Welcome everybody to the first installment of the CDO Matters podcast. My name is Malcolm Hawker. I’m a former Gartner analyst, and I am a former vendor, consultant, senior leader in the data management space with over twenty five years of experience. The last few years, I’ve spoken with literally hundreds of companies, about their challenges related to data management.

And it’s what really kind of led to this podcast, which is this notion that there are a lot of very, very old problems out there around data management, but not very many new solutions to them. Right? There is best practices. There are data strategies.

There are best, you know, recommendations, and all those things are really, really important. But what we’ve seen in the market and what I’ve seen in the market is a lot of the same old, same old when when it comes to recommendations and the things that the data leaders should be doing to improve their data in the states. And on the CDO matters podcast, what we wanna focus on is a new and innovative ways of solving some of those old problems. So if you’ve come to this podcast to to to hear some finger waving about how you need to improve your data quality or how you need to focus on being more business driven, this probably isn’t the best podcast for you.

But if you’ve come for insights around new ways, innovative ways, potentially even irreverent, maybe entertaining ways of solving some of those old problems, then you’re in the right place. And that is exactly why as guest number one, we are talking to this gentleman right here, mister Scott Taylor, the none other than the data whisperer, who, in my opinion, is the master storyteller in the place, but is a great first guest to have because of your different way of focusing on solving old problems.

Thank you, old friend. It’s great to see you.

Malcolm, I’m glad to be here. Always, always good to see you. Another reality check, you know, CDOs and MDM, if you’re a chief digital officer looking for mobile device management, you’re also in the wrong place.

Yeah. Also in the wrong place. Yeah. Yeah.

It’s a good example of the terminology problem we deal with in the space.

Yeah. Indeed. So a little bit of a of a history in the the go back machine here. Scott and I go back, what, like, four or five years?

Probably probably longer at this point.

Probably a little bit longer at this point.

It feels that way.

Yeah. And and and Scott and I were kind of like Sonny and Cher.

May maybe maybe Simon and Garfunkel?

Simon and Garfunkel potentially.

Like a Yeah.

A a duo. Back. Yeah.

We were definitely a duo.

Yeah. We were a duo at a pre at a previous company, and our job was to literally travel the world and to spread kind of the data evangelism of the value of, third party reference data in this case. But it was really about the value of better ways of managing your data.

Yeah. It was foundational stuff around making sure all those piece parts in all those core domains were as strong as they needed to be to enable the rest of the business and reinforcing that with some very basic principles that I think were universal.

By the time we were done Right.

We definitely validated the fact that no matter what kind of company it was, no matter what country it was, and we had the plenty of them across many different continents. Right. These challenges at the enterprise data management were, if not identical, they were more the same than they were different.

Right. Right. And that’s one of the things that that that that I carried forward into future roles, particularly in my role with with Gartner was was understanding that a lot of these problems are the same. But, again, what I was seeing was a lot of the same old solutions for the problems and and people still struggling with using the same old solutions.

Right? The same old you thou shalt do this. And the thing that I kind of love the most working with you is is is that every day, I would learn a slightly different perspective, a different term, a different nugget that was actionable in a way that was never previously actionable for me as a data leader coming into my previous position. So I learned the importance of consistency of message.

I learned the importance of having a message in a way that resonates with business leaders. But I’m I’m putting words in your mouth in your in your mouth. What are the things that think that that that lead you to be successful?

It was that. It was, you know, being able you know, I’m a think I’m a natural storyteller. Yeah. It was really trying to draw on that storytelling aspect of the data space the part of the data space that we’re in, you know, ended up out of all those travels really validating and honing down a core set of messages that I codified in the book that I ended up writing as my COVID project, Telling a Data Story. Data storytelling for data management, ninety nine percent buzzword free.

I didn’t wanna overpromise, so you gotta make sure, I think one buzzword in there. Maybe end up in there somewhere.

Yeah. But this idea that you had to be able to create a compelling narrative that the business would understand so they could really support and literally fund the work that was so important in the data management space.

Right. Right.

So if I’m a CDO and I am trying to get a senior business leader to, fund my initiative or to support the things that I’m doing, what are the two or three things that you would recommend to that person to focus on?

You know, I’ll start with some of the stuff you don’t wanna do. Don’t start with how you’re gonna do it. Don’t start with your technical implementation. Don’t start with here’s our new set of software or data mesh or data fabric, whatever that’s gonna be.

Don’t start with all these kind of buzzword, you know, data bubble things that we tend to be really proud of in the data space Right. Because it’s how we did it. Start with the why. So start with why managing data is of strategic importance to your enterprise.

Yep. Understand that to your core before you even go in and waste the time with the business side, which means as a data leader, you need to understand your business, understand what your business does, why it’s important, the kind of players you deal with, the market you’re in, the dynamics of your category, the way you distribute your product, the kind of customer base you deal with, the all these different piece parts that make up the rest of the business and get fluent in that so then you can apply where data will help.

And those day those those business problems, we know that many of them can be solved by just plain old having better data put in the right place. But wrapping that up in a narrative, wrapping that up in more of a formal storyline, literally, if you’re looking for funding, it’s gonna be a pitch. Yep. You’re gonna go in to try and convince somebody the benefits of what you have to offer.

That close is gonna be we need to fund this. Right? And we need stakeholder commitment, and we need to get the, you know, the business rack and file to change the way they operate around some things so we make sure we have better data and it’s protected and so on. But you gotta be able to put all that stuff together in a really kind of pithy, snappy, impressive sounding, compelling narrative because you’re competing with everybody else.

Right. You’re competing with marketing who’s looking for money too, and they know how to tell a story. You compete with sales who’s looking for funding, and believe me, they know how to tell a story. Right?

You compete with finance who already has everybody’s backup and goes, no. That’s not worth it Yeah. By the way they look at things.

So you’ve gotta touch on where your business is going.

Listen to your own business stories, the way your your leadership and map that, connect that to the value you’re gonna bring out of data management.

Right. So that’s a don’t rely on buzzwords.

Right. I didn’t answer your question. So what should you do? Right. So right.

Right.

So I I I think a simple way to think about it is is is this framework that I came up with called the three v’s of data storytelling, a little bit of play on the three v’s of big data, but it’s vocabulary, voice, and vision. So vocabulary, you wanna get the nomenclature right. The terminology you use is really important. Use business oriented words. Use the words that everybody else in the organization will already understand.

Articulate it in a way that that that literally makes sense. You wanna harmonize that that story to a common voice. Harmony doesn’t mean everybody sings the same notes, but it does mean they sound good together. So you all have in your data department, if you wanna call it that, a common understanding and a and a similar way to describe the value and and the initiative.

And then you wanna point it at your business vision. Again, how does this work enable the the strategic intentions of your enterprise? Where is your business trying to go? And why does managing data help it get there?

That’s different than, you know, what’s your data vision. Right? Right? Or your data strategy. It’s the business strategy.

And you can get a lot of those clues if you’re looking for where to find that out. Look at your annual report. Listen to what your leaders say. Live your public company.

Look at your investor day presentation. That’s one of my favorite places to go to look at what the visionary aspects of a company is about. Because, you know, you got your business leaders in game day uniform all set up and say, here’s where we’re gonna go. Like Yep.

Nowhere in there are they ever gonna say, and one of the big initiatives in this company is better data quality. It’s not gonna happen.

But having better data is gonna enable those things, and it’s your job as a data leader to to connect those dots.

Gotta connect those data dots.

So a lot of this has to do with storytelling, quite obviously. Do you think that storytellers are born, or can they be made?

I think everybody’s a born storyteller. I think everybody can tell some form of story.

They’ve got to. Right? To be human, to be successful in business no matter what. You’ve gotta be able to convince somebody the benefits they have to offer, articulate some kind of need, express, what happened as an anecdote. We all know how to tell stories. Yep.

So I think everybody’s a born storyteller in there somewhere. Everybody I like to say everybody’s got a story to tell. Yep.

You’ve gotta hone it, though. There’s a lot of craftsmanship.

It’s not all art. There’s some science in there around the craft of storytelling. Yep. It’s different than just sharing an anecdote off, you know, across the kitchen table with the rest of your family. You’re gonna be standing up in front of your board. You’re gonna be up and, you know, in front of the whole sales team who’s wondering why they’re even spending time with you. So you’ve gotta learn that craft.

You know, as part of my background, you know, certainly collegially, I spent a lot of time in dramatic arts. I learned a lot of things in that discipline that I pull on still every day. Yeah. And and, you know, knowing sight lines, knowing how to use your voice, knowing timing, understanding some form of stagecraft.

All those things help. You don’t have to go off and be an actor, but you should have some understanding of the basic disciplines of storytelling.

There’s a few other things that really jump out to me. So I I I know Scott to be one of the best, if not the best storyteller that that I’ve I’ve ever met. And I’ve listened to his story many times. And as a matter of fact, I I can recall in my sleep, hearing some of his stories be over be be be be played over and over again.

Have to sit through them all every time.

Yes. Yes.

He he has a grandfather that spent time in Texas.

I know about that. I I yeah. I I I know plenty of the stories.

But there’s a few things here that go beyond just the script and the act and the stagecraft, and you’ve got it. And and I think that these are lessons here for CDOs as well.

One of them is vulnerability.

And and I’ve heard you say over and over, you know, I’m not a data manager. Right? I’m not a data engineer. I I couldn’t I can’t I don’t know how to build a data model, although you probably could.

But that makes you vulnerable. Right? So if you’re in front of a large group, particularly of technology, folks who say, you know, here are the things that I can’t do, but I do know that twenty versions of seven eleven is a bad thing. Right? So vulnerability is one thing that that you didn’t say, but I will say on your behalf is there. Another thing that is really, really important that that you ooze is authenticity.

Right? You you you you are you.

I walked away every time I heard you speak. And at the beginning wondering, wait a minute. Is that the same guy off the stage as he is on the stage? And the answer is yes.

Yes. He’s the same guy. Right? Yes. He’s the finger puppet guy. He’s the guy the the the telling bed bedtime bedtime story guy.

But there’s an authenticity there that is palpable with you. And I think that those two things are kind of being vulnerable and being authentic and lastly, being passionate. Right? You actually believe the things you’re saying.

This is not just a script that that you’re delivering as a part of an act, but you actually believe these things. So I would layer those things on as well. Mhmm.

And that’s I would say, if you asked me, you didn’t, but I’m telling you, the keys to your success. So how do you react to some of the things I decide?

As as usual, you know me really well, Malcolm. So having traveled the world with you, we got to know each other pretty well. But that passion part, I’d even start with. You’ve got people feel that.

They understand that. Nobody’s gonna get have this sort of Taylor’s law of energy. Nobody’s gonna get more excited about something that you talk about than you. Right.

So you’ve gotta come in there with that passion and that energy that says this is important. Now you gotta modulate it based on your your your audience. You don’t wanna be too over the top and, you know but but if you come in and go, yeah. We should do this thing with the data.

It’s like, who cares?

Right.

If you don’t care, I don’t care.

Right. And you and and and I’ve worked with CEOs who look for that. Right? They how much does how much does this person even care about this?

You know, I I work for a CEO who told me, I always say no the first time. And I wondered, well, why you give why you’re he’s like, because I wanna see how you’re gonna come back. Are you gonna come back and fight for it? Are you really believing it even if I think it’s a good idea?

And, again, I was pleased that he, you know, told me his secret move there because I’d always come back a second.

Right.

But, you know, they’re not playing tricks with you, but they are looking for that. And you are competing with a lot of different initiatives at an organization, and you’ve gotta be able to stand out. Plus, as a leader, you’ve gotta be able to inspire your own team to realize the importance of what they do. And that’s not always easy if you’re, you know, a lowly data steward out there just, you know, unduplicating Right. You know, a bunch of, data data records in a queue.

Why is this important to the rest of the organization? Why am I even doing this? So you’ve you know, it plays on both sides. But that’s what part of what leaders do is they help inspire folks to do, you know, go beyond. And that comes from a passion, that comes from authenticity, that comes from showing your vulnerability, that comes from empathy and all those other, you know, those are all pretty soft skills Right. If you ask me.

So Yeah.

No. They’re incredibly soft skills, but but at the same time, difficult to hone. But what I’m hearing you say is they can most certainly be learned. They’re all there. We are all, you know, making drawings on the cave wall as it were, and we’re all capable of that, but it’s a skill that you can hone, and and nobody to nobody better to learn from, than than right here. What about the notion of data culture?

Right? What what what what do you think when you hear people say, well, we we need to change our our our culture to be more data driven?

I think it’s I think it’s probably true. I just wonder how well that plays to the business side. So you’ve got, again, you’ve got a bunch of folks coming in and saying this is what we need to do to help the organization make it better, and they’re from marketing and sales and finance and and, you know, operations.

And then you have data people coming in and say, we have to change the culture. I just think that that’s too much to bite off.

Right.

Can’t you just, you know, fix the quarterly reports?

Right.

Do we have to change the code?

Do we have to change our whole being in the way we work? You know, yes and no. But listen to what that sounds like.

That sounds like an awfully big Right.

Thing to do. Right. So I just feel like a lot of the terms we use you know, one of my basic premises is that one of the biggest things holding back the data space in general is the way we talk about it.

The terms we use, the attitude we take, the the the, you know, the constant need to come up with the latest buzz you know, all these other things just inhibit the real value we would bring.

Right.

And there isn’t another group you know, on the flip side, there’s not another group in an organization that can bring value to every other part of the company. Right. You know, data can help financing, can help sales, can help operation. You know, horizontally, tell me another part of the company that can literally help every part of the the the rest of the company. And, you know, if you’ve got good at MDM, you can do it with the same record.

Right.

So there there there’s a lot of value we can bring. We just gotta check, you know, again, you know, work on the delivery.

Why do you why do you think that is why do you think that there is a lot of dogma out there? Why do you think that there is a lot of what I see online and and what I see in a lot of the kind of the the the pundits, exchanging views is is a lot of, you know, what don’t you get business people? Right? Data quality is important. What what what don’t you get? Right? And and and and a lot of, you know, what what I, you know, would call kind of a little bit of finger waving, that’s not resonating.

It it’s most certainly not resonating. And and if and if I’m being told I need to change the culture and the the what what don’t you get about data management? What don’t you understand about how data how important data is? If I’m if I’m managing a supply chain or if I’m selling something, well, that doesn’t really resonate with me. So, obviously, making the message resonate with with business leaders is key to what you’re saying here without without a doubt.

Yeah. Yeah. Okay. It’s it’s got a breakthrough in their language. You know? In some cases, it’s gonna be foreign to them.

It’s gonna be new. It’s scary a little bit, but I just feel like there’s there there there’s gotta be a better place to to deliver in a better way to to talk about this that we get more action from from the folks that we know we can help.

Right.

So we know that they’re in pain. That’s the other side. We know they’re in pain. Right? Because people are in pain. There’s problems everywhere. Every organization’s got a ton of issues in all those different departments that we all know data can help and data can fix and data can change the nature of an organization.

How do we get that message across in a way that’s palatable and and allows people to believe in this?

Right.

And we’ve been spending an awful long time on this.

Right?

This is the integration of this, and it’s gonna be dead.

Y two k, and now we need a data mesh. I mean, we just, like, cycle not that those two things are connected. But, you know, cycling through all this hyperbole, there’s gotta be some cynicism on the business side. There’s gotta be some weariness. There’s gotta be some, like, really the latest greatest thing again this week?

What about the thing from last week that you said was gonna, you know Right.

The revolution the the next big data. Right? Yeah. Whatever it is. Yeah. Whatever the next whatever.

The next data mesh data fabric. Right.

Analytics, GraphHub, fabric mesh, hybrid cloud implementation.

Hey. You said no buzzwords. You said no buzzwords.

That’s what we sound like.

Yeah. Yeah.

That’s what we sound. SQL, no SQL. Right?

It’s just like Right.

Right. Or a graph or or or no graph or a AI and ML. Right? I I I see a lot of that going on with AI and ML. I see a lot of that going on with data mesh and data fabric. It is like, well, if if we just do these things, it’s gonna solve the problem.

Right? And don’t get me wrong. Right? Having fantastic, very smart robots that can help automate things or make things run faster, that’s probably pretty good. But there’s certainly by no means a silver bullet. And any time that that we lean towards silver bullet, I think that we discredit ourselves. Do you agree?

Yeah. I absolutely agree. Absolutely agree. That just because there is no magic sort of silver bullets.

It’s working out. Okay? It’s you know, if you wanna be a good cook, you gotta have good ingredients. You gotta know how to cook. You don’t, you know, you don’t just buy the new ninja foodie.

Plug it in, set it, and forget it.

Right.

That’s how I think some of this stuff is presented.

It’s one of the best metaphors that you’ve you’ve ever given to me was this notion of data as fuel.

Right? Data as an ingredient and not the output. Yeah. Right? This this is why I don’t have much of a problem with people saying let’s be data driven.

Like, okay, if that’s what it takes or let’s be data fueled. Oh, okay. If that’s if that’s what it takes. But if if to to shift to this mindset of data as an ingredient and data as fuel and not the exhaust, that’s part of the mindset.

That’s part of the culture shift that can happen slowly over time. But another thing that you’re incredibly good at, that I’ve seen over the last that I saw when I knew you and was working with you, that I’ve seen over the last few years is is consistency and message.

Right? It is it is it is just boom.

You just gotta boil it down.

Boil it. Boil it. Boil it. Boil it down. And for me, you know, I’m I’m proud of after after years of this, I boiled down my entire data philosophy to three words. I couldn’t get it less than three words.

Truth before meaning. Determine the truth in your data before you derive meaning.

Determining that truth comes from data management, data governance, data stewardship, MDM, RDM, PIM, DAM, you know, all those foundational piece parts before you derive meaning through business intelligence, analytics, data science, all the things that tend to get the most attention, the most disproportionate amount of of of heat and funding and the rest of it.

But it’s not chicken or egg here. It is egg and omelet. You gotta have truth first before you do you know, get to the meaning. And we spend a lot of time on the meaning side.

Right. And the how.

And and the how. And, you know, make sure you people understand and can articulate that why before you get to the how. Because there isn’t a business leader out there who’s gonna fund your how until they understand the why. Yep.

They believe that why. Yep. So these principles go against a lot of the natural inclinations of many folks in the data space, which are, let me show you that you know, here’s data visualization is much cooler than data government, you know, data stewardship. And let me show you my latest, you know, master data model schematic, whatever it happens to be, and the latest implementation plan when people don’t even know why you’re doing it yet.

Right. Right. One of the hardest lessons I ever learned as a data leader is nobody cares about data quality.

Nobody cares about data quality. That’s kind of a hard a hard fact now. Is it important? Of course, it’s important.

But is your CEO a clinical. Yeah. Is your CEO going to fund a two million dollar initiative in order to to fix duplicate records? Well, maybe if you’re a banker or if you’re an insurance company potentially. But, is it gonna be something that will shift your data culture, a message around, you know, dupe unduplicating your data? No. Of course not.

So They’ll ask why. They’ll say, okay. Why? Right. So you gotta come in with that why. Why is having us, you know, an unduplicated validated customer master critical to the future of this company and all of the customer oriented initiatives we have Yep. That they will articulate all day long as part of the, you know, their their presentation or their the the business strategy.

Connect those dots. As I said, make sure you’ve you’ve got that connection and can articulate that in a really business accessible way.

Yep. So a lot’s changed over the last couple of years without a doubt. Goes without saying.

Are there any reasons to give you optimism about the data management space? Are there any reasons to walk out of the last two years and say, hey. We’ve got a lot to look forward to because of what I’ve seen.

I mean, I’m a naturally optimistic guy. I say I’m a I’m like a empty glass is gonna be full someday kinda guy. So that’s that’s where I am. But I think and I think you’ve you’ve experienced this too that COVID and a lot of the issues that people went through kind of was a shock to the system for a lot of organizations when they realized, oh, we gotta go into ecommerce, but our product data sucks.

We don’t even have it, or we don’t have the attributes. We don’t have the the the, product images in the right place, and the right tags, and all these other things that we’ve been preaching forever. They realize, well, this is really important now. We gotta have it.

If otherwise, we you know, we’re not gonna be able to proceed as a business.

So I feel like I hope that the the enterprise space has had some recognition of the long term systemic value of a lot of these principles we’ve talked about. Right. And there’s a lot of things that I think people recognize aren’t going back. Right? You know, you know, QR codes in restaurants, they’re not going away. Right.

A a lot of these other things that people, you know, teledoc kind of, you know, telemedicine is not going away. It’s like, oh, this was a lot easier. Why don’t we think of this beforehand? And we did it because we had to do it. All that takes to have all that, it takes really well governed, expertly stewarded, strategically reinforced, you know, master data, reference data, metadata. You gotta have it.

Yep. Yep. We certainly I certainly saw that, in my last position, right, when when the pandemic struck and there was a massive disruption.

And business leaders said, okay. We can’t go this way, the way we’ve always gone. We need to go this way. And they turned the wheel of the ship, and the ship kept going the other way.

Oops. Right. And then a lot of senior leaders figured out very quick. Wait a minute.

It’s the fuel. Right? It’s the data. Right? It’s we don’t have the right fuel to get us from where we are to where we need to be.

We need to double down on our product data, on our customer data.

And that’s what gives me actually a lot of optimism going forward even in potentially, in any form of upcoming recession because in the last small one we had in twenty twenty, companies actually ran to data management. They didn’t run away from it. They ran to it because they very quickly had to figure out ways that they could turn the ship and that they couldn’t turn their ship without having that data fuel that we were talking about.

You know, I I, again, I think data management can help change the nature of a business. It’s that important.

It’s got that foundational horizontal value that, you know, give me another business discipline that can do that.

Indeed. Well, on that note, great place to end. Thank you so much, my friend. Always appreciate it.

Mouthful. Thank you. Thank you. You.

And, thanks for having me.

Me. Thank you. And thanks for everybody for listening, and I look forward to seeing you again on another episode of CDO Matters sometimes very soon. Thanks.