Episode #39: Digital Continuum: Leveraging Technology like a Superpower

  • we@designindc.com
  • April 21, 2024


Announcement: Broadcasting from Fairfax, Virginia, you are now listening to The Highlight Cast.

Ashley Nichols: All right. Hello, everybody, and welcome back to The Highlight Cast. I’m Ashley Nichols. I’m the VP for Corporate Strategy and Development here at Highlight. And today I have with me Highlight’s Director of Technology and Innovation, Jim Asselgroff, uh, to help discuss, um, how to leverage technology to expand our capabilities, uh, and how organizations and individuals can utilize technology. Uh, to be our superpower. Um, technology is a continually changing landscape that continues to mature and progress capabilities, uh, across the federal sector. Um, at a more granular level, there’s an ongoing conversation always around, uh, digital transformation, uh, within the federal sector and the technology sector at large. Um, and with the scale of that change. You know, is there a better way for us to define, uh, digital transformation? Uh, around here, Jim, uh, constantly uses a term, uh, digital continuum, um, as opposed to digital transformation. And so, Jim, can you tell us just a little bit, uh, the difference between how you view the continuum versus digital, digital transformation?

James Eselgroth: Absolutely. So for me, um, when I think about digital transformation, which is a critical approach to adopting any type of new technology, and when we mean when we mean new, it could be emerging like large language models or or quantum computing, but it could also just be new to you in an organization. So You know, you’ve never had a data visualization tool, and now you’re going to use a data visualization tool. Um, so it could be new to you or just new and emerging. And when you’re doing through that process, you, you often find yourself thinking about, um, uh, cause really digital transformation is about, um, change management at the end of the day. And when you’re going through that process of change management, you, you have to really think, step back and. We’ll try to go, we’re all the things I need to consider as a part of that transformation. And so you think about, you know, I need to consider the people, the policy, the process, the partners and the platforms, all the different elements that could be affected either upstream or downstream from that change. But one of the nuances of digital transformation versus digital continuum is that you often go through this process of like, all right, I’m going to, I’m going to prepare to freeze. I’m going to freeze. I’m going to unfreeze. Um, and, and then most people. Leave the word transformation to think like, well, when it’s done, we’ve, we’ve, we’ve bought the thing we’ve, we’ve installed it. We’ve made those changes on the five P’s. Um, then I’m good to go. I can just, I can flip the switch and I can walk away. Um, uh, but most of the time when you walk away, it’s really not finished. It’s actually a really, when you, when you finish the change. And you change the state from a, a build to a, um, to an O and M state. So you do an it help desk. You’re doing, you know, maybe you’re doing agile, iterative improvements for the, for the operative, for the, for the app or the application or the, whatever it is that you’ve built. Um, and that could go on for a long time, 10, 20, 30 years. It could, you know, shorter, longer. But the idea is, is that the, the mental use of the word continuum, um, I like that better Um, as a transition from transformation, because to evaluating those five P’s is a continuous effort. And so leaders and people in organizations, um, need to really think, should think about. All right. When we’ve gone through the change, it’s not just a flip of a switch. Um, there are other things that are going to come up down the road. Um, new people are going to be hired. People are going to move up in an organization. And so thinking about things from a digital continuum, um, puts into mindset, the real lift that’s necessary for when it comes to change is that, um, the care and feeding of that change takes place long after. The, uh, the, the change has been actually implemented.

Ashley Nichols: And so then how would you relate the digital continuum to the, to the federal sector? I know you and I discuss a lot about the difference between modernization and transformation. And then of course, the idea of, of the, the continuum, um, I’ve been around long enough that, that we’ve gone from waterfall to agile. To, to really support, I think this idea of being more on a continuum and less of a, I’m waiting five years for a system to come online and then boom, modern. Um, so, so how, how does the digital continuum relate to the federal sector today? 

James Eselgroth: So, um, it relate, I actually thought about it because of our, because of the federal sector. Um, uh, there’s a lot of, um, working in the federal space, um, being former air force, retired air force myself, um, uh, it’s a very complex monster, um, so to speak, and, um, trying to handle how you want to approach change in an organization is as complex as the air force or any really federal government. Um, uh, military or non military, you have a lot of competing priorities. You have a lot of different people at different levels in the organization. Um, and your ability to, um, where the idea generates from, where it actually spawns from within the organization, what the pallet ability is of the leadership to adopt that idea, and then be able to take the bold steps to actually go, we’re going to put money where our mouth is, and we’re actually going to spend money on this change. Um, but I’ve also seen where. Um, I’ve had, I’ve seen leaders where they’ve gone through and they’ve, they’ve spent that dollar. Um, uh, and it was on what they thought was the fix. Um, and they failed to do, um, one, they failed to address one of one or more of those five P’s. They also, um, didn’t do the care and feeding to ensure that after they leave their, their position. Their post and their prep, the person who’s taking that, taking their position, or that they’ve done the necessary work to, um, ensure that the, that the chain sticks. And so what ends up happening is, and I’ve lived this more times than I’d like to count, uh, where someone makes a huge investment. It seems like it’s going to be a great idea. It seems like it’s going to get off to the grounds, but then something doesn’t allow the change to stick. To stick. And so humans, if we don’t do what we need to do to be able to make that change and have it stick, we’ll optimally revert back to the way it was. And so, um, and so what does that do? That slows time and progress in terms of what the advancements or modernization for whatever the organization’s mission is. So, you know, the sub organizations missions are, um, it wastes a lot of time. And it also, uh, at the end of the day, because we’re talking about the federal government, it potentially wastes taxpayer dollars. And so when we think about. You know, when I was in the air force and I was in government, um, when we would spend time trying to invest in something, we worked diligently. Um, and it didn’t work all the time, but trying to address those five P’s. Um, and so the sustainment actually sticks, um, two times, too many times, you know, they don’t think about the sustainment or they fail to plan in the sustainment of that thing. So, you know, the O and M or like I was saying, the digital continuum aspect when it comes to technology.

Ashley Nichols: All right, Jim. So you started to get into this just a little bit in the answer to the last question. But primarily, what obstacles do we face when supporting our customers in the adoption of new tools and technologies? You talked a bit about the people and culture, but if you, you know, enumerate a couple of, of the primary ways that we get sort of held up, um, in bringing in emerging technologies. 

James Eselgroth: So in no particular order, um, because it really deals with people, right? Cause people are very complex. We’re very complex beings. And so each of us knows what we know, and we don’t know what we don’t know. And a lot of times. Um, it’ll be the, um, the soft skills or, or the organizational culture, like, like you talked about, but let me, let me, let me pull the onion a little bit and go a little bit deeper by, by talking about those things for a few seconds. So one of the things that I’ve noticed when it comes to, um, Uh, working with government and, and talking to them about an emerging idea or something that they want to do, or even an emerging idea that we have is being able to have them be able to sit down with them and understand what are their goals, what, where do they want to be able to go? Um, helping them understand that this black box is actually not that scary. Um, and be able to show them, um, how we can actually turn that black, black box into a white box or, or, uh, or put another way, um, uh, um, understanding what it is versus not understanding what it is, because a lot of it. And the reason I bring that up is that a lot of it is fear. Right. So, um, I don’t understand this thing and because I don’t understand it or how it’s used, um, I might be afraid of being able to use that. And so, um, I, I would rather say I would rather err on the side of caution and say no, then adopt it because I don’t know what it’s doing or not doing. And therefore I’m apprehensive to being able to adopt that technology. So that’s an area. The other thing is, is leadership. Leadership within organizations, um, I have found on both sides, both when I was in uniform and post uniform, um, is leadership actually plays a, quite a big factor if someone’s boss or someone’s boss’s boss, um, doesn’t. Hasn’t created a culture to allow people to take chances and be able to look at things then there, then people’s choice is going to be directly dictated by how much they think they will get the support they need from their boss or their boss’s boss. And so, um, there, there’s both the, the knowledge and know how of the technology, there’s the support from in the, within the organizational leadership to be able to provide the, um, uh, The, the, the latitude to be a little risky, um, uh, to be able to take those things and, and on, on, on this post side of being in uniform, um, I’ve enjoyed and have found that if we do our due diligence in the, in the, in, you know, in the professional services firms arena, um, of trying to be that trusted advisor back to the government, help understand what. Both what they don’t understand about the technology, what it can or cannot do as a critical aspect of, of adoption. And the other thing is knowing your customer, figuring out what, what, what’s not only what are they doing in their specific office, but what are the levers and stuff that are being done outside of them? So their leadership or other forcing factors that helps them out so we can help them be successful by understanding what are the levers or what are the things that are affecting them so we can help address those area. And. When you take the time to do that, the majority of times, um, I’ve seen it go very well until, uh, until it’s a money issue, but for the, for the most part, the technology, um, they, they have a far better understanding because they feel like you’ve helped them out. Um, As well as you understand their world and the things that they’re dealing with so that they can move forward, um, with their own leadership and what they’re doing. And if you take just those two, and there’s a handful of different ways to do this, right? Um, but I’ve seen those two act very, very well, um, to be able to do it. The, the final, uh, the, the one final. Point that I like to add to it is, um, uh, Claire, um, uh, the federal CIO. Um, I can never remember her last name. Um, she came out with a phrase called demos, not memos. And, uh, I heard that shortly after she took over and I’ve been using it ever since. And basically, you know, the best, um, opportunities I ever saw to help a client really understand what that black box is. Um, to the senior buyer is like, don’t take my word for it here. And there’s like a mouse across the screen, take a mouse and give them the mouse and say, why don’t you drive? Um, and, and, and why don’t you play around with it? Um, and then they’ll go, Oh, wow, that’s amazing. And then like all these light bulbs start going off versus death by PowerPoint. Um, or handing them a slick sheet. So, um, that would be the other added way I can help. I, I, there’s been very successful in helping leaders or buyers, clients and customers to be able to really adopt and understand that technology, really bringing down that fear and the unknownness of whatever that technology.

Ashley Nichols: Uh, and speaking of technology, I want to ask. Um, from a technology perspective, how critical is open source and open standards to live in the continuum versus just. Like an upgrade or a transformation. 

James Eselgroth: So open standard, I’ll start with that one. So open standards, um, what that really allows us to do is, um, years ago, one of my, one of my, um, mentors and I were talking about. You know, a plug and play tech stack. So an organizational, you know, you’ll, you’ll be in the cloud. You have a handful of different applications that are in there serving all kinds of different purposes. Um, and you’ve got all this different technology kind of in just, you know, take a step back, just metaphorically speaking, you have all these different technology in there and you want to be able to, you know, I don’t know. Chat GPT is the greatest, greatest raise. Once I figure out what it is, how do I plug that in? How do I plug that into my architecture? Um, and be able to be as vendor and technology neutral, basically trying to avoid some level of vendor lock in, but at the same time, be able to take advantage of these huge investments that I’ve done. And so when you have an open standard, what it does is it allows for everybody. Um, uh, both internally to the organization to help scope and then externally, it allows vendors and, uh, and startups to be able to build different technologies so that they’d be able to plug in, so to speak, like a plug and play, although I’m using that very loosely. In this description, but it allows us to be able to adopt those technologies in a faster way so that they know what the interface looks like, um, uh, so they can build to the, they can build their thing, but to be able to communicate with the other things. Right? So, um, one of the things, uh, my old boss used to say, it’s when you’re thinking about the entire ecosystem of all the different technologies that are, that are in that technology ecosystem for an organization, um, it’s more about integrating the data than it is trying to integrate the technologies. But the. But that’s the path to get into what is that open standard so that I can get to being able to, uh, to be able to plug and play and take advantage of new technologies. So that’s one of the huge advantages of, uh, of that. 

Ashley Nichols: Great. And sorry, I took us in a little technical detail, but, uh, getting back to, we talk a lot here about organizationally, how do we make sure our organization is prepared, uh, To sort of live in this ethos of the digital continuum. So how do we, as an organization evolve, um, with the digital continuum? 

James Eselgroth: One of the, one of the things I’ve been thinking a lot about, and I’ve heard several generals say this, both when I was in the service and ironically, two different points in service. So earlier in my career and towards the end, um, and really it boils down to at the pace that technology is changing, um, trying to. Say trying to, um, grab onto one thing and be really good at that. Seems like a really good idea and we need people to do that, but you also have to realize that at the pace that technology is changing, we have to become comfortable being uncomfortable. And so as you think about the digital continuum, which could be about a specific thing, it’s also about looking at going back to that, you know, metaphorically, all of the technology that’s in your ecosystem and that each of those different technologies that are in there, each has their own life cycle, and each of them could be disrupted by some technology that we none of us had thought about. And then we automatically have to pivot. And so you start to think about, well, dang, I, you know, I really loved my whatever, um, but now I got to go and learn this other thing. And this us as humans, we really are resistant to that change of being able to have to pivot. And so we all have to go through, um, our own mental state. Individually to go, I just have to be comfortable being uncomfortable knowing that at some point, I’m gonna have to pivot from this technology and move to the next. Culturally, the organizations can set up ways to be able to encourage that behavior to go. Hey, we, you know, one set the standard, right? So the leadership in the organization, they live that. Comfortable being uncomfortable state, um, uh, through, and they’ll do that through action, not just through words. Um, and then you can incentivize people by, um, to, uh, to reinforce the behavior that we need to be able to do that through different ways by promotions or bonuses, or, um, any number of ways to be able to handle how you want to be able to show that level of encouragement. Public accolades, those sorts of things. Um, and then, um, putting your money where your mouth is, um, being able as an organization, actually not being afraid to plug and play, not being afraid to be able to move to the next technology, um, and being able to get used to it. Cause the more you do it. The better you’ll get at it. And the, the, um, for lack of a better phrase, the more numb you’ll become to that actual disruption. Um, and in some cases you actually may look forward to it, um, when you go to do it and being able to do it quickly, um, or as quickly as you can, because it’s a very, the bigger the organization, the more complex the changes, because there’s just way more cogs in that machine than a smaller organization.

Ashley Nichols: So you talk a lot about using leveraging technology, like a superpower. Um, so how can individuals leverage new technology to be even more effective? 

James Eselgroth: Oh, thank you. Um, I do say that a lot. Um, um, one of my passions, um, for my time in the service that’s transcend, transcended all the way to these moments here and into the future is, um, I’ve always looked at technology as being. Being able to help me do stuff. There’s on the bookcase behind me, I think it’s over in this section. Um, there’s a great book I read years ago on Python and Python, the programming language, um, not the snake. Um, and, uh, the title of the book was automate the boring stuff. And so I started thinking, wow, if, if, if I start looking at technology in a very broad sense, and I come across something that I think is a task, um, that basically, as soon as I figure out what the process is, I can go, Oh man, I can probably get a technology to do that. Um, and so, um, by thinking about how I can leverage technology or learn, learn the technology that a company has invested it in. So, um, I’ll just use a super simple example. Um, uh, Microsoft Office. So I’ve seen a lot of people get very frustrated with Microsoft Office. Um, um, and a lot of that has to do with just the learning process of doing it. But if you really just, if you lean in like even 3%, Um, versus like all in, if you lean in 3 percent to just learn that tool, go online, take a few classes. Um, if you’re in the military, they have all these different free school, free training that’s available to you. Um, I did it. I went in, in the early two thousands, I had to, I, I was the Excel guy, the Excel guru, but I had to figure out Excel. So I took a bunch of training on how to be able to do it. And over the years I’ve learned all kinds of amazing things that you can do with Excel. I was doing. Data science before data science really had a name. Um, but I was doing it in Excel, um, because that’s the only tool that we had to be able to use in the air force at the time, um, we didn’t have Python. I didn’t have Tableau. I didn’t have all these really cool tools that are out there to be able to help either show the data or be able to do some really awesome stuff. So I was only tied with the tools that I have. So if you’re in that, or if you’re in that area. Um, learn the tools that you have. Take the due diligence of the, if you’re a part of an organization, private or public, take the time to learn your tools, figure out, lean in to be able to figure out how that tool operates and figure out how can it help you do your job? Cause if there’s a rote tool. Task. If there’s something that’s very, um, uh, process driven and you can actually start to offload that to the technology, then that frees you up to do the things that we can’t have technology do. And things like, I want to, I, I’m a program owner. Um, I want to improve my program. Well. Maybe that’s writing policy. Maybe that’s reviewing data. Maybe that’s, um, you know, writing stuff. Um, but if there are elements that I can take out of that and I can have a machine go and do that, then that frees me up to really start thinking about the future state. Where do we want to be able to take this organization? I’ve seen too many times, even to this day, where a lot of organizations It’s still very reactive and we hopefully someday we’ll be able to be proactive, but to go from reactive to proactive means I have to stop being able to react to everything. And we react because we don’t know what’s going on. Um, not that that’s a problem of us individually. It’s just stuff arises and you hadn’t thought through that. Um, and so now I got to stop this other thing and take care of this other thing. And so our ability to leverage technology gives us the opportunity to one, have machines. Automate or automate the boring stuff. And then we can have free our minds to be able to do the complex things that machines can’t do today. And so we can improve our programs. We can make the world a better place in a handful of different ways. And so I’ve always been a fan of thinking about technology in that way of, you know, if I see something, um, one of my old mentors, I adopted his, uh, um, his phrase was, uh, uh, an automation first. Mindset, and so I love that. I love that idea that when I’m, when a problem is faced with me, if I’m pretty sure it’s going to be a recurring problem or a recurring thing that I’m gonna have to deal with, I immediately start thinking about, well, how can I leverage machines to help me automate this? How do I leverage technology? What technologies? And the first thing I do is I look at what technologies has the organization paid for? What do I know about them or not know about them? And if I don’t know something, I reach out to a SME within the organization to learn very quickly, or go to our friend Google, um, or your favorite search engine and be able to go find more information on that. So I can figure those things out. And it’s been, it’s been very rewarding with that mindset. And it’s allowed me to be able to do some amazing things over the past 24 years. 

Ashley Nichols: So I think we’re at a time now where. You know, you say, tap into the suite of tools that your organization provides and make sure you can maximize it. Well, we are now at a time where within the last 12 months. There are tools available to us beyond just what our organization provides. Right. And of course, I’m talking about AI and how people are leveraging in their everyday lives. They plan trips with it. They set itineraries. They, you know, we all do all kinds of stuff for like, Whoa, can this help me, you know, gin up a letter I need to write or whatever. So we’ve seen a lot about large language models and AI, obviously like Chachi PT, Claude Bard, all of it. Um, Walk me through sort of what they are and how they can be leveraged. Especially within the federal sector, and then sort of what are the pitfalls and areas that we need to be aware of as we’re bringing these enablers into our everyday life?

James Eselgroth: Yeah, um, so large language models. So there’s still a lot, um, I am by no means an expert when it comes to large language models. Um, like most people, I know what I know and I don’t know what I don’t know. What I do know is, um, uh, uh, the, the transformers that they’re built on, um, and the corpus of knowledge that they’re trained on allows us to have this interactivity. To have an output when we prompt it appropriately, um, to have an output. So I can share much information with them. Um, um, a colleague of mine years ago, um, or maybe it was a book that I read. Um, basically the phrase is, um, if you’re using something and you’re not paying for it, um, if it’s free, then, then you, then you’re the product. Um, meaning that, that when you’re, when you’re going to use utilize a tool, they’re tracking the data. On how you’re using it. Um, so that’s a warning, right? So realize that if you’re not paying for something, then you’re the product. Um, uh, but just know that going in, that’s not to say not to do it. It’s just know it going in, know that when anything that you share could be used, um, in any way, form or fashion that, that, that organization wants to do it. Uh, or utilize that, that information. Um, uh, which actually is why the, the EU came out with the GDPR. Okay. Um, uh, the, the, the, the data rights out of the EU, California has something very familiar, similar, and we’ve been working at the federal level to be able to put something together. Um, they’ve been working diligently trying to figure out how to be able to have that things like the ethical AI, um, memo that came out of the president, um, in the past six months or so. Um, all talk to these, these aspects when it comes to the data. Now, when you’re dealing with this, um, this is what’s what I found really interesting, um, uh, questions are more important than answers. So when, and, and, and, and in no time in our, in our species, have we, where we are, have, can we really see what that means when it comes to just talking to these large language models? Um, so if you ask a very generic question, you might get a really deep, or you may get a confusing answer, but the more specific you can be, or even the. Tell it to act as something. I want you to be a proposal manager. Um, uh, with this much experience, I mean, you can, you can create personas by just uploading a resume, a job description and say, this is, I want you to be this. And it’ll go, okay, I’m, I’m that let’s talk. And now you’re, now it acts. Takes on, um, a good portion of what it’s like to talk to a proposal manager. And so I need your help writing this, or I need you to help to author this thing. And so you could be able to do it. And so you can start to interact with these different models to be able to. Um, get really cool answers. You can have it to write blog articles. Um, it seems that there’s no limit so far to what you can try to do with these things. People are coming up with apps and new AI’s daily. It seems like, um, with a new one that’s out for a very specific thing. And so it turns out also that the large language model may be general, right? So they call it an AGI, an artificial general intelligence, but it’s actually, it’s general in that the corpus of knowledge is just vast, but it actually really shines if you can have it focus, which is where the question and the persona and those other things, if I have it focus, it does really, really well in that very specific area. Um, uh, and the warnings are, um, some of the models. Um, we’ll take your data and then we’ll train the model continuously. So as you ask a questions and share information, it sees that as new information and it’ll go back and it’ll train the model. Um, not all the models do that, or some of them do it differently. It’s why it’s so important. You got to go read the terms and conditions when you’re signing up for any of these. Um, the paid models, um, uh, some of them ensure that when you go to pay, when you go to pay for the models, um, they will not use your data to train. Um, uh, Microsoft and its implementation of co pilot with, uh, that’s powered by ChatGPT. They don’t take your data and train the model on it. Your data is your data. Um, somebody else out there, Nick Chilean, um, created AskSage. Um, that, he, he’s done a phenomenal job of giving you access to all the different large language models. Um, and some of them you can actually work, you can actually, um, Um, uh, upload and talk with CUI data or controlled unclassified information data. Um, he’s in the process of being fed ramped. I believe part of it is fed ramped, um, for his tool, but you just have to know going in what models you want to work with, what they’ll do with your data, how much information you want to share. Um, uh, there was an incident recently. Um, I read, uh, prior to that three, four weeks ago, maybe a little longer than that. Um, there were some engineers at Samsung. That we’re talking with Lord of the large language models and they had accidentally shared a lot of the specs of their engineering and they loaded it into the large language model and someone else somewhere else on the planet was asking a very, it must’ve been asking a very similar question and output the Samsung data. And so they’re like, Whoa, but that’s, that goes to somebody didn’t do their due diligence to make sure that, that, Hey, these are the things that you have. This is how you can pass to it. This is what you not should pass to it and understand really what they’re doing with that data. Um, so that you can actually take advantage of these tools. Um, and so there’s been a lot of investment. Um, and all the major players on how they can leverage those things. What’s the, you know, what you should do with it, what you shouldn’t do with it, and ultimately making sure that your data doesn’t leave, um, whatever fence line, so to speak, in a metaphorical sense. Where do you not want it to go? 

Ashley Nichols: Yeah, absolutely. 

James Eselgroth: But it is by far one of those, um, uh, um, definitely a technology, like a superpower. Um, uh, that’s a great example of being able to do that. 

Ashley Nichols: Yeah, it is certainly one of the most significant needle movers of my 25 year career here, uh, that happened so, so, so rapidly.

I mean, it didn’t really, but it feels to us that, you know, recently get access to this, how rapid it is. 

James Eselgroth: Yeah. 

Ashley Nichols: Um, But with that, besides the buyer beware of what you’re doing with AI, uh, as we sort of round up the chat today, what, uh, can we do as like a first action step after this podcast to get started with making this shift from. Modernization transformation to the big, the bigger thinking around continuum, 

James Eselgroth: I’d say the first step would be, um, take the chance individually to learn any of the technologies that you have today, um, and then take the next step of trying something new, even if it’s small. Just try something new, um, to get used to what that could look like, because you may find that something new. It could be, I’ve never worked with Excel. I want to go learn how to do formulas in Excel. It could be, um, I want to use Copilot inside Word to help me write something in Word today. Um, the hardest part in any new journey is always taking the first step. Um, so don’t make that first step feel like it’s a mile step. Uh, it could be an inch. Um, uh, it’s just about consistency and just trying something new and trying to just learn the tools that you have today access to so you don’t have to pay for anything. Somebody’s already paid for it. Go try it out. Go check it out. Go try to learn more about the tools that you have, which will probably give you more ideas on either how that that tool is used or to give you ideas on maybe the next tool in your organization that may replace that one because it may not meet all your needs. But don’t throw it out. Without trying to fully understand it first 

Ashley Nichols: and organizationally, you know, being prepared to support. Your folks who are doing that, right? We’ve all been part of organizations where you’re like, Hey, I’ve got this crazy idea I want you to think about. And, you know, it gets shut down, which is more about, you know, but when folks are leaning in, like, Hey, I’m going to try this crazy thing, like, you know, like, all right, I’m going to. Give you a minute, go do it. 

James Eselgroth: Yeah. To that point, I would say to the leaders out there, and that’s any leader that if you’re overseeing a small team to the CEO or the commander of an organization, every leader in the organization should take the, should be able to, uh, encourage risk taking, um, allow people the opportunity to do something amazing, knowing that they will likely fail. Um, and reward them for the chance reward them for, Hey, you stepped out of the comfort zone and you did amazing. And when you give that accolade, do it in public, because if you tell somebody, if somebody tried something and it didn’t work and you publicly tell them publicly say within your. Community, um, uh, you know, the small unit, the large unit, the, the public or private organization, what you’re really doing is you’re not taught. You’re giving that person kudos, but what you’re really doing is you’re also talking to everybody else in the organization because what you’re telling them is, Oh my God, that leader is willing to take risk. And look, that person failed. And they still gave them accolades, which means maybe I’ll step outside my comfort zone because now maybe I feel like my leadership will have my back. If I bring a new idea, if I take a risk, the worst thing that you could do is berate that person. And hammer them because all you’ll do is close off any new ideas from anybody in the entire organization. 

Ashley Nichols: Yeah, it goes towards, uh, and this is a topic for another podcast, but you know how you create that problem solving mindset in an organization so that it really pervades the culture. Um, and that, that is a big part of it, right? Acknowledging the success. Of risk taking and failure, uh, as well as the successes that come from it. Um, well, Jim, we’re going to go ahead and wrap up. So I want to thank you very much for, for joining me today to talk about this. Uh, and thank you all for listening to the highlight cast. Uh, to keep up to date with our latest news and activities. Follow us on LinkedIn or visit, visit our website at highlight tech. com. Uh, tune into our next episode where we will be discussing emerging technology. Thanks again, Jim. Thanks. 

Thanks everyone. The views and opinions expressed in this episode are those of the hosts and do not necessarily reflect highlight technologies and or any agency of the US government.