Good morning, good afternoon, or maybe good evening, whatever time it is, wherever you are in this amazing planet of ours. I’m Malcolm. I’m the host of the CDO Matters podcast. Welcome to our discussion today. I am excited to be talking to my friend, Kyle Winterbottom, who is the CEO and founder of Orbition, which is a data and analytics focused staffing and recruiting and hiring organization. Did I say that well?

Yeah. You you got every single recruitment slash staffing slash hiring slash advancing, yeah, acronym in that. Well done.

Perfect.

Well, I didn’t I didn’t wanna sell you short. I I mean, when it comes to what’s going on in the market for senior data leaders, You you guys have got your thumb on the pulse of what’s happening.

Yes. You are based in the UK, but I know that you’re expanding in the US, and I know you’ve got a view over the entire global market for hiring exceptional people in the data and analytics space. So that’s what we’re gonna talk about today. So if you are a director, senior director, maybe a VP of data and analytics and you’re wondering to yourself, hey, how do I become a CDO?

What do I need to do? What does the market look like? Is it hot? Is it cold?

What role is AI playing in all of this? Then you’ve come to the right place today. That’s exactly what we’re gonna talk about in the CDO Matters podcast. Anyway, my opening question was, what are you seeing in the market for CDOs?

Growing? Shrinking? Overall, what’s your synopsis of that role in the market right now?

So I think it’s a very, very interesting kind of marketplace.

I think it’s almost impossible to answer that question because the role in of itself is very contextual to the organizations that are hiring for it, so I think we’re definitely on an upward trajectory from where we were end of twenty three, twenty four, twenty five, while there’s definitely been an uptick.

I’m not too sure whether we are reaching the heights back at the top table of the actual legitimate chief data analytics type officer mandates just yet. I think they are still few and far between, but what that has definitely caused is a real spike in hiring at the level beneath them. So the people that would, I guess, usually report into that type of role, the directors, the heads of, the VPs, there have been a lot of hiring in that space. In fact, probably, I would say, more hiring in that space than I’ve ever seen in my fifteen, sixteen years in this space. I’ve probably never seen as many kind of leadership roles advertised at one time ever before. So it’s a good thing. Whether they are CDO roles or not is a completely different question.

So okay. Well, let’s put aside the title.

Are these are these people what you suggested there, are there they are the people that would be reporting to the most senior data leader, but not the most senior data leader. Is that correct?

Yeah. So I I think this has probably stemmed from the fact that a lot of organizations for what you know, a whole variety of reasons have decided that the CDO role is no longer needed in their organization. Not always, so that’s not a blanket statement, but there was definitely a trend that happened often with the CIO then becoming the person that was kind of given the strategic responsibility in the boardroom for that mandate.

And therefore, that’s kind of led to a lot of director and VP hiring, so someone to come in to own the data analytics function, as in what the CDO role would be, but not at that level, not with that title, not with that kind of comp package and usually reporting up into the CIO. That would be the general average observation.

Okay. So that’s that’s interesting. That’s good news and that’s bad news, I I think. The the bad news is is that it it appears maybe we’re losing losing our seat at the table.

Right? Like, that’s that’s you know, we’re we’re losing the, like, legit chief of of the sea. That’s the bad news if true if what you’re saying is is is true of the entire market. The good news is is that there’s still demand for people who know what we do.

Right? And there’s still demand and growing demand for people who know data, who know analytics, who know AI. So that’s maybe the good news side of the story. Let’s focus on the bad news just for a second.

I I already know the I think I already know the answer to this question.

But I’m gonna I’m I have to ask it anyway. And this gets this gets back to things that we were discussing before we went live.

If we are losing our seat at the table, why? Why why? Why is the CTO assuming responsibility? I’ve even talked to a few people where the CFO is assuming responsibility for AI stuff, which I think is I’ll I’ll I’ll leave judgment aside, which is interesting. If we’re losing our seat at the table, why is it happening, Kyle?

Well, fundamentally, I think, you know, we are still plagued by this whole notion and debate of there’s a lack of value, there’s no ROI, there’s no business outcomes, there’s no impact. Like, however you wanna frame it, whatever context that means in the world that you live in, fundamentally, that’s the complaint.

A lot of businesses have spent an awful lot of money often, on their third, fourth, fifth iteration of trying this role to build this capability and just falling into the same pitfalls.

So I think the headline is we’re not delivering what the business wants us to deliver. I think the caveat to that is that often businesses are setting people up to fail. So I know there’s kind of an underlying conversation that happens in our industry, which is irrespective of what the job description says or what the role profile says.

We all know that the job is to deliver products and solutions and services that help businesses to make decisions that improve business performance fundamentally, if we try to dunk it down into its purest form.

But that’s not what companies hire for, right? So companies go to the markets and hire someone that can build them models and platforms and dashboards and frameworks and yada yada yada, then after they spent two years building all of this stuff, then say, okay, well, we spent a lot of money. We’ve now got all of these people running around doing work with data, but actually, commercially, we are no better off. In fact, sometimes we are worse off because we’ve incurred a lot of costs and we’ve not seen any uplift anywhere across the business in cost savings or revenue generation or whatever the case may be. So I think it’s a very nuanced conversation.

The issue is trying to address that, right? Because effectively what we’re talking about here is potentially on one side of the coin, skills gap maybe. A large portion of the industry was brought up under the premise that well, the job is to build dashboards and build frameworks and build platforms, and that’s what they were hired to do, and that’s what they’ve been incentivized to focus on throughout their careers because that’s how they get paid, and that’s how they get the job to start with.

Equally on the other side, you’ve got these organizations that complain about a lack of value but have a huge knowledge gap around the perception of what that role exists to do, right? So in their mind, it’s, well, that role doesn’t exist to deliver value. It exists to build stuff that value then appears out of the other side of it. And it’s like, well, no.

That’s not how it works. You can’t just build stuff and expect things to happen. So it’s a real interesting I think a real interesting crossroads, I’m into more and more conversations in the boardroom about trying to fix that perception. But I think the challenge is that that’s not very scalable.

To fix that knowledge gap, you’ve got to do it from the inside out, and that doesn’t scale very well, right? Somebody asked me today actually on LinkedIn, what’s the answer to that?

Which group is easier to educate and influence? Is it the data profession or is it the boardroom? And it’s like, well, both really is the answer, you know, simultaneously if possible, but there’s one that’s definitely more scalable than the other. You know? I think that’s fair to say.

Something I I’ve to the skills gap issue, and this isn’t a matter of judgment, folks.

Just just imagine if your favorite sports league, in in your case, the Premier League, in my case, the National Hockey League. Just imagine if it doubled in size over a two to three year span.

Would the quality of play degrade? Of course, it would degrade.

Right? Of course, it would. The quality of the play wouldn’t be nearly anywhere as good because all of a sudden now you have people who would not have been in the Premier League expected to play at the Premier League level and the the quality of play would go down. So it’s not necessarily a judgment per se, but I think the skills gap thing is most certainly real. It’s it’s something that I see I see every day to this day to this day, I I I talk to CDOs who don’t really fully understand how Gen AI works.

Like, that that’s just that’s just one example, and I and I and I could go on. So the skills gap, most certainly. And that’s something in in our control.

So the issue of the the the board, maybe, you know, this this this incessant pattern of hiring for your technical capabilities and, you know, must know Python.

But when they get in the role expecting, you know, a transformational kind of a change agent type, I assume that’s something you you try to spend a lot of time with your clients to help educate them. Like, hey. Listen. This is prob you think you need somebody who needs to code Python, but in reality, you need something else. Is that a conversation you’re having often?

It is. But I think the the kind of incessant kind of obsession with Python, which we had for, you know, two or three years there Yeah. Everyone the wrong way.

I was being I was being glib, by the way. But but I know you think I know you know that’s real. Yeah.

Yeah. Yeah. No, it is real, but I think it’s definitely lessened. Know, not seen Python on too many CDO job descriptions for a good while. So I think we’re definitely moving into the right direction. What I would say with this is that there’s still, as it relates to them putting the role profile together, even though we’re not necessarily always focused on the technology itself or the technical stuff that sits within it, the focus is still very much on the output. So we get brought in to deliver on mandates, and that mandate might be we need somebody to come in, more or less a greenfield site as an example.

They want someone to devise an executor data strategy as part of that, do the whole operating model.

Then as it kind of lays down, it gets more, I don’t know what the right word is, but outputs right? So it’s like, then he goes, Build a data governance framework and process around it, yada yada yada. And it kind of rudders down to a lot of core outputs. And then when I say, Okay, well, how are you going to measure the performance of this person in terms of how are they will have been, how they are, if they’ve been successful or not effectively in twelve, eighteen, twenty four months? And it’s, well, they will delivered the data strategy. And I’m like, okay, well, what does that mean?

What else would they have done? Oh, they have put together a data steward steering committee. And I’m like, yeah, but none of that helps you achieve what your business wants to achieve. That’s just stuff that you are doing because that’s what you think the role is.

So there’s just too much in that, and it’s just a perception thing. It’s just that these people who are outside of our industry and not privy to this conversation look at it and think, Oh, well, it’s data, right? It’s work. It lives in systems.

We need tools to visualize it. We need pipelines to move around. We need frameworks to govern it. That’s what the job is.

And then continue to complain when they’re spending a lot of money and not seeing anything from it. So it’s a fascinating landscape. But I think you’re right to kind of echo the point that this is definitely not a you know, it’s not a judgment around the skills gap piece because because, like, fundamentally, businesses don’t you know, the way businesses hire is incentivized, in my opinion, the entire industry to focus on the wrong things. Like, we all know that the outcomes are the things that matter, but the way you get hired is by demonstrating your ability to deliver outputs.

So what do you expect people to do? They will you know, if they if you want the job that’s gonna pay you x hundred thousand dollars a year, you’re gonna show them that you can deliver outputs.

That’s the job you’ve got hired to do. You go and do that, and then you get fired for for doing it. Right? It’s just a it’s just a merry-go-round that is we’ve turned into a bit of a circus, really.

So, yeah.

You’re you’re absolutely right.

Without turning this into an advertisement for my book, this is something that I talked about a lot, this idea of misaligned incentives. And I couldn’t agree more. Whether it is the incentives between the company doing the hiring, the incentives of the person being considered for the role, the incentives of everybody that supports that person once she or he is in the role. Analysts, consultants, thought leaders like me on LinkedIn, all of our ins all of our incentives generally align to the status quo.

They generally align to the way that we’ve always done things. And frankly, if I’m up for a CDO role and I’m being told and I ask, hey. How will my how will I be measured? Which is a reasonable question to ask if you’re being considered for any role.

Doesn’t matter if it’s a CD or anything. How will I how will my performance be measured? And I hear back, well, you’ll deliver on the data strategy.

Right? Or or you’ll implement a framework.

I’m saying to myself, even though I know even though I know I should probably be focused on outcomes, I’m I’m gonna go heck yes because those measurements are squishy as as I’ll get out. And I know I’ll be able to deliver.

And and I won’t have a lot of accountability because there’s no real metrics there. So so I’m incentivized even if I know that I should be focused on value. There’s an incentive for me to say, got it. You bet I can deliver on that strategy, and I can hit my metrics because I’ll get paid when I do it.

Yeah. And there’s a really important point in all of that, Malcolm, which I think is I’ve seen this firsthand. People that try to address that in an interview, they, you know, get booted out of the door very quickly. When they turn around and say, okay, I understand why you think that way, but here’s actually how you should think about this and, you know, blah blah blah blah blah. You should be thinking about **** and how the business makes money and all of that type of stuff that we talk about.

The interview panel will be like, this person doesn’t have a clue what they’re talking about. They’re trying to change the mandate to fit their background is kind of how they think about it, right? So it’s almost this kind of real strange What I often say on places like LinkedIn is you’ve kind of got a panda to all of the things that they ask for. You’ve got to go there in the interview and say, Yeah, I can deliver your framework, and, I can pull together a steering committee, and, Yes, I can build us a new single source of truth platform and blah blah blah blah blah blah, under the divisor that when you get in there, you then actually have to start that education and influence piece to say, all that stuff that we want to do, can do, but first, this is what we need to get alignment on this in terms of why we’re doing it, where we’re doing it, into what it is, etcetera, etcetera.

So because if you try to tackle that in an interview, your chances are very slim. So, again, you’re not incentivized to do that in an interview. Right?

Well, yeah, I get it. And, basically, you’d be the candidate sitting across the table saying, you don’t know how to run your business or you’re not running your business the right way. Let me tell you how to run your business. And that’s how it would be coming across. Sounds like it.

Yep.

Yeah. I mean that’s, to be honest with you, that’s the type of conversation that I’m having when I go into these boardrooms that say, here’s what we’re looking for, and I’m kind of trying to educate them on, well, maybe we need to think about it like this. There’s obviously a way to do that. But often, and I think, you know, I’ve said this publicly before and maybe even on this podcast actually, there becomes a time where that either lands and they go, Okay, fine. We trust you. Let’s tweak that. Or it’s a case of, Look, can you find us this, what we’re looking for or not?

And I think the difficulty there for people like me in that situation is that morally, I’m like, we’ll put this person in. They will deliver exactly what’s asked for. They will probably get paid their bonus because contractually they’ve done the job.

But eighteen months’ time, twenty four months’ time, that business will be looking at this going, There’s nothing there. We need to restructure. We need to get rid of that person and their team, because they think it’s the person’s fault because they hold the mantle. Right?

But Right.

Well, okay. So if you’re listening to this and you’re a data leader and you’re kind of scratching your head and it sounds like it may be a little gloomy, there is hope.

And here’s what I would do if I were you. If I was a data leader and I was getting into a situation what Kyle and I just described, right, which is I’m being paid by for frameworks. Maybe I’m being paid on on some data quality metrics. I’m being paid on implemented governance program. I’m being paid on implement a data strategy.

What I would do is this.

I I would get the job. I would I would I would take I would take the job. But what I would do as this kind of side covert thing is have this rabid yet somewhat silent focus on value quantification. Right? I would hire what I call and I said this in my book, I would hire hire what I call a value engineer. I would hire somebody who can help with the spreadsheets, who can help with planning and budgeting, and who can help come up with data to start measuring the value of what you do. Because when that eighteen months comes up and the business is getting frustrated because you’re delivering on the exact things that you said you were gonna deliver, but the organization hasn’t transformed or the organization hasn’t successfully launched AI or do whatever the the the kind of the transformational things that they were expecting from your job but not recruiting you for.

When that time comes, you’ll be able to point back to here are the things that I delivered and here are is the value that I drove for the organization. Even though this wasn’t my metric, here are the metrics. What do you think about that approach, Kyle?

Yeah. A hundred percent. Because I think as as we’ve discussed, if you try to tackle that at a time, you’re not getting the job. Nine times out of ten, you’re not getting that job.

So yeah, I think it’s a case of getting through the door, doing the work, but doing the real work in tandem. And I think, as you said, there’s often even when you’re on the inside, there’s often not a lot of incentive to do the work because people are still looking at you like you’ve got two heads. What the hell are doing that for? That’s kind of outside of their job description. But I think the key thing here is that you can deliver exactly what they’ve asked you to deliver, what you’ve agreed you will deliver. And still, there’s going to be a big question mark hanging over your head in the eighteen month time period. So it’s kind of in your best interests to go and do and show something that, you know, demonstrates tangible value that you can kind of, yeah, hang your hats on, I guess.

Yeah. Absolutely. And that way, when it comes time for your next round of interviews, that’s what you can speak to. That’s what you can highlight. Instead of saying, yeah, the last place was f’d up and didn’t have a data culture and didn’t care about data and didn’t care about my role, which a lot of people end up saying.

But I would for me, I would much rather have some tangible evidence that I did deliver value and that that wasn’t necessarily valued by my previous and that’s a very, very different first interview in your next go around than it is of just saying, well, the the last place was messed up and and didn’t know what it was doing. Didn’t have a data culture.

Yeah. Alright. Let’s let’s transition into AI. Of course, you can’t have a data podcast these days without talking about AI. You had mentioned that you’re seeing growth in roles of people reporting to the top most data leader. And in many ways, that topmost data leader is often now a CTO or something else. CIO, CTO, who knows.

What are you seeing in the space for AI? How how were things how were things changed? The technology, crazy, seems to be like leaps and bounds.

What what’s the high level AI story you’re seeing? Are people being hired specifically to to to execute on AI mandates? Is AI a bigger just one piece of the of the puzzle? What exactly are you seeing out there?

Yeah. So I think there’s a huge amount of organizations that are going through a lot of work on this. I think the first thing to know is that there’s a lot of kind of internal reorganizations of capabilities. So like how do we get AI ready is buzzword or lingo that we’re hearing out there, which is all about actually the data analytics and AI capability as it exists today is going to need to change to deliver on the work that we need to do tomorrow.

So I think there’s new roles coming up all the time, new titles. There’s a lot around AI governance. Obviously, it’s a massive thing, AI ethics and stuff like that. I think probably the thing to note from a leadership level is there is one hundred and ten percent a bit of a land grab going on, and I think that’s just been expedited over the last couple of years especially.

Think it was always the case, obviously, then the whole ChatGPT thing kind of blew that up and made it a little bit more mainstream. So it’s kind of all come to the fore, and there’s different debates and views on this, right? Like, A lot of people fundamentally will think it’s a technology where who best owns that? The CIO is one hundred percent trying to get their arms around that.

The CDO now, I know many people who are interviewing in organizations, and one of their negotiation points will be, I need the AI piece in the title. They view AI as the future of the data analytics industry, and they don’t want to look like they are being left behind or stagnating. So I think the optics around it are interesting.

So, yeah, there’s a lot of moving pieces. Where it sits, who it reports to is really conceptual inside a business. It’s either a technology thing, though it’s kind of being housed under the data capability usually in most instances.

But, yeah, it’s just a lot to unpack, really.

About from and this is going to lean a little bit more towards the kind of European side of of of our amazing globe. What about regulatory related pressures? A lot of the AI, a lot of focus on on AI, kind of regulation, ethics, bias, that type of thing. Are you are you seeing a lot of growth there in in Europe around hiring specifically people who can deliver against some sort of regulatory mandate? I assume this is probably more so in in in banking and insurance. Are you are you seeing that in Europe?

Yes. I think in the highly regulated environment, yes. I think that whole AI ethics piece has probably been on the ascent from a popularity standpoint in terms of organizations going and hiring somebody or teams of people even to kind of look at that. So I think that’s absolutely fair to say that that’s a role that has kind of come out of nowhere and climbed to the top of many organizations’ wish lists in terms of what they think they need because of regulation around all of this.

But I think it’s still to the conversation we had earlier, I think still most what I find fascinating is most organizations are still they’re falling into the exact same trap with AI as they did with data, right? Which is, let’s go and hire an AI leader, whatever that reports, whatever that looks like, but let’s go and hire somebody to come in. And then they are building models and AI solutions and then go looking for things to point them at, right? So folks are saying, well, where’s the opportunity to use this within the business?

Where the decisions that we can make that can improve the performance of the business and build specific solutions around them? So I think we’re falling into the same trap on that front, you know, people coming in, centralizing it, building stuff, and then trying to just keep it out and see what sticks, basically.

Well, that’s really interesting.

I I don’t know if you’d noticed. This this kind of made the rounds in social media yesterday. And by the way, we’re we’re we are recording this in late February. You’re probably gonna listen to this in sometime in April.

But in social media, there was there was content making the rounds related to a hackathon that apparently Anthropic had sponsored where the winners of the hackathon like, were five winners. And I I I and and I don’t know all the various detail here, but there were, like five winners of the of the hackathon. And one of them was a software engineer and four of them were subject matter expertise, including like a cardiologist, apparently.

One one like this this anthropic hackathon, which really just iterates and and emphasizes what you just said, which is business expertise, subject matter expertise, understanding how the business runs and how AI can be used to optimize business processes. Right? Automate business process, whatever they are.

But here we are again, right, where where there’s this tension between do I know data or do I know the business?

And maybe AI is making it so that we should be more focused on the business than the data. I don’t know. I’m I’m I’m in my my brain is kind of melting around this and that, like, a cardiologist could win a hackathon because the tools are so good these days. I I don’t know. What do you think about that?

I mean, I think if you were to look at most of the page studies out there where there’s been anything of substantial noteworthiness, I think you would find in most instances that is around organizations that have put AI tools and solutions into the hands of business leaders within specific functions that, to your point, they know exactly processes, how a business works, how it operates, and they almost have that intuition to go, Actually, if I apply this here, that takes away some of this or accelerates this or whatever the case may be, which from a centralized perspective, you’re never gonna have the domain knowledge across all of the domains.

But I think, obviously, back to the skills gap piece there, that’s about knowing that, right? That’s about going right. I don’t know everything here, so what I need to do is get close to these people. I’m the one that needs to build the tool or the solution to put it in the hands of the people to use it properly and kind of go at it like that.

I had a conversation yesterday, actually, with somebody that kind of said what AI is meaning for them in their organization. This is a very large media business. He said, Our data scientists are now effectively becoming the people that build the tool, that builds the tool, which I thought was quite an interesting way framing it, you know, because it’s just about them. They build what is needed for that business user and then let them go, right, and kind of work very closely with them on that.

So this starts to and by the way, I think everything we’ve just been talking about is is at the root of this, whether you believe it or not. This is it is an MIT study, so I have every reason to believe it. But the ninety five percent of AIPOC is failing. Right?

Which is a the wrong tool for the wrong job and a fundamental disc and this is this is what that study said. It’s with the fundamental disconnect between the capabilities of that technology and the overall business needs, what you were trying to solve. And just a a poor match. Right?

A poor fit between what these things can do and what the business needs and the outcomes that you’re trying to drive for the business. So seems to me like the the the well rounded data professional of the year twenty thirty and and maybe we should look that far ahead because who knows what twenty thirty is gonna be. But it seems to me like we’re making a very strong case for data people. I hate to use that phrase, but data people to spend some time in the business.

Right? Like to do a tour of duty in in I did actually the the opposite. I started on the business side. I wasn’t I was in the product.

I was a product guy. I was a chief product officer at one time in my career. So I went the other way. I went from the business side to data, but it seems to me like what we may be recommending here is to find a way, whether it’s job sharing or whether it’s I I don’t know what it would look like from kind of an HR and development perspective.

It seems like we’re making a really strong case for data people to try to find to do a tour duty on the on the business side. What what do you think?

Hundred percent. Yeah. I I mean, I’ve had many people that have come on to our podcast that have probably held, you know, like group CDO level roles at some of the biggest organizations in in the world in various different kind of industry sectors, and some of the conversations that I’ve had with those people has been fairly noticeable. There’s probably two things to mention. First of all, now the people that are getting those types of the real big jobs, the real big jobs inside the real big organizations that pale in the real, real big books. Most of them have spent some time in consulting at one point in their career. So they’ve got that kind of commercial business acumen that is really important in the role.

Second of all, there’s been a group of those people that have actively gone out of their way to get experience in the business, in quotation marks, right? They’ve actual of sidesteps of like a secondment for six months working in, I don’t know, like claims in an insurance business or whatever, right, so running a claims function as an example and things like that. So there’s definitely merit to it. All of this stuff kind of gives us evidence.

It’s not by accident that you have a collective group of people that made it to the very top of their profession as it relates to the size of the job, the pay of the job, the responsibilities of the job, where there’s these kind of themes and traits across all of them that aren’t very similar. So I think, yeah, anything that’s related to sharpening those commercial and business skills and spending time understanding how parts of, you know, the business operates, I think is, you know, is definitely not gonna hinder anybody.

I’m something just kind of been rattling around in my head as I’ve been thinking and listening to you speak. It it’s it’s almost like like disrupt yourself before you’re disrupted.

Right? Maybe from a career perspective. And maybe disrupt is is too too strong of a word, but I think we may be onto something here. Right?

Particularly if you’re a mid career professional and and maybe you’re a little burned out with trying to push the governance boulder up a hill or maybe you’re a little burned out trying to push the data quality boulder up the hill and and you’re you’re passionate about data and you care about data and this is where you want to make your career. But what’s the worst that could happen if you go and work in sales and marketing for a year doing, like, sales ops? Like, being the person managing all the Salesforce data or being the person managing all the procurement data in an ERP system. Right?

Like, at least a sideways move. That’s that sounds like something that would would bear a lot of because in the things that I’m seeing and the trends that I’m seeing is that we’re gonna automate a lot of stuff. We’re gonna automate a lot of data management and stewardship and governance, and we’re gonna automate a lot of business processes. But there will be this happy path that traverses both of those worlds where experts who know both of those worlds and can traverse both of those worlds.

It seems like our our conversation is is giving more and more credence to, hey. We we need we need a utility player who knows both sides of this equation. It’s always been true with CDOs. It’s always been true with CDOs, but it seems like that’s moving down the organization.

What what do what do you think about my ramblings here?

Yeah. No. I I think you’re right. And I think if you think about you know, there’s a lot of debate in our industry, but you get different very different viewpoints on this.

But, actually, there’d be many people that will tell you, if the CEO of a business does their job well to the point of all the things that we’ve been discussing today, they should really make themselves redundant. The notion of needing someone central to a business to oversee data in its entirety across an enterprise, they shouldn’t be needed once they’ve done their job because it should just be that embedded into the business functions that the business leader of that function can do, which leads me on to my second point, which is we all know that data and analytics and AI is going to be a future skill requirement.

It’s happening right now. We’re in conversations with businesses that are turning around and saying, We’re trying to build competency frameworks and skill matrices for our data analytics capability.

That conversation has already shifted because the businesses that did that two years ago now were like, Okay, well, what does that mean in this new world where AI is going to be doing portions of their jobs? So that needs reconfiguring. But also now that’s also being passed into, well, what data analytics and AI skills do people within the business need to have? So think we’re going to end up at a point where, effectively, business people will just have to become, by default, really good with data analytics and AI.

Now, that might not be an immediate thing, but it probably does present an opportunity for data people, to your point, if they want to transition into a specific business function or area and gain leadership chops in that space, that that could be where the future world sits, right? The notion of having somebody that sits centrally and owns data as the oracle of all things data in that organization, as it matures, is that role going exist forever? Possibly not, right? And you’d probably argue the same for AI eventually.

So yeah.

Well, it’s it’s interesting. You’d noted that so many people get into senior leadership roles come from consulting. And I I think that’s easily explainable, which is you you do tours of duty at multiple companies, multiple use cases, multiple large scale strategic initiatives. You get exposure to that, and that’s that’s something valuable.

But what we’re basically saying here is you could become your company’s internal Deloitte consultant or your internal BCG or McKinsey consultant who knows procurement or knows supply chain, who knows procure to pay or sales and marketing.

Seems like that is just solid career advice if you can traverse both of those worlds. Let’s let’s transition a little bit here. I do want you you had mentioned compensation. You had mentioned compensation packages.

And, I mean, I I gotta ask, you know, obviously, you can’t you can’t, dish any names, but you can certainly talk about overall numbers. What are you seeing out there? I mean, I’m seeing all over the map. I’m seeing some of the biggest numbers that I’ve ever seen before in terms of of of comp for senior VPs, SVPs, CDOs that I’ve ever seen, but I’m also seeing, like, a really a lot of lowball stuff, and I can’t get my head around it. Where where are the ranges for for these types of of of roles that you’re staffing these days?

This this is the, yeah, this is the interesting part of it because there’s just a lack of standardization in terms of not just the title, not just the comp, but the responsibilities and accountabilities of the role. So I think what’s probably easier to talk about is if you look at the people who are in the upper echelons of their field, the people that are taking the really big jobs in the big companies that pay the big money, And obviously, there is a very stark difference between the UK and the US. So about sixty percent of our business is in the UK, about forty percent is in the US. So we get a really good view of both sides of the pond.

In the UK, the biggest earners are probably topping out at about one point two, one point three million.

That’s a lot of money.

The UK is big because there’s a lot of money.

There or thereabouts, right? Whereas in the US, depending on the firm and the size of the firm, it could be four, six, eight times that. So there are people in the US who are in that kind of big group chief CDO role who are earning, you know, six to eight, seven figures.

Okay.

Maybe I need to talk to you after this.

I’m I’m I’m all of a sudden, I’m reconsidering going into leadership here. I I got out of I got out of leadership so I could talk at a fancy Mike all day every day, and maybe I should go back and reach you.

I think the the key thing the key thing to note on that is that that is also typically geared around very specific sectors. That usually the very, very top end is usually a banking finance insurance, predominantly speaking. It kind of starts to scale down there.

The interesting thing is on the top end, on the bottom end, if you look at the lack of standardization thing that’s in the UK as an example, if we talk about one point two, one point three million being at the top, there are people with the same title in not the same size organizations, but again, not too dissimilar that might be on one hundred and fifty to two hundred Right? So just the gulf is huge, and there’s no necessarily rhyme or reason to that necessarily.

So Well, let let’s talk about that just for a second.

The no rhyme or reason.

One thing that one of the lessons that I’ve learned after thirty years of being in the game, and I learned this probably in my early forties.

It took me a while because my skull was extremely thick.

One of the things that I learned and and the phrase that I use, and it’s kind of a playful phrase, but I’ve always used it. I’ve been using it for twenty years. Is that there there when it comes to leadership, there are no magic beans.

Right? Like, there’s there’s I I used to think when I was young, you know, twenty something, thirty something working in in the corporate world and trying to climb my way up the man the ladder and I was a project manager and then I was a senior project manager and then I became a senior manager of of a of a of a team leadership function, and director, and then I just wanted to, you know, like climb, climb, climb, climb.

And and I did.

But along the way, I saw people climbing way faster than me.

Way faster than me. And those people are the ones probably ones that are making like, you know, four million dollars a year as a CDL right now and and more power to them. Congrats.

And I saw people climbing the ladder who who I who were not as hardworking. I didn’t think were as anywhere near intelligent, but then again, I got a big ego.

But but who didn’t seem to be accomplishing very much, but what they seem to be really good at, what they seem to be really good at, like, I know what I’m good at. I’m good at complex problem solving. I’m good at collaborating. I’m I’m good at presenting.

I’m good at speaking. I’m good at breaking complex problems down into small pieces. That’s what I know that I’m good at. But these people, what they seem to be good at was climbing the ladder.

And that led me to this conclusion that, you know what? That’s pretty much their core skill with their but when it comes to everything else, like intelligence, drive, subject matter expertise, they don’t have anything that I don’t have.

Is this and is this something that you see in your in in your space? Like, when you when you’re evaluating resumes and you’re going through CVs, and you you you’ve gotta be seeing these people who are who are up in that four million dollar a year out echelon, and then you compare them to the people who were down at one fifty a year.

And there’s not much difference in the role, there’s not much difference in the experience of these, I would imagine. Not a ton of are you seeing that? Is that is that something where you’re just kinda like, why is this person only making a hundred and fifty k a year when they could be making four million?

Yes. I I think you definitely see that, right, because profiles on paper I mean, that’s the thing in this industry. Right? You know, like, resumes and and CVs on paper, they they often look almost identical.

What AI has done to that is a completely other story that we probably don’t have time to address.

To your point, yes, can assess people and look at people and go, Okay, how has that person made it to that role? This person is still loitering around here by comparison, which is really interesting. Think if there is something that is usually obvious, it is usually probably those consulting skills. That would normally be the difference around the things that you said that you were good I don’t think it’s that common, really, in terms of being able to present.

As an example, we’ve just made a shortlist for search as we speak right now. Before I joined with you, I just got off the phone with the business in question, and they basically say, I’m to this guy. He’s very competent, evidently knows his stuff, but basically just talk too much technical detail, struggle to break it down concisely into business language that a panel of business people can understand. And I think that by default is the data person’s way.

And even when you go through and you have conversations with them about, Look, these are the things they’re going to be looking for in a pressure interview situation, people revert to default, right, and they’re nervous. They’re like, oh, I need to show them how much I know. And often, I think if there is one thing that stands out, it’s normally that. It’s the ability to be able to, I don’t wanna say storytell because it’s not necessarily that, but it’s kind of communication skills if you wanna call it that.

And to be honest with you, if you look around the industry at the people that have made it to the top, not all of them, but people that have made it further than the rest, they are probably quite good at self promotion, which goes against the grain for most data people who’d like to be behind the scenes.

Yeah. So if you’re in your twenties or thirties or whatever, any age and you’re listening to this, and you want to break out of what you feel is a kind of you’ve been pigeonholed, maybe not making enough money, ask yourself what are and and you’ve probably worked maybe you haven’t. But if you’re, you know, probably in your thirties or forty, you probably have. If you’ve worked with the BCG, Deloitte, McKinsey, Accenture types who descend on on Monday afternoon because they’re flying Monday morning on business class tickets and then they leave Thursday afternoon, Look at those folks and ask yourself, what differentiates them?

And I think, Kyle, you just touched on a few of them. One one, it’s it’s it’s, you know, in in in Yiddish, would be chutzpah. Right? Like like presence in in in a room.

Right? Presentation. Right? Well polished, well presented, not flapped easy. Right? Like, not shaken easy.

Professional from top to bottom. Right?

Portray yourself as a leader. And even if you’re not a leader, act like a leader. Don’t get dragged down into water cooler talk. Position yourself as a strategist and not an operator.

Now being an operator is great. I mean, I I love your perspective on that one, Kyle. Right? Which is I I think a lot of people who are really good at operations and who are op who are ultimate operators could be c CEOs, could be CDOs, but get pigeonholed down into the to the operational side because they’re so good at what they do.

And they get to a point that they they are seen not as a strategist but somebody who is necessary to keep the engine room running. Do you see that?

Yeah. I think I think that’s fair. Yeah. You know, you you when people are when people are good at that and there is a lot to be said for people that are good at that, right, especially in a data capability.

And that’s the thing. It is absolutely a team makeup, right? And you need all of these types of people. You need the strategists.

You need the operators. You need the people that are going to go and self promote. You need the people that want to sit behind the keyboard and not talk to anybody. You need all of that.

So I think there’s a place for everybody is the point.

Whether we like it or not, yes, the fact of the matter is that there are skills or characteristics required if moving through the ranks and getting promoted and getting the next big job and picking your competitor up here or whatever it is to that job, you know, that’s that’s what it comes down to. And it’s not always fair, but, you know, life isn’t fair. Right? That’s that’s the way it works. So yeah.

One other small thing I would add, and this comes to me from my friend, Saul Rashidi, who who wrote an amazing book about the AI survival guide. But Saul is a seven time CDO. So if there’s if there’s one person that you’d wanted to to kind of, I would say what’s the word I’m looking for? Starts with m.

You wanna emulate. Yep. E m. If there’s one person you’d wanna emulate, man, senior moment, forget my words.

So Sole would be a good one because she she has been a CDO seven times over at some of the biggest companies in the world. And one of the things that she will tell you, and she has said multiple times, is that make the people that you work with, make them the star. Do whatever you need to do to make other people succeed. Do what you need to do to position them as the rock star.

And they and those people, especially if they are above you in the organization, they’ll pull you along. They’ll they’ll they’ll bring you along with them, which is honestly half the battle when it comes to some of this stuff. So, Kyle, I we could speak for hours and hours around this. I always enjoy talking to you.

Always enjoy going back and forth on LinkedIn. You and I are birds of a feather around around some of these things.

If if somebody’s listening to this and they wanted to get in touch with you, they wanted to learn more about what our vision does, what’s the best way to contact you?

LinkedIn is probably the easiest way. Yeah. You won’t struggle to find me. So yep.

You won’t struggle to file find Kyle, and you probably won’t struggle to find me either. If if you find either of us, you’ll it that’ll be the one degree of separation, and we can get each other con connected with you. So with that, I will let you go. Thank you so much, Kyle.

It’s been fun as always. If you have made it to this part of the podcast, you’re still here, please take a moment to like and subscribe and do all the things that the socials like so we can get this podcast to more listeners and more subscribers. We are building a community of data leaders here, and your support is much, much appreciated. With that, I’ll say bye bye for now.

Thanks. We’ll see you on another episode of the CDO Matters podcast sometime very soon. Bye for now.