Latest / Exit Algorithms / Could Your Business Survive a 2-Month Vacation? | Kevin Ziegler (#112)

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Could Your Business Survive a 2-Month Vacation? | Kevin Ziegler (#112) · Exit Algorithms

• Pete Vera, Exit Algorithms: Welcome to Exit Algorithms, the podcast where we decode what it really takes to unlock growth, streamline operations, and prepare your business for a high-value exit. I'm your host, Pete Vera, and today I'm joined by Kevin Ziegler, a Milwaukee-based fractional CTO and four-time founder. Kevin co-founded and scaled a logistics SaaS company to $6 million in ARR in just three years as a CTO. Built and sold a software development firm and now embeds with growing companies as their senior technology partner focused on AI strategy and roadmaps. Kevin, great to have you here. Welcome to the podcast. Kevin Ziegler: Thank you so much, Pete. I appreciate being on and good to see you again. Pete Vera, Exit Algorithms: Yes, sir. Likewise. Yeah. Do you mind starting off, Kevin? Can you share a bit about your background and and business journey and yeah, what what led you to your work today? Kevin Ziegler: Sure thing. Yeah. So I I I went to school, actually intended to become an orthodontist, to be honest. And after a couple of y years in school of biology and chemistry, I discovered I hate it. And in the mid 90s, when I was going to college, I recognized that it's a great time to go into software development. I was programming, you know, computers as a little kid. And I'm really glad that I made that change at that point. out of college, I worked for a large company for a couple of years before starting my own software development agency where we kind of specialized in developing solutions for tr transportation and logistics companies based on one early client. We maybe we'll touch on that in a minute. did that for about 13 years before I sold that company. Moved on shortly after to found a couple of product-based startups and realized I really love that startup space. That's where I went on to found another three different companies, maybe even a couple that really never got off the ground that we just won't count in that number four number. And kind of in between some of those startup opportunities, I really kind of found myself in A fractional CTO role, really just to kind of fill a void looking for my next startup opportunity. but after one fell apart a couple of years ago, I thought I really love being independent as a CTO. I like being helpful, I like the variety of work that comes into play. I've touched a little bit of everything in IT, and that leads me to where I am today, helping out a number of different companies as their fractional technology leadership level. Pete Vera, Exit Algorithms: Yeah, awesome. I love your career career journey. You know, building companies and and then now helping others kind of do the same at as you you know, continue in your in your entrepreneurial path. how about we talk a bit about ex your first exit? You know, the exit algorithms is a the main focus here. So I'd love to if you could share a little bit of more detail about yeah, we know why did you exit and that whole process and maybe some lessons learned. From that experience. Kevin Ziegler: Yeah, sure thing. So the company I started, the Software Development Agency to begin with, it started in roughly 1999. and again, we we kind of focused largely on logistics companies, building things like TMS systems, EDI translators, web portals for carriers, customers, et cetera. things were going great with the for the company for you know. Throughout the period of we're we're every year we'd see a little little by growth. We weren't exactly seeing hockey stick growth at this company. My role at that company was really leading technology. I was a 50-50 partner and my other partner was more on the business side of things. we had a few employees, we had a few many different subcontractors that we would kind of depend upon. And after about nine years, the partner that I founded the business with got diagnosed with bone cancer. Really unfortunate. he had been going through many different doctors' appointments for like two years trying to find a diagnosis. And when they did discover it, it was unfortunately a little bit too late for him. So he had a short time to live for that. He, you know, it made kind of a quick exit of his own on the business. And I found a new business partner, somebody that I knew well, but hadn't really worked with them in business, honestly. And turns out it wasn't a great match for us for a variety of reasons. And at that point, I thought, you know, I've I've done this long enough. I've time to try something new. that wasn't my intention, you know, especially before my partner was diagnosed with bone cancer. I thought this is a company that maybe even someday I'd hand down to my kids, if you will. But again, I thought it was the right time for me to again try something new. So in that exit, it was honestly kind of a stressful period for me as well. And I I think one of the things that I didn't really anticipate was, you know, kind of the key person risk that went into me leaving that company. it In a similar note, you know, as we were, you know, looking to look into part part ways and sell my share of the company, I probably acted on it a little bit too quickly, you know, realizing I probably didn't get as much as I probably could have, you know, just knowing that the stress of the situation was something I just wanted to be done with and move on. Looking back, I I don't necessarily have huge regrets about that, but I, you know, probably could have spent some more time you know, waiting, you know, kind of holding my ground on, you know, seeking a higher exit cost for that company. but again, no regrets, good life lesson learned. But I I I I think as I've seen now from a lot of other smaller businesses that I've either worked with as clients or Or lots of i advising and mentoring of startups that I do, especially in the Milwaukee area, that key person risk is really real. You know, I think that it for any particular founder that's looking for an exit, you know, for them to put their mindset in, like, let's let's say I were to go on a two-month vacation, what would happen to this company? would it would it continue on? Would other people know what to do? Would other people know how to sell the business? so I think that it probably one of the key lessons learned for especially for myself in that scenario. Pete Vera, Exit Algorithms: Yeah. And how do you, you know, w recommend business owners start to mitigate that that key person risk, eliminat eliminating themselves as a the bottleneck? Kevin Ziegler: Sure. I I think that, you know, as a company grows, inevitably as some as an individual or even a couple of individuals starting a company, you know, it there's it going to be some early key person risk that is unavoidable. That's kind of key, no pun intended, to getting the company started. but as a company starts to scale, you know, I think that you've got to be in that mindset of I need things to be documented. I need processes that people are other people are able to understand and take over. If I were to leave this company tomorrow, again, or go on vacation for two months and be unreachable, I need to have the right structure in place so that other people could, you know, take on some of the responsibilities that that key person is handling, whether it's in sales or technology or accounting, finance, whatever it might be. you know, in a larger company, these things are just kind of built into the framework that they do, right? Making sure that at any point in time anybody could be disposable, whether their choice or not. but yeah, again, documentation I think is really helpful. So d defining standard operating procedures, ensuring that you're surrounding yourself with good people, you know, to be able to take those things on. I I I I I think that oftentimes there's there can be a little bit of an ego as a founder and you know, understanding, well, nobody else can do this as good as I am. I can, but that's not the right approach that I would take, right? I think i is as I've even learned myself, you want to hire people that are better than you, smarter than you, so that they can take on some of these responsibilities that you currently undergo. Pete Vera, Exit Algorithms: Yeah. that's smart. Great great advice. And you mentioned timing was a an issue as well. You you wish you would have probably waited a little bit longer or planned more in advance. How far in advance do you think is appropriate? And maybe what are some of the the things you would have done in hindsight to have a more successful exit? Kevin Ziegler: Sure. Yeah. Yeah. I you know, it I the timing I'm sure all depends, right? I inevitably I I think that you probably want to look at this maybe even like a five year horizon. sometimes that may be longer than what somebody might be able to do. Again, in the case of, you know, illness, death, or economic conditions, inevitably you might be that that time frame might be a little bit more compressed. But Again, I think surrounding yourself with the ro right advisors to be able to help you out with that situation that are on your side. I have a very good friend that did help me out to a certain degree, you know, with w a a strong background in finance. And you know, I I think that he always what what I still to this day probably don't do a good job is try to look at how what's gonna be beneficial for me. as opposed to I look at probably what's going to be beneficial for everybody. And, you know, he would always bring it back to me. No, that's not important to you. That's not important to you. And really think about what is important to you. Is it important, you know, is the sale price? Do you want to be part of this company after it's sold, you know, to assist with that transition? and g start writing those things down and really even think about contingency planning or really y y the the next stages of your company well before it's time to actually make it happen. Pete Vera, Exit Algorithms: That's really smart too. Yeah. And getting an advisor, usually they're they're worth their weight in in gold if you do have to pay them right. Kevin Ziegler: One hundred percent. Pete Vera, Exit Algorithms: yeah, and and when you step into a company as a as a CTO, what are maybe some of the the common low-hanging fruit items you you look at and fix first? Kevin Ziegler: Yeah, one of those things is key person risk. you know, that may not sound like a technology issue, but you know, again, through my own lessons learned, I I I think it can come down to a technology issue. Here's the only person who knows how to write this code or use this piece of software. So, you know, d some of the things are really basic, you know. Do you have the right things documented for your business? do you are you protected from a risk perspective? Do you have the right policies in place for your company? Do you have the right security measures in place? You know, security is is one of the biggest risks that a lot of companies see. Are you protecting yourself against, you know, phishing attacks or, you know, other things of that nature? beyond those basics, then you know what I would look beyond that would be you know interviews with a lot of the stakeholders of the companies. I typically go through a three-stage process as a fractional CTO. I'll go through an assessment, I'll come up with a roadmap, and then provide advisory services for my clients. through that assessment process, it's it's a lot of different interviews. again, interviewing key stakeholders of the company. understanding what they do, how much time they're spending on things that they're doing, where the company is going, what direction they're going in, where do they want to be two, five, ten years from now. and then really kind of combining all of that information to put that into a roadmap. that's going to be a collaborative conversation with the customers that I'm look working with to ensure that I've captured everything. Sometimes I might miss some things that have haven't come up or yeah, that reminds me of something I forgot to tell you that's really important. So this process can take a couple of different couple of months, you know, through the assessment and roadmap process, but inevitably it really drives roadmap options that are, you know, let's focus on what's good, what we can do in the near term. What can you do right now that doesn't even have to involve me to, you know, increase your operational efficiencies, increase your revenue. increase your margins in your business. that might involve things like purchasing or building tools to take out some of the manual effort that's being run in this business today. It might be building, you know, exploring a new a segment of the business that you are not in today. that might extend beyond even technology in terms of your sales approach and marketing approach. And you know, longer term, we would just be looking at like maybe things that aren't even ready because they're gonna be dependent upon some of those earlier stage roadmap items, or you're just not ready to do them quite yet, or it's gonna take more capital to be able to do some of those longer term roadmap options. So in a nutshell, that's kind of what my process looks like virtually for every client that I'm working with. Pete Vera, Exit Algorithms: Yeah. that's great. Yeah. And let's talk a little more about the tools because right now I as you know, there's so many tools available right now. And, you know, one solution can have 10 10 different tools that business owners are trying to to choose from. how do you recommend a a business owner go about selecting the the right tool for their need? Kevin Ziegler: Sure, yeah, yeah. I mean, especially in transportation and logistics, I think you know there's there's a lot of opportunities and challenges just because of the number of tools that are in this space. starting with TMS systems alone. there are dozens and dozens, if not hundreds of TMS systems that exist today. And there's not even a single huge market leader. There definitely are companies like McCloud that probably have a greater market share than other others others in this space. but excuse me, what I've what I've seen in you know both in logistics and in other industries are that people are making choices maybe based on recommendations, right? They're going, I know somebody I know another freight brokerage that's using this system. They speak highly of it, they talk to a salesperson, and they're like, Okay, that's great. You know, this is gonna be the solution for me. obviously, people go into more due diligence than that. But in looking at any particular tools in this space, whether it's a TMS system or you know, back office operations or tracking or tracing or whatever it might be, what I would really recommend is coming up with a strong list of requirements. what's important to your business? Where is your business going? and you know, iterate upon this, right? And do this before you even reach out to any vendors. Then do a little bit of discovery in that space. And some of that discovery might lead you to some other ideas that adds to either other requirements or maybe some nice to haves. And then come up with a scorecard. The scorecard would take those list of requirements. And among, let's say, you know, you narrow it down to three to five vendors in that final case. Go through demos with those vendors, go through due diligence with each one of those requirements. And rate them on let's say a one to five scale on how well you think that system is matching your needs. and that's going to come up with a much better solution for you than I like the sales guy or somebody referred to this as a great system to be able to use. so in in picking a vendor, that's the approach that I repeat again and again. And oftentimes my customers that I'm working with today are like, I've never really thought about putting it together this way. and from a vendor perspective, I I kind of call it like a mini RFP. I don't want to scare them off by thinking this is a enterprise-wide solution for picking a piece of software. But I also want them to understand that you know these requirements are important. We want you to respond in kind of a again, a mini RFP format, go through perhaps multiple different demos and other other solutions in this space. One other thing to note, I I think in looking at vendors, is you know, tying this back to security for a moment, is making sure that the vendors you're choosing are can be insecure in their own way, right? You're gonna put likely data in their systems. You wanna make sure that this the the the vendors that you're choosing are rock solid in their security because a breach of their data could be detrimental for your business as well. Pete Vera, Exit Algorithms: Yeah. really, really good to think about. Important. I love I love your your process too. You know, talked about it earlier, how you approach helping out a business as a CTO and then also choosing tools. Every single thing has a has a process. I like how your your brain works. I I think that's really really useful for for people listeners, especially. Kevin Ziegler: Yeah. And maybe maybe even a another thing to add there, you know, we're in the AI age we're in right now, it's getting easier and easier to build tools. you know, I I think that's an option for a lot of businesses, but I I I think even in looking at building your own tools, you want to weigh those the same way that you're kind of weighing a vendor, right? What are the risks that we're gonna have in making this? Are we gonna be able to support this? How much time is it going to take? you know, the the the bells and whistles of a vendor system, you know, might be on your low-hanging fruit for what you might be developing or trying to develop in in even an AI-driven tool that you might be looking at. I I definitely think there's opportunities there, but I I often urge more caution of building your own tools, especially if you're not used to being a software development shop, because building and maintaining that system becomes another challenge of the business that. Oftentimes is better handled, you know, from an outside company. Pete Vera, Exit Algorithms: Yeah. Yeah. Really good to think about too. yeah, let's talk a little bit more about AI and implementation. I know you you co-authored a implementation guide recently about AI. I I think there's a a lot of listeners, business owners are are struggling, especially in the logistics niche, to to implement it appropriately and effectively. What what are maybe some of the the steps they should go to or or ways to think about AI implementation? Kevin Ziegler: Sure. Right off the bat, you know, I imagine just about all of the people in this industry are using AI to some degree. at that basic level, I would just call that citizen AI, you know, that I'm inner, you know, interacting with Claude, ChatGPT, or any other platforms in this space. they're great tools, right? They help you write emails, they can help you, you know, synthesize ideas. I'm sure just about everybody has kind of found some benefits of using some of those tools. taking that to the next level can be kind of challenging. start one of the one of the first things that I suggest any company does is start is create some governance around the use of those tools. whether you're using Claude or ChatGPT, you know, ensuring that you're picking the right system, ensuring that you're licensing this appropriately so that you're not Sending data into large language models that might be used for retraining, exposing any of your company data or your clients' data in these systems. That's really important to get right off the bat and make sure that everybody's on the same page with that. Beyond that, you know, I think what a lot of companies are interested in doing is taking it to the next level, right? What what type of operational efficiencies can I gain by using AI, largely driven by AI agents. there's many different ways to build and run those agents. you know, some of the concerns once again would be security, making sure that you're running secure systems that could be using, you know, known systems like OpenAIs or Anthropics today, or running your own local models to be able to drive some of those agents to make sure that data is not leaving the effectively four walls of your company. And excuse me. The in building those agents, what what we want to do is really focus on some of those low-hanging fruit to begin with. Let's start with some easy use cases. So some examples to this might be things like responding to emails, drafting emails, ensuring that you at least at the beginning, you've got the human in the loop. AI, as great as it is, still makes some mistakes, right? And you don't want to have to make you you don't want to have AI doing things that you wouldn't approve as a human. Looking forward, you know, one of the one of the problems that I've seen companies run into running AI agents is, you know, runaway costs that happen in this space. and we're seeing this in news today, you know, that a lot of enterprise companies are now cutting back on their AI costs, recognizing that their cost of tokens that they're spending time on has absolutely skyrocketed, and they're not necessarily seeing their ROI there. So coming up with some ROI calculations, sometimes it can be a little bit tricky to figure out, you know, how much is this actually going to cost until I actually start doing it in a production environment. But there's some ways to simulate that and you know kind of anticipate what those costs are going to be. Also really important to ensure that you've got the right people to be able to maintain that agent. In the same as we talked about tools earlier, developing your AI tools. I if you don't have the right people to support those and your business is really going to depend upon these tools, you you need the appropriate skills and people to be able to, you know, manage and maintain those going forward. There are many different tools out there to kind of maintain manage or orchestrate agents in the in the enterprise environment or even a small business environment. a lot of those are really good tools to start taking a look at. But y Again, kind of starting with, you know, the the the governance policies in place, making sure you've got your cost under control, making sure you can maintain and support these agents going forward, and repeatedly revisit what they're doing and making sure that they're still doing the job that you want to do. Pete Vera, Exit Algorithms: smart. Yeah. you know, those credits too. Yeah, I can that that rings home for me personally of start dabbling and and it's just crazy how quickly the credits get used and you're suddenly, yeah, spending hundreds of dollars and not always not always for the best, you know, purposes, right? Kevin Ziegler: One a hundred percent. Yeah. I mean and hundreds of dollars is probably the best case scenario, right? Once you once you get that bill of tens of thousands or hundreds of thousands at the end of the month, my God, now what am I gonna do? Yeah. Pete Vera, Exit Algorithms: Exactly. Yeah, how are you personally leveraging AI the most these these days? Kevin Ziegler: Yeah, I use I use some agents for a lot of different things that I'm doing. You know, monitoring my mailbox. I don't have agents respond to emails yet. I'm thinking about doing this maybe for some lower hanging fruit. I I use AI agents to record most of my meetings so that I'm capturing my to-do items so that I can focus on those meetings. I don't necessarily have to be a note taker. To be fair, that's not exactly, you know. Cutting edge technology anymore, but it's really important to me again so that I can be present and that I do capture what I need to do. And I can take the transcripts of those meetings then and really synthesize what I need to do for my customers. What and some of that builds automatically into my to-do lists. Taking from a a meeting itself, I have Claude connected to my my transcripts and say, Here's the things that you need to do, here's when it's gonna be due by, here's the client that it's going to be due for. another thing that I've been really experimenting with myself is also even just kind of working on some of my own side projects of software development as I am helping out my own customers and really kind of helping refine the approaches to truly just vibe coding. as I started off as a software developer, I haven't been terribly involved in coding day to day, but I've really found it honestly a lot of fun to do, you know, vibe coding in a very structured Manner now where I am using tools to write my user stories, and I'm using clawed code to reflect and refine find those user stories, develop the code, write automatic tests, automatically deploy that code in the their appropriate environments, monitor and maintain anything that goes wrong after I've deployed those options. And I'm kind of just doing this in my own sandbox environment. Honestly, it is a lot of fun, but again, kind of refining my approach so that as I'm helping customers, you know, whether it's deploying agents or writing software, I've kind of been through some of this on my own, you know, terms for some of these might actually turn into some startups themselves. I'm not entirely focused on it. I see that maybe as a bit of a side benefit. at the same time, I'm also partners with a couple of different AI orchestration tools. I I've been playing around with those really just to, you know, get get more familiar with them so that it's easier to implement, understanding how integrations happen, as well as, you know, how how I can put these tools in the hands of other people. again, kind of eliminating that key person risk so that they can take these tools and and run with them. Pete Vera, Exit Algorithms: Yeah. great. I I love the way you you think about things and an approach, Kevin. It's great. do you see AI disrupting some of the the industries that you're in? you know, there's a lot of talk of eliminating jobs, et cetera. I I'm curious, how is AI impacting the at least the industries that you're in? I where do you see it in affecting them the most? Kevin Ziegler: Sure. Yeah, I I do to a certain degree. And I've kind of, you know, gone back and forth over this over the last couple of years of where I think, you know, that that's gonna happen most. I I think one of the most important things that AI is able to help us with is that most businesses have ideas and roadmaps, whether they're written down or not. longer than they can imagine, right? There's always things that people want to get to that never do. to be perfectly honest, I have some of those things in my own practice. I think that's where the biggest benefit of AI is able to help us out with today, whether that's in software development, whether that's in custom customer service, in finance, accounting, you know, this could legal. It I I think it happens across all different functions of a business and across all different industries. I I I definitely think that there is going to be some disruption around some things that are even happening today. You know, customer service type functionality, software development, I think, is is really, you know, being affected by this because software developers are now becoming much more efficient in what they're doing. But at the same time, I think it's creating a lot of other opportunity for additional jobs to be able to support that. So getting back to just roadmaps as an example, I what what I what I what I think the the the biggest bottleneck is that's happening for a lot of companies that are utilizing AI for, let's say, software development, is that they they just don't have enough planned work yet to work on. So the opportunity there is for Business analysts, product owners, people that can really be driving that work, prioritizing that work, making sure that we've got the right whether user stories or product roadmap items already defined. And once those definitions have happened, and then getting into a little bit more details about the requirements of those features that need to be developed, the the longer that list is, the better off. companies can be from a like again software development perspective to be able to pursue those. otherwise at the end of the week if I've completed everything that I need to do, Monday comes around, now what now what are we going to be working on, right? So people to help kind of drive the work that needs to be done. So yeah, I I think there's just as much opportunity as there is, you know, disruption that might incur be in this space. there there's an old saying, and now it seems like an old saying is that AI isn't gonna take your job. It's the people that know how to use AI are gonna take your job. while I still think that's true. Well what I think is most important would be not only that, but how people that can recognize where AI can really drive the bottom line of a company. Pete Vera, Exit Algorithms: Yeah, definitely. Yeah, that that's probably the biggest focus, I think, right? The Kevin Ziegler: Sure. Pete Vera, Exit Algorithms: practical implementation there. well, Kevin, this has been a fantastic conversation, so many good insights. I got one final, final question for you. And you touched on this quite a bit earlier. But if you had to pick and choose one practical tip to leave listeners with for a business owner preparing for a successful exit, what would that be? Kevin Ziegler: Just one, okay. planning before it becomes time to do that. making sure that you're setting your objectives. Again, if you're looking at a five-year timeline, could be a 20-year timeline, set your goals in place today. What is it gonna take to be able to get there? Whether it's looking at your margins, whether it's a key person risk, whether it's a a certain revenue target you're looking to hit. Get all those plans written today. again, whether that's now or even if it's gonna be your grandchildren selling your business, having that plan in place now for future you or your future generations is going to be really critical so that you're not finding yourself in crunch time to make a make a sale sooner than you want to. Pete Vera, Exit Algorithms: Well said. Great, great way to end it, Kevin. where's the best place listeners can can find you, learn more about you and your business? Kevin Ziegler: Sure, you can find me on LinkedIn, Kevin Ziegler, based in Milwaukee, Wisconsin. Kevin Ziggler Z-I-E-G-L-E-R dot com is my website. Feel free to connect with me there. I'm also active on Reddit and occasionally some other platforms, but LinkedIn is probably the best place to go. Pete Vera, Exit Algorithms: Awesome. I'll leave it on the show notes. Thanks for coming on today, Kevin. Love this conversation. Kevin Ziegler: Thank you so much, Pete. Appreciate it being here.