How To Pitch Your Data Story with Scott Taylor of MetaMeta Consulting

Key Takeaways:

‍

(03:24) Two types of data storytelling: one for analytics and one for data management.

(05:30) Truth in data must come before deriving meaning from it.

(08:10) Avoid buzzwords and focus on vocabulary the business understands.

(12:21) Listen to earnings calls or strategy meetings to learn your company’s objectives.

(17:23) Master data is foundational to delivering business value at scale.

(22:17) Use industry-specific analogies to clarify data’s impact.

(26:42) Poor data management can amplify errors in AI-driven systems.

(28:04) Master data challenges exist in every industry and era.

(33:19) Developing storytelling skills is essential for career growth.

‍

[00:00:00] Scott Taylor: Avoid the buzzwords, avoid the technical speak. Nobody cares in the business side, whether you're going to implement your latest analytics graph hub fabric mesh and how exciting that is versus what you were talking about two years ago, which was the latest, whatever. If you want to speak to the business, you have to use the language of your business

‍

[00:00:17] Anthony Deighton: Welcome back to Data Masters. Today we're deep diving into the art of data storytelling with a true master of the craft. I'm thrilled to introduce our guest, Scott Taylor, affectionately known as the Data Whisperer. Scott is not just a data expert. He's a translator, a bridge builder between the complex world of data and business leaders.

‍

[00:01:06] Anthony Deighton: You need to understand its value. With over two decades of experience solving master data challenges for global enterprises, Scott has a unique knack for simplifying the complex and making data more accessible. He's worked for some of the biggest names in the business, including Dun Bradstreet, Nielsen, Microsoft, Cantor, helping them to leverage their data assets for strategic advantage. Scott is a recognized thought leader in the data space. He's the author of a must read book. Telling your data story, a practical guide to explaining and understanding the strategic value of data management. And today he's here to share his insights on how to effectively communicate the power of data, avoid common pitfalls, and ultimately drive better business outcomes. Welcome to Data Masters, Scott.

‍

[00:01:57] Scott Taylor: Thank you, Anthony. Great to be here.

‍

[00:02:00] Anthony Deighton: So I love this conversation over the course of, our data masters podcast. We've, I think kind of oscillated between the highly technical and the highly business oriented. And I'm hoping this ends up being kind of a bridge episode where we can really think about how to bring those two worlds together. Let's start, you know, you have this, term you've been referred to as the data whisperer. maybe let's start with that and maybe, if you don't mind, elaborate on what you mean by the data whisperer and,why is data storytelling such a crucial skill for data professionals and what do you mean by data storytelling, which could mean a lot of different things?

‍

[00:02:38] Scott Taylor: Well, as the Data Whisperer, I've been Using that moniker for a few years now. And one thing it does is it gives people a little bit of a smile and curious about what that means. But similar to the dog whisper or the horse whisper, we're all trying to calm data down, especially in the master data space, the data management space.

‍

[00:02:55] Scott Taylor: Data is unruly. Data is wild. Data is unstructured. We've got to try and calm that down. However, it doesn't take long for people to realize a little bit of a spoiler alert. I don't do a whole lot of whispering myself. We save that for the data. I'm out there telling, selling, and yelling about the power and value of proper data management.

‍

[00:03:15] Scott Taylor: And I tried to formalize that a little bit with this idea of data storytelling for data management. Data storytelling has been around for a while. Huge, probably one of the biggest non technical things going on in the space. But looking at it, When it came out and following the leaders who were talking about it, I realized it's really analytic storytelling.

‍

[00:03:35] Scott Taylor: It's really about focusing on how to take a piece of analytics or a KPI or some sort of insight and put it in a business context to drive action. Great, super important. But what about the data management part? How do you talk about why managing data is of strategic importance to your enterprise? We've got to put that story together as well.

‍

[00:03:58] Scott Taylor: And if you don't have that data management story in place and your C level folks don't understand why it's important, then guess what? You're not going to have too many analytics stories to tell either. Because if the data isn't any good in those analytics processes, then we know the result isn't going to be what they want.

‍

[00:04:15] Scott Taylor: So, really this, Tried to create this idea of having two kinds of data storytelling out there, one with data for analytics, and one about data for data management.

‍

[00:04:26] Anthony Deighton: It's a great insight. I like this, with data and about data as a really nice way of thinking about it, I feel like over the last. You know, 10, 15 years, the industry has spent a lot of energy thinking about how to help people tell stories with their data. And one kind of negative connotation of that is this idea that we can make data say whatever it is we want to say.

‍

[00:04:51] Anthony Deighton: And I think differentiation you're drawing is between that and the fact that we want to say. potential outcome, and then actually thinking about the data behind the dashboard to say, like, what's behind that story, and do we trust that? Is that a fair way of differentiating it?

‍

[00:05:07] Scott Taylor: Completely. Do we trust that data? And I summarize my whole data philosophy. I boil it down to three words, and when you get good at storytelling, one technique is what's the fewest number of words you can use to do. Articulate a message. So I got mine down to three. I can't get it any fewer than that. But it's truth before meaning.

‍

[00:05:28] Scott Taylor: You need to determine the truth in your data before you derive meaning out of it. It's not chicken or egg here. It is egg and omelet. You don't have the truth in your data. You're not going to derive the meaning that you expect from it. And you being in the master data space as well. We keep telling this same story, and what inspired me to write my book was a career dealing with data practitioners in the MDM, RDM, PIM, RIM, DAM space, all those foundational activities, and the practitioners who manage those, and realizing they had this dual emotion, one they were really passionate and really excited about what That foundational data could do for the organization, but they were also extremely frustrated because nobody was listening to them.

‍

[00:06:14] Scott Taylor: The story was, it wasn't even a story. They start talking about how it's going to get done. They start talking about things like data quality, data hygiene. Those things are important, but they don't sell. CEO doesn't care about data hygiene in the way that a data hygiene expert would or a data steward would.

‍

[00:06:31] Scott Taylor: And I never met CFO who cares about how you're going to implement something until they understand why it's important. So helping those practitioners, those data leaders who focus on data management, data governance, data stewardship, helping them articulate Why managing data will enable the strategic intention of their enterprise?

‍

[00:06:55] Scott Taylor: company going? And why is managing data going to help them get there?

‍

[00:06:59] Anthony Deighton: Before we go there, and I totally agree with you, you're clearly somebody who's thought a lot about the language behind this, and I think a lot of listeners, by their background and nature, tend to be, technically oriented, maybe think less about how they communicate about these things. In your, in the materials you've built, keynotes you've done, and the book you've written, you've actually really keyed in on this idea about the way we talk about data holding us back, and you've termed this idea, data is the new BS, uh,and given some really practical thoughts about how we can change the language we use to make data more meaningful and accessible. so maybe. Stepping back a little bit, what are the common mistakes you see, data professionals making when they talk about data to their business managers and business leaders?

‍

[00:07:51] Scott Taylor: Overall, they talk about how it's going to get done. When they tell stories, I counsel people, yes, you need to tell a story, but don't tell your life story. Oh, first we did this, and then we did this, and then that didn't You're a leader. You've been, you've seen people pitch to you. The first five minutes are so important.

‍

[00:08:07] Scott Taylor: Avoid the buzzwords, avoid the technical speak. Nobody cares in the business side, whether you're going to implement your latest analytics graph hub fabric mesh and how exciting that is versus what you were talking about two years ago, which was the latest, whatever. If you want to speak to the business, you have to use the language of your business.

‍

[00:08:25] Scott Taylor: And the,the nice. element of that is the language of your business is actually built from the entity types that you manage in master data. Talk about customers, talk about brands, assets, locations, banners, ingredients, the kinds of things that the rest of your organization fully understands and realizes that Bring value to their relationships and use that kind of terminology.

‍

[00:08:51] Scott Taylor: Be really specific and understand the lexicon of your own business and avoid all the tech speak. And again, avoid these really passive, I beat on data quality as a term only because as I mentioned, it doesn't sell. If the idea of getting better data quality really drove the point home, then we wouldn't still be talking about it.

‍

[00:09:12] Scott Taylor: And I don't know about you, but I've been talking about this since pre 2k.

‍

[00:09:15] Anthony Deighton: Sure.

‍

[00:09:16] Scott Taylor: So finding ways to really communicate leads into a framework I have in the book called the three V's of data storytelling. Obviously a little gnawing wing to the three V's of big data, but the first V is vocabulary. Get the words right.

‍

[00:09:30] Scott Taylor: Speak the language of your business.

‍

[00:09:33] Anthony Deighton: So, I think one of the reasons that data professionals make this mistake is, and this is a kind of a common behavior, is we always try to communicate from our perspective out. So here is what I've done. Let me tell you about, you know, to your words, the hard work we've done to achieve this outcome. And one way to think about what you're saying is to communicate from the listener in. So think about what your audience is interested in understanding and then frame the communication in the context of their language and their communication. So in what you're saying here, framing it in the context of business outcomes that a business manager cares about, versus the work you've done as a data professional.

‍

[00:10:17] Anthony Deighton: Is that a fair way of framing it?

‍

[00:10:19] Scott Taylor: When doesn't that work? I mean, that's always the case in any form of communication. I wouldn't even consider it exclusive to talking about data management. speak to your audience, understand your audience, whoever they are, and fine tune and adjust your language, your positioning, your That's what I had to say.

‍

[00:10:40] Scott Taylor: Data folks are so darn important. And so there's a lot of anxiety and feeling about what if the data is all correct? very much. are successful because they've learned the hard skills of programming and coding and stewardship and whatever, you know, all that, all the rest of that stuff. I don't mean to dismiss it at all, but that's how you become a data person is you understand how to work with data.

‍

[00:11:06] Scott Taylor: And for my whole career, I've thought it's ironic that we call the soft skills are actually a lot harder than the hard skills in some cases, but those soft skills of communication, of empathy, of timing, of creativity. If you want to be a leader in any organization, you've got to know how to communicate.

‍

[00:11:24] Scott Taylor: And we are well behind the curve in the data management space, as well as the data space in general, in being able to communicate clearly to folks who are not part of our near set comrades.

‍

[00:11:39] Anthony Deighton: so people often ask at a practical level, how do I do this? how do I understand our business, our business goals as an organization? one, technique I always recommend to people is either, if you're a public company, listen to the earnings call or read the annual report. Obviously for private companies, that doesn't work. What are some other techniques that you've seen that really work for giving data professionals the vocabulary to communicate with business leaders?

‍

[00:12:09] Scott Taylor: Just reinforce your recommendation, which is in my book. And I talk about all the time. Yes. If you're a public company, what your business strategy is published and public. So listen to that earnings call. Watch your, investor day presentation. You will not hear about data quality in any of those things, but you will hear about Customers.

‍

[00:12:29] Scott Taylor: You'll hear about relationships. You'll hear about brand development. You'll hear about all those things that actually are part of the domains you need to manage in the master data space. If you're not a public company, then just listen to what your, listen to what your leaders say. Anyway, you still have a down, a town hall.

‍

[00:12:45] Scott Taylor: You still have a strategy. They're still posting or talking about what the core objectives are of the business. Find what those are. And you will, It's like a parlor game with me because I've done it so much and I tried to put some of these techniques in my book, no matter what, you are going to find the hooks and the,the connections between managing data at the entity level and the strategic intentions of your enterprise, as I like to put it, I try to summarize what every company or every enterprise is trying to do to give people a hint.

‍

[00:13:19] Scott Taylor: Is every company I've ever run into is trying to deliver value to their relationships through their brands at scale. So delivering value, we all want to do that. Grow the business, improve the business, protect the business, really simple stuff. Relationships. Every company has relationships. You don't have relationships, you don't have a business.

‍

[00:13:41] Scott Taylor: Customers, vendors, partners, prospects, citizens, patients, consumers, clients, right? We all have different terminology, back to that vocabulary part. But working at a business, you know what you call your relationships. And then brands, we all have brands as well. Brands, products, services, offerings, whatever those happen to be, whatever your company makes.

‍

[00:14:01] Scott Taylor: Learn that, get fluent in that before you start talking about data stuff. Because you'll begin to see. those connections. And if you 

‍

[00:14:11] Scott Taylor: want to deliver value to your relationships through your brands at scale, you can't do it without technology. Technology is hardware, software, data. If you have data, you need data management.

‍

[00:14:21] Scott Taylor: The core of data management is MDM checkmate.

‍

[00:14:24] Anthony Deighton: so, exactly. And just to underscore this point for a second and go back to something you'd said before, underneath each business strat or every business strategy is a set of. Entities that really matter, you know, whether it's citizens, patients, customers, companies, parts, products, locations, all the ones you mentioned before, and that's a very powerful language for people to talk about the business that they're operating in. And yet, our tendency as data professionals is to talk about columns, tables. Records, databases, systems, you know, is it stored in this, you know, ERP or that ERP? so, would it be fair to say, what you're saying is sort of, move away from talking about the tables, just to be very simplistic about it, and up to talking about the entities, and then connect those entities to business strategies?

‍

[00:15:59] Anthony Deighton: Is that fair? A

‍

[00:16:01] Scott Taylor: You, you've got to connect the entities of business strategy. It's funny, I actually use Table as,as an example of The importance of master data and reference data. Columns are analytics. The rows are the master data. 

‍

[00:16:15] Scott Taylor: Columns are easy. Anybody can add columns to stuff, but you take two spreadsheets and bang them together, you can always add the columns.

‍

[00:16:21] Scott Taylor: Try to align the rows. That's the hard part. You get duplicates, you get Misnomers. Nobody ever complains about the columns, but the rows don't align. So even something as simplistic as a table, you can use to say, you know, it's about rows and columns here. We got to make sure the rows are right. The rows are what the columns are about.

‍

[00:16:40] Scott Taylor: It's that simple to me, but yes, elevating it beyond that to what the business is trying to do. If you've got and challenging those data practitioners out there, especially the ones who aspire to be leaders, you got five minutes with your CEO. don't care about what you're doing. And they just met with the head of marketing.

‍

[00:16:59] Scott Taylor: Who's a better storyteller than you are. Cause that's what marketing does. They met with the head of sales who basically, if they can't tell stories, they don't make quota. You're on and your stuff enables everything those other leaders are going to do. I mean, I am happy to claim to the, at the highest level, which I've done for my whole career, that master data is your most important data.

‍

[00:17:18] Scott Taylor: It is the data that drives your business. It is what your business is about. And you got to get a little, you know, courage to be able to step up and not only say that, but obviously prove it as well. And when you can, the lights go on. I have. You know, illuminated more than my fair share of senior business leaders and taking them from I have no idea what you're talking about to Oh my goodness, how do we live without this?

‍

[00:17:45] Scott Taylor: And that's what you want from somebody as a reaction.

‍

[00:17:48] Anthony Deighton: And so, I think in very practical terms, imagining, a listener is sitting in a meeting with their business partner and they're having this conversation and let's just be positive and they're doing a great job. And then. Five minutes later, they find themselves in this space of technical complexity, having reverted to where it's comfortable for them to talk about how and the mechanics. How do you help people or do you have advice for folks how to bring themselves out of that conversation and back up to the business value that you're aspiring to?

‍

[00:18:26] Scott Taylor: Staying focused on what the objective of that meeting is helps. And having some form of sales training. That's what it is. The data story you're going to tell about data management, I hate to break it to everybody, it's not some sort of epic, hopefully it's not a horror story, it's a pitch. Why do we need this?

‍

[00:18:43] Scott Taylor: Why are you going to get, you know, I need money from you to support this effort. That is a pitch and you've got to really hone it and it's there. So the reason I try to kind of shake the shoulders of our community is because it is there. It is always there. The need is there. I'm fond of saying, you know, the reasons for master data are as, it's as hard to find reasons for master data in an organization as it is to find grains of sand on a beach.

‍

[00:19:11] Scott Taylor: They're everywhere. It really is everywhere, but it's hidden in plain sight. So stay focused on,on the business objectives. And as a leader, you've got to understand your business objectives too. What does your business do? I told my kids when they went out into business and uh,you know, graduated school, I said, it is impossible for you to learn too much about what your business is.

‍

[00:19:32] Scott Taylor: It's impossible. You just learn as much as you can and the data opportunities will present themselves. Because, you know, marketing is trying to create this wonderful algorithmic process to deliver the next best offer to the next possible, prospect. And then you realize that prospect's in there three times.

‍

[00:19:52] Scott Taylor: or 12 times or 100 times. So how good is that algorithm if it doesn't know it's shooting the same thing at three different, you know, at one thing, three different ways. There's waste everywhere. So take

‍

[00:20:02] Anthony Deighton: so, so far, I think, you know, getting a clear understanding of your businesses, objectives, mapping those objectives back to, master data, to the key entities that matter inside that organization, and then thinking about that data foundation that sits underneath that, I think that tiering is the right tiering, but I do want to, Spend a second on, in the weeds for a moment.

‍

[00:20:27] Anthony Deighton: you often talk about this idea of a solid data foundation as being critical. maybe talk a little bit about why you think it's so important. and, you know, what are some of the common mistakes or maybe you say this positively. What are some of the good things we can do as organizations to build that strong data foundation?

‍

[00:20:45] Scott Taylor: cup, by the way. Just a little shout out to you. And just as a sidebar, kudos to your marketing folks. You know how you know great swag when you actually go out and buy one yourself. So I love this cup and I bought another one. So, First of all, why do you think they call it a foundation?

‍

[00:21:04] Scott Taylor: I mean, let's just start there. the analogies work. The,the imagery is so simple. We never call it a data roof or a data wall or a data, you 

‍

[00:21:12] Scott Taylor: know,

‍

[00:21:13] Scott Taylor: it's the foundation. So you've got to build on that solid foundation and even drawing it the right way sometimes gets people, Messed up, you know, draw it on the bottom.

‍

[00:21:23] Scott Taylor: I always draw master data,data management on don't draw it on the top. Don't put it on this, don't put it in the middle. There's always this really egocentric way that people love to draw whatever they're working on in the middle and everything else revolves around it. Your business is in the middle.

‍

[00:21:38] Scott Taylor: You're the foundation on there. And it also works in terms of. You've got lots of silos. You've got lots of verticals. You've got lots of,different applications. You've got a horizontal, you've got, uh, you know, a foundation, sort of the geometry works as well. You got columns, you need a row.

‍

[00:21:53] Scott Taylor: So I find this,this motif shows up often to, to kind of prove my thesis around making sure that foundation and horizontal value in rows versus columns works. So drawing it. the right way, talking about it in a simple way, using simple analogies. One tip I give people is use an analogy that's appropriate to your business.

‍

[00:22:16] Scott Taylor: Like use your business as an analogy. what you do in your business, which you got to figure the premises that most people in the,in the, in your organization understand what your company does and use that as an analogy. And I've heard some data leaders tell great stories. The CDO from Water Utility talked about how we need this reservoir of good, clean information and data.

‍

[00:22:40] Scott Taylor: It's got to run through all the pipelines. Every user has to turn a spigot at their analytics dashboard. And. Trust the outcome that comes out of it. Again, very simple, straightforward.I heard a CDO from, uh, uh,the military talk about how data is the payload of our business. You can't use that everywhere.

‍

[00:22:56] Scott Taylor: Or if you're a healthcare company, you know, a healthy business runs unhealthy data. It's a lifeblood of organization. Those kinds of things as simple and sometimes as corny as you might think they are, actually can cut through a lot of guff that goes on and the BS that I talk about because. People get it.

‍

[00:23:14] Scott Taylor: A shipping company that I work with, actually, they use, we use their shipping process as a way to talk about how they manage data, you know, where it comes from, you know, where it's going, you know, the provenance, you know, the,the destination, all the complications of shipping and where that can go wrong and how the same things can go wrong with data.

‍

[00:23:36] Scott Taylor: People got it really quickly. and the reason I pick on, you know, my. You mentioned this sort of, the title of my keynote, Data is the New B. S. Because Data is the New Oil set us back a long way.

‍

[00:23:47] Scott Taylor: People were arguing about even that analogy. Oh, it's like oil because it needs to be refined. No, it's not like oil because it's depleted and you don't, you know, you need to, you can't reuse it.

‍

[00:23:59] Scott Taylor: It's like the fact that we're arguing about what this analogy means, means it's bad poetry.the reason you use analogies and metaphors of figure of speech is to shorten the distance to understanding. So if you have to explain your imagery again in your first five minutes, you're losing them already.

‍

[00:24:13] Scott Taylor: So keep it clean, keep it straightforward. And even if it's a little corny, take the slogan of your company and put the word data or master data in there. See if it works. You're not running ads on TV. So, one of the data leaders at SeaWorld, who I know, he said, I read your book, and we created this data environment, and we just call it DataWorld.

‍

[00:24:34] Scott Taylor: I go, that's perfect. Yeah, I mean, that's, you know, is that going to go on TV? No. But they, it works. Everybody gets it.

‍

[00:24:40] Anthony Deighton: I love this idea of mapping the analogy to the business you're in. This idea of data as the new oil is a common metaphor. And unless you work for an oil refinery

‍

[00:24:51] Anthony Deighton: company, it probably doesn't work very well. You know, if you do, maybe it's great. and also this point that if you're spending a lot of energy And explaining the metaphor, then the metaphor is not helpful.

‍

[00:25:03] Anthony Deighton: Um, so yeah, ultimately your goal is to create a, a vocabulary language that your business partner can, use and think about and justify why they're making this investment, in the foundation.also as somebody who's relatively recently built a house, I can assure you that homebuilders sell. The pitch is around the paint and the moldings and the, you know, the fits and finish and all that kind of stuff. And in fact, what you're, you know, the really valuable thing is the strong foundation. If you build the house on a bad foundation, you're not going to be very happy with it when you move in.

‍

[00:25:39] Anthony Deighton: So I think that this does work, really, really well.

‍

[00:25:42] Scott Taylor: What does the inspector say, rather than the realtor? That's who you really want to hear about. So, what's the data behind the scenes? We don't want to see the fancy dashboard, but that drop down menu, where'd you get that? Why does that have duplicates? Why doesn't that make sense? Why isn't that hierarchy not right?

‍

[00:25:56] Anthony Deighton: So, shifting gears a little bit, We've talked a lot about, the vocabulary, building the case, connecting to business value. I wanted to shift a little bit and talk about A. I. That seems to be the,the sort of exciting new thing. Everybody's talking about A. I. maybe share your point of view. on this A.

‍

[00:26:14] Anthony Deighton: I. trend, and maybe, I don't know, maybe there are other advanced technologies you want to bring in, but also how you see this affecting data storytelling and data more generally, you know, maybe, there isn't any need for data professionals at all. We can just sort of outsource it all to our A. I.

‍

[00:26:31] Anthony Deighton: overlord. I'm not sure, but what's your view?

‍

[00:26:35] Scott Taylor: I think that, you know, not just A. I., but Gen. A. I., and people that, okay, is there a new story? Can we skip, you know, Data management, because now we have A. I., you still have to do the hard work, I'm sorry. If you want to be a healthy person, you've got to eat right and exercise. There's no ozempic shortcut to data management.

‍

[00:26:53] Scott Taylor: But if you look at, it didn't take long for A. I. to take over the space and for people to start to go, oh, well, wait a minute, what? What about the training corpus? What about AI governance? And you go back before that, when everybody jumped into e commerce during COVID and they're like, okay, this is the way we can do business.

‍

[00:27:11] Scott Taylor: Then they realized their product reference data wasn't any good. And you go before that and it was data science was the big thing. And then suddenly people were talking about how, well, 80 percent of our time as data scientists has spent munging and wrangling data and. Probably the other 20 percent is complaining about munging and wrangling data.

‍

[00:27:28] Scott Taylor: You go back to enterprise systems being implemented way back and when ERP and CRM came out, that's when terminology like silos and harmonizing legacy data started to get into the vernacular. let's go all the way back, I don't know, 1800s, 1700s, to General Ledger, you still need a chart of accounts.

‍

[00:27:51] Scott Taylor: So if people think that there's a new story, I think through that litany, I've kind of proven from Gen. A. I. all the way back to Gen. Ledger, it's still the, it's still the same story. Which is, if the data isn't right, The thing you are most attracted to that's going to be the breakthrough for your business isn't going to work.

‍

[00:28:11] Scott Taylor: So how do we pound through that message again? I tell the same story. I've been telling the same story for 30 years, just trying to figure out new ways to articulate it and When Gen. A. I. came out, I'm not a trends guy. What I do is sit and watch the latest trend and find the master data, reference data, metadata, data management hooked to it because it's always there.

‍

[00:28:32] Scott Taylor: It's always there.

‍

[00:28:33] Anthony Deighton: So, so one thing I think that makes Gen. A. I. different is the potential for,for these challenges to sort of explode. In other words, it's one thing if you don't have a handle in your data and let's say you want to send marketing emails to use a simple example, you will, if you're, if a human is sending the message relatively quickly, they're going to figure out, you know, there's a mistake.

‍

[00:28:57] Anthony Deighton: Here's a problem here. we need to go back. to use your, you know, and look at the data. The challenge with Gen. A. I. is that it can sort of, scale mistakes. Like, all of a sudden, little errors can become exploded into these big outcomes, because the,the Gen. A. I., can do things at scale, at speed. And so it has the potential.

‍

[00:29:17] Anthony Deighton: We see this a little bit in the more consumer examples when you've seen these funny stories on the internet about J. A. I., hallucinating and saying, funny things. It's not hallucinating in the broad sense of that word. It's taking some bad data that are found on the internet and it's using that because it seems relevant to the topic at hand.

‍

[00:29:34] Anthony Deighton: And again, that's Possible in the enterprise as well. So, I don't know if you would agree with the idea that the impact of these shifts can be, heightened with Gen. A. I. because it allows us to scale mistakes or, you know, with ferocity. Is that fair?

‍

[00:29:50] Scott Taylor: It definitely can make things go really bad way that we never even imagined, also really,really well, but it can because of its ability to scale and just deliver things so quickly. yes. So it's incumbent on us even more so to make sure we have the foundation, we have the structured data, we have the Terminology and the governed content to distribute through all our,our enterprise systems that people can rely on that has the truth and the trust.

‍

[00:30:20] Scott Taylor: And when I say truth, by the way, people get a little bit, you know, a little bit,nervous around that topic or edgy about it. It's like, I'm not talking about politics. I'm not talking about your personal truth or your life, but in business, I'm talking about business and in a business you can. You can determine the truth.

‍

[00:30:34] Scott Taylor: You can establish a truth and a standard, if you just want to call it that, for your business and for the business partners that you work with. It is possible. There's lots of examples of it across different organizations and different marketplaces. And it's of critical importance if you are an enterprise and want to continue to scale and bring value to relationships through your brands.

‍

[00:30:58] Anthony Deighton: Yeah, I have an even less controversial word that I use besides truth. I talk about it as nouns in the enterprise.

‍

[00:31:05] Anthony Deighton: So,

‍

[00:31:06] Anthony Deighton: the common challenge, in all of these systems is we,we have these, Nouns. We have these things, these, would say, technically, we would say, entities that exist in the enterprise, and these Gen.

‍

[00:31:18] Anthony Deighton: A. I. systems don't know anything about those, unless it's available on the data set they've been trading on, which is typically public Internet data. They don't know about your customers. They don't know about your products, again, to the extent that they've been published on the internet, great. Maybe they have some training data on that, but they don't know what you know about the nouns in your enterprise. And that's a, I think both a challenge, but also a massive opportunity.

‍

[00:31:44] Scott Taylor: the nouns of the business. That's another classic way to describe it. any way that works for, anyway, anything that breaks through and a point to your listeners, there isn't one way. And to build on what you said about just understanding your audience. You need a variety of different ways to explain this depending on what your audience is and what,what's the best way, the one that breaks through to that audience in that particular time.

‍

[00:32:07] Scott Taylor: That's the best way for that moment.

‍

[00:32:08] Anthony Deighton: we've made a full circle because we started with the vocabulary, the first V and now we're back on nouns. And I think that's uh, nice way to frame it. Well, I think we are, running out of time, but I wanted to give you the last word. there's been a lot of very practical and thoughtful advice for listeners on how to connect the data work we do with business value, arguably the most important thing we work on is, helping to sort of justify these investments in business outcomes. But any. Parting wisdom, if you had one thing to, you know, make sure our listeners left with, or, you know, like, what, what, what do you want to leave folks with?

‍

[00:32:48] Scott Taylor: Other than follow me on LinkedIn and buy my book, Telling Your Data Story,Data Story Telling for Data Management, which is actually a book about how to sell MDM in your organization. It is, and people ask me, data science students come up to me at events and they're like, what advice do you have for me?

‍

[00:33:03] Scott Taylor: And I give the same advice to everybody. Learn how to tell a story. You already know how to do it. You come home after a rough day or a fun weekend. How do you describe that to your family? That's telling a story. So don't be scared of the concept when it's put into a business context. Get better at it.

‍

[00:33:22] Scott Taylor: Get better at the techniques. Get better at standing up in front of a bunch of people you don't know and asking them for money. when you do your presentation in front of the board, don't make that the first time you've done it. And I'm, you'd be surprised and it's unfortunate how many times that is the first time.

‍

[00:33:37] Scott Taylor: Oh, I don't need to rehearse. I don't need, you know what? I rehearse all the time and I'm a professional speaker. So getting better at telling stories is going to help you accelerate your career and meet the kind of goals you're looking for both personally and professionally.

‍

[00:33:52] Anthony Deighton: I mean, that is, really sound advice. And also as somebody who's done a lot of presentations in front of many different types of audiences, I can assure you I've done Many more presentations in front of a mirror.

‍

[00:34:03] Anthony Deighton: Uh, and that's, uh,definitely a good advice. Scott, thank you very much for joining us, and absolutely everyone should run out onto Amazon, and buy the book.

‍

[00:34:12] Anthony Deighton: There's

‍

[00:34:13] Scott Taylor: Thank you, Anthony. It's been a pleasure. Thanks so much for having me.

‍

[00:34:15]

‍

‍