We are five afters, so I'm gonna go ahead and get us started off. I'll start with a little introduction about myself. Hey, everyone. I'm Garrett Sauls. I'm a content manager at Interworks, and my job is to just get smart people to talk about smart things. And that's why I'm doing this webinar with smart people like Annabelle and So I'll kick it over to Annabelle for her to introduce herself and then, of course, we'll introduce our lovely guest here, Dustin. Yeah. Also, very warm welcome from my side. My name is Annabelle Incon. I'm living in Switzerland. I always get confused when Garrett speak with other host about the America geography. So I always have to Google it, but that's fine. I have, like, twenty years experience, fifteen years in data analytic, essentially in banking. And on my last role, I was leading a center of enablement. And that's why I think that enablement is crucial for any digital transformation or any platform implementation. That's why we come up with, Garrett about this webinar, series, and I'm very glad that we received so many guests already. And it's a great honor to receive, Dustin today. Dustin, is, has already twelve years expense in data analytics. He's a patient and promoter of the potential of data to transform organization and the carrier of individual. If you don't follow them in LinkedIn, you probably should, especially if you want to change carrier. And I, he is currently enterprise analytic manager at Medstart Health, where I focused specifically on data fluency and leading their own community of practice. He's Justin is also incredibly privileged into the data community as a Tableau Social Ambassador. He's a creator and cohost of the Data ID podcast and the cofounder and cohost of the Data Carrier Summit. He's quite busy, I would say. That's quite the list. I'm on my third coffee today, coincidentally. I appreciate that. I love that one. Very much for joining, Dusty. Yeah. Thank you. I I'd love to kick it off, Dusty, with this is always such an interesting question, but, because I think there's again, much like the poll question, there's a lot of answers and there's a lot of takes on it. But when you think about what an enablement leader does and specifically what you do in an enablement role, what is that like? I mean, can you describe what your what your day to day is or generally kind of what your role and and function is in your organization? For sure. Absolutely. And I give just a little bit of context, around how I got into a role like this or why I was interested in a in a role like this. You know, enablement has always especially as I got a few years into my data career, always was, it was just very clear to me the importance of it and the clear connection between enablement activities and, maximizing the return on data products, and analytics in an organization. I I started out as many of us did as an entry level analyst and kinda worked my way up in progressive roles. And as I say, as I got a few years into those roles and started to get my first manager role and ultimately few years later director role, what I realized was that, you know, the hands on keyboard technical work that I was good at that got me kind of my foot in the door, into some of those more senior roles, was not gonna cut it in terms of making sure that, I could see an analytics project through to the end in terms of getting the value that I promised the organization that I would get out of it. You know? And in some cases, I started to ask for incremental investment for projects or new team members and things like that. Right? And that's when the the dial really gets turned up pressure wise in terms of getting the full value, out of a project and making sure that people in the organization are actually using it. And so what I found was just kind of naturally by default, I twenty five or fifty percent of my role as a practitioner became dedicated on enablement. I had to get really good at, you know, training folks on the right skills to deliver products and then train people and then get people excited about the data products that were out there and help them feel to their job and how they could add value themselves by using these projects. And so, it was just kind of became a natural extension, those activities did, of my role as, like, an analytics director. And I started to realize over time, I was like, you know, I wonder if someday this is actually gonna be someone's job to do. Because there were times where especially when we were launching new data products or critical data products into the organization, that enablement had to be, like, eighty percent of what I was thinking about. And And this was a, you know, director level role. Right? Thinking about that stuff that that often. And, you know, really when long story short, when I saw enablement roles start to open up and this position open up specifically at MedStar, I was like, you know, I really fell in love with that enablement work, that I was doing kind of as a side job as an analytics director. And I thought it would be really cool, not only for me personally, it's fun, but also I thought would add a ton of value, you know, to an organization to have someone focused on that, especially someone that kind of had the background with with, leading the enablement activities in the past. And so that's kind of how I fell into it. And to answer your original question directly in terms of what are some of the things that an enablement, you know, manager does. Right? I think there's two primary areas of focus. And it's funny because when I stepped into this role, it was a net new role. People were asking me. They were like, okay. Are you gonna focus when you say enablement and education, like, are you focusing on developing analysts, professional development around analysts, or are you focusing on getting engagement, you know, with users of data products out in the organization? Right? Because, you know, Dustin, you could kind of go two different directions with this. Right? And, I really think it's both. It has to be both. It's awfully hard to, you know, get investment in new, you know, new data positions, right, if you don't have the appetite for what they're gonna create out in the organization. And, you know, the I think the the opposite, is is true as well. Right? And so, you know, you have to you have to develop both. Right? And so, you have to develop the analyst side of things if you wanna make sure you're delivering the right stuff to the users and so on and so forth. So, I'm really focused on both of those things and everything that goes into doing both of those things well. You know, developing analytics professionals, make sure they're connected to the right training resources, they're plugged into, a community of practice where they can collaborate, and that they feel empowered to, execute on the skills that they've built, and can, you know, find the people in the organization that they need to to collaborate on projects. And then on the flip side of things, from a, you know, user perspective, it's really helping people feel empowered to be able to find content, you know, to understand the value in it, to get excited about, you know, hey or even if I'm a leader, a nontechnical leader, you know, I see this project that was done, and these people are using it, and I could see us doing something similar. Okay. Now I am inspired and see a little bit of the template to go create something like this in my own area. Right? And so this all becomes a snowball effect. And so everything to support all of that stuff is what I see being the responsibility of an enablement manager. I love that. That's kind of like, I I love the question you asked. Like, what what which path do you think you're gonna choose? And the answer is yes. Yes. What do you think an enablement leader does? Yes. I'm interested for for both you and Annabelle. This is kind of a follow a short little follow-up to that, and I'd love to hear both of your takes. But do do you think that inherently you as a person, do you think you fall into that enablement role because you you like wearing some different hats? You like doing a little bit of everything, some varied work? Or or what would you say? I mean, kinda kind of just as at a personal level draws you to that and you really enjoy about that. Personal. I'll go first. Yeah. I I love sharing what I my knowledge. Mhmm. So that start like this. And, that start last at least, like, I was at, Cadizvi. I had, like, a team of, people under me. So I was also training them to, become better with Tableau, with data analytic in general. And, then on a broader scale, I also start sharing with other people in the organization. That's how I get into it, let's see, by by this mentoring role or this teaching role. And then, when I got this opportunity to, take over the Tableau Center of Enablement for another bank, I, I jump in because I say I really want to see where I can push myself and if that is a right, fit for me. And I like what Justin and Justin said about, having the two, roles because you have obviously to make, the best of your the investments that you already have invest in the platform. So, improve the return on investment by having, as the platform adopt is one of the big, part. And the second part, of course, like, make better professional that make a faster and quicker decision. That's also a good one. Yeah. For sure. What about you, Dustin? I mean, is it kind of that inherent? You got into enablement just essentially by virtue of you wanna share that knowledge, or or was it because I I it's really interesting to me because I think in the world of data analytics, you have some people who are very, very focused. I mean, very niche in what they do. And then on on the flip side of that, you have some people who are very, very broad. Do you think you fall more into that latter category, or is it some other intrinsic motivation that excites you? Yeah. No. It's definitely definitely, you know, more broad. And so, I mean, I I think what drew me to it is, I actually, the reason that I got into analytics in the first place was not because I I was always interested in data. I was always kind of working on data projects since I was a kid, since I had my first computer. You know? But I never really considered myself a data person or thought I would be a data professional. I always thought of myself as kind of an entrepreneur, you know, and in the organizations that I've been in, I thought I feel like I've been kind of like an intrepreneur is the term that some folks use, you know, for being entrepreneurial within the context of being in a large organization. And, once I started to see some of the tools that were available to work with data, and I finished my I I actually went for an MBA. When I, you know, when I finished my MBA, there was no data specific tracks, you know, to age myself a little bit. Right? But what I really wanted to do was I wanted to find an opportunity where I could use data to kind of do an entrepreneurial project, to use data to add value to an organization in a way that it hadn't been added before. And so, once I got started doing that and kind of got some traction with some of those projects and then saw the value that all of the enablement work, you know, added in terms of really getting full ROI out of those projects. Because if I would have done those projects and never sold the value of them or or never got people using them, like, they probably would have just died out. You know? And, in some cases, they added kind of a transformational value. And I just got really, interested and drawn into, this phenomenon that if you can, you know, engage in some tactics to get people excited about analytics using it, help them form the connection points between the data product and how it can help them do their job, like, you can have a transformational impact, and that's really entrepreneurial, I feel. And so, it was just something that was like a natural fit for me. You know? I enjoy training. I enjoy sharing. I enjoy getting people excited about things, and I really understood data and how tools could be used to add value to a business. So I just was lucky to fall into finding kind of this natural bit, for myself with from an enablement standpoint. Mhmm. In our preliminary discussion, Dustin, you mentioned that you you had, like, a a big audience of users. And I wonder I mean, I didn't have so much myself. And I really wonder how you, organize yourself and how you approach a bigger audience in general. What is your training approach? It's a good question. And so and the the size of the, you know, data community that I'm working with at this current organization is definitely, much larger than any, you know, internal data community that I've worked with at prior organizations. So it's definitely it's been new and a learning experience for me too. I would say, you know, the data communities that I've worked with in the past have been maybe somewhere between if we're talking internal, thirty to fifty fifty folks or so. And our community of practice at MedStar has around eight hundred members, and not all of them are, you know, hardcore data practitioners. Some of them are just folks that have an interest invested interest in in how data is used at the organization, or maybe they lead a team of analysts or things like that. But, that size and scale is definitely different. And one mechanism that we have, for bringing those folks together and making sure they stay up to date on what, you know, training offerings we have available to them or networking opportunities that we have available to them is, every two weeks we have we actually have one later today, coincidentally. It's a busy day, but we have our, we have a community collaboration meeting is what we call it. And so it's a virtual, almost like one hour event, where we invite all eight hundred members to it. Usually, we have maybe a hundred or so attend live, and then folks watch the recording, and we do a recap that's almost kind of a newsletter format, where we, you know, have folks introduce themselves. We go through some of the updates on things that are going on around the organization, from a data perspective, and then we'll have, you know, a presentation or two kind of on a featured topic. And and that content that we feature in there is usually informed by to us by the community. So we you know, I do one on ones. I do surveying of the community. I I did when I started my role at the listening tour of maybe sixty folks or so, that were kinda key leaders in the organization just to hear what kind of content they wanted and what their pain points were. And, we just plan out kind of three, six months in advance what content we're gonna deliver that kind of meets the needs of our community. And that's part of our agenda, like I said. And then the other part is kind of keeping them updated on all the offerings that's going on. So I would say that has been a really good mechanism to help scale, our program offerings and just just keep the knowledge distributed in terms of what's going on and what's available to them. And then, you know, we have a little bit more specific offerings, into what we call subcommunity or practices to folks that are more focused on so let's say you're interested in data modeling. We have a subcommunity practice for data modeling. And then we also have tool specific trainings. We have an internal to Tableau training, you know, things like this. But that central hub is kind of the that community of practice and those community collaboration forums where we let everybody know kind of what's going on and what's available to them. I love that. I'm curious, too. One thing I really appreciated so if people haven't, seen obviously, Dustin, you gave a fantastic talk at at Tableau Conference, which I had the the privilege of being able to sit in. And one of my favorite things I literally Gary. Yeah. They yeah. Right. Yeah. But your presentation I not to I just wanted to say your presentation was one of the best, that I've ever seen at Tableau conference. Like, I was so engaged with it. Yeah. Yeah. It was amazing. But, anyways so yeah. I'm glad. I'm glad. I'm glad. Thank you for that. I don't know if Annabelle feels this way, but it really was. It was just like, yeah. I mean, we're just kinda talking about things we learned from well, obviously from Annabelle's expertise, but from other people, you know, through data forum, through stuff like this. And so, I feel I feel not a little bit, a lot of it like standing on the shoulders of giants, so to speak, and just like, here, let's let's just coalesce and, you know, congregate these these big ideas and hopefully share something that's, that's of value. But one I I feel like I talk about this weekly. It comes up in conversations all the time. One thing I really loved, and I think it's a little bit about what you're talking about, when we're talking about this cohort. So, obviously, you have a lot of users. I would imagine that not just the number, but the diversity of roles. And one thing I really appreciated about your presentation was the way in which you really thoughtfully broke down user personas. Can you speak a little bit to just the different types of people that you serve? Mhmm. You know, like, maybe different roles, whether they're technical, whether they're not technical. I mean, what what's the variation amongst your your organization? How do you reach those people? For sure. And I think the breakdown of personas here is very similar to how it breaks down at other large organizations or organizations of a similar size. And I would say I would add a caveat that I think there's fluid conversation around what these personas are and how they're grouped. You know, there's definitely, I think, alignment on eighty percent of kinda how you lay out the personas, but then there's always discussion over, you know, maybe one or two. But, and and that'll continue, I think, for through the end of time, in the analytics space. But, generally speaking, we think of it in terms of, you know, you have consumers, and those are folks that are probably not developing content. You know, they're in the Tableau world, these are gonna be your folks with viewer licenses, you know, or these might be folks that are just consuming Power BI reports, you know, on the front end of things. Right? And they're using that data for their day to day jobs, which probably is not technical in nature. And then, you've got, you know, kind of your analysts, you know, that may create a data visualization. They may publish a report, things like that. And then you've got but they maybe they don't get into as much of the data engineering work. Then you've got and and and those folks, by the way, those folks don't necessarily have to have analyst in title. Right? They may have a position that doesn't say data or analyst in their title, but twenty five or fifty percent of their role, is being a data analyst. Right? And and we have many of those, I suspect, or most large organizations have many folks like that. I think that the number of folks just from my vantage point have been in the field for twelve or thirteen years. I think that group is growing, and that's a growing group that has to be served. I see a lot of folks in that boat that attend, like, my internal Tableau training as an example. You know, they've got a project that could add value in their area. They have an interest in analytics. They have an interest in data visualization. They wanna pick up, learn a tool, learn enough about our data where they could deliver something to add value to their team. So that's one area. Data engineering is kind of another persona. And then there's this increasing, you know, persona, I feel, in the just in the industry in general, which is analytics engineer. And that's where it's kind of a combination of those first two. You know? I feel like at first, you know, a few probably six or seven years ago, you had a lot of folks getting really good at Tableau that were in the business, but there wasn't enough investment in true analytics roles, you know, for them to have a data analyst title. But they weren't data engineers, you know, and then you had folks that were, like, really good on the back end of things, but they weren't necessarily involved at all in the business. Mhmm. And now you have kind of a convergence of the two over time, and I think organizations, it's become very attractive to them to have these analytics engineers. I've seen these roles pop up. We have them on our enterprise analytics team at MedStar, but I've seen a a lot more of those positions out there in the in the market. And so analytics engineer would be another in terms of a persona we think about. And then kind of your data scientist, you know, role is a is another. Yeah. That's really helpful. The analytics engineer one is fascinating to me as well. I wonder too if if maybe and this is just me spitballing. I wonder too if tools like and it's not just Tableau, but, data ETL tools becoming more user friendly. Do you think those are certainly contributing more to, like, the analytics engineer role where all of a sudden, you don't have to have all of the intensely hard specific knowledge because technology has helped filled in that gap, makes it easier to translate those those data models, whatever, easier to set up, easier to function in something like Tableau or Power BI or whatever analytics tool you're using. Do you think technology has kind of helped kind of converge that gap too? I absolutely do. And I think also too just like, from a personal perspective, I think an individual that, you know, you're probably not gonna have someone that becomes a master of both things. You know? I think most people are gonna lean just naturally strength wise towards one or the other, you know, kind of the data analysis or visualization side versus the engineering side. But if you could take someone that was good on the engineering side and make them okay on the, you know, the presentation layer side of things, like, that person is gonna have a lot of value. Like, their their personal value proposition just went up significantly, you know, not only to the the value they're adding to the organization, but also for their career. And so I think you have more folks, like, getting interested, that were in more back end roles and kind of what some of the front end stuff looks like. And I think the other side is true too. You take someone that's a great storyteller with data, you know, and has great business acumen, and now they start to get a little bit better at the back end stuff. Like, that's quite a person. You know? And, also, I think if you're gonna be a leader, if you if you if you wanna be a leader in your organization, organizations have to develop leaders that have a little bit of both of those skills so that they can make good decisions from a tooling perspective or strategy perspective. Right? But also for someone that wants to be a leader, they've gotta get exposure on both sides of the aisle there too. So it's I think it's a it's a step for, folks to kinda take to the next level. You know, good preparation there and also organizations. I I think whether this is the reason why they're doing it or not, I don't know. But I think that, it does prepare people a little bit better for that next step if they have, interest in leadership. Mhmm. I think it's fantastic to hire to be on an organization that value this cross skill training. Not all the organization does that. Some organizations say, oh, you're good with Tableau. You will be always working with Tableau. I never tried, in those engineering side. So I think it's quite valuable. I'm curious too. This is a kind of a an a related topic. Right? When we talk about technology, we talk about learning new skills. We talk about kind of people filling in these technical gaps and becoming more well rounded, right, as as someone who understands data. One interesting thing I know, Dustin, you you had you had mentioned, when we were scoping this episode was this idea of, a, data literacy, but also the difference between data literacy or the the subtle difference between data literacy and data fluency. I kinda wanna ask Annabelle first. Annabelle, what do you when you think of data literacy, what how do you how do you define that? Or kinda what does that look like on the ground? And I'll ask the same of Dustin and kinda see what the difference between That's not a question I prepared. On the spot. No. This is good. I was gonna say, he's bringing the tough questions here. Yeah. And that that's that may be inherent. It's a loaded question. It's very like, what does that mean for different people? So I think that, there is a difference between literacy and fluency. I think that some people also don't like as a term of data literacy Mhmm. Because for what literacy, stands. And, if you say to your big boss, I think that we should have, like, a data literacy training, they will say no. No. No. Everyone know data. Everyone know how to read, something. So it's a subject that is very touchy for a lot of people because they will refer to the, being in alphabet Mhmm. Which is not that at all. It's like just like, make a way of how to read some chart, how to evaluate. And, if more organization will be more open to really open the door and say, okay. We notice that we can progress, it will be better. But sometimes you have to advance with care. Mhmm. I still remember, me teaching a CFO about, like, your weighted average. And this was a big moment of solitude. I was like, well, long time ago. So you cannot even find that on my CV. I love that. What about you, Dustin? What do you think when when when you think of the term data literacy and as it contrasts with something like data fluency? You know, for sure, a couple things come to mind there. One is I I have had and I had, this is cheating a little bit because, I happen to have the slide handy that I prepared because I this question has come up internally as well. And one slide I use to address this is it's actually a quote from Valerie Logan, who is the founder of the data lodge, which is a great resource for data literacy, all things data literacy if you wanna check it out. But, she had this quote where she says whether you prefer the term data literate or data fluent, remember that building data skills and confidence lives at an intersection. And I I agree with that. I think it is that confidence both on the when we go back to the thing I was talking about earlier of are you developing analysts or are you developing consumers of data? You know, both have to have the confidence. The analysts have to have the confidence to deliver good products that are gonna be used, and the consumers have to have the confidence to use those products. And so I think that confidence does live at the intersection. That's what you're going for. The other thing I will just say is I I personally prefer the term fluency. That was actually part of why I was attracted to this role, when it was carved out, you know, by my boss. Fortunately, him and I have the same perspective on this. He used fluency in the title, which was something I really liked about it. When I think of literacy, I do think a little bit more about the skill building, you know, like, the hard skill building. And I don't know if that's right to think that, but it's just kind of the knee jerk reaction I have when when I hear that. When I think of fluency, I think of being, like, totally comfortable with something and and immersed in the culture of something. I actually I gave a presentation once where I started out with the definition of data fluency, you know, to a group of folks where I was introducing this concept. And, I put up an image of when I was in my twenties. I took a trip with a friend of mine who was fluent in Spanish. I was not fluent in Spanish. And we went to, this beautiful city, Tasco, Mexico. If you're if you haven't seen it, take a look. Google it. It's really cool. Up in the mountains, the city, like, built up the hills. Really cool. And it was amazing. But, like, I had to communicate through him, you know, and I wasn't totally immersed in the experience. Like, I wasn't learning everything I could. I wasn't able to talk with collaborate with other people. You know? Like, I just wasn't totally immersed in the culture and getting the full experience of it. It was limited because I didn't speak the language. Right? And I think the same is true, if you're not if you don't speak the language of data. Right? You don't get that full experience. And I think the organization suffers from that when you add up all the folks that don't have that fluency. But also you as an individual in your career, don't get the full experience that you could as a professional. Mhmm. I think a lot of language learners would would would agree with this, and it's very so I have a six year old. He's in a Spanish immersion school right now, and he's in kindergarten. Yeah. It's it's super cool. But I I think to illustrate your point, I I minored in Spanish in college and fortunately had some organic experiences as well. But there is a difference between learning a language from a textbook or even an app, I won't say which app, But learning from from an app and practicing and then being immersed that fluidity. I think that that truly is the difference. There there there's there's a literate portion which is like, I'm gonna learn the thing. I'm gonna, oh, I see it's a. I'm gonna regurgitate a, but I have no idea what it means or the broader context or any sort of organic fluency. I think there's a lot to be said about using that word because the first word that comes to mind in association is that organic component of it. Whereas literate does feel a little stiffer, a little colder. And I would say the opposite of being data literate feels data illiterate, and illiterate is such a charged word in and of itself. So, from a semantics point of view, as a word person, I really, really do, like hearing that difference. So it's really cool to hear, why you would use that in place of something, or why would you you you would shoot for this data fluency, which is just a shut a subtle shift, but an important one. I'm happy that you all agree because I was the first one to answer. Oh, it was good. It was good. Maybe we should continue on this, complicated question. Right? One of the hurricane question that we always, ask our guests is about how do you convince executive that enablement is needed. Maybe you were involved in the setup process or, of this enablement at your, company or not, but doesn't matter because you have to still to continue to convince them. Right? Yeah. For sure. This is this is definitely an important question. It's it's a hard question to, I mean, and I think, you know, there's proof of that when you look out at the landscape, you know, of of all of the analytics roles that are out there. I would be remiss not to mention that I'm very fortunate to be in an an an enablement focused role. There there are not an abundance of them out there. It is growing, but the number of them is still small. And I think, part of the reason for that is this question has not been completely answered, in many organizations. You know, the value of it hasn't been completely proven, proven out. In terms of my perspective on proving that value, you know, it's first of all, I'll say, I've always having been in analytics kind of from since before the boom of all of the, you know, new roles, like, in twenty seventeen, twenty eighteen, or twenty nineteen, like, having started in twenty twelve or twenty thirteen, like, I, had to get comfortable with the fact that I had to always be selling the value of what I was working on because analytics, you know, when I started was not, like, necessarily core a core function to the organizations that I was in. And so I got to kind of practice the tactics of, like, always kind of, like, selling the value of what I was doing. And I remember, like, my bosses were always interested in, like, making sure we had good examples and talking points to continue to demonstrate the value of what we were investing in from a data perspective. And I think, you know, it's kind of a similar way of thinking, on the enablement side of things. I think if you're fortunate enough to be in an enablement position, you know, you want to continue to share the wins, make clear connections between how they connect to value. Those wins connect to value for the organization. And I do think there's a number of ways you can measure this value. I did talk about some of these in my TC presentation. You know, a few that come to mind are, so for example, reducing duplication of work. And you think about increase building a community, right, and bringing people together, especially if you're in a larger organization. You probably have silos and pockets of that organization that are working on, if not the same project, things that are similar, doing duplicative work in some areas. And when you have a large organization and you have a couple individuals or teams, God forbid, working on the same thing, that's a lot of money. You know, if you're if you're spending, near you're paying two teams to do the same type of work for several months out of the year, that's a lot. Right? And so breaking down those barriers and silos, that's one way to instantly, I think, demonstrate a return. The math may be a little bit soft, but I think that it would be not very disputable that especially in a large organization at a big scale, you know, that math is very much there, right, probably to warrant the investment in, in some sort of enablement function, right, and that's just one example. Another I think of is, attrition. You know, if you again, larger the organization, the easier this this math becomes. Right? If you've got several hundred practitioners or thousands of practitioners at your organization and you make a five, ten, fifteen percent, change for the better in attrition, that math is pretty good when you look at what, attrition costs the organization, right, per headcount. I think the ability to attract top talent is another thing. You know, when you get momentum around analytics, you get the reputation of having a great community, you know, an enablement function that invests in individuals, you know, makes it easy for them to develop their skills and careers. You're gonna find yourself in a situation where, and I can say I have seen this first firsthand in multiple organizations, when you get that reputation, you start to get people top talent knocking down on your door to try to get in rather than fighting and clawing and try to find them. There's definitely value that can be assigned to that. Right? And another thing that comes to mind is, this is something I've been thinking a lot about lately, is, I really like there was an article that Brent Dykes, published in Forbes a while back. I think this was back in twenty twenty two. Yeah. I'm looking at it right now, but it still very much rings true today. And it talked about the fact that only five percent of organizations actually their data prod products actually get to the point where they lead people to take action on things, and that's pretty alarming. Right? And maybe it's not five percent today, maybe it's ten percent, but I think it's still, most people would agree, a pretty low number. Think about the investment that's going into those projects from a tooling perspective, from a a labor perspective, you know, from, like, in some cases, a consulting fee perspective. Right? If you throw hundreds of thousands, if not millions, or in some cases, tens of millions of dollars at something, and you only get, you know, five percent of those projects leading to action. Whereas if you had a very, you know, proactive invested effort and enablement where you got the full return out of those projects, The difference between the return on that, you know, it goes from negative to positive, first of all. Right? But, it's significant. It's enormous. You know? And so, that's why and sometimes it's it's amazing to me actually that this hasn't been enablement as a function, hasn't been invested more because to mitigate the risk, the low to no ROI on a heavily invested function project, etcetera, you know, we're talking about pennies on the dollar, right, to invest in enablement. So to me, it just makes sense from a risk mitigation standpoint. But, what I also loved about Brent's example was in that same article where he shows this data analytics marathon where you start with, you know, a hundred percent of companies are doing data collection, and then you go all the way through the the marathon and you end with five percent are taking action after data products have been developed. There's also this image he has image he put together where he shows the data analytics marathon either going people running downhill or running uphill. Right? And he used the example of if you have a strong data culture, you're running that marathon downhill versus running uphill. And I think the same is true. You could almost interchange enablement with data culture. I mean, I think enablement leads to a good data culture. A good data culture is gonna cultivate good enablement activity. So I I think of it as kind of interchanging, but that visual of and I feel this myself as we get better and better with enablement activities, not only at this current organization, but in the past. As you get better with those, you're running downhill Mhmm. And you're increasing that percentage of product projects that are leading people to take action. Whereas if you're not doing anything from an enablement or culture building perspective, you're fighting and clawing and going uphill and you're losing money, you know. And, so that's where it's I think that this I I believe this enablement field, if we do it well, if we get it right, it's it's gonna grow and grow. Because it's a no brainer to like I said, pennies on the dollar to make that investment enable enablement versus what, we're spending on other things around analytics. Mhmm. I think that's fascinating to me. You had mentioned, prior calling this, like, a snowball effect. But, I mean, in my mind, I just visualize a chart. Right? It it feels like you keep things static. You just do rote training and it's it's just this. May or maybe it's maybe it's this. Maybe it's generous to say it's this. But the moment you start doing it more organically and investing in people, it it's an exponential curve rather than a linear curve. Right? Just like that. So I I think that's that's really interesting to to say that you invest in it, you do the right things, you can have that exponential curve up. But similarly, conversely, if you have negative culture and you lose that momentum, it can you can fall off a cliff. Another thing that I thought was really interesting too in a larger organization, because I feel like you can feel this in smaller organizations very acutely, but it certainly happens in larger organizations is just like loss of institutional knowledge. And so if you don't have a dedicated hub where status stored somewhere, if you have this team over here and all of a sudden two or three people leave because they lost momentum and they were the only people who knew how to do x, y, or z. The efficiency loss and then the cost associated with that is is huge. First, I agree. Percent agree. And it's interesting you bring that up, Garrett. That's something I've been thinking about is we've had, not only through our community collaborations folks present on different topics and share their knowledge on topics, but since, we've had other sub communities of practice where folks are doing the same or as we've started to encourage folks to be I'm encouraged by one of my leaders to always be finding ad hoc ad hocs or adjunct faculty throughout the organization, you know, experts on certain topics where we can have them, you know, lead trainings on. Right? And it's not just myself or folks within our analytics team doing that. And the more we do of that, the more we record those things, the more we make those assets available in a repository to the whole community, the more to your point sustainability that we have, around that knowledge base, and the less knowledge institutional knowledge that we leave when one of those people, god forbid, leaves the organization. Mhmm. Mhmm. One thing I've this kinda goes back into the, leadership engagement. You had mentioned earlier that one of the first things you did whenever you came on at MedStar was a listening tour. Right? So I I'm curious. What benefits did you get from that because I feel like a lot of times, especially with data people, there is a tendency to be like I'm just gonna be autonomous, I'm just gonna build it, I'm just gonna do it and then how could people deny the results. The data speaks for itself. But, I mean, I'm I'm curious. The that function or any other function that you do to listen first, collaborate first, what what have what have been the benefits of that, or how do you go about that? How do you get some traction? Because it can be very difficult to get people in the same room or people to care or people to listen and and show up in that way. That's definitely a lot to unpack in that question. I would say in the context of how I started, you know, starting this net new role, which was the first role I've ever had that's that's totally enablement focused. You know? I've never gone in. I've always started roles with having, like, the typical meet and greet setup. Right? But I have to give credit, big time to, the gentleman that hired me, Dylan Clark. I don't know if Dylan's, watching this. I'm I'm certain he'll listen to the recording of it. But, I have to give a shout out to him because, he recommended this approach to, you know, just kind of shamelessly schedule one on one meetings to introduce yourself with, you know, kind of all of the key stakeholders and at the organization. You know? And they're not necessarily leaders. They might be kind of leaders in non manager roles, you know, leaders from a data analytics community perspective. Right? And we put together this very intentional list of all these folks to to talk with, and it was a marathon, you know, to spend a few weeks, you know, meeting kinda back to back with all these folks in the organization. And it isn't something that I necessarily had thought to do in my thirty, sixty, ninety day plan, if you will. You know? I definitely thought I would meet with some, but not kind of this, just shotgun approach, you know, to meeting with all these folks. And, I will say that what I thought was a benefit of that there were many. I would do it I would do it absolutely again if I started another enablement role. Was that what what became very apparent to me was I took probably sixty or sixty five pages of notes during those meetings. But I actually have one slide where, I won't share it, but, it it it actually boiled all the feedback down into three pillars of three different kind of themes or categories that the feedback, you know, led me to. And it was just very clear in terms of what some of the big needs, the big rocks were that we had to tackle from an enablement perspective. And there's different tactics and different initiatives that we launched to to kind of get started with tackling each of those. But, it at least gave us a guiding light of kind of the three big things that we had to go after. And what we did was we worked backwards then was we actually came up with, based on our experience and the feedback we heard, you know, maybe ten or fifteen initiatives we could launch to help with each of those things that we heard we needed. And, we just started to kinda plot them out. Like, took a crack at what would the effort be to do some of these things to move the needle on those big rocks, and what would the impact of them be. And we just started to go after quick wins first and then got into some of the more complex initiatives over time, and we still have a long ways to go. If I look at that grid of all of the things we can do and the effort they would add, the impact they would add, I put a visual up at at TC in my deck. Actually, you've just done the framework that we yeah. To evaluate this. You saw there's a lot of dots on there we haven't tackled. Right? But, again, it was those three themes that jumped off the page. The and it's interesting because the the themes came up, whether it was leader persona, associate persona, technical, nontechnical. There was really these big themes that popped out across to everyone, and, it just helped create an initial road map of kinda quick wins to go after and then, you know, wins that we that would get increasingly complex that we could tackle, later down the road. But, it just it really informed our our road our initial road map. Mhmm. Mhmm. That's massively useful. I think too there's there's inherent value in attaching attaching value to the level of effort and the level of impact a certain initiative is going to have. But I also think just the act of mapping it and the act of just picking one and starting with it, you know, starting with a small win, starting with the next win. And, yeah, it it can be intimidating seeing seeing all the dots or looking up the mountain of all the work that you have to do. But I think that's better than the alternative of we're gonna do some things and we're kinda looking in the dark, and hopefully, we're stepping in the right direction. I don't know. So I think that's a much better approach. I I'm spatially oriented, so I really like seeing things plotted out even if it's a lot. So To hand it to you and Annabelle, though, I my so my all of the dots that I have, the ideas that we have for enablement initiatives, it grows over time. Right? And we have we have an internal advisory council that we formed that they definitely have added a lot of dots to that grid, which is fantastic. And, you know, the potential, all the ideas that we could implement, it's a living, breathing document, you know, and we're constantly reprioritizing those based upon what the biggest needs are. But I will say that when I attended, your session at TC, you and Annabelle's, session at TC, I added some more dots to that grid. You know, I added some some more ideas to that backlog. Yeah. No. I I love it. And I would recommend if anyone is looking to get started with some some wins, you know, that they can get from an enablement perspective, things that are well worthy of investment, I would I would encourage them to take a look at your presentation. Yeah. I appreciate that. I really love what you said, Dustin, with your boss who enabled you inside the organization. Absolutely. Yes. Yes. I I still remember that sometimes it's not so easy to, contact people and ask, for this feedback for having done myself. And sometimes the first interaction I had with them was like, you are using too much resources in Tableau Server. What are you doing? I'm exaggerating, of course. But, yeah, it's a nice introduction to have. I think that's really great. That's that's something we've seen consistently too, when we talk about so, one person I talk with a lot lately is, a consultant at Interworks named Sarah Dorfman, and she's she's the head of, like, our migration from, like, Tableau Server to Tableau Cloud stuff. And so a big part of what they talk about when they when they move those things is really, like, looking at communities and understanding that usage aspect. And and because it's one thing to, like, go from a to b. Right? But how do you wanna do that intelligently? How do you wanna do that smartly? And so I think to your point as an enablement professional, regardless of whatever it is you're using, looking at those usage analytics, and and very kindly approaching people like, I see your I see you have five hundred dashboards. Maybe what would we think about five? Could can be useful not only in just, reducing resources, you know, which hopefully helps with the ultimate ROI and giving other people space as well to contribute, but, also in just engaging, just as an engagement point, as a conversation point to be to to talk with some because maybe they don't know. You know, a lot of people probably don't know, best practices or that they can consolidate something, and they just need an extra set of hands to help them in that way. So Completely. And and, one increasing kind of our understanding of utilization reporting and how to action, insights that you find from utilization reporting was one of the one of the dots that we had, that we've already been investing in. And, this was kind of a natural one for for me to, help kinda get off the ground, in internally was is because in the past, when I was an analytics leader, when I had launched initiatives where I knew I had to get that full return out of it, you know, we had made big promises in terms of the value. Right? Like, that utilization reporting was something I looked at daily when we launched, you know, new dashboards or new data products. Right? Like, I wanted to know who was using it, but also sometimes more importantly who wasn't. Right? And, and get curious to your point, not in a punitive manner, but kinda ask questions. Maybe it's not even of the folks that aren't using it, but maybe their managers, you know, and ask them, you know, kinda what do you think about this, or how do you perceive how your team is using this, and can maybe could we together, you know, do a session with them just a refresher? And maybe would you be willing as their leader to chime in just practically speaking how they you would see them using this in their job? You know? And, those are the kinds of things that are gonna add that kind of order of magnitude level, impact with your data products rather than if you just kinda let them sit. You don't monitor the utilization. You don't be proactive to have those conversations. You know? And some of those conversations, it's not necessarily technical in nature. Sometimes it's it's very much, you know, talking about the business use case or the the practical use case in the organization for and and team dynamics, you know, in terms of why some people culturally may not wanna use it and how do you break down those barriers and things like that. But, it's awfully hard, to break those things down, and and drive change if you don't know if you're not looking at utilization and you're not having these conversations proactively. Yeah. Yeah. For sure. That's a great insight. We're we're in about five minutes, and I'm gonna I'm gonna open this as last call for people for questions, but we'll talk through some things as well while we're while we're waiting. Oh, we got one. We got a live one. That's the one I was asking for also myself that we should have record or TC presentation. I know. I know. I feel like I wanna say that maybe some I don't know which which were recorded and which weren't. But at the end of the day, I think it's something that, you know, if it's not recorded, then Annabelle and I can go. We can rerecord. We have the technology. We know how. We can go do that. And we can invite Dustin to do the same for his. Yeah. Exactly. I'll I'll we'll take a to to answer this question, though, I'll we'll take a look. Sometimes, after Tableau conference, it's it's it's murky about whenever where something will get posted and when and something like that. So we'll we'll kinda connect with the resources and see if things were recorded or where they're at. If they're not, we will provide some additional resources. Obviously, we have attendees registrations here. We can we can add an email list pretty easy to send these things out or connect with us on LinkedIn. I would imagine anyone anyone on here is more than happy to share some some resources with people. But, while while other people are asking questions, stuff like that, I'm curious, Dustin, to talk about, so your podcast, the the data careers, all of this stuff. I want I wanna I wanna hear about that. I wanna hear about how you got into that and what those things are and how people can kinda connect with them. Appreciate it. Yeah. Great question. So, in terms of the data career summit, I started it with another Tableau ambassador, Brandy Beals. And, Brandy was actually the leader of our Tableau user group in our, Milwaukee area. And I got to know her long ago when I first started, in Tableau. You know, I got plugged into that community, and she just did an amazing job of leading it. And over the years, we got to be friends and and kind of just as analytics leaders in our community, stay in touch over, just certain kind of management, you know, topics and things like that and leading analytics initiatives at our organizations. And, around, I would say, twenty eighteen or twenty nineteen, we we we both realized that we started getting asked a lot of questions, like, how folks could break into the field or maybe how their son or daughter could break into the field and things like that. And, I started creating, you know, content, around these topics. And, and, she definitely helped address them in in our local community. And, we at at some point, we're like, you know, maybe we should organize an event around this to help address these questions at a greater scale because, it probably doesn't make sense just for for her and I to try to answer them. Not to say we were the only two people. Right? But, like, we need to bring together all the experts. And, that was how the data career summit, started. And so we've done four of them, and, we'll we'll see if there's another you know, it's I will say it's an awful lot of effort to put in to to put them on. But, we've just been really blessed to have some amazing speakers and folks come together, to just give insight to job seekers and transitioners as to, you know, what tactics to deploy to to get into the field. And then, from a data ideas podcast standpoint, I just did episode fifty seven last week. We got episode fifty eight coming up this week with, Sekou Tyler. I don't know if Sekou has been on your okay. Alright. He did a session, at TC, but, Sekou's actually been a speaker at our internal, MedStar community collaborations as well. Just someone I respect a lot, in the field. So he'll be the guest, this week. But, yeah, we're doing them weekly, every Thursday night live at eight o'clock eastern time recording and then publish out, the podcast to all the major platforms on Friday morning. The theme of the podcast is, growing your career in data and AI. So just trying to continue to deliver more content to kind of that following that's been built around that topic. That's great. I love I love hearing about that. And what a what a a a great niche to fill because I feel like, this is true of any any job searching, any job sort of thing. It it can be really tough to find clarity. It can be really tough to find expertise and knowledge that is actually useful and not just something that is, written to get clicks. And so, obviously, knowing knowing you and others as trusted sources of people who have been there and have done these things and work in these organizations that know what it takes to succeed. Right? Kinda cutting through that noise and how to how to upscale, how the the soft skills as well, the things that people need to know, which are really valuable, just as valuable. That's that's a massive benefit. I mean, so thanks thanks for doing that because it can be tough, I mean, for for job searches out there to know, like, can I trust this source? Is this right? Is this correct? Even if you do all the correct things, it's still very difficult. So It was yeah. It's a good point. I'm curious. It's just kind of a final question. What's what's next for you? Obviously, the podcast on Thursday. But beyond that, what's next for you? No. Something tonight. Remember, it has something tonight, Chris. Okay. So that's right. That's right. Yes. Yes. Yes. Yeah. For sure. So, actually, I think the funny thing is is actually, I think in the next hour, this was prerecorded, but the disruptive data leadership summit is going on. I'm presenting. I think it literally is starting in a minute from now, but, I Two places once. Make it to my own I'm not gonna make it to my own presentation. I recorded it a week ago or so, but, it is a session actually on building data communities and just some of the tactics, that we've used to to build data communities, whether they're internal or external to your organization. I've got kinda seven steps, seven key things that, I think about and have added a little bit of of detail around each of those. It's a twenty minute presentation. Mhmm. And we're probably gonna share that internally at our organization as well. But, yeah, that's literally the next thing, I guess, that I'm doing in a minute for now. But, we got Sekou on the podcast later this week, And, I think we'll we'll leave it at that. We're at time. That's great. Well, I I appreciate you joining. What's the best way, real quick, the best way to connect for people? Is LinkedIn, essentially, if people have questions or anything like that? Absolutely. Feel free to connect with me, reach out. Be glad to to talk anything data or data engagement. Awesome. Well, thank you so much for joining. It's been fantastic as usual. As always, my one regret is we don't have any any more time, so we'll have to do this again at some point. Thanks for coming on. Thanks for a great talk. Appreciate it. And good luck, good luck with your next presentation right now. Appreciate it. Thank you both for inviting me on. I when I saw the list of guests that you presented at Tableau Conference and who's been on, I thought, jeez. How why is it that I'm gonna be the next person on this No. You deserve it. You're in the hall of fame now. That lady. I'm learn and and I'm learning, I feel like, from from two greats here in both of you. And so, definitely had some imposter syndrome, you know, coming on to this one. But, thank you to both of you for having me on and all of the the work that you do, to advance enablement, in our industry. Likewise. Thanks, Justin. See you, Annabelle. Hey. Thanks, everyone, for joining.