Good morning. Afternoon. Evening wherever you are, whatever time it is where you are. I’m Malcolm Hawker, the host of the CDO Matters podcast. Welcome to our podcast. Today, I am happy to be joined by Veronika Durgin, who is the VP of Data at Saks.

Now I I want to keep I want to say just naturally Saks Fifth Avenue. When when did maybe I’m just not with it. When did you rebrand?

Is I think it happened. Well, hello, everyone. Hey Malcolm.

I was like, are you? Yeah. What a great intro. It’s like like pull the rug out from Monday, you can start talking about the name of Saks Fifth Avenue like anybody cares, but but anyway. Yes. Let let’s dive right in.

It happened I think three years ago.

Oh.

In the in the kinda like it was a post COVID thing, and we wanted to focus on kinda digital experience and bring that beautiful Saks Fifth Avenue, you know, special experience to our online.

Alright. I I thank you. I did I did wanna touch on your company name because I know for for a lot of luddites like me who were not very fashion inclined.

I’m not. You you who may hear Saks not know what that is. So that’s that’s that’s why I wanted to touch on it because it’s for for people like me who live in a cave It’s it’s Saks Fifth Avenue. So It it’s fair.

And I get that off until it’s like Goldman Sachs. I’m like, no. Saks Fifth Avenue. Wonderful.

That and so so that’s why I wanted to touch on that. So so thank you so much Veronika for for joining today.

I met you for in person the first time at CDO IQ this summer in Boston just in your in your hometown, well, not home, but where you’re living now in in Boston. But I think I think we had traded a few things on LinkedIn before that. I had certainly known a view, and I I think you had mentioned that maybe you had caught some of the episodes of the podcast before, but We sat down, and it was a morning breakfast. I I am pretty sure.

Maybe it was a very long meal.

Maybe it was just a very long lunch.

Well, that was that’s probably because he got stuck talking to me, that that that that made it long. But To to make a long story short, we we hit it off having a conversation, and I really enjoyed talking to you. And at that moment, I was like, If I enjoy the conversation, well, then maybe others might enjoy the conversation too, and that’s why we are where we are today. So thanks for joining. Happy Friday.

Indeed. Yeah. We we did meet at the CDO IQ. I I’ve been following you before that, I was internally secretly, and I know I’ve, you know, maintained co pays, like, been girling over everybody sitting at that table.

And I was like, oh my god. Oh my god. Like, this is so cool. So super happy to be here.

You and me you and me both. So that’s kind of what’s cool about CDO IQ. And and I had said this in a previous episode, and I a kind of an episode summary. I think with with Scott Taylor when we were talking about this.

I had I had this I had fanboy moments as well, and it was like kind of like surreal. Right?

I think the story I was telling was was reading this really great article in Harvard Business Review about the impacts of I I think I don’t know exactly, but I was like, this is a great article. This is this is awesome.

And of course, you know, written by Randy Bean And then, you know, I sit down and, you know, at the at the breakfast table and there’s Randy Bee, which was which was cool. So I was having those moments too.

So Veronika, I would I’d love to start first with the story of you. I I’d love to hear kind of like your data journey, your career journey, and how how you kind of where you started and and where you got to. I I think I think it’s an interesting story that that our listeners would would love to hear.

Yeah. Absolutely. And it’s kinda like it’s very interesting. I I both enjoy sharing my story and not. It’s a awkward talking about myself.

But so here we go. I’ll start from the the beginning.

I’ve or maybe I’ll start from the end, actually. I’ve spent my entire career on data. But I still kinda fell into it. So and here’s what happened.

So, you’re probably picking up a little bit of accent, and I like to mess with people. Just asking them to figure out where I’m from, but, I still have a little bit of access. So I immigrated to the United States when it when I was seventeen years old. So I finished high school.

I am originally from Russia.

We moved here just slightly after the Soviet Union collapse.

So I finished school there fully bilingual, and I actually started medical school. So my parents were pushing me to be a doctor just like I’m sure many can relate to that. So when we came here, we came here as refugees. Basically, we had no money.

We brought like a bag of clothes each, and we came here to succeed for opportunities and to work hard and to get somewhere. So I spent about a year kinda, like, learning English. I knew the alphabet and maybe how to ask for apple use. When I moved here, so I spent a year studying English and then went to college.

So my entire, kinda, like, graduate education is here. So I learned a lot of things in English. I’m actually not very good at translating back and forth, which is odd.

But I went to college as pre med.

The difference here is that medical degree is a graduate degree.

So I started, a biology major. I actually have an undergrad degree in biology.

I hated everything about biology.

I’m sorry to those of you who love it.

I went to marine biology lab once And I I kinda walked away. I’m like, this smells like fish. Like Vision that stuff they use to preserve and also the cadavers so that you can cut into them. Right?

Whatever I’m like, no. I this is not what I wanna do. I am not passionate about medicine and and I feel like To be in medicine, you really have to be passionate for it. Like, it’s it’s a long journey.

It’s tough. It’s it’s hard, psychologically, hard, it’s physically hard. So I wasn’t really into it.

While I was still in college, I got a job processing Blood preparing blood for testing.

So I started a hospital lab and kinda transitioned into data entry. We had these, like no. This is, like, late nineties.

We had these, like, dumb terminals. I think med med detect, med whatever the app wasn’t. Apparently, it was confusing to everybody. I think it’s still around. And I was like, this makes sense. So this is my journey into, like, oh, I can work with with computers.

As I was working there, my coworker said, hey, my husband’s looking for a, computer operator.

Alright. That sounds cool. Operator. That’s awesome. Yeah. So I was like, alright. That’s awesome. So So still getting my undergrad degree went, got that job.

So this time, you know, this point in time working full time, going to college full time, I was like, oh, this is cool. This is where I kinda like Lord Microsoft Access.

Oh, and why I like this?

As I graduated I got a job as a junior DBA.

My god felt like just I was like, I get it. I love it. I want to know more about it. So and I’m like, okay. But I kind of know nothing about technology, like, at all. I have, like, no background whatsoever.

So I am, like, I need to get a master’s degree. And at the time, there was no master’s degree in data. So I ended up getting a master’s degree in software engineering.

A hundred percent not a waste of time. I learned about software development methodologies. I learned about project management. I learned to code never really used it, like, v b dot net. I’m like, oh my god. This is so cool, but never really applied it. Just continued moving through data.

The other interesting thing is, which kind of funny. I almost failed animal biology.

Because not only did I have to memorize all the, like, the Latin names, like taxonomists.

I also didn’t know the words in English. So I had to, like, translate to English and then to another word. And to this day, I hate when we call things with names that don’t make sense. I hate code project names. I was like, can you make it clear this double hop?

I’m like, I just can’t it’s like learning two languages at the same time. So it just kinda like a funny story.

I guess the other thing is, you know, And this is something that we don’t talk a lot about, and I know you and I kinda touched upon that what we’ve met before.

Being a working parent.

So, we’re a household of two working parents, it comes and, like, if you see my title, Linkedin, it’s, like, chief mom officer. It’s, like, I know it’s, like, cute, funny, whatever, but it is the reality.

So I was getting my master’s degree, working full time and having a newborn all at the same time.

It takes a lot of, like, it’s operationally, like, logistically, you have to figure it out.

I haven’t slept for, ten years at some point. So I was like, you just function. Like, your your life becomes very agile. It’s like, What do I do next day? You don’t plan, like, what do I do ten years from now? Right? Like, like, tomorrow, I just need to survive one day at a time.

The agile live in the agile life, like, literally. That’s that’s pretty much it. It’s like yeah. It’s the it’s the MVP of every day.

But, yeah, it’s like I made it. It sounds like. Well, thanks for sharing.

I I I I I just love hearing these stories.

I I I can’t even imagine what it would be like being dropped into this country not knowing the language. Like, as as a Canadian, you may you may think this is odd, but as a Canadian, it was hard enough for me.

Being dropped away from everything that I knew and my friends and and and into a into a foreign country. And yes, there are differences between you and the Canada. Not even knowing the language, I I can’t even imagine that. That that what do you when you look back, what do you think are the is the one or two things that you’re most grateful for.

But because you came from somewhere else, but because you had to learn English. What what are the things that you kind of hold really tightly now and say, wow, at the time, maybe that was really hard. Or or, you know, at the time, it seemed impossible, but now you look back that you’re most grateful for.

So first of all, honestly, and that’ll be patriotic here for a second, the opportunity that I had to come here.

Period.

This is I I there’s no I can’t describe the appreciation of having that opportunity to be here. And to become what I am. There was nobody actively blocking me from working hard and succeeding.

If you work hard, you succeed.

The other interesting thing is learning a foreign language is very interesting because this is very similar to learning business language. Right? I’m an engineer. I need to learn to speak the language of you know, the business people that I’m working with, it’s very similar.

Right? Like, you now have to learn different words, different phrases. So in in a way, like, Yeah. That’s the same thing.

So, every company I work for, I have to learn a new language, if you will, of how they speak, of how they understand, That’s why, like, I don’t I try not I I actually get very excited when I find the right word, completely dorky. But, you know, let let’s let’s figure out what the words are and what the meaning of those words are and let’s move forward.

So to paraphrase what what I if I were to put it into kinda one word, would be maybe a spirit of gratitude Right? That’s what I’m that’s what I’m hearing. I’m I’m hearing gratitude for the opportunity to to to be here and to work and to succeed and and to to live your life. So I I that’s that’s what I think I’m hearing.

Do do you agree? Country? Oh, absolutely. Hundred percent.

Okay. Yeah. I like, I have a lot of words, but if you wanna put it into one, Yeah. It’s it’s being on a different country.

I know you you’re from Canada, then we’re kinda like, Canada is the same in the US, which is not but being in the country that is quite very different from the United States. It it truly opens your eyes to the opportunities that we have here that I’ve never had there ever.

And and believe it or not, I can actually say the exact same thing. And that’s that is the opportunity is the number one reason why I’m here and why I will die here. So I I’m not one of those immigrants. It’ll say, oh, it’s better back there.

It’s but it’s not. This this is this is the place to be. This is the place I choose to be. This is this is home, and we have the greatest potential.

I think of any country on the planet. I’m with you one hundred percent.

Go USA. Alright. So when we talk about kind of the world of data leaders and and big challenges and how do we overcome those challenges. What are some of the things that kind of high level without without going into into too much detail with your individual company? What what are some of the things that you’re seeing in the market kind of high level as some of the the the bigger challenges that that we need to be focused on as a community?

Oh my gosh. I think I for me, every company Like, we talk about it, Tom. Like, are they all similar or are they all unique?

I think as a data leader, you need to focus on problems you need to solve at your immediate company, and then basically use almost like a lego piece by piece and and put your you know, whether it’s strategy or platform together that is solving problems of your current company.

I I see this a ton where we’re like, oh, this is cool. Let’s bring it in. Or, like, oh, I wish I could do something at my previous company, so I’m gonna do it here. We kinda miss, like, no. They’re they’re, you know, distinct problems in front of you to solve them.

So it’s kind of where my mind’s at. Well, when we had talked previously, what what one of the things that that you had you had kind of grasped about, was was this was this idea of kinda consultant swooping in and swooping out and vendors swooping in and swooping out?

Tell me more. Yeah. So I I have ranted about a ton. Actually, I’m gonna say something. So at the CTO IQ, there was a conversation around the type of data leaders that a company wants to have. And I walked away from and there was, like, I think CDO panel I walked away from that panel being incredibly frustrated.

And I was frustrated because the message was Oh, one of the messages was if you can write, you know, a thirty page memo, you’re the greatest data leader.

I disagree with that. I think depending on the maturity of the company, what they’ve done in the past, what they’re trying to do you need to bring a specific type of leader at that point in time.

Or, like, I actually I I I I was driving home and I was as many days thinking about it. Like, are we looking for unicorns? Who don’t exist?

Or are we saying it’s not my problem in blaming somebody else? Or are we saying I am the best. Right? The reality is companies change, and like I always I often say that jobs are like relationships.

You have a relationship with the company. Sometimes it’s just bad. Like, you’re not good for each other. Sometimes you grow out of that relationship.

Right? I don’t know if you’re married. I don’t know how you’ve been married. Maybe you are you were with your partner for a long time or sometimes you’re with them for a short time.

Sometimes you then then for a long time, and then you break up because you just grew apart.

So at each stage of the company, of each stage of the data maturity. You need a specific type of leader. And as a leader, it’s honestly on me to realize whether what what does my company, my team need?

Am I fitting into that? Can I change to fit into that? Or is this it for our relationship?

And I need to move on and they need to hire somebody who better fits that specific, you know, situation.

So you had you’d mentioned the word unicorn.

Love it.

The the the joke. Well, I’ve I recall when we were talking before the the way that you described the unicorn was very kind of similar to how how I described one. I think you said what remind me your description of the unicorn if you recall it? Well, I don’t know. When I say it probably, like, perfect. Somebody who’s just, like, Perfect all around technical business. You’re you’re like everything in one package.

Yeah. Yeah. The the the joke I tell is is one half business One has one half technical and one half sales.

Right? So, so, you know, the joke is, of course, it’s three it’s three halves. Right?

You’re one and the half person. Yes.

Well, yes. Very much. But you need what you need to be. So for the you as a unicorn, It it seems your, like, your background is not exclusively, but is is reasonably tilted towards technology.

Right? Your database administrator, you you have a master’s degree in computer science. That’s pretty that’s pretty tech centric. What what specifically have you done what what have you seen that that has been effective over your career to get more rooted on the business side?

Learning. Honestly, again, like learning for a language, continuously learning.

I Again, like, I know my limitations. Like, I am not a pure strategist at all. My strategy automatically means me thinking how implement it. I can’t disconnect. I know it’s my shortcoming. It’s also my superpower.

So I know that I will fit perfectly into specific company specific situation at their specific step of their growth.

But if they ever need me to transition and purely strategic role, I will be horrible at it and I would hate it on top of it. I’ll be like, it’ll be the most miserable job I’ve ever had. So I I know, like, I am not a unicorn at all. I’m very, like, self aware what I’m good at, what I’m not good at.

But I am trying to kinda like learn that foreign language of trying to understand the business from their side completely removing any sort of technological and engineering thing. But my brain automatically thinks of how to implement something. Like, It just how it works. And and I’m like, I I am at peace with that. I know where like, I don’t need to be where I’m not good at it, I don’t contribute. So that’s kinda yeah. So has that got but but I’m prone to detail as well?

And when it comes to problem solving, I I I tend to rip at things just like endlessly.

For for me, and I and I know this is true for a lot of other folks as well.

When you’re trying to learn something new, there’s always a question of depth.

Right? How how detailed do I need to in my case, I I came from the business side. I’m not a technologist.

I I I was on the business side. I was a chief product officer. I was a product manager. I l I learned the the trade of product management, and I applied it to data. And for me, I always wrestled with, well, how deep do I need to go?

Right? Like, how much do I need to know? And I learned a few things along the way. Can certainly share, but I I would love to hear your perspective on, well, how deep do you need to go?

Is is it is it transactional or is it more strategic or or how do you draw the line? Do you need to understand, you know, in the case of Sonos? We were we were just talking about, you know, how the how the terminals work. That’s the engineering side.

How how deep would you need to go on the business side in order to become comfortable?

How deep to go on the business side? So I actually I’m gonna mention something. So, there is a book but it’s down nearly. And I can’t remember her co author. She’s, professor at Harray Business School called the digital mindset. And one of the things she talks about is the thirty percent rule, which I absolutely love and can relate to. And what she says is that for somebody to speak English well enough to be at the table how conversation, they need to know thirty percent of the words.

So and and I’m like, this is exactly it. I need to understand thirty percent of something to have a meaningful conversation with that person.

I want to know hundred percent of everything.

It’s not possible, but it just how my brain rolls, but thirty percent is enough to have a meaningful conversation.

So, no, you don’t have to go all the way deep but you need to have an opt out.

That’s really compelling, and it’s about language, and it’s about understanding.

So I think that’s a really useful paradigm.

Whether you’re coming from the business to looking at technology, whether you’re coming from technology looking at the business, can can can you be coherent enough thirty percent coherent.

Yes.

I don’t know how to measure that. Right? Like, the take here we go with technologists is like, well, how would you exactly would you better I would do. Well, I mean, maybe it’s, like, simple words too.

Right? Like, do you understand thirty percent, like, of that technology paper? If you do, you you will have a meaningful conversation. Yeah.

That’s to me, it’s always a bit of a balancing act. I found success in in my past, and this seems a little counterintuitive.

But being rather transactional in what I learn and what I don’t learn mean meaning Like, if I need to learn a technology, I’ll I’ll give I’ll give a good example.

One of the one of the one of the big projects I was involved at a long time ago little software company called American Online, was I was put in charge of of of making portions of their advertising infrastructure speak Japanese.

Right? Like to international character sets. So so back in the day when everything was old school aske, like seventh did aske, and we’re like, oh my gosh, how how are we gonna make this thing actually, like, you know, multiple bytes wide and and and it was all about being able to sell search terms. And we we had built a business around selling English language search search search terms on aol and it was Google picked that up and it’s now what Google is because of that, But we were wanting to figure out, okay, how do we sell search terms in Japanese?

And I was like, I don’t know anything about engineering. Don’t know anything about this stuff. And now I don’t know anything about Japanese. So I’m like five times, you know, behind on what I need to learn, and I figured out maybe it ended up being about thirty percent of, like, you know, what does unicode mean?

Right? What does multibyte mean? What does it actually mean? And, like, I learned that, like, every character on the keyboard is actually a number.

Right? Like, like, it’s it corresponds to a number, and I was like, there’s, oh, wow. It’s, like, So that that’s that’s my little tidbit, which is I I learned just enough to be slightly intelligent to speak with slight intelligence you know, and at least have a conversation with engineers so that they wouldn’t laugh me out of the room. Yeah.

So see But then you need to have engineers who, like, truly know the depth of things. That’s the other part. Right? Like, as as you go up into, like, leadership roles or maybe even, like, principal roles or architect roles, you need to still have a team that knows something in-depth to actually implement it.

Yeah. Oh, abs absolutely. You you yeah. And and and this is this has been true in my experience with the the tech and business in in a in a corporate ladder as well.

Right? If if you are an extremely technical data leader, then then you need somebody who is at your side who is not. Yep. Have you have you experienced the same?

Yeah. You bells out. Like, you you have to fill in the gaps.

So and it’s like, as long as your team is complete, right, like, your team has to be unicorn, but not anybody individually.

So, and that’s another thing I think us as humans, we oftentimes don’t understand that. We think we are perfect. We’re not.

Once we realize we’re not, then we can, like, build a team that is collectively perfect.

I love it. I love it. Aspire to that at the very least. Well, speaking of of technology, when when we had spoke a few days ago, you you had said something that made me catch my breath.

I was actually clutching my virtual pearls as it were. Where where exactly.

Were were were you had said something to the effect of I’m a believer in centralization of data management?

I am. I I I am believer in in central data decentralized analytic, a strong believer, I know there’s a situation where it’s just physically not possible by sheer number of people and etcetera, but I think the only way to truly standardize on the language of data, it has to be it has to have very strong guardrails.

I I I’m I’m with you. And and you drew a really important distinction there. That I don’t think enough of us draw, which is you you said decentralized analytics centralized data management. Yep.

And and and I think that’s a really, really important distinction. And and I think when we use these terms and we talk about data mesh or data fabric or ins insert shiny thing here. We don’t draw enough of a distinction between what are we talking about here? Right? Are we talking about analytics? Because we’ve been doing that for decentralizing analytics. We’ve been doing that for decades.

Yeah. I mean, we call it a data, a data, you know, you call it a data mesh or a data mark or or whatever. I mean, we were calling data marks twenty years ago. Where where where marketing groups could help build their own stuff. But I think that distinction is is is meaningful, and I think we should we should be more specific when we talk about these things, like, because I don’t think we are.

For example, the data mesh is absolutely positively an analytical paradigm.

Mhmm. Like, hard stop. It says so in, like, the first paragraph of Zomark’s book about the data mesh. So very important distinction.

Let’s drill down a little bit. When you talk about centralized data management, I mean, I assume you’re talking about things like MDM data quality, all all the other kind of the Exactly. You know, common definitions conceptual models. This thing is this is what it means, and this is where you can get data about it.

Just so as as an analyst or data scientist, you go to the same place to get the same data. Is everybody else. Right? So that’s how I think about it. But then what you do with it is you can implement that data in whichever way you needed to. Right? This is kinda like now we could be getting into this, like, monetizing data, but not from, like, selling perspective or actually using it for various different purposes.

I love the idea. Do you think it’s feasible?

It is incredibly hard.

And it’s always a push and pull.

When you go into this when you go into anything that’s centralized, then you’re viewed as a bottleneck.

Period.

But but it’s like there in order, like, for us as a society, like, I’m gonna, this whole historical lesson. Part of being when you’re a member of a society, you have to follow a set of rules.

That’s how we all, you know, share toys in the sandbox.

So if you want to use the sandbox and play with the toys, you have to, like, follow some rules.

And I know some people don’t like to follow rules, and that’ll always be happening.

But but that’s okay.

If we do want to collectively be able to safely use things and reuse and repurpose we have to accept the fact that sometimes things will be slower, but for a reason. I mean, they’re traffic lights. Right? Like, oh, you know, Oh my god. I’m stopped the red light. It’s slow, but it’s there for a reason.

Well, that that sounds that sounds like, you know, well, it sounds reasonable. It sounds like, you know, reasonably compromise, but it also sounds like a little bit of a sacrifice that maybe often wanna make, they wanna have their cake and eat it too.

But I mean, there’s there’s countless metaphors here. Right? I love the societal metaphor because you could easily think about the power grid, the roads, right, like, you know, water and sewage infrastructure, like Go go build your own, go try to build your own roads and your own own infrastructure in your own, you know, health care system and and on and on, because there’s there’s not gonna be any economies of scale. That’s the whole thing about centralization. It it exists for a reason, and it it exists because it provides economies of scale that are not there. And highly decentralized worlds.

Yep. The other thing is, like, what I’ve heard recently, I was on a podcast. Somebody said, oh, security is massive bottleneck. Like, that that’s not a good way to look at it.

Security is not a bottleneck. Security is is actually what you wanna do. And it’s it’s part of delivering something. I’m like, would you have a house without a front door?

Would you want anybody off the street to go into your house? Because it’s not a bot like, you remove the bottleneck. Oh my god. You no longer have to knock or ring a doorbell, but, like, do you really not wanna have a front door?

So it it’s I think it’s a perception of, like, what is fast? What is bottleneck?

Right? Like, things take time. And it’s an acceptable time to take to do things a certain way because you’re optimizing, right, economies of scale. It’s safe.

It’s whatever that may be. So, like, I don’t look it as the bottleneck. It just kinda like changing how you think about things. How much of this do you do you think How how much of this may be craze or hype or maybe obsession is too strong of a word.

I think it might be too strong of a word. We’re we’re talking a lot about words today.

But this obsession towards, like, decentralized everything.

How much is of of that do you think is coming from vendors? Are you hearing that on the vendor side? I am so I’ve I’m I’m I’m skeptic by nature. I don’t, like, this whole whatever vendors are selling me, I take it with a grain of salt always.

So I am not in the camp of blaming vendors for everything. We’re all adults. We should be able to make our own decisions and and, you know, figure things out.

I think to me, and again, maybe it’s based on my experience, I worked with software engineers a ton.

And they’ve always looked at me as the bottleneck.

And I was actually, and they’re always also went from monolith to microservices.

I’ve seen this play out a long time ago, and I’ve worked with software engineers, which I don’t know if you I mean, you were on a product where I I managed a team of software engineers for a long time. Yeah. This whole thing of, like, Oh, I can do better. Oh, you blocking me.

You slow me down. I’m better. I’m better than this. I’m better than this person. I’m better than the software.

I think it’s just us as humans being human I I don’t it you you especially as you kinda, like, maybe when you younger, you’re, like, idealistic and you think you can do better. And then you, like, reinvent the wheel for a few times and you realize, like, first of all, it’s boring. Like, why do something that’s already done? And then you also learn and you realize that some things are better left to others.

Focus on what you’re good at and then let others do what they’re good at. So this kinda also comes with maturity.

Well, that that that kind of aligns to some of the insights you shared with me when we were talking a few days ago. I think I think you called it, like, your your martial arts approach. Oh, it’s. Jill Reese is actually called it MMA.

Like, I’m totally running with it. What what to me, I actually I use slightly different phrase. I what I share with you is I I don’t do yoga. My mind’s too active, but this one time that I took yoga. And and the thing that I took away from it is and when we were kinda like relaxing at the end, she said, Take what you need and leave what you don’t.

And that’s exactly it. Take what you need from the tooling perspective, the pattern patterns and methodologies that work to solve the problem that’s in front of you.

Stop obsessing about all the other things, we make things work. Right? Like, it’s it’s not a vendor. It’s not a consultant. Actually, talking about. You asked me about consultants in the past, and I haven’t answered that question. But Well, go ahead.

Yes. Go ahead. Hey, Veronika. I’m a I’m a consultant, and I’m here, and I wanna help solve all of your problems. And the first thing we’re gonna do is an eight month long maturity assessment we’ll we’ll put together a road map. We’re gonna do we’re gonna do, you know, gap assessment to understand where you wanna be versus where you are. What do what do you say?

Sign on the on the dotted line.

What I’ll say is is what you can give me tomorrow.

Okay. Consultants versus full time employees versus, you know, vendors selling their product.

We all have a specific business goal and responsibility.

As a consultant, right, like you just said, oh, it’s gonna take me eight months. And I said, I need you to deliver ABC in three.

And I’m not. And you’re like, but this is a bad idea to do it right. I need eight months, but I’m paying you and, like, I need it in three months. So you deliver what you can. It’s not necessarily your fault. At the same time, generally, I walk in after something was delivered like that, and then I have to fix it. So it’s it’s such an interesting relationship, and the same with, you know, vendor selling product.

They want to make a sale. I get it. I appreciate it. They potentially exaggerate things.

I also understand it, but it’s, again, I put it on me and my team to do real evaluation, to to do the matrix, to understand what this tool gives us and what it’s lacking, and then we accept the trade offs when we make our choice. And I’m not gonna walk around and blame a tool for, you know, all every single problem that I have, it’s it’s really on us how we use the tool, why we brought it in? Was it the right tool for us? And did we realize that the trade offs that we accepted were actually a bigger deal than we thought they were? Exactly.

I think often, and I’d love I’d love your perspective on this. I think often we’re just not being honest to ourselves about why we’re hiring the consultants in the first place. Yep. Right.

Right. Like, there’s a lot of reasons to hire consultants. And don’t get me a lot of the people who watch this, listen to this podcast are consultants. A lot of the people who are engaged in the on LinkedIn are consultants.

I’ve been a consultant. They play an incredibly important role.

But but I think I think, you know, when I look at, am I am I something you mentioned earlier, you said you said, which is just fabulous, by the way. You said, you know, you’ve got a reasonably high level awareness and I would agree, and you’re not you said you’re not very good at strategy.

So that would be a great time to sit down with the consultant who maybe is Right? And if that’s the reason why, and that’s what you’re hiring them for, that that fantastic, maybe you’ve maybe you haven’t you got holes in your organization you don’t have people. You don’t have the people in the chairs that you need to have in the chairs, and you need to augment your staff, and you need to send consults for that. That’s great. They can be very, very effective at that.

But but often I think a lot of the times consultants are just being hired as a checkbox or as as what I would call when I was a gartner, a halo.

Right. Which which is which is the somebody else’s, I’m using this other group in certain name here. It doesn’t matter. To to to bolster my business case or to to build my credibility or to build the credibility of this program, and that’s a different thing. So I don’t know. What as as you’re listening to me rant about this, what what what are you thinking?

It it’s both no. I I do agree. Like, we have to be honest with ourselves.

Two hundred percent. And it’s like consultants or not. You you have to be self aware, you have to understand what your team is and what it isn’t and go from there. I’ve seen consultants hired where, like, there is a project it needs to get done.

We don’t wanna hire full time staff. We would just wanna temporarily bring somebody in. But that’s a short term engagement, which means that whatever, you know, consultants deliver, somebody has to support. If that conversation hasn’t happened, that’s what I’ve seen fail.

So the things are, like, thrown overboard. Like, here now you support, and you’re like, Wait. What? What is this?

I don’t know anything about it. Why was it built this way? Like, again, like, it all comes down. And I don’t know if you think about it.

I think about a ton is, like, psychology with human.

Like, at the end of the day, it’s two humans working together.

And we all know that sometimes it works and sometimes it doesn’t.

Yeah. In indeed. Getting back to your your metaphor before about the relationship between you and a company. And sometimes it’s good and sometimes it’s Yep. Can be dysfunctional.

We’re we’re running low on time. I do wanna ask one more question because this this piqued my interest earlier when we were talking about data management And we’ve talked a lot today about language.

You talked about learning English, and we’ve talked about having a common language and learning words, And when it comes to data management, that’s obviously important. We start talking about things like centralization and having common definitions and data models and and on and on. Have you thought at all about how AI would throw a wrench into this or maybe help or complicate or or or what? What what’s your perspective on on AI and and our development of a common language.

So if we can deliver or or come up with a common language, then AI can supplement automating a lot of other things.

But I don’t think AI will solve our common language problem. At least I can’t see it happening at at this point in time. I don’t know. Maybe it’s point AI will be this magical thing and a robot that, like, understands us.

But, like, grasping the context, the the nuances that the translations of how, like, I I guess what I’m trying to get is is we we still have to talk to each other and agree on things before AI can step in and automate some things.

Awesome.

Next time we’re together, We can share a beverage and and have a a more detailed talk about that because I I wanna I want to convince you Otherwise, but I could be completely and totally wrong. I I I think that there could be something there maybe one day because they seem to be AI seems to be pretty good at language, but I I think there’s universal consensus and and you and I would agree on this that it’s never gonna be a hundred percent. No way. Like, no way. I I I think I think I think what maybe it’s the thirty percent.

Right? That would be cool even if we just got the thirty percent.

And also I also mentioned that I’m a skeptic. So I I, like, I’m gonna say something that’s probably gonna, like, totally, like, date me. I wait until service pack one.

I always wait until things kinda like settle down, stabilize.

Somebody else will do the the high test it all out.

And then I’m gonna be like, okay. Now this is a little bit more stable. Let’s really think through how this can be implemented. And I’m still learning that thirty percent of the AI language.

Right? Like, I I don’t have a full, like, thirty percent of the setting, what it actually does, how it works. So I’m still on that journey. Yep.

Well, even the people that build it aren’t even sure how it works. So you’re a good company.

Alright. That Veronika, thank you so much for taking time out of your busy day to talk with us. My my apologies. We had some technical glitches at the at the beginning.

Hopefully, that doesn’t actually show. But Thank you for taking time out. Thank you so much for having me. Always a pleasure.

Wonderful. And to our audience, our listeners, our viewers of the CDO matter pop CDO Matters, podcast, too much coffee this morning. I’m speaking quickly.

Thank you so much. If you could, I would be thrilled if you take the time subscribe to the podcast so you get a auto automatic notifications from Spotify, Google, Apple, you name it wherever you consume your podcast, thanks again to Veronika. Thanks to more listeners. We will see you on another episode very soon. Thanks all.