Good morning. Good afternoon. Good evening. Good whatever time it is wherever you are in this amazing planet of ours. My name is Malcolm. I’m the host of the CDMatters podcast, and thanks for joining.

What you’re gonna experience today is a little bit different. We’re taking a summer break. It is currently late June twenty twenty six, and we’re gonna take a two month hiatus. We’ve been doing the CDO Matters podcast for over three years now.

We have an amazing library of over a hundred episodes, and we’ve never taken a break, which is, like, crazy to think of. We’ve been publishing episode after episode, and this summer, we’re gonna grab a Corona or some other drink of choice. We’re gonna kick our feet up, and we’re gonna take a little bit of a break. But not really.

Because what you’re watching now is the introduction to one of three of our top podcasts from twenty twenty five. We made some good stuff in twenty twenty five. And instead of just leave you with nothing in June, July, and August of the summer of twenty twenty six, we’re gonna leave you with some of the best gems from twenty twenty five. We’re gonna replay those and post them here because we know that a lot of people don’t go very deep in the catalog.

They tend to look at the latest episode, and that’s great. And we appreciate you doing it, but we want the opportunity to highlight some of the best conversations we had in twenty twenty five. And that’s what we’re about to watch. I don’t know which one you’re about to watch, but I know you’re gonna enjoy it.

And hey, if you do, join this community.

Provide some feedback on the content. Sign up for our newsletter. Check out my Substack. Connect with me on LinkedIn, all the socials.

We do this content consistently throughout the year, not just podcasts, but white papers, blogs, LinkedIn. And by we, I mean, me and my amazing team at prophecy.

We’d be thrilled. I’d be thrilled. Keep speaking to myself and third party.

Everybody at prophecy, including me, yours truly would be thrilled if you joined this growing community. That would be awesome.

We’ll be back this fall, sometime August, September time frame, right just before we start to kick off the Data Hero Summit, which is coming this fall again. I think this is the third annual Data Hero Summit that Prophecy is putting on. We’ll be back this fall with some amazing episodes. We’ve got some episodes I think you’re really, really gonna enjoy.

We’re gonna be focusing, of course, a lot on AI. We’re gonna be focusing on the things we’ve always focused on is how to make CDOs most successful.

We’re gonna be diving deep into enablement. How do I actually integrate data foundations into Agenic Workflows? Just a lot of amazing content coming up this fall. I hope you enjoy this throwback version from twenty twenty five.

With that, I’ll leave you to it. Enjoy the episode. I’ll see you all again for fresh and updated and new content in the fall of twenty twenty six. Enjoy your summer, everybody.

Good morning, good afternoon, good evening, good whatever time it is, wherever you are in this amazing planet of ours. I am Malcolm Hawker. I am your host today on the CDO Matters podcast. I’m also the chief data officer of Prophecy.

I am thrilled to be joined by our returning champion.

Our returning champion, if this was Jeopardy. Mouth. By by the way, if you were ever on Jeopardy, my money’s on you, my friend. This this is Mark’s this is Mark Steuce, our our returning champion who would be amazing at Jeopardy. I’m sure tell the truth, Mark. Do you annoy your family when when Jeopardy’s on?

Like, are you are you do you No.

I actually watch I hardly watch any TV.

Oh, you don’t watch it? Okay.

Yeah. It’s kind of it’s, you know, other than the odd historical drama, it’s kind of a waste of time.

Oh, I okay. Okay. Okay. I I get it. I do I don’t watch a lot of TV, but every now and then I love a good Jeopardy. And and I tend to annoy the heck out of my family as well because I’m the one screaming at the TV.

One thing that is very true about my family, and it was a true about the family I grew up in as well, right? Is that the dinner table is debating club and you had better bring your best game.

It’s it’s interesting you should mention that. I actually talk about that in my upcoming book. I’m not trying to plug, but I am plugging. I actually tell a couple of stories about growing up about how debate, including political debate was a normal course of action at our family dinners. It was normal and you’re exactly right. You better bring it because if you don’t, uncle Dave’s gonna have your lunch.

So

Yeah.

And my dad was a triple engineer CEO and my mom was a theologian.

Heart and mind, heart and mind. There you go.

Yes. Just imagine how those debates went. Right? I mean, was right.

But but I’ll tell you though, there there’s something there’s something interesting there because when when you, in my opinion, when you push science to, the boundary. Right? Like, I I fell down like a quantum mechanics rabbit hole a few years ago, and I just like, I started to consume all these books about string theory and quantum mechanics and relativity and all of this stuff. And when you and when you kind of, you know, push Schrodinger’s cat all the way to the edge, you you you reach this boundary where beyond it kind of starts to look a lot like faith.

Yeah, I have to agree with you.

Right?

I

don’t see actually a conflict between what most people call science and what most people call faith, right?

The sheer volume I mean, defines science? Well, right. It’s not what we know. It’s that which we know we don’t know or that we don’t know that we don’t know, right? So I mean, that’s the push. Right? We as scientists, we push into that sphere of unknownness.

It’s it’s interesting you should say that. Like, there there are there obviously, there’s a lot of perspectives here. And, you know, some of the smartest people I’ve ever known all say the same thing. I’ll say what you just say.

Right? Which there is a there is a place to have a conversation about the interplay and the interdependencies and between between faith and science and that there is this there is not necessarily this overt conflict that many of us would have us that many would have us believe that there is. So that’s not why we’re here to talk today. Although that sounds like a heck of a conversation.

A cool conversation.

That that sounds to me that like that that that would be

amazing That’s two fingers of whiskey conversation.

Well, that’s at least oh, yeah. That’s that’s at least two fingers of whiskey for sure.

I may I may have Canadian whiskey instead of Irish whiskey. I I do love my my rye.

It’s been a while. Anyway, okay. We’re not gonna talk about religion or philosophy or string theory, but we are gonna talk a little bit about data. And Mark’s gonna talk today about something that is very near and dear to his heart that he knows a lot about, which is a recent ruling out of a Delaware state court.

State. Yes. Delaware state. Okay.

Relate Chancery court. Yep.

Okay. Chancery. That sounds fancy.

That’s the court that does all business litigation in Delaware. That because of Delaware’s overall position in the corporate firmament nationally and internationally, what it says kind of ripples throughout the country.

Okay. I get it. Kind of like emissions laws in California.

Exactly. That is a really great idea, which I am going to shamelessly steal.

Take it take it repurpose as as you wish. So I I think it is required at this point. I’m sorry. I’m gonna do it.

Neither Mark nor to my knowledge are lawyers. I know I’m not a lawyer. You’re not a lawyer.

No. Okay. I’ve been accused of being one by my lawyers, but but I am not. No.

Yeah. I I am a member of the a you know, the American Bar Association and all that kind of stuff. But I do that as a you know, for reasons. I’m I’m a I’m an expert witness.

So Oh, interesting.

Oh, okay. That’s interesting. Okay. Alright.

But I’m

not giving legal advice, but I can speak to it operationally.

How’s that? Right?

This is our safe harbor statement. Council can’t can’t. This is our safe harbor statement, Mark. Just run with it.

Right? Just just we’re not we’re not lawyers, and all else being equal, seek counsel from your lawyer if you’re looking for real legal advice. That’s not what we’re here to do. We are here to share what we know about this recent ruling related to data and the obligation of people who are in the business of care and feeding of data.

So with that, Mark, why don’t you spend a few minutes just describing this ruling, describing, you know, what what it said, what it what it found, describe and describe at a high level its implications, if if you don’t mind.

Yeah. So this is all about fiduciary duty, which historically has been a very rarefied idea attached to primarily the board of a company and the CEO.

That’s usually the limits of it.

And it also has historically required a very high bar around proving bad intent, basically, to even have a shot at suing for breach of fiduciary duty.

So there was a case that was filed in twenty twenty two by a group of McDonald’s, like the Ambers shareholders.

And it was all about the fact that there was this huge mess around sexual harassment and really bad behavior inside of McDonald’s.

And so that was identified as a breach of fiduciary duty, failure for the board and the CEO to exercise oversight.

And at the last minute, a young associate on the plaintiff side evidently added the name of the CHRO to the suit, didn’t have any kind of legal basis to do so at that time, but this guy was fairly egregious and just felt like he deserved to be on the suit, I guess. So then what happened was is, keeping the conversation focused, is that in a great surprise landmark ruling coming out of this case, Delaware chance report vice chancellor took the opportunity so like a big time judge, right? Took the opportunity to reset the bar, reset a lot of things about fiduciary duty in any company domiciled in Delaware.

But now it’s kind of spreading all over the place. So the odds of everybody that’s hearing me being impacted have gone way up in the last two years. So in January of twenty twenty three, this judgment came out, and the judgment basically says, you no longer have to prove malice or bad intent or anything like that.

Pure just bad faith and redefining bad faith as negligence, unwillingness to oversee something that’s really important.

That’s enough. And also for the first time, we are now spreading this responsibility to all corporate officers.

Okay, so you got to look at it from so the premise here was the judge said modern business has gotten too so complicated that there’s no way that the board and the CEO can discharge their fiduciary duty to shareholders without the active and integrated support of all officers, because that’s where they’re getting their information from.

What this means is now all corporate officers have individual liability for failure to identify and remediate risks and bad performance in their area.

So it’s not about I want to be very clear this is not about you didn’t make your sales goal, you get sued, Okay? That’s not what this is.

Is putting it proactively, if I were to go back into a large company as a chief marketing officer, I would sit down in an off-site with my senior team, and I’d say, we’re going do a SWOT analysis, but we’re going to really focus on our team. And we’re going to really focus on our risk factors. And we’re going to document those risk factors nine different ways from Sundae.

Right? And we’re going to document what we think is going to be necessary in terms of time, money, and effort to remediate those risks. And then we’re going to file all that upstairs with the general counsel and the CFO.

And hopefully, we’ll get what we need to mitigate those risks. But now they’re identified, and we can show that we did our part.

So on the data side, what we’re seeing right now is that as shareholders, and particularly activist shareholders, and there’s all kinds of flavors of activist shareholder, all kinds of sizes of them. It’s not just Elliott and people like that, right? So they have figured out that virtually every business in America today has a horrendous data situation.

If you look at kind of recent surveys and reports and all that kind of stuff, right, it’s somewhere low 90s to mid 90s percentile of data is crap inside of most corporations.

It’s either crap in terms of quality and accuracy, or it’s crap in terms of accessibility.

In other words, it’s just one way to kind of talk about it more conversationally is, is this data can this data support enterprise AI?

And the answer is usually not a chance, right?

Shareholders see that as profound risk, competitively speaking, in lots of other ways, right? So the lawsuits are starting to accelerate fairly dramatically, and it’s really focusing in this area.

So interesting. Let’s let’s put a few disclaimers out there. Well, first of all, I should have mentioned this a bit at the top, by the way. Mark is the CEO and founder of ProofAnalytics dot AI. They’re a causal AI company. We’ll talk about that probably a little bit more because there’s a connection, obviously, here to what you do day in and day out. Just wanted to get that out there.

Delaware. So this is a state ruling, but Delaware is important because so many companies, particularly big companies, are actually physically well, not physically, are legally, I should say, domiciled in Delaware. If you were operating all over the place, you are General Motors, you’re Ford, you’re Tesla, you’re whatever. I don’t know if those are actually domiciled in Delaware.

But do you know, Mark, like what what percent of of US corporations are are in

in Yeah, it’s like global one thousand or something like that, Roughly two thirds are domiciled in Delaware.

If you’re talking about PE backed companies, so obviously smaller for the most part, It’s ninety percent.

Wow. Okay.

Right. Most VCs, for example, mandate that the company be domiciled in Delaware because the case law and everything else is so robust, and you know they know what they’re getting into, whereas you know you put a company domiciled in Wyoming, that’s a whole different deal.

Well, right. Yeah. I’ve got one domiciled in I’ve had one in Texas and I have one now in Florida.

And companies choose have historically chosen Delaware among other reasons because of the perception of business and commerce friendly judiciary. Right?

That that’s one of the that’s what

would say. I’m gonna actually correct that slightly, and I would say

Which is?

Shareholder friendly.

Shareholder friendly. Okay. Interesting.

Alright. Would business friendly.

Okay. Fair fair enough. Fair enough. Well, that that that chicken has come home to roost in the case of this ruling.

Because if you’ve got shareholders saying, my shareholder value has been negatively impacted because you didn’t manage something properly and I deserve compensation for that. That’s basically what the ruling is saying. McDonald’s, you screwed up. You knew that there were shenanigans going on.

You should have had more controls in place. You didn’t.

And that extends beyond just the c suite. Now that gets into officers.

Do we know what an officer means?

Yeah, basically it’s you’re either named as one, or if you have that word in your title,

okay,

r o c r whatever, right?

But also there’s a lot of them that don’t they’re not they’re non obvious officers, but they are carried as one in the corporation.

And there are actually so one of the more interesting things about this situation is two things actually. One is we live in probably the most litigious society in the world, and yet nobody has challenged this ruling in two years, more than two years. No one, right? And so I was talking to some lawyers about this, and I said, Do I have any thoughts on this? Like why that would be?

And they’re like, Oh, that’s easy.

CEOs and boards love this, because now all the liability is spread out across the company. All these officers share this liability, right? And I’m like, Oh, that’s yeah, okay, that’s pretty interesting. And indeed, what happened ultimately with McDonald’s was they pinned it all on the officer, the CHRO in this case, and let the board and the CEO off the hook.

And so there’s there’s going to be more and more and more of this, right?

And then, you know, there’ll probably be some tweaks to it, there’ll be a rebalancing of it and all that kind of stuff. But the personal accountability piece is not going away.

Well, so you raised something really interesting. I mean, you started talking about data quality.

And it immediately harkens me back to my halcyon days of my youth in the data and analytics space. And the first the first time I I ever landed my own consulting SOW to help a to help a company figure out their data, and I was hired to answer one question.

This was this is I won’t name any names, but it was a publicly traded company. I was hired by a company to answer the question of how many customers do we have.

I remember calling my mother that night, my mother and father, and giving them the the update. You know, this is the this is the son who’s flown the coop and is now, you know, in a different country and doing these cool things. And I said, hey. It’s a big day.

I’ve I got basically my first sale and my you know, I because I’ve got my own consulting gig. And and I said, you know and they said, oh, well, that’s great. What are gonna be doing? Said, well, I’m gonna help this company this customer this company understand how many customers they have.

They’re like, what?

Yeah. Yeah. I’m gonna help them understand how many customers. What do you mean they don’t know how many customers they have?

They don’t know how many customers they have. Right? And and, like, but that that idea in and of itself. Right?

This may sound mundane and it may sound silly, but if you are a publicly traded company and you’re reporting revenue to the street

Yep.

That is that is not necessarily backed by data or has fudgy data or the data is very the data quality to your point is very low where it’s possible that that number isn’t accurate because your data quality is so low. What this ruling is suggesting and what you suggested previously is that if you didn’t have the right systems in place, the right processes in place, or that you were not doing a sufficient job to manage for data quality, that you could be held reliable you’re reliable, you could be held liable for that in a court of law, at least in the state of Delaware.

Yeah, actually I was it went to settlement so fast that I never actually got to play in the game, but there was a

Meaning as an expert witness, you had mentioned you’re an expert,

there was a case, California company, large ish, not like you know huge, but pretty damn big, who was a Delaware domiciled company, and were sued for breach of fiduciary duty around one thing, and that was their CRM data quality.

And I was like, oh they are so toast, right?

Because I mean if you’ve been in the

and I have

heck at all, right?

You know this is like a meme. I mean, everyone knows that it’s screwed up, right? And so the plaintiffs got the judge to authorize the install of piece of software ‘s used to it’s patterning type software, used to find patterns fraud. It’s used a lot in Fiserv companies, and basically two thirds, a little more than two thirds of fourteen years worth of CRM data came back as, I think that the polite term was engineered.

Like Theranos engineered? Like that level of because that gets to intent, right?

Yeah, that’s correct.

So like a lot of them, this company was really well known in the sales area for doing SPIFFs, SPIFF programs

Okay, okay.

To mainly accelerate, to incentivize deals to move faster, to sales guys to get with the program.

And they because of the rules, they found a lot of evidence that deals were not declared when they were actually should have been declared. And so they were triggering these extra payments illegitimately.

So now this company probably I don’t know this for a fact, obviously, but it’s probably sitting there going, Okay, so we have a bunch of people that we probably need to go claw money back from, but is that realistic? And do we really want to go do that? And you know, and all that kind of stuff. But it was bad. And they they were they got a sealed deal.

Sealed settlement.

Right?

Which is why you haven’t heard about it.

Right, exactly.

But it’s a huge amount of money.

So this is fascinating. So you’re a former CMO of a Fortune five hundred company.

You are an expert in AI, data and AI. So you are the expert witnesses getting brought into these cases. Right? You’re you’re you’re getting to see, you know, these these the the kind of sausage being made on the fly, at least in the perspective of litigation around some of this stuff. You just gave one example of that.

You talked about CRM data, and, yeah, it is a meme. Right? It it is a meme, but there are so many things in this that we could be talking about here. The list is just it’s just so long. I mean, how many sales organizations have you worked with where there wasn’t tomfoolery going around from a forecasting perspective and a pipeline perspective? Right?

Everybody

Yeah.

That’s that would be a the only answer would be zero.

Exactly. Like, gamesmanship around and I’m not I’m I’m not casting aspersion, and I’m not casting judgment. It’s just it just is what it is. Gamesmanship around sales pipelines and forecasts. Right? Salespeople don’t wanna necessarily be held too much or they or they or they sandbag or they, you know like, all of the gamesmanship around how deals are being reported and managed in a CRM.

What you just said now this was a little bit different. This is like paying sales spiffs on deals that hadn’t actually happened potentially. But I could easily foresee a situation where that if you as the CDO or e or the CMO either or the CIO pick, go ahead, depending on the organization, didn’t have enough processes in place to make sure and didn’t have enough controls in place to make sure that that the inaccuracies in that world weren’t flowing into what was being reported on a ten ks or ten Q, that is a huge problem.

That’s a very huge problem. I think that for a longest so like if Delaware had passed this ruling ten years ago, right, it would have been marginally enforceable.

Right.

Right. What is really happening today is it’s incredibly enforceable.

AI in general, not just causal AI, other kinds of pattern match AI, is able to rapidly figure this out. And so it’s very, very interesting conundrum.

We have all, all of us, me, you, right, we’ve all operated within what I call a zone of ambiguity for most of our lives.

And that zone of ambiguity was actually quite large.

I define zone of ambiguity as where my representation may carry just as much weight as yours, kind of depends almost on my ability to present well, present better than you, and all that kind of stuff.

That is shrinking substantially.

I mean, one of the things that AI, particularly causal AI, is going to be in the future is a giant ******** detector on all kinds of things.

And and it’s just gonna be a lot harder to fade the heat.

Fade the heat or or or claim ignorance.

Yeah. Because everything will be known or knowable.

Right.

Okay. That’s that’s fascinating. So as you’re listening to this, if you if if you find this interesting, I would invite you to check out next weeks or two weeks from now’s episode where I’m interviewing Bar Moses. Bar is the CEO of a company called Monte Carlo.

And Monte Carlo is what’s called data observability where what they’re focused on is, for lack of a better word, forensics around data and understanding some of these patterns that Mark was just talking about. Right? Like, patterns that would lead you to that would lead anybody to naturally conclude there’s fraud happening here or patterns that would lead you to conclude that there is some massive data quality issues that could otherwise have been stopped through better controls or better process or better governance. So a lot of these issues are kind of come coming and coalescing together, but what you’re saying is there’s increasingly no more plausible deniability.

There’s no more sticking our hand in the sand.

And I’ll tell you this too. Right? I mean, the natural human brain functions as a correlative machine, right? It’s paddle match.

The problem is that as causal becomes more and more accessible, then you have to worry about the delta.

So I actually did some work mathematically, really kind of got into it and had four different tools double check me and had a mathematician who wouldn’t want me to use his name, but he’s like one of the very best in the world. He double checked it.

So you ask let’s say you pose five different questions, and you ask correlative math for an answer, and you ask causal math for an answer, everybody, I think, that with a brain cell knows that there’s going to be some difference.

But it is actually really staggering how much difference.

It’s between three thousand and seven thousand basis points of difference.

That’s just the norm, So that’s thirty percent to seventy percent delta on the two answers.

So the ability to rely on correlation outside of certain clearly indicated use cases and all that kind of stuff is just not there.

And so you’re going to have to really one of the things that’s already being asked in these depositions is they get really technical. They’re saying, how do you know?

What technique are you using to understand this?

And if it’s the wrong one, then you’re kind of cooked.

Meaning, okay, so the wrong one being, in this case, some idea of a correlation. Meaning, I’m a CDO and I’m under I’m trying to understand buyer behavior.

For example, I’m I’m trying to understand buyer behavior because I report expected future sales maybe to the street as a part as a part of some sort of filing exercise, safe harbor agreement, you know, safe harbor notwithstanding, forward looking statements notwithstanding, I’m still go as a CEO or CFO, I’m still gonna probably say, you know, we are bullish on the next quarter.

Right.

And if in a quarter loss somebody asks you, okay, how did you conclude that you’re gonna be bullish? Right? How did you conclude that you are optimistic about the sale of this product?

And you said, well, I I did a correlation between a and b, and we know a is gonna happen, and we rely on b for our product sales. That’s how I came up my data. That court is liable to say, okay, not good enough.

Yeah, absolutely not good enough, because

If they didn’t become true, by

the way.

The world is not a one on one relationship, right? Right.

And so it’s a now what I do think is a legitimate answer is, you know, we used different kinds of correlative techniques. We used causal inference techniques, and we did like statochistic techniques, right, or something like that. Right? I mean, so we looked at it through a variety of different lenses and we triangulated, and that’s where we came out. Right?

I think that that right there is the kind of answer excuse me, in the context of the ruling that would be almost impossible for a plaintiff lawyer to get passed.

Okay.

So We’re kind of belt suspenders. Right?

Right.

So before we get into our our last discussion, which will be around what do we do, acknowledging there’s probably no one answer here. Before we get into the kind of the what we what would we do? What should CDOs do?

I I do wanna just kind of focus on, you know, something we had talked about before we started recording, which is this idea that Delaware tends to be a bit of a bellwether for the rest of the country.

You know, this idea of California emissions. Right? And and what happens in California from an emissions perspective almost ends up happening everywhere else.

You know, there are a lot of our listeners who are maybe listening from outside the United States, including Canada and Europe, who are like, wait a minute. Why does one court in Delaware even matter? Right? Why does one state court in Delaware? Well, it matters because there’s a lot of companies, and it also matters because other other states will will start to adopt these rules over time.

Is there a possibility, though? Of course. I mean, I already know the answer to this, but let’s talk this is very briefly about, you know, legislation in and of itself. Right? We we talked about Sarbanes Oxley and, know, how that was a legislation, and it took a long time to kind of dribble out.

Took a number of years to kind of really take foot take a foothold. Are we seeing the same thing here? Would we expect that maybe the legislative branch will take some action either to harden this or maybe undercut it? What are what are you hearing out there?

Yeah, don’t think so.

Think that in the case of Delaware’s own legislature, know, they’re actually trying to go a little bit the other way and make Delaware because there are some big tech firms that are making noise about leaving Delaware for the Wyoming or the freedom of Texas or whatever. Yeah.

Think that the legislature, for that matter legislatures in general, really prefer the courts to be the iron assets of policy, right?

And so they’re going to totally let the Chancery Court in Delaware do that.

However, you know, Texas has already started to cite the Delaware ruling in its cases.

Oklahoma, I mean, these are clearly redder than red states, right, are going this way.

California, New York, so those are two blue states. So I think that there’s a general view that this is good, not bad.

And I think that one of the things that’s going to be a little bit awkward, I mean let’s kind of call it what it is, is when AI really takes hold in the decision making and vetting processes of corporations, we’re all going to find out, you know, kind of like how wrong we were, right, on a whole bunch of stuff.

Yeah.

And that’s not going to be there’s going to be no respecter of persons, no respecter of rank, no I mean nothing, right? I mean, it’s a totally different situation, but this is something LinkedIn is grappling with.

You know, seventy percent, according to them, of the content on the platform is ********.

Yeah. Yeah. AI generated.

Yeah.

And and it’s just but even if it’s not, it’s still it’s

Human baloney versus machine baloney.

Yeah. Yeah.

You just kind of sit there and say, there’s a and people kind of like at some level understand that that’s true, right? And so it devalues the platform, and they’re kind of wondering how they can best fight that.

And I may have said something like, well, you’re just going to have to put a little ******** meter on people’s pages, right?

That’s tough. They don’t really want to do that, and I understand why they don’t want to do that.

But it really does kinda come down to that.

So this this is another tangent and another rabbit hole that we could fall down. Right? Like, because, you know, getting back to the idea of proof, you and I have been in the business world and been in data, been in senior leadership roles, you know, we we can generally smell this stuff a mile away.

Smelling it and inferring it and deriving it is very different than proving it at scale from the perspective of a link of a LinkedIn. Right? Improving it and what I mean by scale, like in an automated way. Right? So that’s a really hard problem to solve, you know, especially since there there are gradations.

You you and I have actually had some very interesting kind of back and forth on this in terms of, like, what is true and what is not true, and some of the rigor that you apply to some of your posts, which is, like, incredibly laudable, by the way. Like, if guys, if you ever read anything from Mark Stusa on LinkedIn, just just know that it’s been vetted and that Mark actually has, like, a a structured process for vetting his own content and feeding it through multiple systems to to make sure that he’s not saying anything that’s that’s total crap.

So so sleep

I sleep so much better at night.

Right. Well, yeah. And and and you should be lauded for that. And and I I absolutely, you know, I’m I’m two thumbs up entirely on that.

But I also acknowledge that, you know, this notion of truth can be contextually bound, and there are objectives and objective truths, and there are subjective truths at times.

And that’s actually one reason why I think it’s really important to stay away from that word.

What truth?

Yeah. Oh yeah, it’s loaded. Loaded. Yeah, I think that I speak about facts.

Yes, you know, but the argumentarian in me, you know, facts can change over time and they always do.

Our our understanding of some facts changes

over Yes.

This this is this is this is why LinkedIn remains actually a really wonderful place to hang out and meet smart people like Mark Stews.

And and and I love it. Anyway, we we digress. Let’s get back to okay. I’m a CDO, and I know I got some problems because I don’t know any CDOs that doesn’t that don’t have a lot of problems when it comes to data quality, when it comes to data management, data governance, you name it.

This sounds a little scary to me. Sounds a little daunting to me. Maybe I just might wanna go open that winery instead or or go do the passion play instead. But let’s assume that I’m passionate about data and I want to keep doing what I’m doing.

Is this a five alarm fire, a three alarm fire, a one alarm I

think it is actually a five alarm fire for a lot of reasons.

I’m actually in a situation right now with a client where they’re being asked why they have so much data.

And so I was in the room, and I said, well, can you give a little more color on why I mean, why do you care about data volume?