Good morning. Good afternoon. Good evening. Good whatever time it is wherever you are in our amazing Earth. Welcome to the one hundredth episode of the Studio Matters podcast.

One hundred. One one one hundred. And and and we are celebrating two hundred. We are Okay. We’re celebrating.

Like, you’re say saying something to me horrible inside. There’s there’s something about stop. Please stop. Stop. Stop.

We’re celebrating our one hundredth episode by by bringing some of our returning champions back. Right? These these these are the returning champions of the CDL Matters podcast. Scott Taylor, the data whisperer, thank you for joining, my friend.

Scott was with us. You were number one. You were episode number one, and you were episode number fifty, and now you’re on one hundred. Just saying.

Speaker 2

And just a little bit of trivia. I was also episode zero.

Speaker 1

Oh, that’s true.

So What do you mean by episode zero? So fun fact fun fact. Fun fun thank you for reminding thank you for reminding my my my friend.

So we were at a we were at

Speaker 2

souvenir from that day.

Speaker 1

That’s right.

We were at a we were at an event that I don’t think exists anymore. I don’t know if that event exists anymore, but but Scott and I were both at a conference that was being held in the TWA hotel that is that is this old hotel that is adjacent to JFK Airport in New York that used to be, like, an old terminal. Right, Scott?

Like, was

Speaker 2

the t it was the TWA terminal in its day, and it was glorious.

Yeah.

Speaker 1

And if you ever get an opportunity to go there, you you should. Anyway, to make a long story short, Scott, I think you were, like, on the end of a long tour. You had you had but, like, you were tired.

Speaker 2

We were coming out of COVID, and I was we were all sick with not COVID, but other colds, and it was, like, a

Speaker 3

early COVID.

Speaker 2

Yeah. We’ll get you in the other yes. Soon. In the second half hour.

Speaker 1

Yes. We we we Yeah. We will.

Speaker 4

And and yeah. I’ll come back later.

Speaker 1

Yeah. Hold on. Hold on. This is a good story.

Speaker 2

Hundred one.

You’re invited to the

Speaker 1

hundred first.

Is good story. So so I’m all fired up. I’m gonna do a podcast. Right? And I’m like, hey.

Podcast. I went and bought, like, expensive DSLR and all the sound equipment and and just, like, lav mics and and everything. And and I found this conference room that was separate away from the conference, and it was nice and quiet. And I set up everything and lighting and in my expensive camera, and I’ve got Scott Tale, the data whisperer with eight billion followers on LinkedIn.

And I was like, this is gonna be the greatest thing ever.

And and and Scott was like, I don’t feel well. Right? But I’ll do it for you.

Do a solid Good

Speaker 2

for you, Malcolm.

Speaker 1

Yeah. Exactly right. Do and and we we go through. We have an amazing about fifty, fifty five minute podcast, and I didn’t hit record.

Speaker 3

It didn’t hit record.

Speaker 1

I didn’t hit record. Didn’t hit record.

And I’m like

Speaker 4

Oh my god.

Speaker 1

Oh my god. We can yeah. There’s nothing. There’s there’s nothing there.

Speaker 4

Lesson quickly, didn’t you?

Speaker 1

Yeah. Yeah. So that was episode zero.

Speaker 2

Episode zero.

Speaker 4

Yeah. And as in the ether somewhere.

Speaker 2

It was like just Yeah. Hold it out. Yeah. Did I say this already? That’s all we kept thinking the whole time.

Did we say this already, or did

Speaker 1

we

Speaker 2

not say this yet again?

Speaker 1

So that was that was episode zero. So so yes.

Speaker 2

I learned a very important lesson that day. You know what that lesson is?

Speaker 1

Don’t do podcast with me?

Speaker 2

First podcast. Never do somebody’s first podcast.

Speaker 3

Never do what? Somebody’s first podcast.

Speaker 4

Oh, first podcast. Okay. That’s true.

Speaker 1

Yeah. Yeah. So so thank you for joining on this year fourth, technically, your fourth CDO matters podcast, Scott. Of course, we are also joined by my friend Samir Sharma joining from London today. Samir, how are you? Hello.

Speaker 4

I’m very good. Thank you. All the benefit seeing the three of you, specifically Juan with his honest honest no BS t shirt and my man in in Florida or Miami or wherever you are in his are you in a turtleneck?

Speaker 1

Oh, Scott. You’re talking to me?

Speaker 2

Scott. I’m in a mock turtleneck.

Speaker 3

Are you

Speaker 4

in a mock turtleneck?

Was thinking

Speaker 2

Mock turtleneck is the latest thing. I’m actually in Blackrock, Connecticut at the day of whisper Oh,

Speaker 4

you’re in Connecticut.

Oh, okay. Yeah. Sorry. Sorry.

Speaker 1

You’re in

Speaker 4

Back home.

Because you you flip between the two, don’t you?

Speaker 2

I got my we’re snowbirds, so we, like yeah. We go to Florida.

We also go to Antigua, which is

Speaker 4

Yes.

Which I lovely. Yes. Yes.

Speaker 2

But it’s it’s April, so we’re back.

Speaker 1

Because I’m to be Samir is is is is celebrating his recent run off Broadway as Off off off off off off off Broadway. It’s not it’s off Broadway. It’s off Broadway. It’s not Broadway, so that means it’s off broad off Broadway.

Speaker 3

Being honest, it’s true. But Yes. Yes.

Speaker 1

And and his his appearance is Colonel Mustard in the recent production of Clue off Broadway. So Yes. Have have you have you seen any of the trades, Samir? Have you seen any of the reviews of your show? Two thumbs up?

Speaker 4

Absolutely unbelievable. Very good reviews. Everybody’s come out singing, dancing.

It wasn’t a musical, and, they have, you know, rave reviews. They want us back, and, we’re gonna see if we we are gonna put some more shows on.

Speaker 1

Ab absolutely brilliant.

And, of

Speaker 2

course, it was a compelling condiment, which I thought was a was a compliment.

Speaker 1

Compelling condiment. Condiment. I laughed. I cried. It was the stand up and feel good rendition of Clue.

And, of course, joining us from the greatest city in the world, the a the ATX the the ATX, keeping it keeping it weird in in Austin, Texas is my friend Juan Cicada. Hi, Juan. Welcome.

Hello.

Speaker 2

Hook them.

Speaker 3

Hook them. Yes. How are you doing, Malcolm? It is a pleasure to be here in hundred episodes.

Speaker 1

Right. Yeah. I can’t believe it. You are a Longhorn. Right? You went to UT for your PhD, did you not?

Speaker 3

I did my undergrad and my PhD. My wife did her master’s and her PhD here, so we’re a full Longhorn household.

Speaker 1

So you’re still working your way through your student loans is what you’re saying?

Speaker 3

Luckily, no. Excellent.

Speaker 4

Can you can you provide me with some understanding of Longhorn?

Speaker 3

Oh, that’s the mascot for the University of Texas at Austin.

Speaker 4

Oh, I see. Okay. Long horns.

Speaker 3

Alright. Long horns.

They they’re technically

Speaker 1

a a breed of Spanish cow that, can survive in the insane Texas heat.

So that’s why they’re a Texas icon. They imported these Spanish cows that could deal with the heat, but they’re not very good for meat, and they’re not very good for milk. They look great on t shirts.

Speaker 4

What was the point of that then?

Speaker 3

Have great on t shirts.

Speaker 2

It’s just a mascot.

Speaker 4

Okay. Alright. Mascots are in this year, aren’t they, apparently, in America?

Speaker 1

What’s the other what’s I I missed it. Are they I don’t know. They’re always in.

Speaker 4

I don’t know. Oh, I guess so.

I

Speaker 1

just Wait.

Hey. Listen. Hey. Hey. In terms judging mascots, I’m not so sure you’re in the right position there. Like, what the hell’s a hot spur? What’s a hot spur?

Speaker 4

Oh, stop it. No. Stop it.

You went there. Talk about that. No. I was talking about mascots because I said they’re in in America.

Because on my feeds, on every single feed, whether what social media feed, I get all of this stuff about, you know, mascots and how they go around with big bags of popcorn and, you know, throwing them on everybody and It’s

Speaker 3

It’s god’s face.

I don’t know what the heck you’re talking about.

Speaker 4

I don’t know either, but I get When

Speaker 2

are we getting to the part of the show about data?

Speaker 3

I’m just looking there. I’m like I’m like, we’re serving data.

I’m like,

Speaker 2

people are like, are we actually live?

Are we really live?

Speaker 3

We are live. Yes.

Speaker 1

Well, not live. We’re we’re recording. Last five hours.

Speaker 2

Oh, okay.

Speaker 3

Well, I’ll

Speaker 1

do that.

We’re we’re this is recorded. I mean, if we need to edit this bit about my mascots, I don’t know why we would, though.

And I I don’t know where these these popcorn throwing mascots are in the US, but it they yeah.

Yeah.

Weird songs

Speaker 4

in the country, apparently.

Okay. Yeah.

Speaker 2

What we’re do I’ve got the I’ve got the other prophecy mascot here.

Speaker 4

Oh, should you be showing that?

Speaker 1

That’s okay. They’re they’re reasonably adjacent.

I mean, they don’t do MDM, but they’re they’re definitely in our space, which which can create some

Speaker 4

The men in black.

Speaker 2

I got my prophecy swag glasses.

Speaker 1

Oh, it’s oh. This is your fake prop oh, those are the real prophecy swag glasses.

Speaker 4

How come we don’t get any of those? Do do we get some of those?

If one another

Speaker 2

gets dead records.

Speaker 1

So, let’s talk let’s talk about data. If you’re just tuning in, this is what you see Not helping. Yeah. Exactly.

What what you see is what you get. I don’t know where the the road is gonna take us today, but but all these guys have been on the podcast at least twice. Both of you have been all of you have been on at least twice in the case of Scott three times, I think. I think I’ve had you on one twice.

I’m quite certain that I have. Anyway, you’re one of the greatest parts of my job, and and I and I mean this in all sincerity, one of the greatest parts of my job is I get to meet really, really amazing people.

And the three of you are up there, and always and, Scott, you have been for years and years.

Juan and Samir consider you dear friends. And I’m I’m honored that you’re here, and I’m honored that I get to to learn from you. And I do every time I talk to you. So that’s why we’re here today. That’s why you’re joining me on the one hundredth. I couldn’t think of three better people to do it. Let’s talk about data.

So, Sameer, you’re on your way to Gartner, which is very exciting.

Speaker 4

I am. Yeah. It’s your first time.

Speaker 1

I know. Know. I know. It’s a newbie. So so, Juan, what would you what what advice do you have to give to a first time Gartner attendee? I mean, you’re you’re you’re a KG old vet.

Speaker 4

What would Yeah.

Speaker 1

Yep. What do you say to Samir?

Speaker 3

Okay.

Well, knowing that this is being recorded,

Speaker 4

I have to be careful what I say.

Speaker 3

So I I think there’s the there’s two things. There is what you extract what you hear in the hallway talking to people, talking to as much people, and then you see what’s being presented in the presented. There’s two types of presentation. Right?

There there there’s a pure Gartner presentation, and then there’s customer presentations, which are usually connected because there’s some vendors around that. Right? So I think it’s you can you can triangulate between what you’re hearing on the what you’re hearing on the hallway, what Gartner is saying, and then what the customers connected to connected a little bit to the vendors are. And then you kinda just see those patterns, see see what emerges, see what what’s what aligns.

What’s most interesting is the contradictions. It’s like, no.

Speaker 4

Yeah. Yeah.

Speaker 3

Yeah. People are saying this, and then but these other people are saying this. And then and then then then swing this is when you realize, we don’t even know what we’re talking about.

Speaker 1

Well, Sameer, you a you had made a comment on on LinkedIn, and I actually responded to it.

And and well, you made a comment where you’re like, you’re excited to go see, you know, what’s really happening Yes. In in in the world of data analytics, what’s really happening. And my kind of comment, you know, wary of the Gartner police, my my comment was there’s there’s a lot of capability washing.

Speaker 4

Look. Look.

Speaker 2

A lot.

Speaker 4

I think yeah. I I I’ve got to say at every single conference that we all probably attend, you have to you have to wade through that noise, don’t you?

Have to always filter that out and understand and try and get the real narrative of what’s going on. I think Juan mentioned it in in the response to my post is it’s a little bit like, you know, when when when deals are done at the UN. They’re not done in the chambers. They’re not done in those big conferences.

They’re done in the hallways. Right? That’s where the real stuff gets done. And so I’m assuming that this is very similar, and and that that’s Juan’s point about it.

But, look, you know, you gotta take it with a pinch of salt in terms of I I’m there to to to sort of meet a lot of people. And and, of course, it’s my first time, so everybody talks about this one. They do.

You know? Scott Scott was at the last one in in was it Florida? Orlando?

Speaker 2

Orlando. Yeah.

Speaker 4

Yeah. Yeah. Yeah. And, you know, loads of people were posting about it. I I never get FOMO, but this, I think it’s gonna be interesting just for me to get that firsthand perspective without really you know, without mudding the waters and reading a lot of stuff. So, yes, I will be there. I will be reporting on stuff as well as well.

So you will see posts from me about my take on it, and what is actually happening on the ground. So there will be I I will cut through some of that as well, hopefully.

Hashtag sponsored.

Speaker 1

Scott. Hashtag sponsored. Yes.

Speaker 2

Good for you. Awesome.

Speaker 3

Hashtag sponsored.

Speaker 1

What’s what’s what’s your advice, Scott? What what do you say to the Gardner newbie?

Speaker 2

If you see any good swag, make sure to get on the first day because they run out.

And

Speaker 4

Oh, really?

Okay.

Actually, they’ll give you

Speaker 2

a swag

Speaker 4

bag or

Speaker 2

something like see somebody you wanna take a selfie with, make you know, get that early too because you don’t know when you’re gonna run back into them.

There’s a practical advice to get that content going. Watch the keynotes because those are, like, the funnest, biggest, broadest. Yeah.

They’ve they they narrowed it down this year to one major metaphor, which I think was an improvement because they usually swim they mix all kinds of the in in in the in the in the keynote discussion or the keynote presentation.

Speaker 1

Well, the metaphor was was the raft. The white yes. The white water the white water rafting. And I and I thought it was was kind of effective except and and, Juan, you actually agreed to this when I when I posted this. And it it to me, the the biggest concern and I fully expect that the keynote in London will be the same as it was in Orlando. They typically are, by the way.

Speaker 2

Yeah. Not the same people even. Right?

Speaker 1

No. You’re different people, but the message will be I suspect the message will be the same. And then so the whitewater raft metaphor was, hey. We’re in this raft, and some people are love it, and some people are throwing up in the back.

And it’s okay if you’re one of the people throwing up in the back. Right? And the metaphor was, we’re all on this raft, and we’re it’s it’s crazy, and it’s disruptive, and it’s hectic, and and, of course, the the raft is AI.

And and we’re on the raft and we’re going down the river and we and and it’s all gonna be okay. And and you may be the guy at the front who is happy, or you may be in the guy at the back who’s throwing up, and it’s okay to be either.

But they they actually kind of even went a little bit further and and said that you have a few years to to to get over your your your fear, to get over being the person in the back who is the the AI doomerist or the AI, I don’t wanna do this, or the late adopter, that you’ve got time. They said clearly to me that you’ve got time to figure this out. I don’t think we have time.

Juan, do you think we have time?

Speaker 3

No. This stuff is moving so fast and everything is changing. And, I mean, look at stock prices and every and layoffs and stuff and, like, the like, there is no time. And I I I should go back to we’re talking about they’re talking about ROI, the return on but the word I was not for investment.

It was for

Speaker 2

Yeah.

They they had that rift too. Yeah. What was it? Return on information, return on insight, return on I I played with that too. They added that.

Speaker 3

And I was like, well, where is the end of the day, it’s all about money, man. I mean Yeah.

Speaker 4

Yeah. Yeah. Absolutely.

So Well,

Speaker 2

we’re in business.

Speaker 4

Well, so the funny news How how did they connect that to money, though?

How did they or or did

Speaker 1

they not Was was

Speaker 4

it just giving people insight without what what what was the intention on that?

Speaker 2

This was the I

Speaker 3

mean.

Yeah.

Speaker 1

Wait. What what was the I one? Do you recall what the I was?

Speaker 3

What was intelligence? What was I don’t remember. I honestly don’t remember. Right? Yeah. It was I I just I remember so clearly how they said and I’ve I’ve been bringing this up.

Know I I is fifty percent of the people are doing are doing AI, but they’re be doing AI because they’re being told to do AI by the board. So they have like Fifty percent. Fifty percent. Right?

Fourteen percent said that they felt great on governance and how things are going. But then you said, forty five percent have already done semantic layers this year, and the other forty and another forty five percent will do it next year. I’m like, no. They haven’t.

Well, they no. They they they have done something. Right? So for me, this the the if and interpretation, and this is what I take is, oh, you have to do AI.

Perfect. I’ll do AI. I’m gonna do this chat with the data because that’s AI. I need to have this semantic layer.

I’m gonna go just build a semantic layer, and I got chat with your data. It’s not governed, and and that was a quick thing to go do something. And I’m saying I’m doing AI to keep the board happy because I have a chat with my data. Like, that’s everybody’s doing that.

So that fits that mold. Now is that really transformational? Is that really provided this? No.

That’s just like I’m just slapping something over there.

Speaker 4

So Doing it yeah. Yeah. Keeping up with the genses, really.

Speaker 2

They say fifty percent of the AI budgets are wasted. They just don’t know which fifty which half.

Speaker 1

It’s the Bartima and Bailey. Right?

Isn’t isn’t that isn’t that immense or metaphor in the

Speaker 2

No.

That’s the old average. I know half my advertising budget’s wasted.

Speaker 1

Oh, oh, right. That was, a Deutsch. Wasn’t that a Deutsch? Wrigley. Yeah. Something. I don’t know.

Speaker 2

Wanamaker. It’s credited to all kinds of people who start with w.

They did say it’s the year to double down on foundations. And I’m, like, looking around, like, when wasn’t it?

Speaker 1

Well, exactly. They were saying that four years ago.

Speaker 3

Four years ago? It’s every year for the last twenty years or whatever. Right?

It’s always

Speaker 2

Well, this idea that, you know, data management is back is, like Well we’re we were never gone.

Speaker 3

Well, no. And then and then it’s context, which is, like, which context of the I was just gonna say the same thing. Context and context, which is look. But look.

I I’ll be I’m very lucky that I have been able to kind of be in certain kind of circles and now be able to talk to amazing people. In the last nine months since the move to ServiceNow, I have been able to kind of ex expand my circle and get into new circles. And I’m like, oh. Right?

I’ve lived in the and I’ve lived just in my data bubble, I’ve kinda been in this. And and what I realized is that we have lived in this world, which is, like, data is the new oil. We have data driven, and we have to democratize data, data literacy. So, like, data is the center of the world, and and and everything we do is data.

And now I realize, like I mean, data obviously is super important. Context is king. Obviously, context is important, but that’s not the center of the world. You know what?

Why do we do data? Why do we do context? Why do we do governance? Why do we analytics?

Why do we do insights? It’s to get work done.

Speaker 4

It the It’s to drive business.

Speaker 2

It’s a business.

Speaker 3

It is to drive Yeah. Work in this. Need to increase revenue. That means that for the sales team, they need to be able to have all the context for the customers that they’re gonna talk to today.

So give them that, that type of stuff. I wanna There are enough There is some IT issues that are on the board for the last three month three weeks or whatever. Like, that should be that should be dealt with as faster. Like, that’s how we get work done.

So I think what we need to be the shift is I’ve been talking about this. It’s like, what did pre Copernicus, the Earth was the center of the world. We live in this data’s at the center of the world, and we we’re not saying that data’s an important thing.

Speaker 4

But how many of us have been talking about that? How many have been saying that?

Somebody like

Speaker 3

and I bring this up all the time.

It’s like, we’re saying something that’s obvious. Yeah. You can say it over and over again.

Speaker 4

You know? But the thing is, we’ve we’ve also been saying this this the thing about you know, that’s why I commented on your post yesterday with that big yippee it was like, oh, finally. You know? What what I’ve been and others have been saying for the last ten, fifteen years, it what is it at the end of the day?

It’s not, you know, context, you know They’re all literacy. Blah blah blah. I remember us having this conversation about four, five years ago, and you you and I were talking about graphs and this and that, and you you kindly gave me your book, which I sorry. I I No.

I know.

I I’ve always I gave it to

Speaker 3

you on purpose knowing that you would never read it.

Speaker 4

I was honest. I was honest.

But the thing is

Speaker 2

your was it your book, Juan?

Speaker 3

Yes. This is.

Speaker 4

It’s your book. Met. It was his yearbook from university.

Speaker 1

This is this is dissertation.

Speaker 2

I have that book in here.

Speaker 1

This is dissertation, and you just ignored it, Sabir. Come on. I have Sabir’s book.

I have

Speaker 3

I don’t like

Speaker 2

don’t think Malcolm’s book, but I I don’t have your book.

Speaker 3

Oh my gosh. I need to keep that.

Speaker 2

Need

Speaker 4

you.

Well, you’re gonna get it now. Believe me. There it is.

Speaker 3

There it is. You gotta get it now.

Speaker 2

There it is.

Speaker 4

There it is. Well, look. Back back back back to Juan’s point. Juan, it’s always been that way, but we’ve been living in in this bubble that that many people have created because they believe that the only thing that exists is data, and it will always be that way.

Speaker 1

But but

Speaker 4

this is just the wrong way of looking at things.

This is what I’m saying for a business.

Speaker 3

Just to say, I think data’s important, content’s important, governance is important,

Speaker 1

all that

Speaker 3

stuff is important.

Of course, these are these are what we need to do is what is the work should be at the center. And by the way, AI is a way of getting that work done. Like, these all these are so we just need to put work at the center and data enables all this off. And I think we just Well, you just said it.

Speaker 4

I I remember doing a post maybe five, six years ago when and I’ve done subsequent posts. And I said data and data is an enabler. Oh my god. How many people, you know, were were oh, how can you say that?

It’s, you know, blah blah blah. It’s the as you said, the new it’s just an enabler. It gets us to do something. It helps us.

It’s an input. Remember the old framework at, you know, university? Input kind of, kind of, you know, feedback loop or whatever, an out an output, and something happens, and you get something else. You know?

That’s all it is. Right? And that exhaust that you get something out of goes on to something else because it’s an input for something else. So this is just something that’s you know, that’s all data is.

It’s just giving us a a a way to move along the chain. But our final point, our final exit is actually that result, that outcome, and that’s where we want to get to.

So,

Speaker 1

yes, all the above.

And and frankly and

No. And and frankly, one of the reasons why I’m not a Gartner analyst anymore is the very things that you guys just said, which is that I was talking to CIOs and CDOs all day every day, and I was saying the things. Right? Like, focus on customers, focus on business process, focus on process excellence, focus on ROI, focus on everything that that is in the data.

Stop talking about data first because you’re inverting the value prop. Right? All of the above. And it never happened.

Right? It never happened. I was like the consultant that was consulting, and nobody was implementing my ideas. And I was like, okay. Well, I gotta find a different way to tell my story, which led to the podcast. So, Scott, how do we get out of this?

How how how do how do we

Speaker 2

we get out of it.

It’s it’s it’s been I, you know, I go back to pre two k in this space, and it’s the same Yeah. Stuff. You know, people talk about how they’re a data company. You know, I work for Nielsen.

That’s a data company. Okay? A manufacturer that uses data to be data driven with their new semantic ontology layer for extra context. They’re not a data company, but as you both said, it’s the enabler.

It gets things done. It’s the fuel for the engine. It’s the water for the pipes. It’s whatever analogy you wanna do, we gotta talk about it in a way that business understands it.

And we continue to do this. I saw somebody talking about how they post they they posted a job for a a chief agent officer.

I saw that

Speaker 4

too.

It’s like What? Yeah. The And I posted on that. I I I did a post on that.

Speaker 2

Maybe that’s where I saw it.

Speaker 4

It’s like That’s what yeah.

Speaker 2

And this whole idea of a c d a I o

Speaker 1

I hope you it’s it’s getting too much.

Speaker 2

Why? It’s just like we keep adding more more levels.

Speaker 4

Keep Leveling and less.

Speaker 2

Individual capability is actually a c level job. And if you think the rest of the business enjoys this, you’re crazy. And if you go through enough of these cycles of here’s the latest greatest thing, here’s the crushing disappointment that it didn’t bring value, but here’s the next latest greatest thing that’s gonna help us.

Speaker 4

And Yeah.

Speaker 2

If you you hear that enough if you’re a business person, you start to wonder if this you know, that voice that’s coming at you about what the latest greatest thing is has got any credibility. And, you know, you guys know that I think the way we talk about data is holding the industry back, And we we we just continue it. I I don’t know how you break the loop. I know it keeps me in business, this craziness, but it’s still this fascination with the coolest thing and, you know, saying you’re not gonna talk about technology, but then doing a demo.

It’s like, you know, there’s

Speaker 1

Yeah. I think it’s fundamentally a leadership issue. I think it’s fundamentally a leash Juan, you’re gonna say something, though.

Speaker 3

No. Quick quick parentheses. This is just I need to rant for a second here. Yes.

Speaker 1

Please. Go.

Speaker 3

It is so freaking tired when you make a like, I I’m making a post about something, which is clearly saying that the problem is about people and process, and then somebody comes in and promotes their own technology and say, I gotta

Speaker 1

do a bad deal.

Speaker 4

Yeah. Yeah.

Speaker 3

Yeah. Yeah. Yeah. Oh, how many times?

Speaker 4

How many times?

Speaker 3

In parentheses. That was it. Yeah.

Speaker 2

I I told people too. I I I have a problem even with that. Oh, it’s about the people. No kidding. It’s about the people.

Like, what else is it gonna be about? Business is about people. People are about people. It’s like those books, you know, a thousand and one movies you should see before you die. It’s like, when else am I gonna see them?

That’s, like,

Speaker 1

so obvious that no.

Of course

Speaker 3

it’s about people.

So Yeah. Could be there’s a thousand and movie you should see.

Speaker 4

Jeez. Have you started have you have you almost finished the book then?

Speaker 1

Alright. Next next hurry up.

I don’t know how we get I don’t know how we get out of it. Well, I I do know how we get out of the trap.

Don’t. Don’t. Well, I think it’s about leadership. I I think it’s about mindset. I’ve and I’m not trying to to to pedal my book, but I’m indirectly peddling my book.

That’s what it I wrote a book about it. About about changing your mindset, focusing on customers, focus focusing on making your customers’ lives. Thank you, Scott. Making your customers’ lives better.

And and and if you start thinking that data is the center of the universe, which most people in our world, frankly, I think do, right, that’s the that’s the problem. You’re inverting the value What you said, Juan, is the business process, the business outputs. What the business does is first, we we need to we need to embrace the idea that we exist to serve.

Right? And I think if if we can if we can embrace that, like, we exist to serve others. Right? We don’t exist to to to care for the data. We don’t exist to govern the data. We don’t exist to to control the business processes and stop salespeople from doing dumb things in the CRM. We exist to serve.

And I think if we start with that,

Speaker 3

maybe that’s a good start.

We’re we’re so following on this and, actually, I’m connected. We had Kyle Winnebago on our on our podcast recently, and we’re discussing about this. And his point is, like, yes. We agreed that, but the issue here is that the at the board level, they’re actually hiring the wrong people to go do this.

So yes, we

Speaker 4

need that.

But but you’ve got but you’ve gotta look at where are

Speaker 2

they getting their advice from. His his perspective being a head of

Speaker 4

But where are they getting their advice from?

Come on. No. Where are they getting their advice from? That is coming from an external consultancy who wants to put somebody in there who is gonna then provide them with a tail end of business. This is the problem that we have. Boards, that’s why I I I am working with boards in order to counter that problem. You know, that’s one of the ways that that that you can do that.

Speaker 3

More Samirs in the world.

Speaker 4

Well, it’s it’s it’s not just me.

I mean, you know

Speaker 2

And don’t forget his book,

Speaker 1

the stretch book.

Thank you very much.

Speaker 3

I have

Speaker 2

a very technical book,

Speaker 3

so you’re not really gonna bring it up here.

Speaker 4

But but still

Speaker 2

I’ll put mine up instead.

Pretend this is one

Speaker 1

book.

Yes.

Speaker 4

But that’s the that’s the biggest thing we have on our, you know, on our shoulders. It is the external advisory that is providing the the wrong avenue.

And I’ve seen it. I’ve seen the I’ve seen the JVs that have been done, and I’m thinking, hang on. That doesn’t that doesn’t make sense. Where did that come from? When I asked, oh, it came from, you know, the usual suspects. Right?

Speaker 1

Yep. Yeah. It came from the cat sultan at Miao Kinsey.

That’s a It came from the cat sultan at Miao Kinsey. That’s that’s where that’s where the that’s where the job description came from.

You know, the cynic the cynic in me

Speaker 2

to the chief dog officer.

Speaker 1

Yes. This is little me.

Speaker 2

My my newest character, by the way, coming. Lam Altman. It’s gonna be great. Altman.

Speaker 1

Lam Altman. Just give me seven trillion dollars.

Speaker 4

I love it. Thank you.

Speaker 1

I love it. Yes. You can trust me. Yes.

Speaker 2

And and this guy, AI.

This is I was I was interviewing swag animals with this little

Speaker 1

I’ve got a story line for you.

For for Lam for Lam Altman, you you you could write a story line there about him thinking that he’s gonna solve the world’s problems, and meanwhile, his entire team is trying to find ways to get him off the board.

Speaker 4

I was thinking silence of the lambs.

Speaker 2

Exactly. Oh, nice. Get one of Who’s got a data hero official? There we go.

Speaker 1

I have a yeah. Bobbleheads. Bobbleheads. I haven’t got one of those.

Son

Speaker 4

Son and I are left out again.

That’s not great.

This

Speaker 1

is We need to be you need to to join us on our data hero summit.

It’s our virtual event in October.

We’ll get you

Speaker 3

a bobblehead.

Speaker 1

All the speakers get bobbleheads.

Speaker 2

Oh, they bobblehead.

Speaker 1

Yeah. Yeah.

That that was that was the only the only gift that we could we could give to people who work for large companies who have, like, caps on the amount of, stuff

Speaker 4

that they can or I

Speaker 2

mean, by the way.

I did not check that box. I’ll take whatever cash you wanna give me. No problem.

Speaker 1

Oh, okay. Well, yeah, we’ll have our people talk to your people. So what what were we talking about? Leadership and getting over the I’m actually talking about you, though.

Speaker 4

Talking about the job descriptions.

Speaker 1

We we were talking about so so I I again, I I wrote a chapter about this, about these feedback loops in our industry. And the cynic in me, you know, as as long as there’s a vested interest in the big name consultancies to maintain the status quo, I would argue this the status quo would be maintained.

Right? And and it’s just it’s this re it’s this circling, you know, circular door of CDOs who last eighteen months. They’ll go to the next company. They’ll be interviewed and say, what happened?

Well, there’s no data culture. They didn’t embrace data governance. They didn’t give me the funding that I want. They didn’t give me the support that I want.

So, you know, I’m you know, what am I gonna do? I’m trying to climb up the hill, but they’re rolling boulders down on top of me as I’m climbing the hill, so I had to leave. Oh, great. You’re hired.

Right? And and over and Another eighteen months of the same. Bingo. And the exact same thing.

Wash, rinse, and repeat. And you can make a lot of money as a CDO doing Oh, I’m sure. You can make a lot a lot of money. So yeah.

I I don’t know. I’m still an optimist. I’m still an optimist. I I I still see the power of data.

You know? I don’t want AI to be the the the the the next Hadoop. I don’t want it to be that. I don’t want it to be the next digital transformation.

And there’s reason to to be optimistic, I think. Juan, are you an optimist?

Speaker 3

Of course. I’m a rational optimist.

So the the if you read the book,

Speaker 1

it Scott, one or Experian.

Speaker 4

Which one?

Speaker 1

Which one?

Speaker 4

It might be worth Well,

Speaker 2

the one book for it is it’s

Speaker 3

Rational Opinions by Matt by Matt.

Confessions Somewhere.

Speaker 4

Confessions of a Rational Optimist.

Speaker 3

And check out his book, man. Books by Matt.

Oh,

Speaker 1

okay.

Speaker 3

Cool. Look. At at the end of the day, I just the rational op is for me is, like, you take all the pluses and all the minuses, you’ll have more plot. You you end up in the positive.

So there’s a lot of negative things happening in the world and stuff, but there’s more positive. So that’s how we we we net out. So I I think that what AI is what AI is gonna what what AI is doing right now is we’re we’re it’s it’s the we’ve we’ve seen this before. Right?

Oh, it’s the web how the web changed. It’s electricity and all these types of things. Right? It is so that’s very true.

The thing that’s different from everything else is that it is at a speed that is completely unprecedented. Right? So that’s something that that many people that I talk to, they’re like, but we’ve seen this way before. They’re not saying it’s so fast.

Then people are like there’s other people who saying, hey. It’s this the speed that is very different. So what’s gonna what’s happening right now is this gap that this is this is the concern that I have, and this is where the negative says is is coming out. But I think there’s gonna be more positive at the end. I am telling people right now, especially, like, junior folks coming out. I’m I’m very worried for them, and I tell them I tell people junior folks, I’m sorry.

Life’s gonna suck for you for a while. It I mean, it like, you’re like, it’s gonna be really bad. But there’s three things I’m give them that book, one thousand and one movies then. It’s two. So there’s three things that I want people to go do.

Number one, this is the moment that you just start really think about systems thinking. And this is all about go back to your saying, Samir. It’s like, understand what are your inputs and what are your outputs, how to break this problem down into smaller pieces. Like, this is systems thinking. This is problem solving. Right? I think and it’s not just about how to go put a prompt and let the LLM vibe code hold.

Speaker 4

Yeah. Yeah.

Speaker 3

Let’s architect these things and do this. Right? So the systems thinking is number one. Second, those things that we call soft skills, I mean, those are really the strong skills and, like, this is where the people and the communication like, that’s what’s gonna differentiate you.

Because at the end of the day, people are still wanna talk to other people and and and and you’re able to communicate what you’re trying to go do and why is this a problem and so forth. So communication is key, not written and orally. This is really important. And and this is where I’m like, if you’re an introvert, you gotta figure out how to become that introvert extrovert a little bit around that thought.

And the third is, I think, people need to start figuring out what baskets to put their eggs in. And we need to start figuring out a particular expertise in a domain in an industry because I think we’ve been very generalist. Just technology this thing technology applies. Oh, we have the technology that does x, and we focus on again, back to the technology.

I’m like, but what is the problem that you’re solving? And I think what’s important right now is to really understand a particular industry and figure out who are the players in that industry. What is the current status quo? Like, what it like, how is this dominated?

How is this market changed? Like, be able to understand that language, and I think that’s what’s gonna differentiate you, and you bring that up to the strong skills. And then you figure out how to go solve your problems with that. So I think that that it it that’s the advice I’m give giving junior folks, and not just for junior, anybody.

And that’s what makes me optimist is, like, that’s gonna be the changes that we’re gonna go see and and and things are gonna change. I think these are three pieces of advice I’m giving people to say how you can take advantage of this moment.

Speaker 4

I think those are system is is is up to snuff for that.

Do you think that that the education system I’m I’m just looking for So I think to

Speaker 3

It’s not right now.

It’s not right now, and and there needs to be a lot of change in education. Some stuff that I’m starting to go see, which can get makes me optimistic.

One is, for example, there the this was just announced last week. The like, Khan Academy is connecting with TED. And so this is a TED Khan Academy where you’re actually gonna be able to kind of have a continuous education at at a much lower price. And it’s not accredited at this moment, but it’s just giving opportunity to people to kind of upskill themselves very quickly.

We need to have a change of education too where it’s actually, it’s a continuous a truly continuous education, which is not like, oh, you go to high school and then you go to four years of college and then you go off to work.

No. You you’re like, every five years, you go back. It’s natural to go back to school to upskill yourself for the next thing you wanna go do.

So there’s a there’s there’s things that I’m starting to go see around, that I’m that, yeah, gives me optimism. It should happen faster, but it’s better than it’s not happening at all.

So so I I I this is this is the rational optimist to me.

Speaker 1

Follow-up with your point

Speaker 2

number two, obviously, with the soft skills.

It’s all I ever that’s all

Speaker 3

I ever Here’s here’s here’s my here’s my call out, please.

Let’s stop calling it soft skills.

Speaker 4

Yeah. Yeah. Yeah.

Speaker 3

Strong skills.

Speaker 2

Yeah. Strong skills. Soft skills.

Speaker 4

Whatever it is.

Speaker 2

Vernacular that exists today in people’s minds. And so hard skill, soft skill, we didn’t come up with it, but people get that quickly. And Sometimes if you wanna change too much terminology to then make your point, you’ll you you you kinda lose folks. And and and so that’s why, you know, people don’t write a while.

Speaker 3

I mean, just let’s let’s put the labels away. People have been thinking about more, I need to figure I need to be great at using a tool.

And then I’m it’s like and then the human aspect, oh, that’s that fluffy thing. And and it’s more it’s more important. It’s like this is, like, the issue with, like, with peep not an issue, but, like, we talk about STEM.

Oh, we elevate STEM so high, but then there’s, like, oh, the arts is sometimes you you you

Speaker 2

really Right.

And they came up with STEM. Right?

Speaker 4

That was Yeah. Exactly. That’s that’s why they did that. Yeah.

Speaker 3

This is the but you the arts is what gives us back our gives us back our humanity, which is what we actually need right now for AI that would seems to be taking it away. And this is a pendulum swinging that we just push the pendulum so side so much on one side for technology that history shows us pendulum will swing back, and this is us regain our humanity, and this is the strong skills. This is the Shabir, love what you’re doing. You’re going off and acting.

Like, this like, this is these are examples of what we need to show people. It’s like, life is not just one side. Right? There’s a whole balance of stuff, and this is this is how we were getting our humanity.

All of this is for me how I feel I’m rational optimist.

Speaker 1

You know, I I don’t I don’t know if it’s all doom and gloom for the the young people. And I know you’re not saying it’s all doom and gloom. You’re saying it’s gonna suck for a while.

But I don’t know. Like, if if my old employer is right and eighty to ninety percent of all data is unstructured, and I don’t wanna get into this academic asinine argument about, you know, whether it’s semi structured, structured JSON And it’s not even necessary or whatever. I don’t it doesn’t In in tables are not a table. If that’s true and I I saw a stat recently that said that only twenty five percent of data being used by AI models is actually governed in any way, shape, or form.

Basically, the our total addressable market as data people is mostly untapped.

Right? Is is, like, is fallow ground. Right? All of the stuff sitting in SharePoint servers, all of the PDFs dangling on on hard drives out there

I and and plus One one would

Speaker 4

think it’s it’s easier to get that now. One would think it’s too

Speaker 1

to Right?

Yeah. But but, Juan, to your point about the pendulum, every time it swung too hard this kind of reminds me of the of the offshoring craze, like, fifteen years ago when we offshored everything, and then everything went to hell in a handbasket, and then it pivoted back. Right? And and I think that we’ll inevitably pivot back. And I think the people who have the systems thinking, right, like, who understand the business processes, but could also deeply integrate data and understand how data works. So I I do think there’s still a generalist layer there. I do what you’re describing one is a t shape.

Speaker 3

It’s like, yeah. A hundred percent is a t shape. T t shape.

And it it my plan has

Speaker 4

been for for a long

Speaker 3

long time.

A little bit deeper right now in this moment, you have to get a little bit deeper into that stuff. And then and if you’re already deep, you start becoming a pie shape. Right? You get two down. Yeah.

Speaker 1

But right now right now, data people are are are are I shaped. They don’t have the the top on the t, Scott. There’s no like, you know There’s the I. Scott’s got the Scott’s got the I.

Speaker 4

It’s all seeing one.

Speaker 1

Yeah. I I’m I’m a little more optimistic on the short term. You know, I think that this will induce more and more demand. I think paradox will play out. The more that we produce, the more demand there will be for our for our services.

Speaker 3

If we

Speaker 1

can just figure it all all out.

I don’t know, Samir. What do you think?

Speaker 4

I I I do think there is there’s there’s a notion of short termism. Because right now, most organizations are attempting to do efficiency on efficiency on efficiency on efficiency. Right? Because that’s where we are. That can’t be maintained for that long.

No one can sustain that. Yep.

So what’s gonna happen

Speaker 2

is shrink the greatness.

So Yeah. Exactly. Efficiency.

Speaker 4

And apart from the, you know, the what was it called? The the the shrinking guy? Not Ant Man, but there was a you know, before that. Oh, yeah.

Anyway Yeah. The Incredible Shrinking Man, I think it was called. Anyway, the idea of of organizations continuing to play the efficiency game isn’t is not gonna work. They are gonna be in a hole because there won’t be enough people to actually then create that that that up upward trend in terms of that revenue.

They won’t be able to get their products and services out quick enough.

And I think they are they are you know, it’s like the lemmings when, you you know, when they go off the side of the cliff. Everybody’s using the set. They’re just following the the the lemming in front, and then we must we must be efficient. Every digital transformation has been, let’s talk about let’s talk about efficiencies.

Speaker 1

Yep.

Speaker 4

Yeah? Now we’re now we’re talking about AI transformation efficiencies. How many how how much more can we take of that?

And I don’t think these are really So

Speaker 1

what you what you’re saying, though, assumes the status quo on legacy processes.

Right? And and if we can agree that in the data world, we we are hindered by by this this devotion to the status quo. Right?

I’m sure the same thing is true in procurement and manufacturing and HR and all the all these other processes that are running on, like, TQM demoing stuff from forty years

Speaker 4

ago.

Yeah.

Speaker 1

Yeah. Right? Yeah.

And if we could to Juan’s first point, if we could reengineer those processes for

Speaker 4

first reengineering, or is it is it is it actually about blowing up what’s happening right now and starting from scratch?

Because if you think about it

Speaker 1

I think

Speaker 2

it’s the latter.

Speaker 4

You’re you’re lay you’re layering on AI onto what you said is a legacy business that’s been running in the same way for the last fifty, sixty

Speaker 1

Faster steam engine.

Faster steam engine. Yeah. Yeah.

Speaker 2

It all can blow it up, though.

Speaker 4

That’s such a that’s

Speaker 1

such a

Speaker 2

risky proposition for some these big enterprises.

Right? Saying, okay. We’re just gonna blow everything up. I I I get that bit.

Speaker 4

But you somebody’s at some point you know, who was it? Was it Allbirds? Is is it Allbirds?

The shoe

Speaker 1

company. From

Speaker 4

being a shoe company to now being an AI company.

Yeah.

Speaker 2

Yeah.

And

Speaker 4

selling compute and data centers and stuff like that.

You know, that’s They liquidated a few But their stock their stock price went booming. But but, look, that was a pivot, and I don’t know where that’s gonna end up.

Speaker 2

And that just felt like a a total stunt.

Speaker 4

Of course it was. Of course it was. Because yeah. Yeah.

Of course

Speaker 1

it was.

Of it course it was, and they got rich.

Speaker 3

But I I I think what what Yeah. What what’s gonna well, predictions always I don’t wanna predict this, look looking at the history of what happens is whenever new innovation comes in, right, we’re trying to accommodate that innovation to the way how we do things today. And then you’re trying to go make efficient going back more efficient, more efficient. And then you’re like, well, this isn’t as efficient.

And people like, oh, this wasn’t really as

Speaker 4

good as it was, but

Speaker 3

then people realize, wait.

Maybe the way we’re doing things before needs to completely change. So we’re bringing electricity in.

Well, that means that we have to re redo our factories from scratch, not just be a bulk electricity that we’re

Speaker 4

But it’s the business model then, isn’t it?

Speaker 3

Well, it’s I I think it’s rethinking how biz how your business processes and your and how you do this.

Speaker 4

Right? But that’s fundamentally a good model. That’s the way it works. So I think the process is is a part of it.

Speaker 3

In a short term, we’re, like, figuring out these efficiencies, but I think this is where, like, the bit larger, quote, unquote, legacy companies have to start thinking about how am I going to reinvent myself or reinvent our businesses around this and saying, okay. But you this is not a big bang. You don’t do for everything. You have to be very kind of strategic, but we’re gonna go start.

Here’s how we go do this today. Here is how we could go change this with the current technology that we have, and then we start learning from that. And and that and then we’re entering new territory, and then those are where new roles are gonna come in and how to how to reshuffle people into this new stuff. Newer native companies won’t have to deal with their, quote, unquote, legacy stuff, and that is their opportunity to grow, and that is the risk.

And I think this is why, right now, you need to have businesses need to reinvent themselves. There’s gonna be AI all over the place. That’s why we need to able to con on one side control AIs, but at the same time, we need to be able to enable them enable this this this whole reinvention. That’s and and and then the Chevy Globers gonna do that shift faster are be the winners.

Speaker 4

But but if we think about where where where we currently are, we’ve we’ve we’re talking about a lot of agents, you know, spun up by companies who are you know, I was speaking to somebody last week. We spun up thirty agents, and those agents are gonna be doing, you know, not only marketing, but some of their customer service stuff and so on, you know, the chatbots or whatever. Right?

That that becomes a new level of of what’s the word I’m looking for?

My my my mind’s completely blank. A A new level of organizational principles, right Yep.

Where we are gonna have agents going off and doing stuff that we may not know what they’re doing. We may not know what the result is. We may not know the decisions that have been made. We may not know why they want to do that in the first place because they just decided, oh, I’ll go off and get that because I couldn’t get that API before, or nobody told me about that, but maybe I should just make it up and do you know? So so so there’s got to be a level of organizational principles behind governing these things.

Speaker 3

We do do the different for humans.

Speaker 2

Oh oh, I I get it.

Speaker 4

I get it. So so but but the thing is people are being unwieldy about it now. It’s just like, well, let them loose. You know? And maybe this is the experimentation phase. The experimentation phase where people are saying, let’s see how it works.

Speaker 3

Is a But the minute they the minute they the minute they Was it Yeah.

Speaker 2

But the

Speaker 4

problem is one, the minute your, you know, PII data is leaked by an by an agent

Speaker 3

But then But this but hold on.

But this is when everybody, like, oh, but something’s good oh, something bad’s gonna happen in my PII. But guess what? There is I think there’s an eighty twenty rule around this where probably eighty per the eighty part is where you can actually be okay for use cases that it’s gonna be fine. And that twenty percent is something that needs to be very highly contained and regulated.

But we’re gonna be able to live live with that eighty percent, and we’ll in that eighty percent, it it I’m just saying using eighty twenty as a Pareto principle. Yeah. Yeah. Different, and it’ll be it changed by industry, of course.

But I think that’s what’s gonna happen. And then, this is the change, and I think people who are gonna I’m going to let loose. I’m gonna be more strategic knowing that I I will be okay letting loose in these types of areas, which which is a little bit possible because today, I don’t even know what the humans are doing. I trust the humans to go do this stuff.

Right?

It’s the same thing, and there’s a reason why we have policies and so forth for everything Well, the

Speaker 4

Well, the humans.

Speaker 1

But but but we we know that there is a fairly obvious anti technology bias here. And I’m not saying that from a conspiracy theory perspective. It’s just a fact. Right? Self driving cars are infinitely safer than human driving cars, and all it takes is for one accident of a self driving car. And everybody’s like, forget this. I’ll never get into a self driving car.

Speaker 3

Hold on. Let me stop that. What happened with planes? How many people died? How many plane crashes happened?

And do we thought we stopped? No. We kept learning and learning from that, and people died, and then things improved. And now is the safest means of transportation.

That’s my example of being a rational optimist. We’re gonna have more pluses than the minuses. People died. There are a of bad things, but we learn from it, and we learn from it so quickly.

And we created policies and governance around that stuff so we can go learn.

Speaker 1

Well and and what I’m seeing is that some, not all, and I would say not even most, but some companies are doing exactly what you said, Juan. Right? Like, they’re letting her they’re letting her rip. They’re buttoning down the data that needs to get buttoned down.

But for everything else, let’s give it a shotgun

Speaker 3

and see what works.

Speaker 4

And and and that’s why I said it. That experimentation phase is probably good, but the the as long as they as as long as what happens is we’ve got to learn, and I think that’s what Juan was talking about, You know, if we get that feedback loop and that learning, and then how do we change our operating model? How do we change the way that, you know, we orchestrate our business? Then we then we then then that’s the way.

Speaker 3

Going back to, like, when we talk about data as a center of the world, and you look at these architectures, like, you look at the medallion architecture stuff

Speaker 4

Oh, yes.

A flow.

Speaker 3

It’s a flow that goes from data to insights, and it stops there.

Speaker 1

Revolutionary.

Speaker 3

Right. So when but when I when I think about, like, work is at your center, part of the things that you wanna push work, but you want the feedback loop is something that is never part of, like, traditional data architectures. And now that is something that is gonna be so critical because you need to have the feedback.

This is where it’s not just human You

Speaker 4

should see measurement framework.

Should see my measurement framework. Fun. I have feed feedback loops in there ad nauseam, and people look at and they go, oh my god. You’ve got feedback. Of course, we have because we need to know whether we’re doing the right stuff here.

Speaker 1

The the the the the reference to the feedback loop?

Speaker 4

Actually, something referenced it the other day, which is really cool. Isn’t that brilliant?

Speaker 2

Think your point about all this short termism. How do you balance that with the idea that almost every, you know, pundit out there when they’re talking about what to do as this, you know, a hundred days as a CDO, get for the quick wins. You want the quick wins.

Right? Look for the quick wins.

The Well,

Speaker 4

so so

Speaker 2

here’s thing.

With, like,

Speaker 1

the idea with

Speaker 2

the short

Speaker 1

You know, getting back to our previous comment that was not recorded, thank goodness, around the fifty over fifty, the fifty data leaders over fifty.

Right? These all of these years are fine, bud. Oh, yeah. Yeah. Easy there.

Speaker 2

Been in that club for a while.

Speaker 4

You’ll be there one day. Yes. Exactly.

Some

Speaker 1

of the, you know, some of the things I’ve learned in those over fifty years is that it’s never an either or.

It it’s it’s it’s never all short term or all long long term.

Speaker 4

It’s both.

Bunch of things that you need to add

Speaker 1

on the plate.

Always both.

Speaker 4

Yeah. Yeah. Yeah.

Speaker 1

So if you focus on the short term, the short termerism, right, like, do need to do that. Like, you do need to show some movement in the in the first ninety days. But at the same time, you need to be building these these systems that that that rearchitect how you operate, that challenge the status quo, that do all the things that we need to do in order to, you know, adapt to this brave new world.

Speaker 4

Listen. Let me ask you let me ask you a question.

Speaker 2

Just just one

Speaker 4

question first.

Right? How many how many times have you ever heard anybody go into an organization and say, tell me about the way this the decisions are made in your organization?

Speaker 1

People Good question.

Speaker 4

People None. Right? None.

Speaker 1

Well, because people But, Sameer, that’s that’s that is that is a that is a a one way road to I don’t know.

We decision science, the idea of, like, tracking

Speaker 4

I’m not talking

Speaker 3

about decision science.

I’m not talking about decision science.

Speaker 4

I’m talking well, of course, is. But the decision is basically where we wanna where we wanna get to. Right?

We wanna get

Speaker 2

to that point.

Wanna the next phase after the insight is the decision that some sort of action

Speaker 1

that Exactly.

Speaker 4

Exactly. And we get a result from that. So, you know, if we can map that and and and we know what data needs to be there for that decision, we know where that workflow is. We We understand, you know, who where the where the handoffs are between people. We understand, you know, whether it’s gonna be a a decision tree that’s that’s gonna be kind of, you know, fixed list, then we do that, blah blah blah.

If people knew that, I think that would help a huge amount for for for understanding of how a business works.

Speaker 1

Well and not all decisions are created equally. Pareto’s gonna apply. Right? Twenty percent or Absolutely.

Speaker 2

I I

Speaker 4

get that.

Right? Yeah. Yeah.

So But if we change

Speaker 3

from how work how work gets done.

Exactly. Only work at the center. Let’s understand that. Yes. Under understand your business process. Yeah.

And then once you get that done, then you realize what is needed and then realize, oh, wait. This is how we do.

Speaker 4

Each of that.

You you you go

Speaker 2

That’s a million problems in every business. You just gotta go

Speaker 4

But but you go back to what you said earlier, Malcolm.

You know, just working with customers. If you mapped out your customer journey you know, how many times I’ve seen a customer journey where somebody’s mapped it out, and they just look at maybe two or three levels? But then what about going below that? Going data, going measurements, going decision flows. And then suddenly, you’ve got a way bigger picture of like, woah. This is I mean this is actually how how I how I create my business, how I create my data models, how I do all that. But, actually, we’re looking at it right up and down, you know, left to right and saying, this is how I’m gonna be able to actually make a I make a system work.

Systemic thinking. That’s what it is.

Speaker 1

Yeah. I’m I’m a huge believer in driver maps. What you just described is what could best be described as a driver map. What’s actually driving the performance of the business.

Yes. Right? Whether that is what is that that is a metric or decision point. Jets, I’m recording a webinar in, like, three minutes.

So, sadly, we we could do

Speaker 2

their show.

How can you leave your show?

Speaker 1

Alright. We could leave y’all. Okay. You guys Yeah. Yeah.

Speaker 4

We’ll just continue.

Speaker 1

We have to celebrate the hug anniversary. We’ve gotta we’ve gotta wrap. We’ve gotta wrap.

Speaker 4

I still haven’t spoken about your, you know, Captain America shield behind you, Scott.

Speaker 2

Tell the stories of how we met you. Really? I thought this was gonna show was gonna be about you, Malcolm.

This is

Speaker 1

Well, no.

It’s about you. It’s about you. Yes. And and it’s about sharing your insights.

He’s leaving

Speaker 4

us.

He’s abandoning us.

Speaker 1

Alright. Okay. Mark your calendars for the two hundredth. So y’all will be back for the two hundredth.

For the two hundredth. Mark your calendars.

It’s about three hundredth

Speaker 2

years from now.

Speaker 4

Right?

Are you you potentially making a hundredth

Speaker 1

this year?

Sure.

Speaker 4

Yeah. That will will be the, what, the sixty under sixties then.

Speaker 1

Yeah. Exactly. All of us.

Speaker 2

Congratulations. All of us. Exactly. You know, of it’s like point x number of podcasts ever get to a hundred.

Speaker 1

Yeah. Yeah. Yeah.

Speaker 2

And Welcome to the club, Melvin. Voice out there. You’re strong. You’re opinionated, but you let people talk. You get great folks on there.

Really, it’s it’s a testament to your

Speaker 1

Thank you.

Speaker 2

To your intellect and your perseverance and your creativity, and we all congratulate you heartily on on that.

Speaker 1

I couldn’t have done it without amazing people like you. With that, I hope you’ve enjoyed this one.

Have a

Speaker 2

nice I have a hundred swag animals.

Speaker 4

My god. That’s a lot.

Speaker 2

All of them here. They’re coming COD to your place.

Speaker 1

That’s fantastic.

Speaker 4

I hope I hope you enjoy it.

Speaker 1

Alright. With that, we’re gonna sign off. Thank you for supporting a hundred episodes of the CDO matters podcast. I hope to see you on the next episode sometime very soon.

Speaker 3

I’ll see you in person.

Speaker 1

See you, Garner. You, Samir. Pleasure now. Thanks, gents.

Speaker 4

Everybody.