George Jagodzinski (00:00):

Today's episode is part of the miniseries that we will be peppering in amongst our other interviews. For this series, we go inside the walls of Intevity and hear from experts who are doing the hard work to help our clients. We discuss the patterns and the pitfalls, and we glean some insight from their many years of experience. I love showcasing our team. They're solution-obsessed, and in my very biased opinion, I think they're some of the best out there.

(00:21):

Today, we discuss why your data sucks and what you can do about it. This is a judgment-free zone. It's just a phrase we've heard over and over again. The good news is that there's always a path to improvement, and "good" data is in the eye of the beholder. I'm joined by Michael Wiseman, our Data and Business Intelligence Architect who eats data for breakfast, as well as Eric Webster, AKA Web, our Director of Digital Solutions. Let's hear from the team.

(00:44):

Welcome to Evolving Industry, a no-BS podcast about business leaders who are successfully weaving technology into their company's DNA to forge a better path forward. If you're looking to actually move the ball forward rather than spinning around in a tornado of buzzwords, you're in the right place. I'm your host, George Jagodzinki.

(01:21):

Mike, Eric, thanks for joining me.

Eric Webster (01:23):

Thanks for having us.

Mike Wiseman (01:24):

Yeah, thanks for having us.

George Jagodzinki (01:26):

Today, I think I wanted to call it your data sucks, and you should feel awful, but I think you guys had more of a hopeful slant where it was like, your data sucks, and that's okay. Let's maybe start with what does that mean to everyone's data sucks, and why is that?

Mike Wiseman (01:40):

I think the good news is over the last several years, I think a lot of organizations have come to the realization and understanding that they have to be in the data game, that data is an asset for their organization, and it's involved in every facet of consumer's life, of a company's life, so they have to be in that game.

(02:00):

The challenge that a lot of organizations are running into is there's a spectrum, right? There's a spectrum of you are not doing anything with your data to you're Netflix, you're Google, you're Amazon and you know everything about every person that's ever even thought about using your service. But most organizations are falling somewhere within that spectrum.

(02:20):

The challenge that we see organizations are running into is, one, being honest with where they fall on that spectrum. Organizations who think they're at the top of the tier or using their data to a strong degree, but then you go and peel back the hood a little bit and ask some questions about what do you mean when you call your product — or you have your sales volumes or your membership records and things like that, and they can't answer that. How are you driving that strategy for an organization if you have some underlying fundamental challenges with how that data is being utilized?

(02:58):

And then, on the flip side, organizations that say, "This is cool. We know we need to be here. We hear about AI and machine learning and all of this cool stuff, but we have no idea where to start," right? This is a massive ball that we don't even know where to start pushing it up the hill, so we're just not going to do it at this stage.

Eric Webster (03:16):

Yeah, I think data is siloed everywhere. Everywhere you go, everybody wants to own your data, and they want to make it easy for you not to own it. I think it's even more important for you to own it because of that.

George Jagodzinki (03:29):

Yeah, yeah. I mean, it sounds like it's not that there's a lack of data or a desire to leverage data, it's more like it's not painting you the picture that you want it to paint for you, and you're maybe getting bogged down by it, right?

Mike Wiseman (03:44):

Yeah, it's tough because there's so many different facets of it, right? The platforms, the technology, the terminology are changing every day. Sometimes it's hard to get into that.

(03:57):

But I think, with the key things and some things that get overlooked are you don't necessarily need all that to get started, right? You don't necessarily need to have these huge expensive platforms to get started with understanding your data and finding where those skeletons in the closet are that you need to work and address, and, ultimately, establish that focus and vision for an organization.

George Jagodzinki (04:21):

Why do you think it's so broadly not working for organizations? I've talked to so many, I've been at roundtables, and you have, from a brand perspective, these are top top brands. They're very successful in what they do. But when they do a self-assessment, they're saying, "Yeah, we're maybe a C, a B-minus, or a C, as far as how we're leveraging data."

(04:41):

What are the real reasons that this is happening out there?

Mike Wiseman (04:45):

I think there's a number of reasons for that. I think the biggest culprit or challenge is that organizations tend to look at data as a afterthought, right? They tend to see data as a means to get reports, as a tool to achieve an endgame. But we all know we've been in those meetings, those organizations, have received those reports, where you're like, "I don't know what this means. How did the organization come up with this answer? How does our accounting team know report on sales volume, and our sales team reports and sales volume, and it doesn't match? How is that not in alignment?”

(05:27):

Part of that is not having the focus and the strategic focus at a top line at an organizational level and working to establish that as a portion of an organization's culture, right? When new products and services, mergers, acquisition, systems are onboarded, having your data strategy be a cornerstone of what that looks like. How are you going to be integrating these systems? When you onboard a new CRM system, how does the data in there with what you currently have? Does it overlap? Does it not overlap? Where's that information going to be stored? What are the definitions that are going to be used? Does that change how you manage things?

(06:06):

A lot of times, that's an afterthought, and then, all of a sudden, we get familiar with that term tech debt, right? You have all of these systems that from a tech debt, but then there's this data debt. You've got data across all these disparate systems, and now you can't make heads or tails of it. Or you're trying to make heads or tails of it, and you're getting different information, and you're struggling with moving forward.

(06:28):

I think the key piece is what is incorporating data as a top-of-the-mind component when you're engaging in whatever the service product industry that you're in as you're moving forward with your strategic initiatives.

Eric Webster (06:45):

Yeah, I think a lot of people think about integrations with other platforms and services first. They don't think about data first. It's a little bit more of an afterthought.

(06:54):

We talk about it all the time that data could be an anchor, right? Like, “Oh, I got so many years' worth of data stored over this platform. We can't leave. We can't go anywhere,” right? That's the primary system that houses all that information. Doing that afterwards when you're trying to move away from the platform, that it just becomes very expensive and hard to do.

George Jagodzinki (07:15):

Yeah, and never mind data becoming a liability as various privacy regulations are put in place around the world, right? It's a double dagger that if you both have it, and it's a liability, and you're not getting what you want out of it. That's tough.

(07:28):

To move forward, as with most problems, there's always some fundamental things that are wrong. People might think that they've got the fundamentals in place, but they don't. Maybe there's just some fundamentals that they're not even thinking about.

(07:40):

Mike, when we think about what are the fundamentals to be able to just be better at data?

Mike Wiseman (07:47):

I think, to start, is sometimes it's best to start small, right? You don't have to go solve all of your data problems with one clip, with one platform, go out hiring chief data officers, all of that sort of stuff. Because that tends to lead to more challenges, and then you're saddled with all of these processes and you're still not sure where to go.

(08:10):

Start small. Start small with something as simple as establishing data definitions within your organization, right? Sitting down with, let alone manage your employees or your individual contributors, things like that. Sit down with your executive team and look at your goal sheet, your KPIs, whatever it is that you're managing your organization to, and ask them. Can you guys give us a definition of what all of these things mean?

(08:40):

I had an opportunity working with a regional credit union where the organization understood it had a vast wealth of data, wanted to get into understanding and utilizing that data. I went into a senior management team, and I gave them all a sticky note. Going around CTO, CEO, CMO, all the C-suite and said, "Can you guys, on a piece of paper, write down how many members you have as an organization?" Some of them wrote a number down, other ones looked at me and said, "Well, what do you mean by member? Do you mean accounts? Do you mean people? Do you mean number of checking accounts that we have?" Things like that.

(09:24):

That was the exact point that we were trying to make is this was a core goal of the organization to member acquisition, growing market share, driving marketing strategy, driving acquisition strategy, driving where you're going to put new branches and ATMs and all of that. That was a core strategy. But at an executive level, they didn't have a definition of what that meant, how many were in the organization at that point in time. That was where we started, is we sat there.

(09:56):

It took a while. It took several months to come up with what that meant because there's nuances in there, right? There's what about people who have multiple accounts, who are joint? There was a whole bunch of nuances that went into that, and it's not always as easy as you think. That's part of the challenge, right? That's part of the problem why people get in and organizations get into these holes because it's not always easy. But sat there and went through the corporate goal sheet and worked to make sure that we had established definitions for each of those KPIs so that now everybody's marching towards that same goal.

(10:32):

When we say, "What's the member acquisition strategy? How are we going to increase it? What is the percentage increase that we need to do in order to achieve the goals," we know how that's being tracked. We know where that's being tracked. We know who's responsible for that. If there's an issue or a challenge, who's the person that we're going to talk through with that? What's the department that's now reporting on that as opposed to having it reported by 14 different areas? Where is that information stored? How are we going to monitor that going forward? It starts to get to that dictionary state, and you can track that lineage of where that lives and then use that to build upon. That's just starting small.

(11:11):

There wasn't any cost to that exercise other than time, but achieving that, it opens up so many doors for now we know where to spend our money on a marketing strategy and how to focus on those items.

George Jagodzinki (11:26):

Evolving Industry is brought to you by Intevity. We bring order to chaos wherever people, process, and technology converge. Our culture drives our solutions, and we are solution-obsessed. We see every challenge as an opportunity, every partner as a collaborator, and every project as a chance to share our values and commitment to excellence.

(11:42):

Give us a shout. We'd love to hear your challenges and turn them into opportunities. Find out more at intevity.com. Now, back to the show.

(11:54):

Oh, man, what a facepalm moment that's got to be as an executive. It's like, "Hey, do you guys know what a member is or how many?" "No, but we want more of them." Great.

(12:04):

But the funny thing there is I bet they all thought they were aligned, and it's not until you really dig into it. I talk about common language all the time and that you need to spend a lot of time talking about words. You just said it took two, three months, maybe, to get everyone really aligned around there. What I think the gold in there is not just from a data perspective, but I bet that accelerated and aligned so many more conversations across the whole organization.

Mike Wiseman (12:32):

You start to realize how ingrained some of your traditional processes have been. Every door you open, there's those gotchas that you have to figure out.

(12:42):

“Oh, we have this system sitting on the side that only one department uses, but they use it because of legacy processes that have never been updated.” Well, why? Open that door. Understand what is the reason for that. Can you deprecate those processes? Can you roll them in? You just onboarded this new CRM system. Can you roll out those items into that as opposed to continuing to accumulate all of that debt? And yet not even necessarily data strategy, it starts to inform your entire organizational strategy but starts to become that foundation with how to handle.

Eric Webster (13:17):

Yeah.

(13:18):

Another couple of things: when I think about getting started on this journey, you don't need a large team, but you should have some focused individuals that are focused on this problem, and you need to make sure you're enabling to rise to the challenge and drive that clarity. The data you may have been using for years might have been wrong, and that's okay. It's okay for that data to be wrong. Focus on just getting to the truth, right?

(13:40):

I think that's super important. I think a lot of people worry like, "Oh my god, this has been wrong forever. We've had our company goals based upon a number that's a lie." It gets pretty hairy. You just got to make sure that that team knows it's okay for you to find fault, that it's okay for you to drive and challenge what the status quo was.

George Jagodzinki (13:59):

I love a good blame-free culture.

(14:01):

This is a silly detail, but I'm also a sucker for a war room, man. If you can get a bunch of stuff up on the wall that people can point to and just really connect the dots, I find it makes a big difference.

Mike Wiseman (14:10):

A lot of sticky notes.

George Jagodzinki (14:13):

Definitely a lot of sticky notes.

(14:15):

We talked a little bit about getting started, but then, really, how do you craft a vision, and how do you mature the organization as a whole? Because I think some people, they think thoughts like, "Oh, big giant data bureaucracy, organizations," but how do you really move it forward in a nimble yet clean way?

Mike Wiseman (14:32):

Yeah, and different organizations are going to be at different stages and have different capabilities and capacities. I think Web started hit on that point is regardless what you do, ownership within the organization, right? Establishing somebody who's going to champion your data vision and culture. It doesn't necessarily need to, like you said, be as chief data officer or something like that out of the gate, but it's got to be somebody who has the influence and has the ability to drive decision-making within the organization that has a seat at the table.

(15:04):

The other piece is a lot of times data gets tacked on to somebody's job, right? It's Susie in the account maintenance team who knows how to find the information, has her magic spreadsheet, so everything always goes to her to do. And then, it becomes gets backlogged and it just never rises back up to the top of the list there.

George Jagodzinki (15:29):

Can I pause you on that one? Because that one, I think, is worthy of digging into because it's not even like someone was deliberately given that as a side job. I don't know about you guys, I'd like to hear some stories, but I find so many times this mistakenly happens because someone is tasked with something else in the organization, right? They're tasked with looking at churn, or someone's supposed to be coming up with a pricing strategy, and they're looking historically. And so, they're coming at it sideways. And all of a sudden, it's taken a long time. They're spinning it around, spin around and you realize this really needs us re-looking at all of our data, not just this one part.

(16:04):

I don't know. Have you guys seen that? Any examples?

Mike Wiseman (16:07):

Yeah, absolutely. Having, like you said, that person comes at it from that side angle, then somebody in the organization likes what they reported on, right? They like the information that they got. It provided them that data. And now, guess what? They own it, and they have to produce it every single week, every single month, whatever that cadence is. Now, they're the owner, right? They own that process.

(16:33):

That's not necessarily a bad thing, but it's understanding that are you, as an organization, are you making the conscious decision to say you own this data. You're the data owner and are now going to give them the space, the time, the capacity to continue to drive that forward. If you have a new program come in, you're spinning up a new website or e-comm product or whatever, that person now, do they have a stake at the table? Can they make sure that we've established these definitions? Is this going forward?

(17:04):

I think in addition to, yeah, you're coming at it sideways is now there's ownership behind that and keeping that going forward. A lot of times, that's not the case, is it's just the means to get a report that somebody wanted at some point in time.

Eric Webster (17:20):

A few times, we have used a way of remembering the future, right? Where did you get to and what data empowered you to get there?

(17:28):

I think the big thing is a lot of people become data hoarders. I just want all the data. Just give me all the data, as much data as possible. It really becomes very hard to see the signal through the noise. Remember the future and what was the most important data that you need to power that future because data really is your second most business asset right after humans.

(17:50):

It's one of those things that a lot of people say, "Hey, our data is important," but they don't truly understand their data. I think understanding what the most important signal is I think is the way forward to have a true, strong vision.

George Jagodzinki (18:02):

There's a lot of dashboards. I've gotten Frankenstein beyond belief out there.

(18:06):

One of my favorite things I've heard when I'm even thinking about my own data that I want to look here at our company is if you were stranded on a desert island for a few months and you came back and you only had a few things to look at, what are that handful of things that you'd want to look at? I think that's a really cool mental exercise to go through.

Mike Wiseman (18:25):

Right. It's amazing how much you realize your KPI reports, all that — bloated, right? But what are the true key metrics that are needed for an organization to drive it forward? There's other things that need to support that in different areas, and different teams are going to have different metrics that they want to manage and manage too, and that will ultimately roll up. But you don't need to see everybody's little piece of data across every single part of your organization on your executive dashboard. It becomes to the point where you just... It's too much and not. It lessens the value, cheapens the value.

George Jagodzinki (19:00):

And then, I've also seen, when I say come at it sideways, here's an example of maybe someone's putting in place a new e-commerce platform web. Web and I were just talking with Jason Anthony on a prior episode about headless commerce and commerce in general, and maybe that's just in one part of the business. But to do what they're doing now, they need some sort of enterprise ID. And then someone's spin up this kind of like, "Oh, we need an enterprise ID thing." And then, you hear, "Oh, well, we're going to need to get 10 other stakeholders involved in this that this is going to happen." And then the next thing you know, it's like this 12-long-running initiative to get an enterprise ID. Everyone's lost hope in it, and everyone's just doing workarounds.

(19:37):

I'm curious, your guys' examples of where you see people lose that hope, and how do you push through it?

Mike Wiseman (19:43):

Yeah, it's a challenge sometimes because it gets depth, it gets deep, and there's a lot of complexities, right? When we use that membership example, why it took several months to get to an answer was because you open that closet, and there's all of these other facets that get bolted onto the side, right? You try to keep that focus and what is it that you're marching forward towards? What's the business question you're trying to answer?

(20:14):

It takes some discipline, and that's where having that executive or the person at the seat of the table who can keep that vision going forward and push it forward. At some point, you have to make decisions, right? You have to say, "This is the path we're going forward." You can always revisit it, right?

(20:30):

I think that's the other piece that sometimes gets lost in when organizations are starting up a data process or a data culture is it's not a project, right? It's not we did it, and we're done, and we move on to the next thing, right? Being a data-driven organization means that you have a data-driven culture that is continually evolving, continuing to iterate on what you learn and know.

(20:55):

Like Web said before, you may realize you've been looking at your data backwards for years. You stop, you pivot, and you move forward, right? You iterate and evolve. You've gained more information, and now you move forward. That doesn't mean that if you get saddled with this really complex process that you can't stop and say, "Okay, we're going to move forward with this," and then chunk it up and go follow those iterative processes to continue to evolve and push forward on it because it can get overwhelming, and that's where I think sometimes organizations automatically go to, "Well, let's just get a data platform. That's going to solve our problem," right? We all hear those solutions that say, "Well, we're going to be your single source of truth." We're going to spin you up out of the box with the information in a couple of weeks, and you're going to have a data-driven forward organization and-

Eric Webster (21:50):

Easy-peasy.

Mike Wiseman (21:51):

Right.

(21:52):

The reality is every organization is different. Every organization's data is different. Every industry is different. Everyone's facing similar challenges, but there's an out-of-the-box solution is challenging because especially if you haven't gone through this process before, right?

(22:09):

Take it in chunks, establish that vision, understand the business questions that you're trying to answer with your data, and having that leadership that can say, "We've made a decision, we're going to move forward. We can revisit and continue to evolve on that process."

Eric Webster (22:24):

Yeah. I mean, I think we see this all the time. We get around a table, and there's 14 people with a point of view, and it really, at some point, less can be more and people and in data. You got to remove the red tape. You got to put people on the fast track. You have to allow them to work around rules that were in place previously, establish new rules that are important.

(22:45):

Take your time and move with purpose, too, right? I think a lot of people want to jump in and get it all done right away, rip the bandaid off, and let's get all the data done. Let's fix all the data. It's just not realistic. You can't boil the ocean.

(22:59):

I think one of the big things is, too, is that a lot of people don't want to lose context or they don't want to lose... You can store all the data. There's nothing stopping you from just having a giant cancerous ball of data, right? You can always go back and reference it, but you got to have an organized core where you could always add more information in later. But it's like one of those hoarder houses where you just walk in, and there's just data everywhere. You're just confused, and it's tough sometimes to understand what is reality.

George Jagodzinki (23:25):

Yeah, and in that hoarder house, it's very tempting to I'm when I just burn it all down, and I tend to be a burn it all guy. Honestly, if I didn't know what I know at this point, if I was a data-illiterate, technology-literate CEO, and I heard that my team was spending three months talking about what a member is, I'd be like, "Guys, are we still talking about what a member is? I want us to grow this." And so I think there's an education needed for that executive air cover.

(23:52):

And then also maybe an acknowledgment that once you get that alignment, there's a real accelerant that comes, right? It's a real exponential curve to that accelerant, I would imagine, right?

Mike Wiseman (24:04):

Once you gain that momentum, once you realize, "Oh, we are all now speaking the same language, we now have a definition, we understand what our platforms are, we found how the lineage works there," it starts to get that ball rolling, and then you move on to the next one. And then, it starts to compound and become a program and working towards that culture of establishing ownership.

(24:26):

You get teams and people who have been saddled with struggling, and it takes forever to get their information. They know the data's wrong. They've got all of these workarounds to get information that they've got. They have to go to six systems to get the information that they need in order to do their jobs. You start to reduce that overhead on your team, and you get the momentum, right? You start to get that data culture ingrained, and ultimately that's where you want to go, right? As you've got that culture where people understand when you're bringing on a new platform, you're integrating a new system, you're going through a merger, you're going international.

(25:06):

Whatever it is you're working on, how that data is going to be utilized and brought into your organization and talk about that upfront, right? Don't leave it as an afterthought rushing to get something done just to get something done. Whereas if you took the time to think about how that incoming data is going to be used by your organization, and you'll be able to use that and not put all these band-aids over everything to keep that ball moving. You ingrain that into your processes.

Eric Webster (25:36):

I go back to a lot of the same things is really just about have some rules in place. Focus on keeping the data clean, and make sure that the rules of engagement for the entire team are consistent. Don't allow sideways actors to come in and start to change the rules up while they're in mid-flight, too. Focus on that stability and that consistency of the whole team and you'll slowly start to see that acceleration for the usefulness of that data.

(26:03):

Mike just mentioned it, too, but you may have to keep that old data around a little bit longer than you want it to, but it's definitely better than rushing a solution that doesn't get you what you want it to be at the end of the day.

George Jagodzinki (26:11):

Yeah, yeah, totally agree. Selfishly, the best advice for a hoarder house is you need to bring in some outside expertise with fresh eyes, which are us, right?

(26:20):

But I think the challenge is you guys have both said this, which is you need to be clear on what are the questions that we want to ask of this data. It's a simple statement and such a hard thing to solve. There's real soul-searching and alignment that you have to do to do that.

(26:38):

By the way, everyone's AI is becoming more and more mature. It's even more important to ask that the right questions, right? I'm curious, outside of just deep, soul-searching and peyote trips in the desert, have you guys learned any tips or tricks to figure out what are those right questions to ask and how do you get aligned on it?

Mike Wiseman (26:59):

Looking at what are your short-term goals, what are your long-term goals. What is it that you see facing your organization doing? Exercises like analysis and things like that of understanding where do we want to be today and what are we trying to achieve. Is it a new product? Is it expansion? Is it cost reduction? Whatever those items are and then figuring out, assigning ownership behind it too, right? You go through and say, okay, "Here's all the goals we're going to track," and you walk out of the room, and now, who's owning it? And you come back six months later and, “Oh, we didn't get to that.” Assigning the owner, going through your project management one-on-one processes, and get that in alignment.

(27:44):

But I think it's going through those exercises. Where are you today? What are you trying to achieve in the short term? Your three, six, six, 12-month goals? What are your middle-term goals and what are your longer-term goals?

(27:55):

And then, from a data perspective, do you have the data today that can answer those questions because the reality is you may not have that data. You may need to go either mine your own data, see if it's living somewhere. Is it in your ball of databases that you haven't looked at? Or do you need to find a way to acquire that data? Is there a third-party data that you can get? Is there information that you can get to answer that?

(28:19):

You may not be able to answer your current questions with the data that you have, but now you know where to go after that. If that's not a third party that you can get, is that something you can start to acquire from your current customer base or whatever that is? How are you going to go about that? Is it a marketing campaign? Is it adding features and functionality to your website or your mobile app to start to capture the information that you're looking to drive that information and achieve those goals?

George Jagodzinki (28:45):

Love that.

Eric Webster (28:46):

Yeah. I mean, I go back to a similar thing, which is really just having a very strong unified vision of where you're going as a company first, right? It's very hard to piggyback data on top of an amorphous goal, so have a very sharp goal of where you're going.

(29:00):

And then, understanding what data is going to help you get there, I think, is really the right way for you to align what data you should be focused on to get where you want to be from a vision standpoint.

George Jagodzinki (29:12):

Yeah. Yeah, clear vision. I'm a sucker for a good data workshop, just locking people up in a room and getting people aligned on what is it that we're really trying to do.

(29:21):

I think, Web, you were talking about remember the future. One of my favorite exercises is imagining your organization as a cover article in a magazine a year from now. And not just the headline, but what's the blurb? What are the two bullet points in the cover photo? It's almost like if you can connect the dots between each one of those items and what data are you looking at, both from an early indicator and also a confirmation perspective, then you can start to narrow in on there.

(29:46):

But I think at the end of the day, I think there's really no magic wand to figuring it out. It does take some soul-searching and getting people locked up in a room. Mike, like you said earlier, lots of Post-its involved. Post-its, blood, sweat, and tears, right?

Mike Wiseman (29:58):

You can never have enough Post-its.

George Jagodzinki (30:00):

Well, guys, I've really enjoyed this. I'd like to finish on one question, which is, what's the best advice you've ever received?

(30:06):

Mike, I'll start with you.

Mike Wiseman (30:08):

Best advice I've ever received? It's cliche, but keep trying, right? Fail forward, keep trying, right? You're going to mess up. In being surrounded and in an environment, whether it's personally or professionally, where you have the ability to do that, you learn from your mistake and you'll do better next time. Keep failing.

George Jagodzinki (30:30):

That's great. Going back to the earlier point, that's why it's so important to just have a blame-free culture. It's never going to be perfect, but the best you can do with regards to that, right?

Eric Webster (30:39):

Best advice is measure twice, cut once. It works perfectly here.

George Jagodzinki (30:45):

That is perfect. In our last episode, we were talking a little bit about many trips to Home Depot, so that's very relevant.

(30:52):

All right, guys, well, thank you so much. I enjoyed it.

(30:55):

Thanks for listening to Evolving Industry. For more, subscribe and follow us on your favorite podcast platform, and, pretty please, drop us a review. We'd really appreciate it.

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If you're watching or listening on YouTube, hit that subscribe button and smash the bell button for notifications. If you know someone who's pushing the limits to evolve their business, reach out to the show at Evolving Industry at Integrity.com. Reach out to me, George Jagodzinki on LinkedIn. I love speaking with people getting the hard work done. The business environment's always changing, and you're either keeping up or going extinct. We'll catch you next time, and until then, keep evolving.