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405- From Submarine Periscopes to the C-Suite w/Roy Cherian · You've Been Heard

• 0:10
  Speaker A: So talk to me about how did you get started in this whole IT thing. What was your first computer? Where did you start out as an engineer or creative writer or something like. No one starts out in it at our age.
• 0:21
  Speaker B: Yeah. And nobody does started out. Commodore 64. Yeah. So I was in the Navy, and I worked on optical electrical systems for, like, submarine periscopes and stuff. So I went the engineering route. And honestly, when I was an engineer, I didn't really respect the IT guys because all of the problems are all logical. Right. When you're working with, like, something like submarine periscopes, you got temp vibration, seawater pressure, all these other factors that come into the systems, et cetera. So. But then I was going through graduate school and I took.
• 1:05
  Speaker A: Let's hit on this subject first of all, because this is actually an interesting subject because one of the problems that IT guys have a lot of times in organizations, especially if they work in an organization with a lot of R and D and a lot of engineers. So they have a lot of smart people. They're the smartest people in the room. And what do the engineers not want to do? Follow security protocol and not be able to die.
• 1:22
  Speaker B: Oh, yeah, they do.
• 1:23
  Speaker A: Whatever. Exactly. So you were that person.
• 1:27
  Speaker B: Yeah.
• 1:28
  Speaker A: So why did you have no respect for them since you were there and now you. What can we do to fix that?
• 1:34
  Speaker B: I was young, all right? Was very young at the time. And I really didn't get into it until I took a community college class. Just to sharpen my IT stuff. I took Cobol. It was a micro Focus Cobol and RPG for the AS400. This is back in the mid-90s, right. And the first day in the RPG class, it was a community college class, Right. A guy came into class, he looked like Jimmy Buffett. Been working, obviously, doing some Bermuda shorts. Bermuda, yeah, Bermuda shorts type guy. And he. And he. And he started out the class saying, the class officially starts at 6, but it's. He says, I'm not gonna get here before seven. I'll stay as late as you guys need to get the work done. And so I was like, I'm gonna like this guy. So I started.
• 2:23
  Speaker A: We gotta go back in time, set the. Set the stage. What year was it?
• 2:26
  Speaker B: This was 1997 or 1996.
• 2:31
  Speaker A: All right, Windows 95 nearing N. XPNT or whatever. I don't know. Anyways, where were we? Anyways, go ahead.
• 2:38
  Speaker B: Yeah. So I took the RPG class and I was like, this stuff is cool. Just being an engineer. RPG is very formatted. Right. So I, I read the book. It was by a woman named Judy Yeager. That was the. For people that worked in RPG back in the day, they know who Judy Yeager is. So it was very easy to read. And I just fell in love with coding. I would read ahead, he'd go through if then else. And I would say, well, can I use subroutines? Which is later in the book. He says, absolutely, do whatever optimally. So this is where we still had green bar printers and all that. So that's how I fell in love with coding and started. I was still in the Navy at the time. So when I left the Navy, I went to a company that had AS 400 loss and financials, all the AS 400 related software products. So how would you fault. Yeah, so that was down in Birmingham, Alabama and then moved all over the place, worked in multiple industries, went from a retailer to construction concrete products to a defense contractor and then continued from there. But the, the, the great thing about it in my viewpoint is if, if you have a passion for completing that puzzle or we're puzzles oriented people. Right. Fixing it.
• 3:59
  Speaker A: Here's how it people say it. After almost 400 shows, curiosity should be one of the number one ways of being in it. If you're not curious, then you might as well get out.
• 4:10
  Speaker B: Yeah. If you're not curious, then you're just sucking up air.
• 4:14
  Speaker A: Here's the thing.
• 4:15
  Speaker B: During the dot com era, we had a lot of folks taking those classes just trying to get into the business. Right. And I could see they're very linear in their thought. They didn't really. My instructor, the Jimmy Buffett guy, said, roy, you should really get into this. He knew I was taking it on the side going through grad school. Right. So MBA is what I was going after. So I said, well, there's no money in this. This is too easy. Right. Because it's not hard like some engineering. Yeah, There's a lot of money in it. And that's how I got into it. I really enjoy doing it. And at the defense contractor, when I first interviewed there, my manager asked me, well, what do you want to do five years from now? I said I'd want to do the same thing I'm doing now, which is coding. Right. So but from there I realized even
• 5:04
  Speaker A: you realize there's a really good subtopic here that we're skipping.
• 5:07
  Speaker B: What's that?
• 5:08
  Speaker A: There was a really good subtopic that I want to skip over because you mentioned.com phase. We still haven't answered the how Jimmy Bucket from Unisports wearing guy somehow led you to respect it people and not be an arrogant engineer minded guy. You somehow there's some connection there that we're.
• 5:23
  Speaker B: It's an artistry you mentioned. I forgot we got into the puzzle conversation. Right. But it was. You can make artistry in code and make it very tight. Right. And very cool when you make your first. It kind of reminded me back to the Commodore 64 fooling around in my room. My being able to code and do something. Right. So that's what I. Baywatch encoding. Yeah. Yeah, babe, watch Hasselhoff guy. Love to be that tall.
• 5:55
  Speaker A: David Hasselhoff.
• 5:56
  Speaker B: Yeah, yeah.
• 5:57
  Speaker A: And again it's a very interesting correlation because most people. The other thing that you really want to like kind of go side by side with engineers also is like maybe artistry and art but there is kind of a mix of people. But it's like this artistry, yet perfection at the same time. And the reason why I'm saying there's a really good side topic here is. Well, first of all, you mentioned the dot com area and he said that you should really get into this. Which I would love to know what getting into it meant and how does that correlate with a new era of.
• 6:25
  Speaker B: He meant getting onto it as a profession. Yeah.
• 6:28
  Speaker A: Okay. Okay, great. So now what about AI? Because we have some similarities and some very big differences because back then the dot com era was like, ah, I don't know if this is really ever going to take off. Sears had the wrong approach, obviously. Toys or had the wrong approach, they're all sunk down dead. And obviously Mr. Bezos did not have the wrong approach. So people were kind of like screwing around and late to the game and. And now it's almost the opposite. It's like everyone has to get into AI. We have to get into AI right now. And it's kind of a. There's some similarities, but differences. I'm just curious as to what if you have predictions, what's your prediction. What's your prediction here of what's happening?
• 7:06
  Speaker B: Right.
• 7:11
  Speaker A: If your Internet goes down and you're calling carriers yourself, that's not strategic. It's. We help teams centralize monitoring proactive tickets and escalation across every location without capex. Less noise, more uptime, make it boring again, just go to you've been heard.com and answer the seven questions to simplify, streamline and save.
• 7:33
  Speaker B: It's funny you mentioned that. Right. The.com Similarity here, my prediction. And I said this, I put this on a LinkedIn post. Actually, I loved my BlackBerry and when I went to the iPhone, Samsung, I didn't really see the value of the iPhone because all I cared about my BlackBerry was my email and phone. Right.
• 7:56
  Speaker A: Physical keyboard.
• 7:57
  Speaker B: Yeah, physical keyboard. Right. And it wasn't until later and I was like, I have all these apps. I'm going to have this app for ways that I can navigate the optimal path and know where law enforcement is in case I have an emergency while I'm driving. Right. So yeah, so now I'm looking at some of this agentic AI solutions as. Stop looking at it like you have to build the ERP of AI. Maybe point solutions that bring immediate value or near term value can help a business out and just like those apps. Right. I wouldn't go to the Waze app for weather necessarily. Right. But I know it does a good job in what it does. So maybe the Agentix solutions, while you still have an overall path to get to kind of the ERP of AI, you kind of build these little nuggets along the way and then success breeds more success. The CEO is wanting to do something in AI, but so does every other CEO in the country. You build those use cases out and you put them into fruition. I mentioned also like 5% of AI use cases right now are successful and bringing ROI. But that's a bad success rate when 95% are failures. And I'm wondering what's.
• 9:12
  Speaker A: But the ones that.
• 9:12
  Speaker B: But the ones that are successful are extremely successful.
• 9:17
  Speaker A: Yeah. I was just talking about this with the team this morning and I have the statistics here. Well, I mean, yeah, you're absolutely right. It's the opposite. It's 95% of engine deployments fail to generate ROI.
• 9:31
  Speaker B: Yeah.
• 9:31
  Speaker A: And audio City. Yeah. Enterprise. Yeah. Okay. No, no, yeah. In 5% are extracting millions of dollars of value and kind of this. It's perfect for the mid market space because I think mid market guys have in or mid market to Fortune 500. Some people get offended when you say mid market. I'm not mid market. Like, okay, Fortune 5000. Yeah, emerging. Fortune 5000.
• 9:53
  Speaker B: Yeah, emerging.
• 9:55
  Speaker A: What else was in that? Like 43% of data readers point to data quality, completedness and readiness as the biggest obstacles for Gen AI. 45% believe that concerns over the responsible use of AI prevent them from demonstrating the business value. Okay, so we got security in there. 91% of mid market. 45,000. We've got to add in. 45 firms have adopted Gen I and 25% of companies using Gen I say it's fully integrated across their core operations or workflows while 42% say it's integrated across some operations. So we know there's like a lot of people that just say oh yeah we're win, we're, we're fully deployed AI and you've got CTOs are like, are like so. But that's like beside the point. How does this compare to the the.com era? And why is, is everyone, is everyone ready for it now? Because back then they weren't ready for technology because we didn't even have the Internet yet.
• 10:47
  Speaker B: I, I think one, a lot of folks are scared of AI. We had the general user community right. They were afraid of not having a job type stuff. We had a big poll when we had a whole bunch of folks in. What are you excited about AI? Yes. Are you scared about AI? Almost everybody had their hands up. Maybe five people didn't out of a group of 50. So it's unlike the dot com era. There is the am I going to still have a job concern and then AI literacy is the big thing I hit on. I told in our senior managers meeting I'm not you have agentic AI and then you have artificial general intelligence. And I kind of said hey AGI nation states are battling for supremacy there. I'm not worried about Terminator from the business sense. Right. Or Skynet personally I am. No. Well yeah, that's a different topic. Right. It's just a different topic. So what we can control and be able to use is agentic AI solutions. And that's where my focus is and being able to take advantage of the capabilities in there and find the right solution there. I had a scenario at my old company where we were trying to find a contract. Any type of email traffic on a contract would bring significant revenue legal related activity. Right. And we were looking at the usual email ediscovery and the Microsoft said here's the benefit of like a copilot, it's a vector related search compared to the standard eDiscovery search that we do. And you may be able to get the end result you're looking for because you're attacking it at two different angles and it makes perfect sense to me. Unfortunately we didn't find it. There was no historical document seven, eight, nine years ago that could have made a difference. But the point is I was like okay, we're looking at it differently. It's not just the same Google search right. That we had before. And when I said AI literacy people agentic versus artificial general intelligence business users don't know the difference. Right. And then even with agentic and understanding, you still have to train the models you have to start with. Not really build your own. Right. Maybe get a COTS commercial off the shelf product that then you tune it to what you need. I'm not going to have a model that or an AI, say chatbot or something that a person's going to come to it because I sell coolers and ask me what the capital of Argentina is. Right. So they're going to be very business centric. So train it correctly and spend that time.
• 13:31
  Speaker A: So everything you said is right on point from that piece. Yeah, I'd be interested to see what kind of point solutions you guys are interested in. So that MIT article had like three main, it basically had three main reasons why people struggle with it. It was, number one was misaligned strategy and people don't even have an AI strategy to begin with. And then poor adoption of anything that they actually do implement because most of the so called in quotes sanctioned tools fail to meet the employee needs. So poor adoption. And so you have people doing shadow now you've got the fear of shadow AI and security issues. And then to your point though, implementing this point solutions and everything leaves fragmented platforms and complex.
• 14:16
  Speaker B: There's a, there's a potential for that.
• 14:18
  Speaker A: But I disagree with a lot of what they're saying though, by the way.
• 14:21
  Speaker B: Okay, so I, I only disagree because.
• 14:24
  Speaker A: Because I can understand the building thing versus like don't build like buy versus build. I think that might be one of those like kind of gartner pay to play things where they're like no, because we want to buy stuff from people. But I'm telling you we built something. I mean if you have a really good AI team and you have a DevOps team that's not, that's ready for this onslaught of change and they're like on top, they're like ahead of the curve. I think those point solutions can be, you can start like knocking those out of the park one after the other and you don't.
• 15:04
  Speaker B: Yeah, 100% agreement. The key thing is AI literacy across the board, IT and operations and back office. Because what ends up happening is they pick a tool and it's like if all you have is a hammer, everything's a nail. Right. So they're not necessarily looking at it as use cases. And seeing if I had this, if I could lower my defect rate from one part failure per 1000 to one in a hundred thousand, it's a hundredfold increase. Right. Because the rework Costs, et cetera. So it's changing the paradigm shift, or having a paradigm shift to get to look at it almost as process improvement elements. Right. And forcing people not to think this is one big magic box here. That magic just suddenly happens without the diligence and putting some elbow sweat into it. Right. To get to the end result before you start picking, don't start with a tool and then apply the use case. Find the use case and find the applicable tool.
• 16:08
  Speaker A: Yes. And that's what's difficult if you don't have someone at the helm creating a strategy in a way that people understand how all this stuff really, really works. And I think there's going to be a lot of fail forward type of stuff.
• 16:25
  Speaker B: And it's not always bad to fail because hopefully you learn from your failure to move on to the next. Right. But it's better to fail with small things and then be able to get that success. And you learn. Just like they use the crawl, walk, run. Right? Yeah. When you're crawling, the baby stubs his toe, falls on its base a couple times. But it's better than falling when you're standing up. Right. Or running. Yes.
• 16:48
  Speaker A: So much has happened in like two months. Like three months ago, I went from saying that the AI coding is like really sloppy to, well, it's sloppy, but it works great. Now and then as of this week, I saw actual, almost like a knowledge worker happen with the Claude opus, like release and the kind of worker thing, which actually scares the crap out of me and it should scare the crap out of a lot of security people because it's just like, yeah, have access to my drive. Yeah, go ahead, search. Go to my browser. Yeah, do this, do that. I can see that being very problematic with a lot of companies right now, but I think a lot of people probably don't even know what it can do.
• 17:29
  Speaker B: Yeah. There are going to be changes that are more rapid. Right. If I go back, I was unemployed for about six months on the job search between my last and this. Right. So I spent a lot of time. I actually read Google's article, attention is all you need. Did a lot of. Because I really wanted to understand. I didn't want to get into the math of the algorithms behind the scenes, but I just wanted to understand what it does. Right.
• 17:53
  Speaker A: So what was the summary of that? Attention is all it needs?
• 17:55
  Speaker B: Well, it's almost like to me, if I was going to summarize it, it's almost like parallel processing. Instead of looking at it as linear, think of the searches. Right. The vector Searches being parallel and then building within the LLM space. Right. Building a full paragraph. Because now I look at it back in like teradata days when oh, they have multiple stacks going, multiple disks going to. Not single threading, multi threading jobs. Right. So that's how the crux of it for me, that's what I learned from it is oh, okay. That's pretty simplistic when you think about it. A couple Google engineers said why don't we do it this way. Right. Multi thread. So use that same philosophy there. And as far as AGI, my only two bits on that until I really get to quantum computing. I'm not afraid of Terminator. Right. So maybe a couple years down the line. It's not that long. Right. But we were talking about.
• 18:51
  Speaker A: So you're reading the time off six months. Read the Google thing and. Yeah, yeah.
• 18:57
  Speaker B: And did Harvard course, the free Harvard course, et cetera, try to soak right into AI. And then my present organization, we make world class refrigeration units. We were looking at AI simply from an RPA engine. That is AI because that's all they see is that the hammer. That's the hammer and everything's a nail. Right. Instead of getting AI literacy down to the masses, to the decision makers, et cetera, and then finding the valid use cases, having an AI steering committee or AI working group doing the foundational stuff, right. To get people knowledgeable and then let's not make the mistakes of the past. Let's not be part of that 95%. Let's nail down the use cases, let's find tools and let's get a partner. Right. Why do we have to do the journey by ourself? So we're looking at a partner that will help us on our journey. And 20% of their client base is manufacturers. And when I looked at Gartner to see, well, what's the use cases that manufacturers do, Right. Gartner, I consider librarians, right. To help me get the knowledge I need to pursue. And they said defect tracking for manufacturing space, basically all the stuff that reduces cost of goods sold. Right.
• 20:12
  Speaker A: Process.
• 20:12
  Speaker B: Yeah. Process engineering.
• 20:15
  Speaker A: Yeah, yeah. Because I mean in manufacturing there's a lot of things that we just do from a kind of to your point, like a linear start stop type of thing that could be organized better for better output, batching and things like that. I mean we've had plenty of people on the show that were able to increase like efficiency by like 107% and get rid of temp staff, all because they were they're batching orders wrong and placing a broom in the wrong end of the warehouse and having to clean machines just to make a new thing and stuff like that. Whereas if they had batched orders correctly and it was just like in manufacturing,
• 20:53
  Speaker B: I see a lot of similarity between like a Six Sigma process improvement approach with layering AI on top of it. It's almost like it's.
• 21:02
  Speaker A: Do you think it would be useful if we all put our heads together and had a. Almost like four hours to get the outline of your AI strategy together in like seven steps or something like that? I'm just trying to think of like, is there, I don't know if there is anyone that's done that yet, like how to put together your AI steering committee and your, um, AI strategy. Would that be helpful?
• 21:27
  Speaker B: I, I think it's helpful for any organization that's starting. Yeah, absolutely.
• 21:31
  Speaker A: Or even how to train your end users. Everything about AI the right way the first time without, you know, I mean, that's something like that. Because I think our producer, Greg, he's been, I mean he. We've been on this kind of like AI thing from the very, very beginning and made all kinds of mistakes. And I think that's what I realized is if your end users don't learn it now, it's going to get to the point where if you start using it, you're going to be behind because you have to build this entire almost library of skills and resources and train models to work for you versus you. Kind of like you said, just hammer and nail. Like, I'm only using it this way. Whereas if you really kind of understand how things work, you won't. I just realized I'm, I'm like way behind on a lot of. Kind of. For a while it was like, okay, which LLM? How do we use this? What do we use for this? What do we use for that? It's just kind of like this like insane asylum of like each week, oh, well, this is better than that and this is better than that. And finally you get to the point where you're like, no, I've got to pick one thing. Or if I don't pick one thing, I have to have my own personal strategy for information that I feed these models in a certain way and it's got my data has. It's the same thing that everyone talks about all the time. It's got to have my data organized in a way that's going to be efficient for these mobs.
• 23:00
  Speaker B: Yeah, you're mentioning stuff. I put my LinkedIn on there with coming in ninth place on AI. Right. I call it the participation trophy. Right. So my how I was relating it to AI is you can define what first place is, whatever. Right? Because there is no first place. We're racing against ourselves. But if we nail down those incremental wins and we get those big wins, then ball game, right. So. And it just approves from there. Let's stop trying to find the perfect answer is I think the crux of what you were just saying, take a, a path and stick with it and then mature as you go on. But by overanalyzing, starting the process, at least getting steering committee, at least getting AI literacy nailed down to the masses, education kind of first. But I know CEOs are always looking for what quarter are you going to have some product ready. But emphasizing AI literacy and having that maturity curve keep on growing I think is going to be the path to get the solid results for a lot of.
• 24:07
  Speaker A: And it's a great transition. Okay, so the C level executives are like, okay, what do we got in production? What are we doing for AI? Are we all in for AI? Cause I already told the board, yeah, we're spending on AI and they've got a lot more pressure than Haas, believe it or not. A lot of times CTOs and CIOs were. There's this interesting duality going on because a lot of times we're saying, oh well, we haven't seen the executive Roundtable. Okay, great. I want to hear how you answer this. And I know you probably already answered it and I didn't, I didn't look at the answer, but I'd rather do it. Vive. So after all these episodes, everyone knows nothing gets done in any company without it anymore, whether they want to admit it or not.
• 24:41
  Speaker B: Great.
• 24:42
  Speaker A: But I still think that there's a lot of insecurity around do we trust it with the business and making business decisions and that's it's fault because we need to speak roi, ebitda. We need to speak bottom line, flow through profit, all these different things, right? So we may have a seat at the executive Roundtable. We complain about being the department of IT or not being the whole company or not being there. Kind of like right up with like, do we see our team as the C level executives or do we see our team as the help desk and all the guys if we're in charge of. So anyways, having seen the executive roundtable, Nice. Right? We started out in technology, we rose all the way. Here we are in this Position. But how much nicer would it be to be heard? Do you have any thoughts on that? Well, like I said, I mean heard and understood, like from a technology perspective, a lot of times we understand them and we may not enough and we may not speak up enough and speak in ROI and all those terms.
• 25:31
  Speaker B: But.
• 25:31
  Speaker A: But how nice would it be for us to be heard and understood from the technology angle?
• 25:37
  Speaker B: Absolutely. First week, know your audience, right? So if I'm not going to do technobabble in what I call technobabble in front of the C suite, right. To the CEO, et cetera, I always use analogy to explain concepts, right. I use the analogy of BlackBerry to iPhone to apps Waze. Right. To explain how for agentic AI, we may need to look at this. Right? So using analogies and being able to relate it to bottom line impact, et cetera, the C suite IT managers that want to move into like C suite type roles need to be able to convey that. And without the technobabble, right. My boss or my boss's boss, right. Would know what VLAN separation is or any of the other stuff technology professionals would understand. Right?
• 26:30
  Speaker A: So explain edr.
• 26:33
  Speaker B: What? It's funny you mentioned EDI because depending on the company, I, I came here and I've been working in EDI type stuff for 20 years. EDI been around for forever, right. But how they see it is not how it really is. I was like, yeah, well that's not edi, that's a requirement.
• 26:54
  Speaker A: So how do they see it?
• 26:56
  Speaker B: Yeah. So that tells me technology maturity had challenges. So each company is unique, right. Each corporate culture is unique. So you're you originally ask, I hope I answered is use analogies. Don't use the technobabble. Try to get it to home on the C suite. To say that I'm a partner you have and a trusted confidant like the internal counsel, the legal officer, whoever it is. Right. Is out for the company's best interest. Showing that you're out for the company's best interest. Why you see this is going to lower the cost of goods sold or why this is going to increase revenue or reduce risk. Have that solid business relatable item in front of the C suite and even if you have to take them on a journey to get to that relatable item, educate them to get to that relatable, relatable item to them. Right?
• 27:48
  Speaker A: Yeah.
• 27:49
  Speaker B: I love it.
• 27:49
  Speaker A: I think security is one of the harder sales because it doesn't always necessarily point to new revenue, it points to not losing revenue.
• 28:01
  Speaker B: Yeah, it's a risk mitigation. The world is a dangerous place and I emphasize this all the time. We're looking at our Microsoft agreements. The other things to see do we have the right security posture. My partner in this AI journey to help facilitate it is our ciso. So I wanted to make sure hey, we're not running off. I even said it to the managers. The worst case scenario to me is someone does I have an AI engine of some type and you ask them what the company's individual salaries are for all of our managers. And all the eyes went up and said yeah, that's why we need to protect against it. And we have to have a strong security dimension to how we build these AI products and how better to do that and then have the CISO actively engaged as a facilitator in these projects that we're doing.
• 28:49
  Speaker A: Do you start with the the fear slide or do you end with the fear slide when you're selling security? For example I was just talking about this the day and I'm just looking at presentation they were doing around health care and security and the average health care breach in 2025 was 7.42 million. Yeah, supposedly if these numbers are right. Right.
• 29:08
  Speaker B: Yeah it is probably higher which was
• 29:11
  Speaker A: three times higher than other industries and it was up from 2.87 let's see, 2.87 billion. No change in healthcare attack in 2024. 67% of healthcare orgs were hit in 2024 with something that's. That's really astronomical. The average downtime per attack was 19 days.
• 29:34
  Speaker B: Oh, I didn't hear that metric before but.
• 29:37
  Speaker A: But this is for the ones that were like really hit with bad ransomware.
• 29:40
  Speaker B: Right. Well that should remind non IT professionals how serious it is for our discipline to exist. Right. And we can't just be a truly just support function. Right. To keep the lights on et cetera is to be at the table preventative measures. You try to do the best job you can to prevent scenarios and then when a scenario happens having a good mitigation plan. Somebody had told me it security look should look at a set of like looking at it visually as five basketball hoops that go backwards and forwards and for the hacker to penetrate has to hit the right sweet spot that all hoops are all centered. Right. So you, you try to make the multi layer defense. You know that it's not a question in it if but when a scenario happens that a breach happens or attempted breach happens and then what's your mitigation strategy? Don't fool yourself into thinking it can't happen to me. Regardless of how impenetrable you may be from the outside, you may be very impenetrable from the inside.
• 30:47
  Speaker A: 340% increase in OCR enforcement. That means therapy, healthcare, Max annual penalty last year HIPAA penalty 2.1 million. The largest ever Anthem. I'm assuming that's Anthem Blue Cross Blue Shield or whatever settlement was 16 million. That was the security piece. But just from how it can partner with the business, if you had like three steps, five steps or six steps for your technology, digital transformation or to partner with the business, when you come in and create that type of really great relationship with the business, what are some of the big ones for you?
• 31:26
  Speaker B: Well, you asked originally the fear or the promise, right?
• 31:31
  Speaker A: Yes, yes, yes.
• 31:32
  Speaker B: And I say both. One, even on the promise, it's not going away. It's not like the.com era in that instance where Internet was still new. We are living in an AI world whether we want to be a part of it or not. Right. And that's not going away. So let's adapt there. But realize the fear component and being able to mitigate risk on this side is just maybe not just as important. I. I think we sometimes go too far into the fear to get to the right end result. It's coming and we're in our beginning stages. Right. So adapt and be willing to adapt. Don't worry about losing your job even if you are on the security side because the machine isn't that smart yet. Right. And look at the potential for growth.
• 32:23
  Speaker A: Right.
• 32:24
  Speaker B: As a business and how it is essential part of that. We can't own the AI journey. We can help facilitate it in it. Right. The operations, in my case manufacturing, the back office guys, the CEO have to help because they set the strategic objectives of the company. Right. So we're part of that journey. So I don't know if I answered your specific question there.
• 32:48
  Speaker A: Okay. So I'm just saying if we had to break this down into like three things. You did kind of like three. It doesn't have to be three. Let's say we do break it down into three things. What I heard there was first check security. Make sure that we find out what our security posture is. Find out what the goals and direction and main priorities of the of the business are from the a CEO's perspective.
• 33:10
  Speaker B: Right?
• 33:11
  Speaker A: Right. Because it has to align with that. Yep. And then we have to make sure that we don't blow the whole thing up because we had ransomware attack. What's the third Thing.
• 33:22
  Speaker B: Well, the third thing is realize you're going to fail. Right. And how are you going to recoup from that failure and yeah, fail faster. Yes, exactly. And how you limit cost and risk and all of that, but socialize that. This is all new turf. It's not like it's been around for 20 years. So this is new turf.
• 33:43
  Speaker A: If we had to fix one big challenge in IT leadership tomorrow, the craziest thing that you deal with, what would that be?
• 33:52
  Speaker B: In IT leadership? Stop with the fluff. I see postings on LinkedIn all the time. We all know every software vendor is claiming that they've just made the next great AI component of their software. Right? Read through that stuff. Stop with the fluff. Don't make the promises and don't be a puppet on AI. Sprinkle some AI on it, right, and it'll solve the world's issues. It doesn't because I, I look at AI as great tools, but those tools are different in that they're learning and recoding themselves in my mind to be able to be more and more efficient. So look at AI as a child, very strong child that you need to grow and nurture and along with the business, along with AI literacy in the business to get to the end point and don't get those small incremental wins. But you should have the AI overall AI strategy built or thought through, aligned with the corporate strategy. Right. It becomes a component of the corporate strategy. That's my frustration. I see a lot of fluff out there.
• 35:00
  Speaker A: Yeah, it hit me the other day because I had one person that was calling out a vendor for being overly salesy and I was like, you do
• 35:08
  Speaker B: realize that that's their job.
• 35:11
  Speaker A: All like, do you do realize that sales fix all problems in any business, period? Like, was it Mark Human that he basically said sales fix all problems? And I agree. More revenue, a lot more revenue makes these problems a lot smaller because a loss of revenue doesn't hurt as bad. But it wasn't that. It was like. My thought was like, well, you do. The reason why they seem that way is because they're actually being authentic. And I think it's the other person that you thought was not salesy, who I happen to know being a ridiculous behind the scenes, heavy sales organization. Just as much better at maybe being, I don't want to say fluff, but more kind of bleeding with this kind of like arrogant tone of like, we're the leader in the space type of thing. And you get that a lot. You get a lot of People that are. You mentioned Gardner earlier, upper right hand quadrant. Gardner Magic Quadrant, leader in the space and everything. But they're the leader in the space because they maybe during COVID had a tool that did very, very well. So now they've got crazy revenue coming in. But what you don't know is that the back office department or operations completely overloade and there's like a four month backlog and all these different things. So it's. I guess what you're saying is that transparency in reality would be nice.
• 36:35
  Speaker B: Really?
• 36:36
  Speaker A: Actually knowing word on the street, I'm always. I still am a big fan of word on the street because word on the street is real and it's in real time. It's not just a snapshot and time that was paid for to get yourself in a magazine. So nothing against Gartner, it has its place. But it's very, very interesting how much money some people pay for that.
• 36:54
  Speaker B: Yeah, gardeners, I call them the librarians. Right. But you still have.
• 36:58
  Speaker A: But no one uses the library. I asked these guys, I was like, why are you paying 120,000 per garden? And they're like, well, use a library because I can Google all that stuff. And the events are kind of.
• 37:09
  Speaker B: There's absolutely some merit to that. I see some merit to that. But I rather pay somebody to give me that research and give me those metrics faster so I can get to a decision faster.
• 37:24
  Speaker A: So the value is insanity checks is what I was told.
• 37:27
  Speaker B: Yeah, well, critical thinking and sanity checks. You have all these decisions and your experience as an IT executive comes into play. If it walks like a duck, talks like a duck. Yeah, it's a duck. Right. So all of those that you were mentioning before, the fear and security. Right. Because will this replace my role? Well, you just go through the critical thinking. If I had said this is in the top right part of Gartner quadrant, this, whatever this is. Right. And I just went off that metric and I'm just the AI bot or AI engine looking at that. And that's the end result. And I don't have the critical thinking skills to say, oh, during COVID oh, they came out with this, you know, all of those other attributes you just mentioned, that's still our critical thinking skills to make a competent decision. Maybe we don't. We'll go with the Gartner top guy and we go with the emerging guy that we find better metrics on. Right.
• 38:22
  Speaker A: Moral of the story is you can't really ever sit back and if you're critical thinking about your Role is like, am I just sitting stale? Because I just didn't want to work hard and I like sitting in this role for so long. You're done. I like bringing up Gartner because there's a lot of people in our private community with only CTOs and CIOs that do pay that to be a part of. Of Gartner for sanity checks. But we also have people that are the actual CISOs in Gartner helping do those sanity checks. And then we have other people in the group that were stump the Gartner sanity check guys.
• 38:51
  Speaker B: So I can see that.
• 38:53
  Speaker A: Awesome. Do you have any common sayings or quotes, dictionary terms, for example, herding cats, turning the Titanic?
• 39:02
  Speaker B: Well, my thing is on my signature block where I quote President Harry Truman. And the phrase is, it's incredible what you can accomplish when you don't care who gets the credit. And that's. That's more. That's a. That's a team centric approach. It's been very helpful to me in my career. So that's my quote.
• 39:21
  Speaker A: Yeah, it's authentic. It's when you really. And it also shows people's intentions. And being authentic, I think is very, very important for success in this world.
• 39:29
  Speaker B: Right.
• 39:29
  Speaker A: There was Zig Ziglar. I think he was the one that said anyone can climb to the top, but only character and integrity will keep you there.
• 39:38
  Speaker B: Yeah, he's absolutely right. Yeah.
• 39:41
  Speaker A: So is there something that you believe most IT leaders get wrong? In other words, is there like this universally kind of accepted best practice or thing that you see IT guys do that you think is stupid? And it could be. It. There could be a brilliant. Yeah, everyone's doing this. And that's really just dumb.
• 40:06
  Speaker B: I don't know. I just got through budgeting. So Bias is heavy on budgeting and trying to explain why we have to do certain things or why we should do certain things. It's the pretzeling of ourselves to explain why we have to do certain things. And that's. It's not blaming the IT leader. It's maybe we're just not doing as good of a job with the organization. Right.
• 40:29
  Speaker A: Okay. So why do we have to do certain things? We gotta have an example. Because maybe we can break this down because it's. A lot of times it has a big decision coming up. We've talked about this before. When you migrate. I can't remember who it was. I got to go back to the archives of the shows. And someone said on the show once, there's two things, Phil, that are going to happen after an ERP implementation. One of two things is going to happen after an ERP implementation. You are either going to have a job or you're not. Hilarious. But what is the point of that? So a lot of IT guys, they want to be heard. They want everyone to understand the technology. We want everyone to know that nothing gets done without it. And we need to be brought in at the very beginning of these conversations. We need to have all this and everything and. But when it comes time to make a very, very big decision where our job could be on the line, if we're a good leader, we always make sure that every department has been involved in that decision. We make sure everyone that has had, has voted and had their buy in. And ultimately we're saying, well, you guys chose it. I just did all of the research and providing all these things and you guys chose it. I like that. Right. It's like we advise, you decide. It's one of our sayings, we advise, you decide. However, that is also why we might not get as big of an ear as possible because we don't always put like the money where our mouth is or however that saying is in. In other words, how often do we actually say, you know what, I've involved all you guys. At the end of the day, this is the best decision I'm going to tell you and this is why. And it's going to drive these numbers. But about these numbers in this range and I'm willing to put my job online, I don't think we do that that often.
• 42:14
  Speaker B: Well, that's a big deal, right? Then you're looking at how do you represent ownership? And we all ever represent our ownership because like I said, good stewards of the company's money, looking out for the company's best interests. And just think of it as a jury pool. If the juror is affected by the outcome, then the bias, normal human nature is defensive at that point. That's. So if I know my job is at risk and I'm putting that as part of the success or failure criteria, then I'm taking a huge leap forward.
• 42:51
  Speaker A: There has to be the opposite. The opposite has to also be true.
• 42:55
  Speaker B: So.
• 42:57
  Speaker A: And if I do drive these numbers, then I get X percentage of growth. Yeah, exactly. It can be, oh, a managed by objective.
• 43:05
  Speaker B: Yeah, we know that's not how it works, but. No, but it is. A lot of guys, you get it. Your incentives, your LTIP and or long
• 43:14
  Speaker A: term incentives are willing to do that. So I guess the question is how many are willing to do that. And I don't think many. This is my.
• 43:21
  Speaker B: I'll tell you that right now. No.
• 43:23
  Speaker A: And that could be why we don't get the respect.
• 43:27
  Speaker B: But you should. If you're a confident leader and a humble leader that understands the problem, then yeah, you should be able to say, look, in my professional opinion, with 30 years of experience and this specific scenario, I am giving you my best approach on this and I will lead that effort to success. And this is what the metric is. Take it granted. If I don't hit that metric, then if I'm let go of or terminated or et cetera. I understand. So you, you shouldn't make those type of statements without having confidence, not the fluff of being able to deliver on them. And then you should have done the detail level analysis in your head on its viability for success.
• 44:17
  Speaker A: And this is just me having these hypothetical conversations. Obviously. Very like. To your point, each company in each industry with all of their individual different group of end users all need different solutions to make something happen.
• 44:35
  Speaker B: Right.
• 44:35
  Speaker A: All with different levels of leadership, all with different levels of good leaders, bad leaders, mid market middleman managers, all that type of stuff. It's actually quite amazing. Well, it has been an absolute pleasure having you on the show. Is there a big disconnect between IT and C level leadership and are we closing the gap on that?
• 44:54
  Speaker B: Because that's. I think we're closing the gap. C level used to probably see us as annoyance. You have to have it to. Some of it is fear then that stage of fear where everybody's being hacked and paying ransomware and all that from the security aspect. And now it's like okay, potential of AI and really advancing the business and getting it from point A to point F, G, whatever. Right. That transition has occurred. I mean you can see it in C suite salaries. There was a big slowdown and now it's going up as far as the IT manager senior manager executive type positions. So there's obviously education that has occurred from managements of companies to know used to be a support function to a. A fellow team player to a strategic advantage. Right. That growth path. And the challenge is companies that don't see IT as a strategic advantage. We're already team players. Right. Is not understanding the IT component how you win the game. So those companies is where I see the challenge is when they don't truly see the IT dimension as a strategic advantage for success.
• 46:12
  Speaker A: Well, I love that you mentioned that the iPhone and the BlackBerry because we literally say that the goal of this podcast was to do to IT leadership what the iPhone did to the BlackBerry.
• 46:23
  Speaker B: Oh, I did the soda. That's good.
• 46:25
  Speaker A: I love.
• 46:26
  Speaker B: Literally.
• 46:27
  Speaker A: And so for those companies that actually still where it's just still the department of it, what's your message to them?
• 46:34
  Speaker B: Oh, my message to their leadership. If they were listening to these IT related podcasts, think about where you see your company in the next not don't even look 20 years in the next five years. Right. And be wary of not looking strategically with an IT dimension to it. That's what I would say.
• 46:54
  Speaker A: Yeah, for sure. Roy, thank you so much for being on the podcast. You've been hurt.
• 47:02
  Speaker B: This has been pretty fun, Phil. I've enjoyed it. Excellent.