Interview with Mark Stouse

You're listening to One Sharp Sword cutting through to what Matters Most with outfluencer Dr. Wayne Purnell.

Welcome to One Sharp Sword Cutting through to what matters most. I'm your host, your guide and your coach on this journey, Dr. P. Dr. Wayne Purnell. Today I have with me a special guest. My guest is a gentleman who lives at the intersection of CEO, CFO and cmo while at the same time bringing a what I would call a philosopher's curiosity and a radical pragmatist discipline to how leaders make high stakes decision decisions. He's the founder and CEO of Proof Causal AI and one of the most thoughtful voices and one of the smartest men I've ever met. Thoughtful voices on causality, fiduciary risk and executive accountability. My guest, welcome, Mark Stuss. So glad you're here. Amazing.

Thank you.

Yeah, so good. So yeah, the background on this. I met Mark, you know, doing some outreach to leaders and he responded saying, sure, I'll have a conversation with you. And in having that conversation, a 30 minute call turned into over two and a half hours. It's true, oh so true. Yes. Rare that you find somebody that just sparks you and you keep going. It's good. So I'm smiling already at, at what we're about to produce and I have no idea what that is. Let's talk a little bit about, about proof causal. Let's start there, what you're doing, why there's a need for it and, and, and how you created it. And then I'm going to ask you to back up and go, okay, so what got you there?

Right?

So but start, start by talking a little bit about, you know, proof causal. This is what we do, this is how it works.

So causality is really the nothing more, nothing less than the study of why things happen the way they happen, what makes them happen that way. What could you have changed to maybe arrive at a different place or different outcome. You wanna, it's not just about what you do. So let's say that you're running go to market in a corporation, right? It's not just about the stuff you control. It's very much in fact mostly about what you don't control. And in fact if you don't, that's like 70 to 80% of the whole equation is what you don't control and how you react to it. And so really understanding that and then putting it all together is what Causal AI, which is actually, you know, a whole category of AI. It's not just for us, right? We have excellent competitors in the space. And it, it brings it all together and allows you to quickly and in a very agile sort of way create these causal models to look at whatever it is that you're trying to understand better and thus make better decisions about. And so we do work with, you know, probably the more and more of the mid tier and then obviously the enterprise.

So do you specialize in any particular vertical? Could it be banking? Could it be retail? Could it be. No.

And actually we don't really have to. We have to, you know, the, the tool itself, the math. Right. Is agnostic. Right. And it's very reality based. And so you don't really have to worry about that. What we have really learned how to do across many different verticals and many different situations, because even within a vertical companies are different, is we really have gotten, I think, pretty good at asking really good questions. So we ask clients, you know, tell me, tell me what you think is going on here. You know, if you think about like macroeconomic factors, interest rates, things like that, tell me how that impacts your business. How does it impact the way your customers make decisions? You know, so we ask, that's, that's.

Really the key, right? How do customers make the decision to buy? Really? Right.

Yeah. And the same thing is true for investors. What makes them want to invest, what makes them feel scared to invest? You know, attracting talent, keeping talent. Same idea, right. I mean basically there's kind of, there's kind of like three vectors that are fairly constant across any question you want to ask. And that is how do I get more of something? How do I make it better or deeper or more profitable or whatever. It's qualitative thing. And then how do I accomplish that faster?

That's awesome. I mean, those are questions we should all be asking ourselves, right? How do I get more of something? The thing I want, how do I make it better? How do I make my life better and how do I do it faster? How is there some magic to parsing out. Correlation versus causality?

Yeah, it's completely different math. I mean like completely different math.

And it's just math. That's all you look at mainly.

Yeah, yeah, it really is. It's mathematical technique. Right. That's, that's effectively distilled into algorithms. Right. But it is very different math. Right. Correlation. Go ahead.

I guess. How do you know what to look for? You know, it's, it's like in the summertime it's easy to say ice. The increased use of ice cream causes sunburns. Right. It's it's like that happens in the summer.

That would be correlation for sure.

Exactly. So how do you know what to look for when you, when you go, well, it's summertime, of course more people eat ice cream. Of course more people are outside. Sun causes sunburns. But it's easy to correlate an increase in ice cream use with sunburns. So how do you know what. I guess really what not to look at?

Yeah. If it. I mean, this is not a perfect rule by any means. Right. But if you can't. If you can't figure out a mechanism by which ice cream causes sunburn. Right. Then that's correlation. It's not causality.

Well, I mean, obviously.

And that. And obviously, obviously ice cream doesn't cause sunburn.

Correct.

Right.

I'm. I'm using it because it's a really easy example.

Right.

It's like it's in the summer, increased use of ice cream. Increased. Increased cases of. Of sunburns. Therefore.

Yeah. Like, I mean, like in business. Right. Again, we'll use go to market just because it's a great. It's a great way.

Yeah, good one.

70 to 80% of why people buy from you or don't buy from you has to do with where they are and what's going on with them and what's going on in the marketplace overall. Not. It's not something you can dictate. Right. You can make happen. So the primary impact causally. Right. Is. Is. Is what I just said. The, the reality is that you have got to figure out your angle. Like how if. If the interest rates are going up and that is on the surface, a reason for your customers not to buy, how do you transform that into an opportunity to buy? How do you add so much value so fast.

Right.

That it overwhelms their fear? Right.

And that's causal.

That's causal right there.

Do you guide, then Is, is that your role, or is your role simply to point out you can't control this 70 to 80%? And so is that the guidance or do you actually.

Yeah, well, you can't control it, but, boy, you'd better understand it as best as you possibly can.

So then do you guide your. Your clientele on what to do?

Yeah, absolutely. I mean, we, the first model that we actually create for most clients is a marketplace model and helps them understand the environment in which they are doing what they do. Right. And that is usually extremely illuminating for them.

It's extremely eliminating. Oh, I heard eliminating. It's like, what do you call that?

Too. Occasionally. Yeah. But I mean, it's. It's a. There's kind of aspects. I mean, I would. I would not want to, like, stretch this too far by any means. And I'm not a therapist. Okay. But there are.

Do you play one on TV at least, anyway.

But not, not really. Not like in a classic therapeutic sense. No, you know, the, The. But you. You know, I, At. You know, what I'm trying to do is I'm trying to use the Socratic system, the Socratic dialogue system to ask really great questions that make them think about things that maybe they haven't thought about before. And you become progressively more and more and more discerning about what's actually happening. And, and what is a pattern of behavior? And what is materiality in that pattern? Right. I mean, it's kind of a shock for a lot of people when they. When they hear me say this, but about 80% or so of patterns that we observe in life have no significance. Right?

Yeah, we. We attribute meaning where there is none.

That's correct.

Yeah.

And so that in one very real sense that is what we're trying to accomplish with causality is to say, hey, these three patterns actually really do mean something. Anyone who, who wonders how a. A repeating pattern, in other words, something that people do over and over and over again could possibly be not material, I would only point you to a website. I can create a website that drives very strong patterns of human behavior that mean nothing. In fact, that happens all day, every day in most businesses around the world. Right.

So social media is driven by it.

That's right.

Right. So it's like, if I can make you feel afraid of something, you're gonna start paying more attention. That's right. And then if you get input from someone else who says, did you see this thing? And now you've got social proof. Now there's two people giving meaning to something that doesn't actually exist. Right? Yeah, that's right. Yeah.

No, it's. It's a. So, I mean, it's one of the things that's really an accurate statement to make here is that causality is all about reality. So we don't really. We. We don't talk about truth. Not that there isn't truth in the world. There is. Okay. But it's kind of what my mom used to say was a conversation stopper, because truth usually has a lot of belief in it. And if I don't believe what you believe, then we've just killed the conversation. Right. So nice, though, in terms of making Progress. Truth is oftentimes not again, this is not all true all the time, but it oftentimes is not helpful. Then you have facts and facts are better, but facts change, right? So the common they use the, the example I use all the time on that is that I can remember when Pluto was made a plan a planet. And I can remember when that status was taken away from Pluto and it was. And they said no, that was a mistake. It's really a moon, right. Not a planet. Both are fact statements, but because we figured out things in between those two, right. One isn't a fact statement anymore. So facts are useful, but they're not determinant. What is determinant at any given moment is what is reality. Regardless of whether we understand it completely, there is an. An objective reality. And so that is what we are seeking to study and illuminate. Right. Using causal AI.

Nice. Nice. And yeah, it's interesting. I love this. The. I'm, I'm a big proponent of truth and that's because I'm a big proponent of the individual. So each individual has their own truth and to my mind they must pursue that truth. Not, not forsaking or excluding other information that might change that for them. But if they have a belief and they want to live into a more.

How would you, how would you differentiate but between truth and belief?

And let's add one more which is faith. Right? So yeah, yeah. So a personal truth is a, is a. Is strongly founded in belief and, and, and belief is. Belief and faith overlap at this point. And so belief like the, the difference between regret and worry.

Right.

Anxiety about the future and regret or shame about the past is that it is belief placed in the wrong direction.

Right. So. So let me give you an example of how that plays out in our line of work. Right?

Yeah, perfect. This is. Right. So can I jump in real fast? This is. Let's. A business owner goes, I've got a really strong gut feeling about this and I want to produce tada this whatever XYZ is. And you go, sounds good. Then what right is that? Well, you're gonna go with it or.

The way I was going to illustrate it is. Aggregated belief. Right. Is tribal wisdom. Okay.

Oh, that's well said.

Okay.

Yeah.

And so what happens though when the tribe is objectively wrong?

So a great example that happens all the time, right. It's generationally we were taught, right. We were taught this and we were taught that. And you know, grandma used to make the pot roast by cutting off the ends. So we all make the pot roast by cutting off the ends.

Why?

Because her pan wasn't big enough to hold the pot roast. So we all learned to make the pot roast.

That's exactly right.

Right?

Yep, yep. It, it. If we, if we were able to peel the onion and get all the way back to the original fact set. Right. We would find most often something like that.

Yeah.

Right.

Yeah.

So like the go to market professions have, where you really see this very powerfully is in gen AI tools like chat GPT and. Okay. Because what they're doing is, is they are a. What's called a stochastic mirror of human tribal knowledge. Right?

Yes.

On the Internet and you know, in particular on the Internet.

Yeah.

And so you, you get a situation where there's a. There are domains like physics that are dominated by fact. Not they don't have opinion in them, but it's very strongly skewed towards evidence. Let's call it evidence. Right. And then you've got domains like marketing and sales and leadership which are dominated by non fact. And non fact can mean everything from personal opinion to outright lie, an untruthful to our best guess, our best practice, our accumulated experiential knowledge. Okay. But because we can't say yes, we know this to be accurate, we call it non fact. Okay. Now the problem with this is, is that like in the go to market area, those tribes have some of the strongest cohesion culturally of any professions and they get their information from each other, which actually has been a huge part of the problem for quite some time. Because a lot of what they pass along to each other is not correct, not accurate, not representative of reality. And we can show that, we can prove that that's, that's not just another form of opinion. Right. That's not belief. That's not my truth versus somebody versus their truth. Right. This is reality. It's kind of like gravity. Gravity doesn't give a rip whether you believe in it or not. If you have a personal truth that says that gravity is a fiction and you choose to jump off of a building to prove it, the same thing is going to happen over and over and over again. That is a deterministic outcome.

Yes.

Where you land and whether or not you land on somebody else is in is totally probabilistic.

Okay.

So that's, that's kind of where we are right now. And, and the reason why that is coming into sharp focus right now is that the environment in which we all operate is full of turmoil.

That's for sure.

Okay. And very rapid change. So it's invalidating all of the past patterns.

That's interesting too, then. See, this is why I love talking with you, Mark, because it, it just sort of sparks some things in me. From my perspective in working with humans, either as individuals trying to get better or as individuals who are leading teams or as a group of leaders.

The.

Truth that they have to present is changing. Right? It's like the. Because the information they're getting is changing. We as humans now are in a space where we are questioning the things that we were taught, which is great news in so many ways and terrible news in so many ways. Because now it's like, well, who. Right? There's the existential dilemma even stronger of who am I? If what I've learned is no longer accurate, then who am I? And the good news is you get to be whoever you want. Follow certain laws, right? Follow certain rules, like gravity. I mean, there are laws of, of the universe that exist. Great. Follow those and create what you want. Do you. I'm gonna bring this back to, to the work you're doing. Do you have like a use case? Do you have a, do you have a case example where somebody called you and said, yeah, help us where we're going and how to cut out the things that don't matter? Like, is that why people would call you?

Yeah, I mean, that may not be. It may be a little more practical and less philosophical or elevated than that. Okay. But you know, they will say, wow, you know what? We get the feeling that what we're doing right now isn't working anymore, and thus we're worried about wasted spend and how to improve allocations and things like that. Can you help us? I. I had a call today with people representing a large pharmaceutical company who was getting pretty concerned about its go to market. And it wanted to know. These people wanted to know if we could help them. And I said, look, I said, it comes down to this. It really does. You're doing all this stuff to accomplish this, these outcomes over here, you've got all this stuff that you don't control in the middle. These are headwinds, tailwinds. You either, you know, there are the known knowns, the known unknowns, and the unknown unknowns. Right. About that.

Right.

And you've got to make sense of that. And what you're going to find out when you start working with causal AI with proof is that probably about a third of what you've been doing, minimum, is not working. So now you know it, you can stop spending that money on that stuff. So that's really good. You just saved a bunch of money going forward. And you can then invest that money in other things that you know to be working now because of the models. And so this is classic opportunity cost. In this case, you're winning both ways, not losing.

That's great. Yeah, that's great. I love this.

So basically, even though this is going to sound like I don't want it.

To sound okay, nice inoculation.

I, I, I really believe in and support personal freedom, personal agency. In fact, you could argue that what I do, what we do at Proof, is all about improving that. Improving personal agency, improving outcomes, improving decisions. Right. That said, if I hear somebody say something in their, you know, professionally, in their area. Right. That we already know to be not true, I would not be acting in their own interest if I didn't raise that and didn't attempt to show them the evidence for a different point of.

View if they were a client. It's not like you walk down the street and you go, there's some BS right there.

Oh, no, yeah, that's very true. But when I'm here on a, like on a podcast, one to many type of thing.

Yes.

And, and I'm doing it right now. Right. I mean, I'm sort of doing that. I'm not, not.

Yeah.

I mean, the only, the only thing that, that gives me permission is you. And the fact that they chose to listen to this conversation.

That's great. So, so, I mean, personal agency is really, what you just said in a, in a different way, is that you have personal agency over about 30 of your life.

Yeah. At most.

Isn't that great? Like, I think it's, I think it's an amazing thing to actually say and go, okay, so 70 to 80% of your life, you have like, it's just out there. And, and partly it's because of what other people do. Partly it's.

It also breaks, it also breaks down further. Right. Depending very much on the situation.

Yeah.

So Major league baseball player. Okay.350 batting average. Okay.

Oh, I love this. Yes.

That's a heroic batting average. And yet it means that you struck out two thirds of the time.

Yes.

On an academic scale, on even a business performance scale, you're not just a failure, you're a abject failure.

Yeah. Epic, Epic failure. Absolutely.

So, I mean, we talked about surfers, right? Champion surfers. Their wipeout rate is 98 plus. And, and so the payback on that 1%, forgetting the money for a second, just psych. Psychically psychic income has got to Just be intense for them to put up with the 99%.

I love this because it just sort of came to me during this conversation is that we do get to choose a hundred percent agency in the 20 to 30% we can control.

Yeah. Or, or in those two examples, less or less. Yeah.

In, right. In, in sports, in baseball, in surfing, much less. See, because if you said what you did, we have control over 20 to 30% maybe of our lives. That's pretty upsetting, right, For a lot.

Of people that, that is, right. I mean, particularly if you are the kind of person who believe that you're a master of your universe. Right. That's a very discouraging statement that I just made.

It could be. And yet, and I take it personally.

I, and I don't lack ambition. I'm pretty type A. Right. It was when I realized that like for real, it was actually quite liberating and, and, and not in that it liberated me to be somehow lazy.

Right, right. You didn't abdicate at that point.

No. But what I really did realize, this is something that, that my parents used to say all the time to us when we were growing up. Right. Your obligation is to do your best and to do what is right. And you have no control over the outcome. And existentially that is true. Occasionally we have a, let's call it a run of luck, right. That makes us believe that somehow we have defied gravity. Right. And that we are somehow much better than everybody else in terms of controlling our fate. And that is a delusion.

Doesn't the ability to believe in a particular way influence where you put your energy? And doesn't then where you put your energy influence the effect on the outcome? If you go to a.

Leaving out the third leg of the stool though, gotta understand reality.

Good one. Okay, so using the baseball player, right. There's this belief I could be an all star. And that belief brings that person to practice more and to get, get in front of the right people.

Right.

Then. And then there's the reality of there are thousands of other people who have that belief and are trying to practice more and be in front of the right people. And then you don't have control over the outcome of who the scouts pick, but you have control over your outcome of having been in that place to be among the selected or among the observed for selection.

The other, the other part to this, which is where it really gets pretty stout, right, is that almost everything in life from a cause and effect perspective is time lagged. In fact, the only thing that Isn't time lagged?

Yes.

Really bad stuff.

Wow. Okay.

Okay.

So go offer more, please. This is great. This is great.

So, you know, there's an immediacy to bad stuff that you think about a. So somebody murdered Rob Reiner and his wife last night.

Yes. To put a time stamp on our, on our podcast. Yes.

And so that is a. That's something that didn't take any time at all to. To whisk its way around the world. It was probably, if you were aware of. If you were on a news channel or social media or whatever. Right. I would, I would just guess that well over half the world knew about that within one hour. And yet really good news takes a long, long time to make its way out into the world and to have an effect.

Wouldn't you say that's true about goodwill as well?

No, not really.

No. You put in, you put in good effort and it takes a while to be noticed, but.

Oh, that, that, yeah. Okay.

So you do one bad thing and suddenly you're labeled for that bad thing.

Yeah. No, that is exactly what I'm talking about. That is exactly what I'm talking about. You. You know, we all talk about the fact that it takes a lifetime to build up a reputation, but you can destroy it in five minutes. Right? That's exactly what we're talking about. And that's exactly the way it really works causally. You really can see that. So one of the things that a causal model computes is just a normal output, right? Is it's looking at the time lag effects for everything. Every causal element or potentially causal element that you're examining. In B2B business type stuff, those time lags are anywhere from like nine to 16 months. But if your CEO has a terrible flagrant affair with the CFO, right, and it comes all unwound, it's going to come unwound really fast. The consequences are going to be experienced really fast. That's what I mean by, you know, immediacy versus not immediate.

So what, I'm the perpetual optimist. And what, what's the feel good out of this? Like, yay, we get the bad news right away.

And that is because, you know, honestly, I'm writing a book right now on unlearning.

Yes, okay, talk about that.

So, and so you have to be willing to, not only to learn, but to unlearn. This is actually a nearly fatal issue with Gen AI is that it never unlearns. It just re. Averages new stuff with old stuff. Right. So it's very It's a very dilutive thing, particularly since it doesn't maintain any kind of North Star about reality socially as well.

Right. That's the. That's generational wisdom is. Well, we've always done it this way, whether that's in a company or in a family. This is, this is what we do because this is who we are. And I didn't know you were writing a book. This is fabulous news. Unlearning is. That excites me a lot because I.

Think, I think it's. It's one of the most ego less things we are called upon to do.

Absolutely. Because you let go of. Right. Ego is. Is what identity have you given yourself?

Right.

Have you accepted, have you taken on? Have you. Do you continue to perpetuate? And if you can unlearn, it means you're willing to let go of the things that no longer serve you. That's amazing. That's amazing.

Actually, it happened to me as recently as last night.

Oh, okay.

So we are putting up the Christmas tree, and my oldest son, he's 20, he wanted to kind of run the show. So he is putting the lights on the tree, and I see him connecting many strands of lights as if they were one strand. And I made a comment to him, I said, I think that you'll find, like, if you go on chat. Chat TPT or something like that, that there's a maximum of anywhere from three to four, maybe five, depending on wattage, that you can string together as one long strand before you have to start a new extended strand. Right. And so he looked at everything that was on the boxes with the lights, and then he asked chat GPT, and he goes, dad, you're wrong, because these are LEDs. And the wattage is so much less that I can connect every single one of these and not even come close to the limit. Right. And I thought, you know what? I probably really needed that.

Yeah.

Not. Not just on that issue. Right. But it punctured a balloon. Right.

That you. You're the dad and you know everything, and this is what you were taught.

That's right.

Right. Your dad taught you not to string things together because, you know, there's only so much.

Many amperage.

So much amp. Yeah. Right. Yeah.

And so it's. It's a. And so I, I just kind of said, well, okay, I just learned something new. Right. And this is very much so. Life is, you know, I mean, if there's something that you find all the time in 60s, 70s, 80s and 90s rock and roll, right. It's about grabbing and letting go. Okay. And so this is not a new observation at all. Right. But usually it's been talked about more relationally or abstractly. Right. It's never been really applied until very recently to knowledge because we collect knowledge.

Nice. Yes.

And it informs, as you said, it informs so much of how we see ourselves. Right. The problem is, is that like, right now, we're actually working on a model right now for this book, right. On what is the rate of obsolescence on knowledge. So like, if you've been doing what you're doing for say, 25 years, right. And you kind of say, okay, so number one, the question is, is there sort of like a, a way of dividing it? Right. Like, how do you segment out? Almost like chronologically, but it's a little blurrier than that. Right. Because of the way we use it. How do you segment it out? And then at what point is a piece of knowledge totally obsolete?

Yeah.

Right. So you actually, for reality right now, you know less than you did five years ago.

Well, I, I came face to face with that. Right. My doctoral dissertation had to do with sleep and performance following. Actually, it was sleep following exercise and daily performance following that. And so the research into sleep during the time this was 40 years ago. So right at that point, what we knew about sleep was so different than what we know now. It was relatively new. The sleep stages were just assigned maybe five years prior to my dissertation. And and so I was the expert, darn it. And then not using it and being out of the field and doing other things, and I come back to it and someone's like, here's the research on sleep. And I'm like, that's B.S. there's no oh, oh, that's new, huh? And just having to let go and going, you know, there are pieces of my research that still stand. They're really solid. And there are pieces of my research that were, that we now know are based on what was known at the time. And great, I would build on it from there. But right. So letting go of that being my identity, it's like I did the work, I got the doctorate. Tada. But the research itself is not my identity, which is amazing. And so, you know, from Christmas trees to clinical research, it's like, you know, what you're uncovering is so important. It affects, it does affect individuals, it affects organizations, it affects the way leaders lead a lot. Love this so much. It's like this is the kind of stuff that just sparks and it's hard.

It's. It's hard, particularly when you're trying to sell something to someone because you, you kind of.

What?

Part of what's necessary about that is that they, they almost kind of have. If they don't like you, they at least have to trust you and you know all this kind of stuff. Right. And so if you are saying, well, actually the most common frameworks and best practices around how B2B teams are taking, going to market. Okay, so this is marketing and sales and customer success and product.

Right?

All together.

Yes.

That is, they're doing it almost without exception. They're doing it wrong for today.

Yeah.

Right.

Yeah. And almost.

And they don't, they don't like that.

No. Well, people.

Are people not open to buying from me? Okay. It's their CFO that buys from us.

Yeah. I mean, people's responses to emotional tugs are always going to be people's responses to emotional tugs. But beyond that, buying behavior is based on so much. And do you, do you go into even the details around packaging? When you talk about, go to market, when you talk about, like, how are we packaging it versus what are we saying about the package, do you go.

Like, if it's relevant. If it's relevant.

I just didn't know how deep your organization went.

Like, well, the thing about, the thing about what, what causal AI can do is it can go as deep as you want to go. Right. There's no, there's not a practical limit on how you can focus it, how can you can use it, or how many factors you can bring into it. Now, I will say this, having said that, most.

He say this about that. Go ahead.

Most customers are really surprised and we tell them this up front, but they're still surprised. They will bring it, you know, they'll bring us like 300 variables to put into a model.

300 verticals. Into one variables. Oh, variables. Okay. Into one model.

Into one model. And we're like, okay, well that's fine. I mean, we can do that. But you need to know in advance that only about 10 ish of those are going to be material. Right. And then if we start, you know, pulling less material ones out, you'll be able to see just how material or immaterial those really are. Because if you pull it out and it, even though it is, as a singular factor, not very important, not very material, if you pull it out and a lot of other things change, then you're going to need to put it back in. Right. But if you pull it out and nothing changes, then you have to really question why you're doing that thing at all. And at least in this context, whatever it is we're looking at. Right. And so it's a, it's a very. You're. You're pulling people's beliefs through the eye of the needle.

Yeah.

Right.

Well, I think this is Right. Is it? So to pull out some gems that our audience can use, use individually, independently. You're talking about focus your work. Like if you were to reflect on your day, each of us, if we were to reflect on our own days, we would probably find about 80% of our time is in, is in activities that don't actually matter. Right? That's correct. Yeah.

It's not that you should strive to only do what matters. Okay. Because then you'd be a very productive but probably unhappy person. Right. It's about a balance. Striking a balance.

Yes. Good.

And you also have to realize that you're never going to strike that balance perfectly, even with causal AI. Right? You're not going to do it perfectly. And so there is a. So again, we're not talking about fate, right? No, I actually don't believe in fate.

Right.

I, I think that what we are talking about is agency.

Yes. Yes.

Part of agency is the agency that you have over your agency.

Which is where I said, look, you can, you have 100 control over the 20 to 30% in your control. Right? Right.

So but if you choose to go take a nap, right. You're exercising agency over what is ultimately a blank. Right.

I actually have, I actually build naps into various parts of my week. So do I have control of what happens while I'm sleeping? No. Do I have control of the result of, of rejuvenation partway through the day? Yes.

Okay, so that's actually a great example. I'm so glad you brought it, brought that back around because, well, you said.

Naps, it just clicked.

So if you were to run naps in a causal model on some business outcome. Right. This is great.

I love it when you smile and go, this is actually a great example.

It's awesome. You're going to say as a standalone variable in the model, the naps are not going to mean much. But if you remove naps, okay. The knock on effect of that could be very substantial.

Absolutely.

Right. And so that is a, that's a great illustration of what it is you're talking about. Right?

I mean, well, I have agency over my day. Like I know I'm super productive before the sun comes up. I'm Good until about 10, 11, 12, maybe, maybe just approaching noon from noon to about 3, I'm sort of like in this I'm good space, but if I can get a nap between, I don't know, 2:30 and 4, just even 20 minutes somewhere in there, then I'm good to go till 10 o' clock at night and it's like, I'm up, I'm ready to go, go, I'm in it. So left to my own devices like.

That is the, actually the, what you just described is the genius of the siesta.

True. Right.

So my grandfather raised my, my dad and his brothers and sisters in Mexico city during the 30s and 40s. And, and he, he had a really great position and all that kind of stuff in a, in a business. But he, he would go home around 1 o' clock in the afternoon, he would have lunch with his family and then he would take about a 45 minute nap and then he would go back to work and he'd work until like 8. Because in Mexico, at least in that part of society, they didn't eat dinner until like 10.

Right, right. Yeah.

And so you, you, you just, you realize that if you want to achieve certain things, there are hard and soft investments that you make.

Right, Right.

And that yes, you could work harder and steamroll through the whole thing and have a sense of accomplishment and then just be totally wiped out.

Yes.

Right.

People used to say, oh, sleeping's for sissies, I'll sleep when I die. And it's like, well, not sleeping will get you closer to that. So. Right.

Well, I think that also, you know, when things get really chaotic in the macro, I'm using it now, macro as everything, not just economics.

Okay.

You start really appreciating the idea of sustainability. And so what you're really doing with causal analysis is that you are figuring out where the balance point is and everything and you're kind of maintaining that structural balance and that, and so that means you're not wasting nearly as much and you know, all that kind of stuff, you're getting more output, you're getting more effectiveness from what you do do than you were before. And so that makes you among other things, more efficient and more sustainable right now. Where the fallacy is right now in business everywhere is they, they talk about efficiency and it's not efficiency that they're talking about. They're talking about cost cutting.

Yes. And sometimes just busyness.

Yeah. And you can't here, and here's the big deal on this. And this is a statement of absolute fact. Okay. So people can believe whatever they want to they can have their truth around it, whatever they want to. It's up to them. But this is one of those things like gravity, that just is what it is. You are, you are not going to defy the odds on this, right? You are, you're not going to be able to say, well, I'm just going to make whatever we do more efficient, meaning each incremental unit of it cost me less without knowing first is it effective. So efficiency is a derivative of effectiveness every time, all the time, no exceptions.

I have an example that I use with organizations when I consult, and that is you could have two really finely tuned race cars lined up side by side and they are really tuned to be super efficient. They burn, they purr, right? And if one is tilted off, just the slight, just 2 degrees off and the green light goes, and they're on this salt flat and they're ready to go, and one goes straight toward the finish line, the other goes straight off 2 degrees. They're both running efficiently, but only one is effective.

That's right.

That's, that's the way I describe it when I, when I do consulting. So that it's, it's like, is what you're doing actually getting you closer to the thing you said you wanted?

So another way of putting it is, is that the single greatest contribution that you can make to your overall efficiency is to stop doing whatever is ineffective.

That is great because there's so much now more and more and more. The message is successful leaders make the few fewer decisions.

Right?

There they are decision you efficient, right? In that if you rule out, if you take out all the distractions, all the noises, all the noise, all the distraction. I mean, Steve Jobs was famous for wearing just the, his black turtleneck, right. So he didn't have to decide what to wear.

That's a super easy example, right?

It is. And, and yet it allowed him to stay focused. So in a normal day, for people who like to wear different clothes, right. And have different decision making at your, at your organization, what is it that you need to do as a leader to eliminate the external noise? Right. So, right. You're, you're saying that to be effective or to be efficient, you eliminate the things that are not effective.

Right. I mean, another kind of corollary to this. Right. Would be something that Dave Cody, who was the, the chairman and CEO of Honeywell for a long time, and I, I had the pleasure of working around him a lot. And he would say this is, this is actually about time lag too. He would say, anyone can Manage for the short term and anyone could manage for the long term. The trick is in doing both at the same time. Most leaders don't know how to do that. And in a world like we live in right now, they are going to struggle like they've never struggled before. I mean, I think that if we, if we continue to see what we're seeing right now in the marketplace for say the next five years, there's going to be almost a wholesale change in leadership in large companies.

That makes sense. And it's probably needed given. Yeah, given what we're doing, given the, the new climate.

Well, also, they also no longer have a choice. So things like Delaware and the EU's redefinition of fiduciary duty and what that really means. It means if you're not proactively running your business from a risk adjusted basis, right then you're not doing your job anymore. And the business judgment rule that's been accepted by courts for the last 50 or 60 years is out the window. If you look at what the SEC announced about a month ago for 2026, that if you are using AI in any part of your operations, not just financial reporting, but anywhere, you're going to have to show what happens to shareholder interests as a result of using that AI. That is accountability deluxe. Okay.

I think it's necessary because people are making decisions based on AI, which as you've pointed out, is, is getting aggregate information which is not true, truthful or not useful. So it's great. I want to go back. I want to. We're gonna, we're gonna wind up here in a second. I wanna, I wanna highlight just something you said a few. It feels like just moments ago. And it was, it was a few minutes ago. Strike a balance of what matters and what makes you happy was one of the key things you said amongst.

Yeah.

All the other things that were very somewhat technical and somewhat philosophical and somewhat pragmatic and I love all of it. And it's just like this is, this is one of those like, cool, we're going and going, but strike a balance of what matters. And it's what.

Why this is why you. It's just completely dumb. Really.

Okay.

When we judge each other's tastes.

Isn'T that great?

It's really dumb. I. One of the best conversations I've ever had in my entire life was with my oldest son around a campfire and we were talking about that exact issue. That question.

Right.

Yeah. Because there's certain foods he doesn't care for. That I really like, and a normal. Unfortunately, a normal human response is to go, what is your problem? Right. You don't like mashed potatoes. Like, who doesn't like mashed potatoes? And yet the reality is, is that it's just a. It's just personal taste.

Yeah.

What we're really saying is I want to be able to share my love of mashed potatoes with you. And when you say I don't like it, I don't like mashed potatoes, I feel rejected.

Right. Becomes a personal identity thing. Someone's a. Someone is rejecting the thing I love. It's like, you've got an ugly baby. What? That's right. No one says that, but that's the way it feels.

Right.

Is that, oh, we're not allowed to dislike. It's so interesting because that's. That gets to tribalism. You know, we have particular tastes, we have particular likes. We also assimilate. We were taught to assimilate as our own. You must like, you live in this territory. You must like this sport sports group because they represent you and your territory. It's like, well, actually I'm. People don't like. Yeah.

You know, I'll give you, I'll give you an example I just encountered not too long ago. So. And I realize that this won't be, you know, what some people listening to this conversation are going to like. But I love to bird hunt and I love to fly fish, both of which entail the death of animals. Okay.

Do you eat them?

Oh, yeah, very much so.

Okay, so I mean, they're feeding you.

Yeah. So. So I. And yet they will. A lot of times people will immediately believe that I have a certain set of political beliefs because I hunting fish that actually are. I, I have the exact opposite beliefs politically. And yet we. So we, we do. We pattern match our lives. We pattern match each other.

It's a huge. It's a. That's a huge phrase to, to.

And so we're. And that's correlation. That's correlation. We're pattern matching. And just look at how often we are wrong when we pattern match. This is why actually, from a purely statistical perspective. Right. This is why racial profiling in law enforcement is such a. No, no. Because you're going to get it wrong a lot.

A lot.

Like a lot a lot.

Yeah. Right. Yeah. One way of the good news is we care now.

Right.

Like back in the 50s.

Right.

Back in the 50s it was. Or before. I mean, there was this sense of there's close enough. And it's like, that's terrible. Right. So, yeah, yeah, yeah. Pattern matching. Pattern matching is a. It's interesting. It's.

We make it. We make a really big deal today about intuition. And I'm not saying it's bad, okay? But we are not born with intuition in the way that we are born with instinct. Okay? Instinct is hardwired. And you only get intuition by collecting experiential data. And. And it begins to flesh out what are called heuristics, right? Shortcuts to decision making. Right? And this is. These are all pattern match 100 pattern match. So your intuition is really very much like your own personal, private machine learning.

Wow.

Okay. But we have all known people who just seem to always make the wrong decision, right? Particularly in certain areas of their life. I would submit to you that this is gigo operating, right? Garbage in, garbage out, right? And their data sets are really screwed up. And the way that they interpreted their data sets is. Are even more screwed up. And so when you look at your intuition, which is part of your subconscious, right? And you look at the duty of the subconscious, which is to defend your life, right? If white is black and black is white, your subconscious is going to steer you in the direction that it believes will save your life.

Yes.

But if that actually in point of reality exposes you to greater danger, that's a problem.

Except. Right? And it's a problem in the real sense, except your subconscious goes. Because you know how to handle chaos, so you're safe. That's the. Right. That's where people relive the same bad rep. Relationship over and over, over again. The same bad handling of money, the same bad decisions. Your subconscious is keeping you, quote, unquote safe based on previous data sets that it said, well, we've survived this already, so this is what survival is. This is great. This is awesome. All right. You. You and I could go on and on and on and. And it. This is fabulous. Let's. Let's go ahead and wrap this one. We may choose to do another because what the heck. I may choose just to fly up and see you and have lunch with you at some point just because.

What?

What. If anything, I really love the, you know, just the whole idea of strike a balance of what matters and what makes you happy. I'm reading from some notes I took. This isn't about fate. It's about agency. Find the balance point to get more effectiveness and efficiencies from what you do do. And then just be aware of your own data sets. Like be willing to unlearn and I can't wait when's your book coming out?

That one, I think is going to come out. August, September.

Beautiful.

I've got another one coming out pretty shortly. It's on Causal AI.

Okay. All right. Is there anything, like, we've said so much and there's so much more to talk about. Is there anything that you were hoping we'd talk about that we didn't?

No, I think that, you know, I, I think that one of the things that I would just stress here at the end, right, is that all of this sounds incredibly deep and heavy. Right. And you don't have to live it out on that basis.

Right.

You can live it out rather superficially. Most business analytics in Cosmo AI are very superficial.

Right.

They're just designed to help you make better and better and better decisions and trigger the laws of compounding in your favor. That's it. So it's not trying to psychoanalyze you or anyone else. It's, it's just, this is just operational stuff. By the same token, what I, so, I mean, it, it doesn't get. I'm a very concrete, very pragmatic person. I realize that the last hour of conversation doesn't necessarily necessarily come across that way. And it's not that I'm not a philosopher. I, I am, but I'm, I'm a philosopher in a kind of a very pragmatic way. Right. Like, I don't get into how many angels can dance on the head of a pin sort of conversations. I want, I want to mean something. Right.

You'd have to know how big the pin was, how big were the angels, what kind of dance.

Right. Exactly. Exactly. And, and, and it all just gets too abstracted. Right. And so, and so I, I, I would just encourage you guys, as you think about what you've just heard today, is to realize that at the end of the day, this is rooted in radical pragmatism. If you choose to, you can use it. You explore the meaning of the universe. Right. You really.

For yourself. Right. It's an individual, it's an individual interpretation, which is, which is really great, Mark, because this is where radical pragmatism turns into individuality and agency. And agency. Yeah.

I mean, like, this is one of the things.

Darn it, we're gonna keep going for another hour here, aren't we? Yeah.

There's so many, there's so many people that we both know, all of us know, right. That try to control people. Right. How exhausting.

Right?

I mean, I can barely control myself most of the time. Right. I mean, how in the world. Am I supposed to control all of these uncontrollable people?

Yeah, you just get to control.

I can motivate them, I can guide them, I can talk with them, but I can't control them.

Right. Influence versus control.

Yeah.

And that's. And that's done from modeling what you honestly, truly believe. And that's. And what you believe you might be encouraged to.

Yeah. And actually what it really is, is it's an attempt. Attempt to get as close to reality as possible so that you know what parts of your understanding you need to change.

Nice. Choose to change.

Yeah. Yes. That's true. Although I would say sometimes feels very much like must it.

It. Right. And. And that's. It brings you back to the mashed potatoes. You must like this. No, it exists. And you.

But there is a. There's a price you pay.

There's always a price you pay. That's the piece that most people miss. Right. There's always a price you pay.

Yeah. So if you choose, part of the agency. Right. Is you're. You're not just choosing to do something you were choosing not to do something.

Correct. Yeah.

Okay. So right there, road less traveled. Right. That you're making. That's an opportunity cost. Right. And then the consequences of both, you may or may not have thought through all the way.

Exactly. So, yeah. Give yourself. This is good. I'm going to. I'm going to land this with. Give yourself a chance to reflect on what you do during the day. Does it matter to you? Does it matter to the people in your life?

Right.

Does it make a difference? Does it make a positive difference? And to recognize you have choice about the difference you make for yourself first. Because if you're not aligned with the difference you're making in the world, it's going to be a pretty horrible kind of outcome.

So if you, if you define making a difference as you doing what you do, that's a problematic perspective. There is an independent understanding that is possible to get of all of our contributions, all of our relative importance. Right. In any given situation, I think that one of the things we actually see in the models all the time, which is just fascinating to watch this happen, is the idea that. Well, it's mainly around paradox. So different things, including all of us individually, can simultaneously be very small players.

Yeah.

And then at a particular time and place, we can be the only thing that matters.

Yeah.

That's not a. That's not a persistent reality. That's of this slice.

It's toggle. It's toggle. Right.

Because.

Right. Yeah, no, I'm gonna wrap it with that. Make that a conundrum that we wrap with. This is awesome. I like, like, it's, it's something to ponder if people want to find you and.

LinkedIn.

Yeah. Okay. The best place.

My email box is a disaster because of all of the spam that I get.

Okay, Mine too.

So basically, yeah, I would say it's LinkedIn for sure.

All right, Mark Stuss. S T O U S E stus Mark Stuss on LinkedIn Proof Analytics. Mark, thank you for being my guest today. This is fabulous as always to talk with you. Thank you, Wayne.

It was a blast.

Thank you. It is a blast. So good. All right, Mark stews my guest on one sharp sword cutting through to what matters most. I'm your host, Dr. P. Dr. Wayne Purnell, host, guide and coach on this journey. We'll see you again next time. Thanks for being here. Please like and share this. Thank you.

Thanks, guys.

Thanks for listening to one sharp sword cutting through to what matters Most without.

Fluencer Dr. Wayne Purnell. For more information please go to onesharpsword.com.