necessarily mix and match. However, as leaders, you better have that overarching understanding. And so it was incumbent upon us to figure out what does the program look like that actually can develop those leaders. So they have the functional expertise, which marries up with this other skillset that they already natively have come with because they've grown up in a world that's taught them that.

Don Finley: 15:58

That's incredibly cool. And it's, it reminds me of a friend of mine who studied two different disciplines in, for his doctorate. And the way that he pointed it out to me, he goes, he's you have experts that are in this area. You have experts that are in area B. But there's an overlap of A and B that nobody is studying and it's just this wide open space. But I also think you're highlighting the easiest opportunities for efficiency, for growth, for opportunities with inside a business happen at the folds. They happen at the crossover that can enable a company to identify that. And if you have a group of people that are, aware. and sitting in leadership roles. You can really drive the organization forward in a much more efficient path. Where else, like what else in supply chain? actually this is. Interesting. What else in the supply chain, like side of this around the personal development, but then also around like where advancements in technology are happening. Do you see any crossovers?

Michael Prokopis: 17:00

Yeah, there's all kinds of things to consider. there's companies out there that do process mapping. Like when I came on board, someone, one of my department heads came up to me and said, I need 13 FTEs. And I'm like, what's your baseline? And they said, I have 39 people. And it's can you at least explain why or how you got to 39? No, I can't, but I need 13 more. And so it became evident to me, we don't understand our processes well enough. We don't understand how much time we're spending in the individual tasks. And so somehow we've got to be able to do that. Now, somebody can say, get your stopwatch out. And that's what I would have done back in the day. And we had gone to time study and we would have written it down and we'd have put an Excel spreadsheet and we'd have run a regression against it. all of that can happen automatically. Now there's companies that do process mapping for you and they'll tell you, all right. Your standard process looks like this and it takes 27 minutes to complete a task, but 60 percent of your tasks or requests are outside of the normal process. And so they point out all of these branches, if you will, that are, if you will, consuming time away from the normal. And so the question is your normal, right? Or is one of the other branches, right? And, or is it something in between? And where we can start applying learning process mapping. With some AI sitting in the background to help us understand dwell times and how long sub segment tasks are taking. Now all of a sudden we have a chance to start looking at our processes and saying, are we holistic and inclusive or not? so there's just one example where I think technology is really going to make a dent going forward.

Don Finley: 18:26

I like that. We're, it's funny that you bring up process mapping. Cause it's not something that my company focuses on, but I have a partner that does. And so they do the process mapping and then they're bringing us in to help them with agentic AI solutions. So figuring out like, Hey, what can we actually do to make it so that it's not another 13 people that you need to hire, but that basically you can repurpose the 39 to do things that are, much more valuable or things that you haven't gotten to, lately. As you're looking at these opportunities inside the business, how are you finding, let's say the positive ROI? opportunities in a space for and actually if you're doing anything with AI in a space that is really rapidly changing right now, or are you staying with that core kind of stable AI that we've known has been working for the last, 10 years type of approach?

Michael Prokopis: 19:18

We're going to push the edges and I think there's a balance, right? there's the right amount that you can invest in and you can explore and then there's probably the wrong amount. a couple of areas that I'm really intrigued by, is how do we take cameras and put them in an inventory location and I don't have to necessarily measure consumption, but I do want to know if it's a par location where the requisition reorder point is. And so if I can train the camera to look at the bin and say, Oh, It's only, it's a four day on hand bin. There's only two days on hand available. I better put a requisition in because it will likely take two days to get the supply and to fill the bin. And so if we start being smart about how we apply those things, there are natural ROIs that will come. Now, one of the things that I'm really tight on ROI is I don't necessarily just say, this is headcount reduction because oftentimes we don't take the heads out, we reassign and we do other things with them. And an ROI completely based on, you're just going to reduce the number of people who work in your company. Most of those fail, and they never do pan out. And so I'm much more about how am I going to improve my process? Can I change the amount of inventory that I actually have to, carry on hand? And can I change the re reordering points in a way? That makes it more economical for me to order. Now, on top of that, we talked about value mapping a second ago. Value stream mapping is really important internally, but when it really becomes powerful is when you overlay it on top of your vendor and you look at your interaction points, how am I touching you? And what am I doing to you that either hurts or helps your economics? And when we start thinking about it in strategic partnerships, in that regard, Now all of a sudden we can start finding ROIs that are around us, aren't necessarily just coming out of what you can immediately control because those upstream and downstream impacts are extremely important to follow and track.

Don Finley: 21:04

I absolutely love it because you're, I have this thought that basically, back in the eighties, it took 50 people to make 10 million, right? Like it's give or take, you needed some divisions, you needed a lot of resources, but then as we've gone through the years. Early 2000s, I could do that with 10 people. Google in their first earnings report was reporting a million dollars per revenue per employee. and so that's right around 2004, I think was their IPO somewhere around there. but then, coming into today, we're, you can basically do 10 million as a single person. What I'm hearing you say is that it's going to become more important for us to understand our impact both inside the organization, but also with suppliers, with partners, and like how we can be a good steward of that economy that we're creating. And I think as we look at like organizations becoming more lean, that's a much more important aspect to know because we need to be playing well in the sandbox that we've created. Now, where do you see I've totally lost my question, which is we'll edit this part out.

Michael Prokopis: 22:10

We get to edit this part out.

Don Finley: 22:12

That's exactly it. We can tell that's the greatest thing about doing this is we'll end up editing it, but I keep on coming back to what you're talking about with demand planning and then as well as like camera systems, That component of your systems and like how you're applying technology in those spaces. Sorry. All right. Let's scratch it all the way to here. We'll make this point. The question that I really wanted to ask you was, I agree. I have done many projects in the past where we've looked at employee reduction and I can tell you that I have never seen an employee let go because of a project implementation. There's always a justification for keeping good employees. And additionally, most companies are understaffed. They have more opportunity than they know what to do with. and then they have more tasks that they need those people for that they weren't previously able to get to. And so from an ROI capacity, it looked nice on a spreadsheet to be saying, we're going to have a reduced head count, but from actual implementation, I don't think I've ever seen anybody ever Losing their position. But when we talk about things such as like checking bins, using cameras and vision there, and then also demand planning, like that's an aspect that has a somewhat human component to it today. How do you see those activities working together, whether it's the human side of it and also the technology that's fulfilling the in person need.

Michael Prokopis: 23:39

Yeah, I'll talk about procedure cards for a second. So in a healthcare organization, we have procedure cards and that basically defines what a doctor is planning to do in a procedure. And so if they're doing a GI tract, whatever it happens to be, there's a list of the products that they want in the OR and they're going to open them and they're going to consume them in that procedure, but what happens is procedures change or the patient changes, right? the physiology of the patient's different, larger, smaller, whatever. And You may consume more, or you may consume less, or you may not consume at all because you've changed the way you think about the practices as a clinician. all of that gets documented in a preference card, but the problem is then how do we update them? And what ends up happening is if I have 10 items on a preference card, I take them all in the OR, and because I want to be expedient and efficient, I open them all up. if the doctor only uses eight of them, I'm going to throw two of them away because I've already exposed them to a contaminated environment and I can't use them again. So all of that stuff ends up in the trash basically as waste. And depending on the cost of it, that can be a very expensive throwaway. So what we try to do is we have the AI, the machine learning, they say, Hey, 80 percent of the time, these are the items that are opened. And so you say, okay. And, but you look at it and say, yeah, I disagree with this one item. I'm going to take it. so I think there's always going to be an interaction. And I love the idea when we talk about robotic process automation to say, attended and unattended. Unattended robots are doing something in the background, which we don't need to see that probably looks like you clicking on a keyboard to upload an Excel spreadsheet into a, into an ERP, right? But that may be one aspect of it, but an attended is a robot that's going to go do three or four things. And then it's going to spit an answer out to you and you're going to do three or four things. Then you're going to send it back to the robot. and we find that, and I started exploring around with robotic process automation back in 2014, and we actually deployed it for one of the large. digital telecommunication companies. And what's interesting is they actually, they challenged us with automating their top 10 call scripts. so a customer calls in and they say, what's my bill? And so we put a robot in place. And so you got a human interaction, taking the call. Understand what the question is. They push one on the keyboard because one on the keyboard is going to go and run the routine. It's going to pull the information out, tell them who the customer is and what the bill amount is. And then maybe some other details of the account. And then depending on where the conversation goes, they can hit another button. So there's an example where I think we are going to, we're going to find this world where we're always going to be interacting with. And we're still going to need the higher order thinking on some of the tasks. but what it does is it makes us much more efficient and able to do that. And then one final thing I'll talk about, and I found this to be very fascinating. and I know Apple was one of the first companies that started exploring it. When you call into the help desk to schedule an in store appointment, that's all done by an automated attendant. What you don't know is that there's a person in the background because the robot gets stuck and doesn't know how to answer the question or doesn't know what to do next. And so it literally kicks it out as an exception cue, but what you have is these really smart kids sit in the background and it's like a video game to them. They got headphones on, they got a screen, it pops up, it gives them the last three seconds of the conversation and they push a button that tells the robot what to do. That was being done back in 2014 and 15. And and that stuff still exists today. And so that's where the intersection of technology and people really becomes powerful.

Don Finley: 27:05

It's incredible. I caught a brief news article about the CEO of Bumble, the dating app, talking about how in the future it's going to be your AI talking to another person's AI that gets to know each other and then sets up the dates. I don't consider that one so dystopian, but I also think about it in a way that like, if you actually take that idea and expand it upon like my entire life, or anybody's entire life, and have an AI that goes out and finds people that I want to connect with, right? we got you on the show because your profile hit a few spots. We're connected on LinkedIn. And I was like, I want to talk to him. And so that's how it got bubbled up. But now we're talking about it could actually get us to this point of us having the conversation and you and I can just share the space and enjoy each other's company to be able to share the ideas with the world as well. and so that sounds like a really awesome advancement for both taking RPA. as well as what we can do with like more sophisticated models, but we need that baseline of what Apple was doing 10 years ago to help create what we have in this moment. It's just that progression. I gotta say, it's been a blast talking to you. I really enjoy the conversation. one last question though, what would you recommend to anybody out there today who's focused on making sure their career has legs for the next 10 to 20 years?

Michael Prokopis: 28:25

It's an interesting question. And I'll tell you when I started, I, I never said I was going to be a chief supply chain, anything. It's not as I'm going to run a supply chain and here we are. But what I always did is I always looked at what's the next opportunity and how is it going to progress my thinking, my intelligence, my skillset, my toolset. And I was always looking for the next challenging opportunity. And I took on assignments that nobody else wanted. and sometimes they worked out great and sometimes they didn't work out so great. But there's just this constant churn, I think, as a professional, you need to have in the back of your mind that says. I'm interested in that. It's not in my day to day job today, but maybe I'm going to go learn about it. And I'll give you a prime example. I did a really interesting project at a previous company I worked for, where we, it was on process technology and we were doing a piece of work for Dell EMC that said, can we predict the next product failure? And we took all of their historical data for two years and we ran it through all the machine learnings. And MIT was part of that conversation and we failed miserably. at predicting the next failure. But counterintuitively, we predicted the next part. And the reason is when your screen goes dark, it's the card, it's a wire, or it's the screen itself that are bad. And when a technician opens it up, they're just gonna replace all three parts, because they're not going to open it up three times just in case they got it wrong the first time. So we found out with a few intelligent questions, they were more likely to get the right part the first time, and that reduced trunk stock by about 8%. Massive savings opportunity. That, that led me to a conversation with MIT where they said, why don't you come get a master's degree, a certificate program in supply chain management. And I said, I've got an MBA from Dartmouth college. I think I'm pretty set, pretty happy with my Tuck School of Business credentials. Went back and forth and they finally said, and I agreed. And so I went and got the certificate award. And then Stuart HealthCare called me out of the blue and said, Hey, why don't you come talk to us about healthcare and supply chain? And now, six years later, I've got a supply chain career that's evolved. And it's a mishmash of how you get there, but I think that the core of it is keep learning, keep challenging yourself, keep taking on assignments, keep aggregating skill sets, and sooner or later you'll get to something that truly makes you happy.

Don Finley: 30:36

I really enjoy what you just shared there. Cause it reminds me of a few things. I don't know if you're spiritual in any aspect, but there's this author, Michael Singer, and he he talks about, actually, so the guy's a yogi and then he ends up being a university professor buys like an IBM early and he starts playing around with it. And then he gets some programming jobs, blah, blah, blah, blah. Fill it out. And he's just the entire time he's telling you, just stay present. whatever shows up in front of you, learn, be engaged, be like, be inquisitive about the world around you. And it will respond. he ends up selling his company to WebMD. a nice little exit that he ends up getting out of it. But then also it reminds me of the Steve Jobs commencement speech, right? you don't know how the dots are going to connect. But if you stay engaged, you learn, you critically think about what you're doing and you apply yourself. Yeah, the picture will paint itself. that's really good advice for everybody. Thank you, Michael. It's been an absolute blast having you today. I really appreciate it. And one last thing, if anybody wants to get ahold of you, is there any way to reach you or to connect with you?

Michael Prokopis: 31:45

Yeah. I try to stay active on LinkedIn. I do better some months than other months, but Michael Proco at LinkedIn, but if you really want to, I'll tell you what, and I don't know why I'm gonna do this. I'll probably regret it. But here's my, my, my work email address, and I keep my inbox empty. So I'm always happy to take a questions and answer'em back. Mt. Proco. And if you reach out to me, just let me know where you came from and you got a question or an answer or you're curious about anything I can do to help, I'm always glad to try and connect dots for you as well.

Don Finley: 32:15

Michael, once again, man, really appreciate you. And when you reach out to Michael, remember you found him on the human code. Thank you for tuning into The Human Code, sponsored by FINdustries, where we harness AI to elevate your business. By improving operational efficiency and accelerating growth, we turn opportunities into reality. Let FINdustries be your guide to AI mastery, making success inevitable. Explore how at FINdustries. co.