AI Is Only As Good As Your Data

[00:00:00] Tessa Burg: Hello, and welcome to another episode of Leader Generation, brought to you by Mod Op. I’m your host, Tessa Burg. And today, I am joined by Dean Smith, the CTO at Credit Benchmark. We are so excited to talk to Dean today about, about why trust matters more than ever in the age of AI. Dean, thanks so much for joining us. 

[00:00:22] Dean Smith: Thanks for having me.  

[00:00:25] Tessa Burg: So this is such a big topic because we’re living in this age of uncertainty. All we hear are updates on models keep releasing more and more features, and I think it’s clear to everyone we’re in this bubble of, you know, what is possible versus what can we actually do and where can we find value. 

[00:00:44] Tessa Burg: And it makes it hard to trust what you’re hearing. It makes it hard to trust even what’s coming out of these tools. But before we start exploring all of this, I wanna learn more about your background and your role today at Credit Benchmark.  

[00:01:02] Dean Smith: Sure. So, um, I mean, you know, I’m, I’m in my early 50s, so I’ve been doing this for a, for a long, a long time. 

[00:01:08] Dean Smith: Um, most of my career, since about the age of 25, I’ve been an architect. So, so I come at things from a, from a very technical standpoint. Um, and, and to be honest, for a long time I thought I was just gonna be doing that kind of thing for, for my, my whole career until about, I don’t… Little over, um, eight years ago. 

[00:01:25] Dean Smith: I was kind of parachuted in. Uh, I used to work for RELX PLC, which is, which is the biggest company on the, on the FTSE that people have never heard of. Um, and I was kind of parachuted into a team of about 120 people to, to sort it out. And, and that kind of was where I went from being sort of an individual contributor, um, to a, to a, to a leader. 

[00:01:44] Dean Smith: Um, and I, I did that a couple more times until ultimately, uh, RELX sold the part of the business I was in. And so, so I, I went with it. Um, and I, I did a few, a few things the last couple of years and then, uh, in, um, in April this year, I was lucky enough to be put in touch with Credit Benchmark, um, who have an incredibly interesting, uh, business model. 

[00:02:05] Dean Smith: They somehow managed to convince a bunch of banks 15 years ago to share some of their most sensitive data, which we then combine and give it back to them so they can compare their data with kind of a, a- an average of everybody else’s, and they can, they can do that comparison. Um-  

[00:02:21] Tessa Burg: Okay …  

[00:02:21] Dean Smith: so it’s, it’s, it’s, it’s quite interesting for me. 

[00:02:23] Dean Smith: It’s a, it’s much, it’s a much smaller team, so I, I’m, I’m, you know, I’m a lot more at the coal face than I perhaps have been in the, in, in the bigger roles. Uh, which is quite nice for me again, and I’m, I’m getting to do a lot of stuff with AI, uh, in this company. So we’re, we’re really trying to push that out. 

[00:02:38] Dean Smith: We’re hoping to, to launch our MCP, uh, in the, the latter half of this year to, to just give our customers that other way of getting our data into their businesses 

[00:02:49] Tessa Burg: That is really impressive, and it’s nice when you’re at a point in your career where you can take the processes and the frameworks that you’ve built in other places and apply them to a completely new area because you, you know, you have those capabilities now- Yes … and those learnings. Yes. Uh, so tell me, you know, you’re, you’re at a new spot, you’re using AI. 

[00:03:11] Tessa Burg: AI has made information feel almost limits- limitless. Why has the explosion of data actually increased the importance of trust?  

[00:03:20] Dean Smith: So the thing that’s really key, our, our dataset is pretty unique. Um, y- you know, there literally isn’t another dataset like it. We- we’ve got a lot of the G-Sibs, the globally significant banks, and so nobody could really come along and build that dataset, and the banks rely on it to compare what they’re doing around credit risk with, with the wider banking community. 

[00:03:39] Dean Smith: Um, and they really trust that data. That is the fundamental basis because they know where it comes from. They know the heritage of data. They know that it came from their peers, um, that they can absolutely put trust in the fact that our consensus credit rating is an honest view of the rest of the b- the rest of the industry’s view on that, on that entity. 

[00:04:00] Dean Smith: Um, and that’s incredibly important because they make decisions based on that data. It, it’s not something an AI has imagined, or i- it’s not something an AI goes and checks Google for quickly. Um, it, it’s grounded in very, very real data, and I, I think that’s incredibly important. You know, AIs hallucinate. 

[00:04:19] Dean Smith: AIs randomly, quickly read web pages, summarize them badly, and then regurgitate it to you. Um, it, it’s not always that factual. Now, look, they’re great. I use them all the time, and they’re really good at, at helping you do problem-solving. They’re, they’re absolutely amazing at, at doing that collection of large amounts of information. 

[00:04:38] Dean Smith: But sometimes getting that real factual stuff becomes really, really important. Um, and it, and it’s not something that the AIs can necessarily just, you know, go out and get from their own memory or, or, or crawl off the internet  

[00:04:52] Tessa Burg: So I think a lot of marketers feel today like they, they have been collecting more and more data. 

[00:05:00] Tessa Burg: They have more first-party data, third-party data. They’ve done market research. Uh, they want to be confident in the decisions that they’re making against this data. How do leaders distinguish between simply having more information and having information that they can trust?  

[00:05:19] Dean Smith: So, so I would almost, um, if you’d asked me that question three years ago before the AI, uh, bubble kind of happened, I’d, I’d give you much the same answer. 

[00:05:29] Dean Smith: Um, to me, to me the value of data has always been the accuracy of it. Um, and especially in marketing. You know, there’s, there’s vast amount of data that’s captured from all over the place. And if you, if you bring in the sales data and things from Salesforce, from your sales team as well, the problem has always been in that space, to me, accuracy. 

[00:05:48] Dean Smith: Um, because if people aren’t updating the data and you don’t have vigorous, uh, rigorous processes on how you collect it and how you clean it up and how you process it, it almost doesn’t matter whether you’re putting it into a dashboard or putting it into an AI. If you put bad data in, you’ll get bad data out. 

[00:06:04] Dean Smith: Um, and that’s, that was true five years ago, that was true 10 years ago. Um, and that’s still true. What, what AI has almost done is made that problem worse, because if you feed bad data into an AI, given that it then extrapolates from that and comes up on flights of fancy and, and does all the things that it does, you can get a very long way away from, from the truth if, if your raw underlying data is not accurate and correct. 

[00:06:27] Dean Smith: Um, but, you know, but that was the case with dashboards. I, I’ve seen that many times where, “Oh, we’ve got a dashboard that says this,” and you go and look at the underlying data and you’re like, “But the data is largely useless.” So your dashboard may say that, but as the underlying data isn’t, isn’t accurate, I wouldn’t, I wouldn’t trust it. 

[00:06:44] Dean Smith: Um, you know, so, so I just think AI’s made it worse. But if you’ve got good data, it’s amazing. Um, absolutely fantastic.  

[00:06:54] Tessa Burg: Yeah, and I, I feel like sometimes marketers get caught in this trap of trying to get good data the same way they did five years ago. They’re like, “Well, we’re gonna make more of these fields in Salesforce required,” or, “We’re gonna start-  

[00:07:09] Dean Smith: Yeah 

[00:07:09] Tessa Burg: uh, not allowing- Okay … salespeople to enter something in the pipeline or even count towards their commission unless these nine things are done.” And-  

[00:07:19] Dean Smith: Yeah …  

[00:07:19] Tessa Burg: there is an opportunity where AI has actually made it easier to collect data, but you, instead of going back and saying, “Let’s institute more requiring, requirements, put more on the users-” There is an opportunity to start thinking about, like, what, what’s a different way to even collect the right kind of data? 

[00:07:42] Tessa Burg: And marketers should really look and say, “What, what is that right kind of data?” And, and h- like, what can they do to make sure that they’re getting the, the data they actually need to make decisions, and not just all of it?  

[00:07:57] Dean Smith: Yes. Yeah. And I… Look, and I think AI helps with that kind of stuff. If you think, you know, I know our sales team use, use, um, Gong a lot. 

[00:08:03] Dean Smith: You know, they record all the calls. And, and that, that new thing is very, very powerful for kind of disseminating information across your whole business and letting people pull information out of it. Um, that’s kind of the other side. I think, I think there is a big help on collecting the data in the first place. 

[00:08:17] Dean Smith: But, but I, I… Your, your point about fields is, is really key, especially, especially ones where salespeople are filling them in, because it just becomes a box-ticking exercise if you’re not careful. And they’ll just put anything in, um, especially if their, if their commissions and things are tied to it. 

[00:08:31] Dean Smith: They’ll just put anything in the boxes just so they can close out the form and say that they’ve done it, and that, that’s not helpful. So I think, I think we’ll start to see AI used at the other end of the process to kind of look for that kind of behavior and go, “People are just putting nonsense, nonsense in here.” 

[00:08:46] Tessa Burg: Right.  

[00:08:46] Dean Smith: Um, i- but yeah, it, it’s, it, it’s tricky. There’s, there’s, there’s so much data, and, and, and kind of deciding which is the, A, accurate, and B, useful stuff is a real… Is a bit of an art. Um, it, it’s not a… It’s… To be honest, it’s not a thing I can, I can necessarily do as a CTO. It’s, it’s, it’s somebody who really, in the marketing organizations, really lives and breathes the data. 

[00:09:10] Dean Smith: Um, I mean, I mean, that is another thing I’m quite keen on. Um, you know, I, I’ve, I’ve built big data platforms for internal analytics for companies before. And, and where that’s most successful is where the different parts of the business have their own analysts. They invest in people that understand the data of that part of the business or that function. 

[00:09:28] Dean Smith: So don’t come to technology and ask them what they should do about marketing data. Go to marketing, and have someone in that organization that fully understands the data you’re collecting and, and is the data owner for that information. That, that is a very, very powerful thing to do. Um, you know, at the end of the day, techno- technologists are not marketeers. 

[00:09:48] Dean Smith: Um, we, we can’t tell you whether the data is accurate. Um, we can keep it for you, we can present it, we can, uh, give you tools to, to, to analyze it and display it, but we are not the best people to be telling you about, um, whether it’s any good  

[00:10:03] Tessa Burg: Yeah, and I think that’s a really empowering statement, and something that marketers skip themselves, is first start with what questions do I wanna ask? 

[00:10:16] Tessa Burg: And I’ve seen marketers just say, “Well, all of these things.” But use the filter of what am I gonna do with the answer, and how valuable is that answer to my stakeholders? And then you can start to prioritize which answers add value, which answers are gonna drive decisions that are aligned with delivering that customer value. 

[00:10:39] Tessa Burg: And from there, you can partner with an analyst, you can partner with tech to say, “What kind of data would we need, and what kind of data do we already have that help get to these answers?” But I do see marketers, when you need fast turnaround, when you need something just measured, when you take for granted your, even your own knowledge or expertise, just because you understand what that data is doesn’t mean everybody does. 

[00:11:05] Tessa Burg: You tend to just jump to the solution or, or even just, like, throw a tool at it before really taking a step back and saying, “But what, what’s the end experience, and how does that experience align to delivering value to our end consumer?” Uh, it i- it’s, uh It also helps get away from doing things in silos. 

[00:11:29] Tessa Burg: You know, because when, when we have these use cases or these questions documented, then you can start to see patterns on how you can serve different departments of the business and, and create more show where those processes are building trust, and maybe even come up with some universal trust signals for quality data. 

[00:11:46] Tessa Burg: Yeah.  

[00:11:47] Dean Smith: So, so, so I think, I mean, uh, you know, this, this is not a new idea, but, but at, at the heart of every business these days should be the business data set. You know, what- whatever kind of business you are, you need to have accurate data about every facet of your business, how it operates, sales, marketing, operations, everything. 

[00:12:05] Dean Smith: Um, and, and that should all be in one place. Um, and, and in my head, um, I’m a big fan of the, the democratization of data. Yes, there’ll be small pockets. You don’t want all the HR data visible by the whole company. You may not want some of the most private finance data to be visible in the whole company. 

[00:12:22] Dean Smith: But every other scrap of data, you kind of want to be available to everybody in the business, and you want to serve that up in a common platform. So, you can hire analysts within marketing, within finance, within sales, and yet you’re not, you’re not beholden on a central function to answer the questions, but you’re all working off a common view of what’s going on. 

[00:12:41] Dean Smith: So there is a role for technology in making sure that the data goes into that common view, is clean, is linked together, is accurate from all the source systems. But then if you’re all working off a common view of what is going on, that’s where I see the most value come out of that. And, and then putting AI on top of that, that’s when it becomes really powerful because you’re working on top of something that as a business you have a great deal of trust in. 

[00:13:06] Dean Smith: You can say, “We, we are confident that is an accurate representation of our business, and so I’m quite happy for AI to look at that.” And there’s a, there’s a big, big difference to what AI does with information that you give it live, accurate information in the context that you’re talking of now, and the stuff it remembers from stuff it learnt. 

[00:13:25] Dean Smith: Um, it, it’s a lot more powerful giving it that live, real information about your business  

[00:13:32] Tessa Burg: Yeah, and I, I feel like that is been a dream where we hear this all the time. You know, especially in marketing, you hear phrases like the single view of the customer or we wanna have all of our data in one place- Exactly. 

[00:13:44] Tessa Burg: Yeah … data is siloed. Where do, where do people start today? Like, I feel like there is a sense of urgency to show value right away. Is there a iterative way to start to get all the data in one spot so that you’re able to show sort of proof of value and steps as you go along while you’re also centralizing? 

[00:14:07] Dean Smith: So, so I, I’m gonna use an example of, um, some- something… You know, this is going back maybe as much as 10 years. Um, we had a business unit that was… With, it had very high first year churn. So, so they would sign up customers, um, and they, they had a very high drop off at the end of the first year. And, um, and so they started looking at the data, and they started going through that process of making the data accurate, and they got all the usage data from, from… 

[00:14:32] Dean Smith: It was a SaaS product. They got all the usage data from the, from the product, and they linked it together so they could tell absolutely all the information from Salesforce about the customers, and therefore what the usage for each customer was. Um, and they tied it back and they, they found a hypothesis that they thought people were canceling because they weren’t using it. 

[00:14:51] Dean Smith: And so they went back and they looked at this model, and they, and they basically did a thing where, right, if any customer hadn’t used the product in the first three months after buying it, it would automatically create a task for the account management sales team to reach out to the customer. It would just poke this task into Salesforce, reach out to this customer, offer them some more onboarding trainings, set up support, and that kind of thing. 

[00:15:09] Dean Smith: Um, and it, and it radically altered their churn. It was transformational. But that kind of got the ball rolling for them 

[00:15:20] Dean Smith: in terms of thinking about… So you kind of have a problem, solve one problem, get the data right for that problem. You’ll learn a lot about how to clean up the data and how to link the data and how to kind of snowball it. And, and you, you should get a good result out doing it. And I, I think, I think when people start with, “Let’s just boil the entire ocean and try and put every single bit of data in first, first go,” you, you won’t succeed because you haven’t really got any objectives for it. 

[00:15:47] Dean Smith: So, so I personally think have a, have a problem, get enough data to solve that problem, and the tech team will have to build a platform to, to solve that problem, in which can then kind of grow to solve the later problems. But, but for me, do it problem-based, um, rather than boiling the ocean and hoping some problems turn up at the end  

[00:16:09] Tessa Burg: Yeah. 

[00:16:09] Tessa Burg: I love, love, love that example, ’cause that is something everyone can do today. Just pick… And what… And that challenge of churn and learning, you know, why are people actually churning, you also introduce the opportunity to collect new and different types of data that most likely marketers and even sales weren’t aware they even needed- Yeah 

[00:16:31] Tessa Burg: that information. Yeah.  

[00:16:32] Dean Smith: Yes. Um, yeah, during the, during the journey of solving that problem, you will go, “Oh, could we, could we get information about that thing that’s going on over there to bring in as well?” And, and, and so you kind of pick up information as you go along. Um, and so, so you end up, you actually end up even doing the first things with quite a lot of your data linked together and working. 

[00:16:50] Dean Smith: So it, it’s quite a, quite a good way of, uh, of solving that problem.  

[00:16:55] Tessa Burg: Yeah. I think this is amazing, and if you are sitting in a seat where, uh, people want to boil the ocean, ’cause we’ve all been in those meetings where they’re we’re gonna do this massive initiative, we’re gonna have people from every division come in- Yeah 

[00:17:12] Tessa Burg: share their use cases, and then we’re gonna, you know, it’s gonna be this grand vision. It  

[00:17:17] Dean Smith: is, it… Yes. You  

[00:17:17] Tessa Burg: can have the grand vision, but start with one problem, and-  

[00:17:22] Dean Smith: Start small. Start small. Yeah. Well, it, I, I mean this is just a personal thing. I’m, I’m a very big fan of just get moving. You know, if you, if you pick roughly a compass direction and you, you, you set off, you might be a bit in the wrong direction and you might have to slight course correct as you’re going, but you’ll have still gone quite a long way towards the, the, the right direction and, and you’ll deliver some value along the way. 

[00:17:46] Dean Smith: And so I’ve, I’ve never been a fan of the let’s sit down for six months and have a think and, um, produce these really grandiose plans and, and, and then get going, because you’ve wasted six months and you could have been delivering some value along the way. Um, and, and especially with this kind of project, because the tooling is not difficult these days. 

[00:18:05] Dean Smith: You’ll, you know, you can, you can get an out-of-the-box solution from Microsoft Azure or AWS or, or Snowflake just really, really quickly. Your tech team are not gonna take a long time. And so, so the best thing to do is to just start collecting data and answering questions. Um, and while you are doing that, you’ll find the dirty data and you’ll come up with ways of cleaning it up and, um, and, and you’ll start to build value as you, as you go along the journey. 

[00:18:30] Tessa Burg: I think that’s another really important point for people to hear is it’s a journey, and the part that’s actually taking the longest is bringing the people along on the journey. And as we learn new things, we can act on them, but we have to start somewhere. The other piece I really love about this approach is specifically for banks and hospitals, where I know I’ve been in rooms and worked with those style clients, where sometimes they point to the governance, compliance, the rules and regulations they have to operate under as a stopper for doing anything. 

[00:19:10] Dean Smith: That, that can be a, a problem. I mean, uh, and, and it’s not… there’s not a magic bullet solution to that kind of, that kind of issue, because some, you know, um, hospital data, you, you can’t, you can’t democratize patient data. You can’t let everyone in the hospital see patient data. Um, and, and banking’s similar. 

[00:19:28] Dean Smith: Um, so, so I think, I, I think there are, there are things you can do in that kind of scenario is, is solve problems that don’t involve your sensitive data to kind of learn how to do it. Um, okay, well, we’ve shown some value by doing this process over here, and it wasn’t sensitive data. You know, and, and kind of for those people who are going, “Oh, I’m really worried about this,” and, and a bit nay-saying about doing it with the sensitive data, show that the maturity is there to, to kind of move over into the more sensitive data can be a way of kind of getting those barriers to come down. 

[00:19:59] Dean Smith: Um, you know, because you are gonna have that, you know, there are data sets in, um, in, in, in those kind of organizations that are just held very, very close to people’s chests, and for very good reason. They cannot have leaks. They cannot have problems. They cannot have that going public. And so, so the, the, the, um, the kind of reticence is really understandable. 

[00:20:20] Dean Smith: Um, so I think, I think you just have kind of, kind of demonstrated maturity in the approach that then makes people feel a little bit better about applying that approach to some of the more den… sensitive data sets.  

[00:20:33] Tessa Burg: Yeah. Again, I think when people know that, that those data sets are protected and not available, and focus more on, like, what are the problems and what kind of data you need to answer those problems- When you go through that journey, you find it has nothing to do with the sensitive data. 

[00:20:48] Tessa Burg: It- A lot of the times- Yes … the gaps are in, yeah, your own behavior, your company’s own processes, which you often find are siloed or, oh, I didn’t even know there was a drop-off there. I didn’t know they didn’t have access to when we were pushing out these promotions and driving them into an office or a brand. 

[00:21:05] Tessa Burg: And so I would, you know, for those indust- industries where, and I’ve talked to clients at marketing level where they’re told they’re not able to do anything. Maybe a good starting point is just to frame those problems that you want to solve to show technology and to show the leadership that, hey, we don’t even want to touch the sensitive data. 

[00:21:25] Tessa Burg: Yeah. We want to solve- Yeah … some challenges where we are really focused on improving our experience and value to the customers without, without any of their sensitive data being exposed or used. Um, so we’re gonna… We’re almost at time, so we gotta end on the big grand finale question. Uh, when we look ahead in three to five years, everybody has access to all this data, everybody has access to AI, and like you’ve said, it’s made it easier for us to do things we haven’t been able to do before, to answer questions, to get insights. 

[00:21:59] Tessa Burg: What companies are going to win, and… Or what are the companies that are winning? What are they doing differently?  

[00:22:07] Dean Smith: So, so I think, you know, I’ve, I’ve talked a lot about that, that, you know, trustable- trusted data in the middle of all this, but, but you kind of touched on it. You know, the, the data that you wanna collect is changing, and it will continue to change. 

[00:22:21] Dean Smith: And, and AI will probably, from a consumer perspective and a, uh, uh, you know, the other end of the funnel perspective, change what’s, what’s kind of flowing in as well. So, so I think, I think the really, the ones that will succeed are the ones that really, really put this having trusted data at the center of their business really into the, you know, kind of heart and soul of how they operate the business, but remain really, really adaptable about we need to be looking at what new types of data are available all the time. 

[00:22:48] Dean Smith: We, we can’t think that because this year we’re able to answer all our questions, that the sources of data we have this year will be the ones that we need next year to answer the questions. So, so it, it’s about, it’s about a culture of data first- Mm … and it’s about being open to the data that you need changing all the time and, and just kind of institutionalizing that. 

[00:23:10] Dean Smith: Um, because if you don’t do that, you’ll think, “Oh, we’ve got it all sorted out this year,” and you’ll come around next year and you’ll… And, and people will be asking you different questions. The CEO will go, “What’s happening about this?” Um, or the CFO or the COO or the CMO, and the questions have changed, and your, and your data hasn’t. 

[00:23:27] Dean Smith: Um, so, so I think, I think that’s where the success will come from. So, um, institutionalize the approach and, and continually look for new types of data and how to get those new types of data in and be clean and, and linked together to, to drive the insight.  

[00:23:44] Tessa Burg: I love that as a way to end in the final takeaway. 

[00:23:46] Tessa Burg: I will say that has come true for us even in our own space. We recently launched, um, an answer engine tool where we started looking at how questions people are asking on the open internet have, have changed- Okay … when they’re looking for products and services. And it is crazy because, you know, SEO has been a practice for a long time, and you- Yeah 

[00:24:08] Tessa Burg: do something similar like, oh, what keywords are they using? You know, what questions are they asking? But the questions customers and clients are asking today have dramatically changed- Yes … why they ask those questions when, because they have more access to information.  

[00:24:24] Dean Smith: Yes, absolutely. I mean, I don’t, I don’t spend much time manually searching the internet anymore. 

[00:24:30] Dean Smith: Um- Yeah … I’ll, I’ll get Claude to do it for me. It’s much quicker. Um, or Gemini. Gemini’s great ’cause it- it’s Google, so it has all the, it has all the information about products. It’s, it, so, so I think, I mean, that fundamentally changes things like SEO because I don’t, I don’t think Claude is looking at adverts. 

[00:24:46] Dean Smith: Um-  

[00:24:46] Tessa Burg: Right. Right. And so, uh, I think people are just sort of realizing this right now and waking up to it. Like even- So- … the kinds of questions are different, and I love what you said about making that data-first a part of the culture, and knowing you’re… It’s going to continue to rapidly change. You’re always gonna have to be-  

[00:25:06] Dean Smith: It’s not gonna  

[00:25:06] Tessa Burg: slow down. 

[00:25:07] Tessa Burg: Mm-hmm.  

[00:25:08] Dean Smith: No. No. Right. I mean, I was talking to somebody the other day. It’s, it’s, you know, we were talking about the, the beginnings of the internet and how fast things changed. You know, we’re talking 20, 30 years ago. Um, and, and it felt like things were changing incredibly quickly then. That’s got nothing on how quickly things are changing today, I don’t think. 

[00:25:27] Dean Smith: It, it’s astonishing how fast things are moving. Even from a year ago, the adoption by everybody of AI to do lots and lots of things. So, so the world will not look anything like it does from a, from a marketing or a technology perspective in five years’ time, I don’t think. So you’ve got to be adaptable. 

[00:25:46] Dean Smith: Yeah. I think that’s the absolute key message.  

[00:25:49] Tessa Burg: Yeah. Well, I really appreciate the insight you shared today because it is just perfect for marketers who know they need to be adaptable, and now you’ve given them a great first step. Just start with one challenge, with one problem, and know that it’s gonna be a journey, but it’s a great way to start building that data-first culture across your entire business and be a part of the team that leads that change. 

[00:26:16] Tessa Burg: And that’s, that’s what is required, is, is change and leading through change. Dean, thank you so much for joining us today. We appreciate your time and all of the insight. If listeners have questions, where can they find you? 

[00:26:39] Dean Smith: Mm-hmm. Um, they can find me on LinkedIn. Um, I, I will share my, uh, my tag for you. That’s probably the easiest place. Um, I’m not, to be honest, I’m not a massive social media person. I’ve, uh, I kind of, I kind of stopped doing that about 15 years ago. Uh, but, but I am on LinkedIn.  

[00:26:56] Tessa Burg: And if folks wanna hear this episode and find your LinkedIn profile, we’ll have it on our podcast page at modop.com, that’s M-O-D-O-P .com/podcast, or search Leader Generation wherever you listen to your podcasts. 

[00:27:12] Tessa Burg: Until next time, thanks Dean, and have a great rest of the week.  

[00:27:16] Dean Smith: Thank you, Tessa.