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AI Won't Fix a Broken Culture, It Amplifies It · Business Roundtable

0:14
Speaker 1: Welcome back to the Business Roundtable podcasts. I am your host,
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Speaker 1: David Carr, founder of Steward of Your Business, where we
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Speaker 1: help leaders build healthier businesses through stronger communication, leadership, alignment,
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Speaker 1: and internal stewardship and intentional stewardship. Today, I'm really excited
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Speaker 1: we're going to actually dive into one of the most
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Speaker 1: important perhaps conversations we've had here on the podcast. Right now,
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Speaker 1: everybody is talking about AI. You can't go anywhere without
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Speaker 1: hearing about AI, but very few people are asking this question,
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Speaker 1: what kind of lead are you becoming as AI becomes
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Speaker 1: more powerful? How are you showing up? Because what I
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Speaker 1: found and you're going to hear it from our guests today.
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Speaker 1: You know, technology is not going to fix a broken culture,
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Speaker 1: poor leadership, pounder dependency, or really unhealthy teams at all.
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Speaker 1: In some cases, it's going to actually amplify it and
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Speaker 1: make it worse. And so today I have two and
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Speaker 1: two guests. I don't usually have to have two guests.
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Speaker 1: I'm super excited to have joining me on the podcast.
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Speaker 1: Number one, we've got Christopher Skinner. He is working at
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Speaker 1: the intersection of AI cognition leadership really helping organizations understand
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Speaker 1: how people think and how AI can really truly help
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Speaker 1: that partner be a partner with you and as a
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Speaker 1: leader rather than just another tool out there. And Chris Westling,
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Speaker 1: which is he is known as the process dude. I
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Speaker 1: really like that title. Chris helping organizations create systems and
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Speaker 1: processes that free leaders from being trapped in the day
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Speaker 1: to day gentlemen, welcome to the podcast.
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Speaker 2: Thanks for having me.
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Speaker 1: Absolutely absolutely. As we go through the podcast, I'll let
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Speaker 1: you guys unpack a little bit more about your background
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Speaker 1: and so forth. And for those that are interested, we're
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Speaker 1: all connected on LinkedIn and there's gonna be a lot
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Speaker 1: more information that you can follow up with both Chris
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Speaker 1: and Christopher. But one of the things I'll just start
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Speaker 1: off with Christopher. When we first talked, Christopher, I liked
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Speaker 1: how you brought up the point like it it was just, hey,
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Speaker 1: you said, most AI produces generic results. It doesn't understand
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Speaker 1: the person using it. Can you unpack that a little bit, Christopher?
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Speaker 3: Yeah, So let's think about it this way. What is
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Speaker 3: AI's personality is that any idea? What is its mindset driver? Well,
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Speaker 3: if you study it a little bit, it turns out
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Speaker 3: it's an expert with a lot of discipline. Sometimes it
2:49
Speaker 3: goes off the rails and it's a little bit of
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Speaker 3: a psychopath. But overall, if you met this thing on
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Speaker 3: the streets, gave it a personality test, it would consistently
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Speaker 3: have one kind of personality and it doesn't really adjust it.
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Speaker 3: But as humans, we have a lot of personality types
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Speaker 3: out there. There's theories we've certainly heard. Everybody's heard Myers Briggs.
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Speaker 3: That's sixteen. We've heard disc yep, four or five, whatever
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Speaker 3: you want to call it. Reality is, there's thousands. It's
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Speaker 3: really complicated. And think about this. What happens when you
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Speaker 3: have a one size fits all If I came into
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Speaker 3: a big company with a size eight men's shoe and said,
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Speaker 3: here's your shoes, or I noticed you guys both have glasses.
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Speaker 3: What if I had a one size fits all pair
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Speaker 3: of reading glasses. No, that's it, it's all we issue.
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Speaker 3: Why does that have to be It's a mistake. And
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Speaker 3: what we discovered is that AI just doesn't really know
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Speaker 3: who we are. So therefore it's trying to figure it
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Speaker 3: out to the best of its ability. It's wrong and
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Speaker 3: it's not very helpful. It's helpful functionally. But when it
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Speaker 3: comes to as humans, what are we really good at?
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Speaker 3: In theory, we're good at making decisions, discernment, we're good
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Speaker 3: at thinking, creating. That's the best of our abilities, right
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Speaker 3: for things that are just fundamentally not built into AI.
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Speaker 3: So I tend to be a little bit on the
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Speaker 3: yon lukun camp, which is you have a level of
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Speaker 3: adopt adaptive intelligence that humans can do really really well.
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Speaker 3: AI does things really well when it doesn't involve being
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Speaker 3: a human.
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Speaker 1: Yeah, I love that you brought that up. I use
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Speaker 1: a framework called five voices, Christopher, and I agree, you know,
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Speaker 1: there's a spectrum. And I love these assessments like this
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Speaker 1: and fix me because it's our human human means are complex,
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Speaker 1: not people, and not straightforward and quite honestly not logic.
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Speaker 1: In fact logic. We lead a lot of times with
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Speaker 1: emotions over logic, and so you know, we're And I
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Speaker 1: like how you said this, Christopher. You said, AI does
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Speaker 1: have a personality, if you will, but it's it's it's
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Speaker 1: generic kind of one. It's just so it's so it's
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Speaker 1: giving you this kind of mish mash. And and I
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Speaker 1: guess my follow up was that, Chris, because I've heard this,
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Speaker 1: and I think it's something new, But I mean people
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Speaker 1: are saying it's it's like hallucinating, or give me these
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Speaker 1: different questions or or would you say like biases or
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Speaker 1: blind spots or limitations. Christopher in its own personality and
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Speaker 1: the way it looks at the world.
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Speaker 3: Well, I would say that it does. It's operating with
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Speaker 3: a set of specifications that's incorrect.
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Speaker 1: Mmm.
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Speaker 3: So if we're trying to go to the moon, we
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Speaker 3: need specs, don't we. If we're trying to build a transmission,
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Speaker 3: we need specifications and we need to adhere to those specs.
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Speaker 3: What happens if those specs are fundamentally wrong? Do we
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Speaker 3: get to the mood? Do we get back? No? Specifications
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Speaker 3: are how we build things. And it turns out there
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Speaker 3: are specifications to how we think and make decisions. And
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Speaker 3: if we have those specifications about ourselves, and we have
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Speaker 3: the specifications about who we're talking to, then all of
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Speaker 3: a sudden, we have a blueprint, if you will. And
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Speaker 3: this leads into Chris, if you all of a sudden
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Speaker 3: have a set of specifications that's causal to the outcome,
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Speaker 3: that's important to where we're trying to get to, doesn't
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Speaker 3: the process moves the better or Chris doesn't. If you
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Speaker 3: don't have specs at all, isn't it good just to
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Speaker 3: guess at process?
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Speaker 2: I mean, I mean there's a process.
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Speaker 4: There's the hallucination thing, which I think is you know,
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Speaker 4: I I when I talked to my wife, and I
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Speaker 4: don't always get the results that I'm looking for right
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Speaker 4: A lot of times it's because I didn't communicate what
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Speaker 4: I needed to communicate.
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Speaker 2: At the front end.
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Speaker 4: When I was in semiconductor, what I recognize in a
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Speaker 4: lot of complex situations, the problem was typically between the
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Speaker 4: keyboard and the floor. I mean, the problem was with
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Speaker 4: what I was doing, but the problem was with with
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Speaker 4: what the user was doing. So and I'm just going
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Speaker 4: to say, Chris, I'm not going to say Christopher, I apologize.
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Speaker 4: Just David next time. Let's get a third Chris on here.
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Speaker 3: I think. I know.
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Speaker 4: David's in one, Matt, I think, but with what with
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Speaker 4: what Chris was saying, If we don't know what the
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Speaker 4: question is that we're asking up front, if we if
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Speaker 4: we don't even know what good looks like at the
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Speaker 4: very beginning, how in the world can our dialogue partner,
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Speaker 4: whether that's AI, whether that's our wife, whether that's the
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Speaker 4: people we work with, are ever going to be able
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Speaker 4: to do it? You see this all the time, especially
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Speaker 4: with with you know, solopreneurs building something.
8:18
Speaker 2: They hire somebody to do something.
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Speaker 4: And because they don't, as Chris said, to find the specks,
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Speaker 4: that because they don't communicate what good looks like, because
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Speaker 4: they have done all this stuff in their head and.
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Speaker 2: What is it obviously how it's supposed to be done.
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Speaker 4: And I'm quoting myself here, you know I'm not I'm
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Speaker 4: not puting fingers at anybody else that or parenting even right,
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Speaker 4: this is the way it's supposed to be done. How
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Speaker 4: in the world did you come to a different conclusion
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Speaker 4: or come up with a different output than what I
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Speaker 4: was thinking in the first place.
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Speaker 2: It, I don't know it.
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Speaker 4: We end up with things we don't like. We end
8:55
Speaker 4: up with frustration, We end up with stress and all
8:58
Speaker 4: the all the stuff that comes in. And then we
8:59
Speaker 4: end up people because they're not performing the way we
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Speaker 4: want them to even though we never told them to
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Speaker 4: perform the way that you know, we never we never
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Speaker 4: let them know what success would look like.
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Speaker 3: That's right. I'll give you one example that's fun. A
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Speaker 3: lot of times you can have leadership which you would
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Speaker 3: call a disciplined mindset kind of they set of rules,
9:22
Speaker 3: they follow rules, they learn very strict process and they
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Speaker 3: go about that and then something changes like supply chain problems,
9:32
Speaker 3: you know, or something kind of that throws everything off
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Speaker 3: the person who's a systems thinker. A lot of times
9:40
Speaker 3: you can kind of they kind of give themselves away.
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Speaker 3: They look up and then they start pointing to things
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Speaker 3: and they're perfectly in their head. They're pointing to up
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Speaker 3: in the air and they're saying, you connect this to this,
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Speaker 3: And the disciplined mindset person is going, I don't know
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Speaker 3: what that person's doing. And as a real just not communicating.
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Speaker 3: It's not that either one side's wrong, but they don't
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Speaker 3: share a common vocabulary and getting into the details, like
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Speaker 3: they aren't even using the same verbs, and so they're
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Speaker 3: looking past each other on communicating and defining what it
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Speaker 3: is that they're trying to get to. And once you
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Speaker 3: find out, like true story, companies that flew through supply
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Speaker 3: chain problems without much of a hitch, without a problem,
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Speaker 3: for instance, autoism are filled with systems thinkers that plan ahead,
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Speaker 3: They look for variability. They understand that they have to
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Speaker 3: build optionality. What happens if we have a supply chain problem.
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Speaker 3: Jimmy Diamond, for instance, is a systems think er. Guy,
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Speaker 3: what are you going to do if interest rates can
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Speaker 3: stay high? And his answers are always similar. We have
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Speaker 3: a team, We look at our options. If it goes up, down,
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Speaker 3: stays the same. When we see clarity, we implement the plan,
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Speaker 3: and we return value to our shareholders and our customers.
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Speaker 3: Every answer is in a way formulatic, but every answer
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Speaker 3: is a system's thinking approach to a problem. The discipline
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Speaker 3: is going to be more. I'm using one methodology and
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Speaker 3: I'm reacting to it. M h. It tends to be
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Speaker 3: highly efficient because you only need one team to do
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Speaker 3: one thing very efficiently, like, for instance, make driver's licenses. Yeah,
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Speaker 3: but it's not good for change.
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Speaker 1: Mm. Yeah, that's that kind of follows my question of
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Speaker 1: like you're both hitting this and in a different way
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Speaker 1: of like, you know, there's some leaders are getting extraordinary
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Speaker 1: results with AI, but others are extremely disappointed with this
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Speaker 1: and they're not getting the results. And what are you
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Speaker 1: both seeing that? Business owners? We are trusting this too quickly,
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Speaker 1: these AI and these tools where it's like hold on,
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Speaker 1: we need to slow down a little bit. To your point, Chris,
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Speaker 1: or we're not communicating. Well, what is it that you're
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Speaker 1: seeing in business owners today that they're really maybe trusting
12:14
Speaker 1: or what are the mistakes that they're making in this
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Speaker 1: AI adoption or race with AI.
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Speaker 4: One that I saw very very recently with a client
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Speaker 4: that hadn't been using AI, and I tend to demonstrate
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Speaker 4: so people can take that on. People will take seem
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Speaker 4: to take things on better by observing rather than by
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Speaker 4: being told. He had a customer issue, and I kind
12:45
Speaker 4: of walked him through what to do, and he just
12:48
Speaker 4: took what I said and sent it.
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Speaker 2: Out in an email.
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Speaker 4: He just kind of ran off with it rather than
12:54
Speaker 4: probably probably made his life worse with what was going.
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Speaker 2: On there.
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Speaker 4: And looking for and going to AI for answers rather
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Speaker 4: than going.
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Speaker 2: To AI AI Right, what does that what even mean?
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Speaker 4: For better questions? What are some better questions that I
13:16
Speaker 4: can use to frame my thinking? What are some things
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Speaker 4: that I'm not seeing? How can I expand my Overton
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Speaker 4: window to be able to capture more of these things
13:25
Speaker 4: so that when I do make my next step, I
13:28
Speaker 4: can I can I can have more information for my
13:32
Speaker 4: decision making process. I think that's sort of a subset
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Speaker 4: of this, and I try to use this very simple
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Speaker 4: model or deterministic things that I would never go to
13:44
Speaker 4: an LLM for. If you know, if I'm trying to
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Speaker 4: decide whether this number is I'm not sure how much
13:50
Speaker 4: of it, but if this number is higher bigger than.
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Speaker 2: This number, I'm not going to l M.
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Speaker 4: I'm going to use some sort of terministic thing, some
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Speaker 4: mathematical tool to do that. If I'm looking for inferential
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Speaker 4: you know, what's the what's the meeting behind the meeting
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Speaker 4: when they said this in response to this, what are
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Speaker 4: the potential ways that we could go? They're talking about
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Speaker 4: the personality and how could we use that. I think
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Speaker 4: that's where we can use LLLM to help inform our
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Speaker 4: The third portion is that decision framework, and that's what
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Speaker 4: one of the things that Chris was talking about. I
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Speaker 4: never never is a big word, but I try not
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Speaker 4: to hand deterministic things off to AI. I try not
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Speaker 4: to hand I don't hand decisions off to AI. I
14:39
Speaker 4: let it inform my decisions, but I do look for
14:41
Speaker 4: additional inferential insight from the AI tools. Now, going back down,
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Speaker 4: I'm going to coach the sky a little bit more. Okay,
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Speaker 4: this what happened?
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Speaker 2: What did you do?
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Speaker 4: What were the results? What were the results that we wanted?
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Speaker 4: How can we shift our workflow right, workflow process and
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Speaker 4: then automate how can we shift our workflow and our
15:06
Speaker 4: expectations right, probably even come before the workflow of what
15:10
Speaker 4: we're going to get out of it, so that the.
15:12
Speaker 2: Next time we go to use this tool right.
15:17
Speaker 4: To actually get something that's not getting the tool to work,
15:21
Speaker 4: but that we actually get the outcome that we want
15:23
Speaker 4: and the outcome that he want wants this customer to
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Speaker 4: pay his bill, right, Yeah, Christopher thoughts there.
15:36
Speaker 3: I thought he some Chris something up. Well I don't really.
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Speaker 1: No, let me let me follow up, Christopher, because one
15:44
Speaker 1: of the things I really thought that you are working
15:47
Speaker 1: on and that standing out to me is that there's
15:51
Speaker 1: this what you said, Chris, Chris Wesley, you were saying, Hey,
15:54
Speaker 1: I think business owners are like just trying to buy
15:56
Speaker 1: a software AI and it's not running into like this
15:58
Speaker 1: example you just gave this it's not working and hoping
16:01
Speaker 1: that's going to fix the problem. What I've what I'm
16:04
Speaker 1: excited what I've seen you being, Christopher doing is you're
16:07
Speaker 1: looking at taking years of psychology and cognitive understanding and
16:12
Speaker 1: getting more at to your point earlier about how do
16:16
Speaker 1: we think, how do we lead? How do we communicate?
16:20
Speaker 1: And and talk a little bit walk us through a
16:22
Speaker 1: little bit, Christopher, about you know how you have seen
16:28
Speaker 1: a shift for folks that are looking at from that
16:30
Speaker 1: perspective when they're going in and using these tools, like
16:32
Speaker 1: you said, Chris Wesling. But from what Chris, Christopher, what
16:36
Speaker 1: I've been excited to see what you're developing is a
16:39
Speaker 1: way of helping communicate and and for me as I
16:43
Speaker 1: saw this, and I work with teams and like helping
16:47
Speaker 1: them have some kind of roadmap of like how to
16:50
Speaker 1: communicate with each other, how can we do this better?
16:52
Speaker 1: How can we make decisions better before we just jump
16:55
Speaker 1: into the AI, you know. And I loved how you
16:59
Speaker 1: were showing me some some of the technology and things
17:01
Speaker 1: that just helping company step back, slow down a little
17:04
Speaker 1: bit here, you know, before we keep rushing ahead. You know.
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Speaker 3: Yeah, well, so there's two pieces to hear. This that
17:12
Speaker 3: I think about is thinking and making decisions, and so
17:17
Speaker 3: communicating is part of making decisions. Going to communicate. We're
17:21
Speaker 3: trying to communicate and work something out to make a
17:23
Speaker 3: decision about something. There's some finality to communicating. It's not
17:28
Speaker 3: just an endless loop of discussions with no end right
17:32
Speaker 3: bigging up a topic. The point is to get to
17:35
Speaker 3: something that we can make a decision about. Yeah, before that,
17:39
Speaker 3: let's think through what are we trying to get to.
17:43
Speaker 3: Everybody has different thinking styles and specifications to their thinking.
17:49
Speaker 3: For instance, Chris might have a very high Deming score,
17:53
Speaker 3: which is a focus on quality Edwards Deming. David, you
17:57
Speaker 3: might be more of a Clayton christiansen higher innovation score.
18:02
Speaker 3: Now it would be extremely rare that both of you
18:05
Speaker 3: have equally high, equally same amplitude of both scores. If
18:11
Speaker 3: it were the case, you would have an easy time
18:14
Speaker 3: communicating between each other about an innovative product, that product
18:20
Speaker 3: that needs to be built with high quality, easy conversation.
18:24
Speaker 3: It's not really much different than dating any kind of relationship.
18:30
Speaker 3: So when we think about we have to think through
18:34
Speaker 3: a problem then we communicate it. The inside of companies,
18:40
Speaker 3: that alone is enormous. So if we both understand each
18:44
Speaker 3: other with a set of specifications about Deming christiansin about
18:50
Speaker 3: our anxiety levels, about our Socratic reasoning levels, and we
18:57
Speaker 3: don't have to say your score is a nineteen point
19:00
Speaker 3: point five. You know you dummy. Now, if it's baked
19:04
Speaker 3: into something, as we are preparing communication and thinking, we
19:09
Speaker 3: can modify that material to improve how Chris understands something. Now,
19:17
Speaker 3: one other layer to unpack. So by thinking and communicating,
19:24
Speaker 3: you form a relationship. But there's three legs to this
19:26
Speaker 3: stool that are very important that can't be ignored. A
19:31
Speaker 3: successful relationship is made up of three components, safety, challenge,
19:38
Speaker 3: and investment. If you don't let's unpack the easiest one.
19:43
Speaker 3: Let's take away the leg called safety. We're left with
19:47
Speaker 3: challenge and investment, meaning I'm going to invest in you
19:51
Speaker 3: being here and getting stuff done. I'm going to get
19:53
Speaker 3: you the tools, but I'm going to constantly raise the
19:57
Speaker 3: bar and constantly push you to the limit. That environment
20:02
Speaker 3: is called toxicity, which is prevalent in about half the
20:08
Speaker 3: companies in America. There's no safety. What do you hear
20:12
Speaker 3: young people complain about psychological safety? If you want to
20:18
Speaker 3: have a fun survey older boomer leaders say ninety percent
20:24
Speaker 3: of their team is aligned, and the culture's great gen
20:27
Speaker 3: z say sixty three percent say I am not safe
20:31
Speaker 3: at work. Wow, what a differential. Right, Yes, we've got
20:37
Speaker 3: boomers retiring, leaving the workforce, we've got gen Z and
20:41
Speaker 3: psychologically massive differences. Why that's another thing to unpack later.
20:48
Speaker 3: But wow, what a topic. What happens if we don't
20:52
Speaker 3: have challenge, If we're just left with safety and investment,
20:57
Speaker 3: that's called friend zone. It doesn't really progress anywhere. It's
21:02
Speaker 3: I mean, it's good, right, it feels good, we're hanging out,
21:06
Speaker 3: it's nice, but there's no challenge to the relationship to improve.
21:11
Speaker 3: And then of course the last if there's no investment,
21:13
Speaker 3: if there's just safety and challenge, it almost as ends
21:16
Speaker 3: up like a professor relationship. So if we can specify
21:22
Speaker 3: these things, we can specify the adjustments that need to
21:26
Speaker 3: be made so that we learn better, we adapt to
21:31
Speaker 3: each other, and that we think and treat people fairly
21:36
Speaker 3: and essentially go faster, come up with better ideas. You know,
21:45
Speaker 3: let's pretend you have to be designing a new brake
21:48
Speaker 3: caliper for some break on a car. You got to
21:53
Speaker 3: think through, like, got to do this a different way.
21:57
Speaker 3: You know, there's a challenge, there's a business challenge on costs,
22:00
Speaker 3: there's a you're thinking through. You present your ideas and
22:03
Speaker 3: your boss says you're an idiot. That's a dumb idea.
22:07
Speaker 3: There's so many subtle things that for instance, AI out
22:11
Speaker 3: of the Box never picks up on. It never reads
22:14
Speaker 3: that into the conversation. It wasn't designed to listen. It's
22:18
Speaker 3: not hearing those specifications, but it can be yes. And
22:23
Speaker 3: if you say whoa, whoa, this is not right, and
22:27
Speaker 3: you start communicating back and forth like I don't appreciate that. Look,
22:32
Speaker 3: I'm just trying to take my chances and come up
22:34
Speaker 3: with the answers to this problem. Hold on, and how
22:39
Speaker 3: can we communicate that? If you're you know, a person's anxious,
22:44
Speaker 3: if they're a systems thinker, if they're just all these
22:48
Speaker 3: things lead up to specifications, and if you have them,
22:52
Speaker 3: and if they're baked into something, you can improve the
22:55
Speaker 3: communication and the outcome a lot faster.
22:59
Speaker 1: Yeah, and you you you shared a lot there, Christopher.
23:03
Speaker 1: I know this is fantastic. I use a tool when
23:07
Speaker 1: I'm coaching folks, I call I call it a support
23:09
Speaker 1: challenge matrix. To your point, Christopher, we have to have
23:12
Speaker 1: we have to have that challenge and that support if
23:15
Speaker 1: you will, But ultimately in the investment. What I call
23:18
Speaker 1: it is kind of moving you in this place of
23:20
Speaker 1: liberation because you're going in a postive up, you know,
23:23
Speaker 1: in a positive directions. You need both. And what I
23:25
Speaker 1: found with my experience to your point, Christopher, is naturally
23:29
Speaker 1: most focals will lead from the challenge perspective or from
23:33
Speaker 1: the support and neither one is. We don't want, like
23:36
Speaker 1: you said, only one of those things. If I am
23:38
Speaker 1: a high support person, what I found is I can
23:40
Speaker 1: create a culture of entitlement sometimes almost it's not healthy.
23:43
Speaker 1: I need to bring some challenge to the room. And
23:46
Speaker 1: so and again, if we're going in to using AI
23:50
Speaker 1: or any technology and we're not aware of this, we
23:52
Speaker 1: don't understand how we're influencing it, not in the positive way.
23:56
Speaker 1: And I think this is where you know, breaking this down,
23:59
Speaker 1: like you saying, Christopher, of like we got to get
24:02
Speaker 1: we do want to get to the specifications, but we
24:04
Speaker 1: understand these these users, the folks that are in the
24:07
Speaker 1: mix here and how we're communing. And I like, Chris,
24:09
Speaker 1: how you said, you know, I'm married almost twenty one years,
24:12
Speaker 1: so I can I can say, you know, you know
24:14
Speaker 1: where I missed the mark And I wasn't communicating this
24:17
Speaker 1: and I've been This is you know, something that I've
24:18
Speaker 1: lived with for twenty plus years and we still have
24:20
Speaker 1: communication problems challenges, right, So how do you so? I
24:26
Speaker 1: want I want to pack it a little bit further
24:27
Speaker 1: here in coming at to you, Chris Westling. So if
24:31
Speaker 1: we're breaking this down and starting to one thing, I
24:36
Speaker 1: really love you bringing this up, Chris is like where
24:39
Speaker 1: is your baseline? Where is our starting point? So that way,
24:43
Speaker 1: like you said, Chris, Christopher, like we're how we're talking,
24:45
Speaker 1: how we're showing up, But you know, where have you seen, Chris,
24:49
Speaker 1: businesses maybe rushing before understanding? And you mentioned that we
24:53
Speaker 1: talked about this before this this podcast about a company
24:56
Speaker 1: kind of rushing before misunderstanding what they're trying to get
24:59
Speaker 1: more leads, every get what it was exactly, but you
25:01
Speaker 1: know it was like, where's your baseline in assessing that?
25:05
Speaker 1: And I'm going to come to you Christopher too, because
25:06
Speaker 1: I think you have some good tools and reasons looking
25:09
Speaker 1: at the where are we at today? Like before we
25:12
Speaker 1: then we can make some actually informed decisions about where
25:14
Speaker 1: we want to go. But Chris, Chris wess In for you,
25:18
Speaker 1: I really like that question or that phrase you've shared
25:21
Speaker 1: with me.
25:22
Speaker 4: So there there's a there's a very frustrating answer. In
25:26
Speaker 4: the ball riage world, there's a very frustrating answer when somebody.
25:31
Speaker 2: Asks me what I want for lunch? And the answer
25:35
Speaker 2: that question is. It depends.
25:37
Speaker 4: It really depends on what what the what the outcome
25:43
Speaker 4: is right? Are we looking for information? Are we looking
25:45
Speaker 4: for transforming in a situation? From my background, that goes to,
25:52
Speaker 4: you know, are you having a teaching or a training
25:54
Speaker 4: sort of intervention? Informational is tea is teaching? Transformation is
25:58
Speaker 4: a training thing. And rebalancing those three safety, challenge, investment
26:03
Speaker 4: things happens differently depending on whether you're looking for change
26:07
Speaker 4: or you're looking for somebody to be able to select
26:11
Speaker 4: the correct answer and a multiple choice question and I
26:18
Speaker 4: want to I guess the two words that are coming
26:20
Speaker 4: in my head right now are pain and communication.
26:24
Speaker 2: If we're looking in the business situation or we're looking
26:28
Speaker 2: in our life.
26:28
Speaker 4: Situation, any amount of pain we have is a process issue.
26:37
Speaker 4: I think I can say that almost almost exclusively. Large
26:41
Speaker 4: If there's pain, there's a process problem which becomes boring,
26:47
Speaker 4: you know, to sort of break it down that way,
26:50
Speaker 4: and then from the other side.
26:51
Speaker 2: On the communication.
26:53
Speaker 4: And I would say a lot of our pain comes
26:54
Speaker 4: from the process of communication as I think through the
26:58
Speaker 4: pain that I'm going through right now, or discomfort or
27:01
Speaker 4: frustration or you know, pick your pick your specific descriptor
27:07
Speaker 4: you know. I go back to that great philosopher and
27:10
Speaker 4: ego Montoya.
27:13
Speaker 2: This this word, I do not think it.
27:14
Speaker 4: Means what you think it means right, coming to terms
27:17
Speaker 4: on your terms, right, and whether that's individual communication, that's
27:22
Speaker 4: whether that's within the group, within your corporation or organization,
27:25
Speaker 4: or whether that's between organizations right understanding what the what
27:29
Speaker 4: the terms are there. But the communication serves for me,
27:35
Speaker 4: I'm just pragmatist, practical sort of thing. It serves the
27:40
Speaker 4: change and that that change serves the outcome. So what
27:43
Speaker 4: is what is the outcome? If in and there's a
27:47
Speaker 4: little bit of a mess there with what I just
27:49
Speaker 4: gave you, So it depends comes from within that. So
27:55
Speaker 4: if you could restate your question from within that messy
27:59
Speaker 4: frame work.
28:00
Speaker 1: Just gave you, well, so I appreciate this the breakdown
28:10
Speaker 1: of it. It depends at times, Chris, I think what
28:14
Speaker 1: I was trying to get at and and is what
28:19
Speaker 1: I find is a lot of folks don't maybe the
28:25
Speaker 1: true facts of of of everything, and they're miss misassessing
28:29
Speaker 1: some things. And so there's some misassumptions they're they're there,
28:34
Speaker 1: We're thinking something is actually there, it really isn't. And
28:36
Speaker 1: this is just going to amplified AI. And this is
28:39
Speaker 1: something I'm going to come to you, Christopher Army too,
28:41
Speaker 1: because I feel like another tool resource that you've shown me,
28:43
Speaker 1: which I'm excited about, is kind of assessing companies objectively,
28:47
Speaker 1: you know, where are they at?
28:49
Speaker 2: Right?
28:49
Speaker 1: And Chris for you coming in of like, you know,
28:52
Speaker 1: how are we you know, really getting the facts of
28:56
Speaker 1: where we're at and and not deluding ourselves. So that'll
28:59
Speaker 1: be actually do something about it. But if if somebody
29:02
Speaker 1: is setting it's oh, I think it's like you, Christopher,
29:04
Speaker 1: you said this earlier. The baby booners think, hey, we're
29:06
Speaker 1: really good, but there's there they're assessing the base and
29:08
Speaker 1: it's actually inaccurate, it's actually wrong and so and and
29:14
Speaker 1: here's the thing. Facts change. Okay, I get it, So
29:17
Speaker 1: the fact today may be different tomorrow. But how do
29:20
Speaker 1: we Chris coming in there, like make this because what
29:23
Speaker 1: I feel like is people are going in with kind
29:25
Speaker 1: of a house of cars or some facts with AI
29:27
Speaker 1: and it's not fully there, and so the baseline right
29:30
Speaker 1: is is off.
29:32
Speaker 4: So so David, I've shared this situation with you, but
29:35
Speaker 4: I'll share it with kind of with everybody one of
29:37
Speaker 4: my clients right now. In our first sort of introductory
29:40
Speaker 4: discovery call, I asked four questions, what does what does
29:44
Speaker 4: your day look like? What does your week look like?
29:46
Speaker 4: What does an ideal week look like? And if everything worked,
29:49
Speaker 4: what would life look like?
29:51
Speaker 1: Right?
29:52
Speaker 4: And whether I ask those questions, those are the answers
29:54
Speaker 4: that I'm listening for, because it's in that pain that
29:57
Speaker 4: people actually get the impetus to make the change right,
30:01
Speaker 4: to overcome the.
30:02
Speaker 2: Rest of it. And what this business owner said, successful business.
30:06
Speaker 4: Owner, millions and millions and millions of dollars of revenue
30:10
Speaker 4: a year. He just wanted to get back to writing
30:15
Speaker 4: his mountain bike three times a week.
30:18
Speaker 5: And that became that that that became I wouldn't say
30:23
Speaker 5: the baseline right, but that became the basis for the
30:27
Speaker 5: change kind of moving forward.
30:30
Speaker 2: Went from there to observation.
30:32
Speaker 4: If you're familiar with the term gimba, you know I'm
30:35
Speaker 4: I'm always on a gimba walk I'm always observing.
30:37
Speaker 2: I'm always looking for you.
30:39
Speaker 4: Know, like the the Bruce Willis movie, the sixth Sense,
30:42
Speaker 4: right that that little kid sees dead people, I see
30:45
Speaker 4: inefficiency and in affected them. And this business owner from
30:54
Speaker 4: the perspective that he was sitting in, not based on data,
30:58
Speaker 4: just responding to the feelings and letting those feelings provide
31:04
Speaker 4: the evidence for the conclusions he was coming to.
31:07
Speaker 2: He's like, well, this is wrong and this is wrong,
31:09
Speaker 2: and this is broken, and this is broken, and this
31:10
Speaker 2: is broken.
31:12
Speaker 4: And he wasn't wrong. Those things were causing pain. Those
31:19
Speaker 4: things were definitely problems, but they weren't they they were
31:25
Speaker 4: symptoms of the problem or a more fundamental problem. And
31:31
Speaker 4: going in and taking a look at the data both
31:34
Speaker 4: observation to get the get enough evidence to figure out
31:39
Speaker 4: where you want to start looking.
31:40
Speaker 2: For the data.
31:41
Speaker 3: If you.
31:44
Speaker 4: Have an anti infestation in your kitchen, which I've had
31:47
Speaker 4: a few times in my life funny stories, you know
31:52
Speaker 4: you don't you don't look in the bathroom for the
31:53
Speaker 4: source of the ant infestation in your kitchen, for instance, right,
31:57
Speaker 4: you kind of try that. What I observed in that
32:02
Speaker 4: situation was and this is just how many calls are
32:08
Speaker 4: you getting how many interruptions during the day. This guy's
32:11
Speaker 4: working from three thirty in the morning to nine o'clock
32:13
Speaker 4: at night, and starting about seven o'clock in the morning,
32:18
Speaker 4: he's getting a call or a text.
32:20
Speaker 2: Every seven minutes on average an interruption.
32:24
Speaker 4: Right, all of that appeared to be downstream of their
32:30
Speaker 4: estimation process. They weren't when the salespeople would go into
32:35
Speaker 4: the client, they weren't getting enough information, which wasn't getting
32:40
Speaker 4: handed off to the back end of the business enough,
32:42
Speaker 4: which just kind of cascaded and expanded the number of
32:45
Speaker 4: those calls where I got. So that was observational anecdotal
32:50
Speaker 4: at that point. But and this is where I used
32:53
Speaker 4: the tools available to me. I was able to actually
32:59
Speaker 4: go through through pull down twenty nine hundred of their
33:05
Speaker 4: estimates over the last two years, and do statistical analysis,
33:09
Speaker 4: inferential analysis, you know, sort of lean six sigma some
33:14
Speaker 4: other things on it, and identified that they had two salespeople.
33:20
Speaker 2: And not only was this salesperson.
33:24
Speaker 4: Continue consistently quoting twenty percent less for the same job,
33:28
Speaker 4: but that that salesperson was also consistently not quoting specific
33:34
Speaker 4: subcontractors that they had to bring into that job. And
33:38
Speaker 4: they were and so this whole system systematic cascade downflow
33:42
Speaker 4: sort of thing happened. So the first intervention in that,
33:48
Speaker 4: which really isn't that hard. Let's set up a consistent
33:54
Speaker 4: set of expectations for what the estimate, what the salesperson
33:57
Speaker 4: is going to be getting from a note standpoint, and
34:00
Speaker 4: how what goes into the estimate on the other side. Now,
34:04
Speaker 4: to minimize the change the burden of change in that,
34:11
Speaker 4: there are portions of that that we can take out
34:14
Speaker 4: of the hand of the person.
34:15
Speaker 2: Having to type up the estimates.
34:16
Speaker 4: Sure, you can actually automate that right there, whether it's
34:20
Speaker 4: API calls, whether it's using the deterministic tools that are there,
34:24
Speaker 4: whether it's using the inferential to go to you took
34:28
Speaker 4: pictures of this situation, you made notes about the sort
34:31
Speaker 4: of situation. Chances are you're going to need to have
34:34
Speaker 4: a demo person come in to do this. So let
34:38
Speaker 4: me surface that in the estimate and then the decision
34:41
Speaker 4: the person that reviews the estimate at the end of
34:43
Speaker 4: that will decide whether or not that stays in or
34:46
Speaker 4: goes And just for you know, just just a scope
34:53
Speaker 4: sort of.
34:55
Speaker 2: Or an impact, it's a seven hundred thousand dollars impact
35:00
Speaker 2: for that.
35:01
Speaker 1: Wow, that's huge.
35:03
Speaker 4: Without changing that actually reduces their work, they're going to
35:07
Speaker 4: be able to see that much of an impact increase
35:11
Speaker 4: in their in their revenue, the outcome, the the sort
35:16
Speaker 4: of observation and then actually finding that baseline, this is
35:18
Speaker 4: actually where you are, This is where you can.
35:22
Speaker 2: Be putting that in place. Yeah, hopefully answered your question.
35:26
Speaker 1: Yes, yes, Well then that tees me up for Christopher. Christopher,
35:31
Speaker 1: you know what you are showing me when we met
35:33
Speaker 1: what I loved how you were able to look at
35:37
Speaker 1: companies with publicly available data information assessing kind of their
35:42
Speaker 1: their baseline. And if you wouldn't mind, I would just
35:45
Speaker 1: because I think it's so fascinating what you're doing at
35:47
Speaker 1: Self Doubt Labs. Talk us through this work that you've
35:51
Speaker 1: been doing with over what is a million three companies.
35:53
Speaker 1: You've looked at so many different companies and being able
35:54
Speaker 1: to get like a baseline understanding where they're, where they
35:57
Speaker 1: have been, and where they are currently. I think is
36:00
Speaker 1: just such an amazing work that you're doing. If you
36:02
Speaker 1: wouldn't mind just unpacking that a little bit of like
36:04
Speaker 1: how you're looking at that and getting a pulse on
36:07
Speaker 1: the companies that are out there.
36:10
Speaker 3: Yes, So let me answer that, and then I want
36:13
Speaker 3: to go back to what Chris was talking about after
36:15
Speaker 3: you the So it turns out way back, long ago,
36:23
Speaker 3: this is the thirty second history. Yes, you can go
36:27
Speaker 3: back to the Greeks. You can go back to Sir
36:30
Speaker 3: Francis Galton. The lexical hypothesis, which is the origination that
36:36
Speaker 3: our personalities can be encoded into a single word, is
36:41
Speaker 3: giving away who we are. Our choice of words is
36:46
Speaker 3: like opening up a toolbox. And for me, you know,
36:51
Speaker 3: certain people love vice cripts, other people love crescent wrenches.
36:55
Speaker 3: Some people like closed in box wrenches. Right, they kind
36:59
Speaker 3: of do the same thing. But right, you know you
37:03
Speaker 3: can hammers are pretty good for nails, right, so you
37:11
Speaker 3: could also dig a hole with one, right, yeah. Yeah,
37:18
Speaker 3: So depending on who you are deep down subconsciously, you're
37:24
Speaker 3: going to go to your box of tools and you're
37:29
Speaker 3: going to use them in a certain way, certain amount
37:32
Speaker 3: to figure out stuff. Okay, And you can capture all
37:39
Speaker 3: of that public data and form pretty damn good theories
37:45
Speaker 3: about a business. And when you put all that together,
37:50
Speaker 3: you can then connect it to financials and you could say,
37:54
Speaker 3: can I predict where this business is going based on
37:58
Speaker 3: just language. Now, a lot of people want to go
38:01
Speaker 3: to NLP or something just semantics. No, in the language
38:07
Speaker 3: psychology world, you can think of it this way, cow
38:11
Speaker 3: jumped over the moon. NLP is going to basically say,
38:15
Speaker 3: there's a kinetic event, there's a celestial object, there's you know,
38:20
Speaker 3: it's going to describe things just in a different way.
38:23
Speaker 3: That's my criticism of NLP language psychology. The cow jumped
38:28
Speaker 3: over the moon. Somebody making that statement is an indication, huff,
38:32
Speaker 3: how much you love your mom? Quite different? Right, So yes,
38:39
Speaker 3: Now I'm going to bring it to a real story
38:41
Speaker 3: that was. Imagine a company they have to put out
38:45
Speaker 3: a ten case statement and everything's going well. Company is
38:50
Speaker 3: just doing fine, up and up. There's a certain language
38:54
Speaker 3: pattern to that, okay, and a lot of times it's
38:59
Speaker 3: present focused language. Now, all of a sudden, the team
39:05
Speaker 3: that has to put together the ten K realizes there's
39:09
Speaker 3: some big problems developing. Oh my gosh, we have to
39:15
Speaker 3: collectively lie. Now you could also call that another thing.
39:20
Speaker 3: You could call that shallow coping. Okay, okay, Oh, let's
39:25
Speaker 3: parking lot that topic. Hey, we got to really look
39:27
Speaker 3: at this fraud problem. Put that in the parking lot
39:30
Speaker 3: for now, and let's get to it Chris next week.
39:33
Speaker 3: That's called shallow coping. That can be measured true story
39:37
Speaker 3: three years, This company slowly goes from present voice to
39:45
Speaker 3: future voice. There certainty scores go from up here where
39:53
Speaker 3: anxieties go up. All this pulled from language. You can
40:00
Speaker 3: call it collective lying, you could call it shallow coping.
40:04
Speaker 3: But maybe the best way to explain it is imagine
40:07
Speaker 3: if a group of people getting a run and they
40:09
Speaker 3: have to release a public statement, and it's something along
40:14
Speaker 3: the lines of like when you were sixteen and you
40:16
Speaker 3: stole your dad's car on a Saturday night at three am,
40:20
Speaker 3: and you went cruising with a friend for a couple hours.
40:24
Speaker 3: Dad marches into your bedroom in the morning at seven
40:27
Speaker 3: am and says, Chris, what were you doing last night?
40:32
Speaker 3: What happens to your brain? Shoot, chemicals are just flying,
40:39
Speaker 3: the mind is going sleeping. That's really interesting, Chris. The
40:47
Speaker 3: engine's warm, I don't remember driving it last night, and
40:51
Speaker 3: there's a couple of beer bottles in the back seat.
40:54
Speaker 3: Oh right, what is your brain doing? Yeah, you're going
40:58
Speaker 3: into that toolbox and you're pulling out all kinds of
41:01
Speaker 3: stuff you don't normally pull out because normally is an
41:04
Speaker 3: honest guy. M hmm. All of a sudden, all this
41:08
Speaker 3: language structure changes. And guess what the example company I'm
41:13
Speaker 3: talking about three years before a complete implosion in bankruptcy,
41:19
Speaker 3: they started collectively lying and it was right there. It's
41:24
Speaker 3: right there, right there, all of these one metrics going
41:29
Speaker 3: this way, This one's going this way. You'll see a
41:32
Speaker 3: lot of times where clout or certainty in the business
41:36
Speaker 3: model the people on the earnings calls. Over time, the
41:41
Speaker 3: confidence in the model is doing this, the anxiety is
41:44
Speaker 3: going up. The future folks present shifts to future focus.
41:49
Speaker 3: Sell that stock.
41:52
Speaker 6: I can ask you a detailed question or real quick Christomer,
42:00
Speaker 6: go ahead, could you list three.
42:05
Speaker 2: Had big thinkers or.
42:09
Speaker 4: Well accepted frameworks for the lexical or the lexic hypothesis
42:14
Speaker 4: or the language philosophy?
42:19
Speaker 3: Oh well, certainly, sir Francis Galton's the beginning of it all.
42:24
Speaker 3: But that's going.
42:24
Speaker 1: Back right.
42:27
Speaker 3: Gordon Alport. And wow, there's so many. Okay, there's a
42:36
Speaker 3: lot of it. The best thing to do, I tell you,
42:39
Speaker 3: if you really want to learn about this. Now you
42:42
Speaker 3: know my English grades in college weren't the best. But
42:46
Speaker 3: if you know a particular piece of language. First person pronoun,
42:53
Speaker 3: go into AI, go into go. I don't care where
42:55
Speaker 3: you go. First person pronoun, high indexing psychological meaning.
43:04
Speaker 2: Okay, and have at it.
43:07
Speaker 3: Prepositions pronoun, look at the specific and look at all.
43:12
Speaker 3: If you go into the research section of Google, look
43:15
Speaker 3: at the tens of thousands of citations on single bits
43:21
Speaker 3: of words that have been studied over the last one
43:25
Speaker 3: hundred and fifty years. That's what I did. I basically
43:27
Speaker 3: pulled one hundred and fifty years of research, normalized, pulled
43:31
Speaker 3: in the results, and created an algorithm that looks at
43:36
Speaker 3: thousands and thousands of words and the meaning behind that.
43:40
Speaker 3: But that is just academic to that point.
43:44
Speaker 4: Are you familiar with the book how to Read a
43:46
Speaker 4: Book by more Adlert?
43:48
Speaker 2: Oh my goodness.
43:49
Speaker 3: Yeah yeah, yeah, yeah, yeah, that's cool. I'll have to
43:52
Speaker 3: look that up.
43:53
Speaker 2: Yeah, thank you, thank you for the interruption.
43:57
Speaker 1: That's good. I always shared this information on the podcast table.
44:01
Speaker 3: Well, it's all academic until you connect it to something causal.
44:05
Speaker 3: So if you connect it to hiring, you connect it
44:08
Speaker 3: to not so much ratings of companies, but the written ratings.
44:17
Speaker 3: The ratings of a company over time are incredible sources
44:21
Speaker 3: of data to tell you what's happening to this company
44:25
Speaker 3: over time. And it's really complex, but it's really touched
44:28
Speaker 3: a lot. You can combine semantics with language psychology to
44:32
Speaker 3: understand what is really happening with this business's return policy
44:36
Speaker 3: or customer satisfaction. But I wanted to go back to
44:41
Speaker 3: Chris's bit about that you were talking about this company
44:47
Speaker 3: and you had these two salespeople. Was this addressed at
44:52
Speaker 3: any time before? Or are you the first person to
44:54
Speaker 3: identify it?
44:55
Speaker 4: I'm the first person to identify it. Do you think
45:00
Speaker 4: the finger pointing and the blame was around other things?
45:08
Speaker 3: But a lot of times what you see in an
45:12
Speaker 3: organization is something called shallow coping where they parking lot
45:17
Speaker 3: it or will defer that to the next that's not
45:21
Speaker 3: on the priority list, or the value of that problem
45:26
Speaker 3: is not you know, for today's discussion. So there's always
45:29
Speaker 3: of businesses how they cope, and so bringing it back
45:32
Speaker 3: to AI, hey, you know we're going to release all
45:37
Speaker 3: these tokens and we're going to have our data science
45:39
Speaker 3: team do all kinds of things. Do you have any
45:42
Speaker 3: governance model around that? Put that on the parking lot
45:45
Speaker 3: for next week? And then you're Uber, and you go
45:47
Speaker 3: through three point four billion dollars worth of tokens? Did
45:52
Speaker 3: I mean? I would expect the return on investment to
45:55
Speaker 3: be at least ten to one for this AI project?
45:57
Speaker 3: So clearly Uber is making already four billion dollars more
46:02
Speaker 3: per year because of those tokens.
46:05
Speaker 4: Right makes me want to scream all the tech bros
46:08
Speaker 4: out there, all these claims.
46:12
Speaker 3: And so the other thing that that comes into play,
46:16
Speaker 3: and I have to thank a guy named John Boyce
46:18
Speaker 3: for bringing this up, is this concept called the hidden curriculum.
46:23
Speaker 3: And so who we hire and how we think about
46:26
Speaker 3: problems is are there's broadly three categories and this all
46:32
Speaker 3: dials back again to psychology. Are we hiring an obedient workforce?
46:39
Speaker 3: Are we getting the factory, make the gears, don't complain, that's.
46:45
Speaker 2: Not if you're hiring me.
46:48
Speaker 1: Well, so to your point, to.
46:51
Speaker 3: Your point, Chris, are you then looking for the loopholes
46:55
Speaker 3: so you understand the obedience model? Are you looking for
46:59
Speaker 3: the loopholes? Or if you're in the privileged category, are
47:03
Speaker 3: you allowed to change the rules? And the problem is
47:07
Speaker 3: is if the leadership team is obedience or just loopholing,
47:12
Speaker 3: then they're not likely to feel comfortable changing the rules
47:17
Speaker 3: which allow them to prevent shallow coping. All this stuff
47:23
Speaker 3: can be measured in real time to prevent, to prevent
47:29
Speaker 3: what AI is really doing to businesses, which is a
47:33
Speaker 3: lot of Wow. Just factory model worker meets AI and
47:42
Speaker 3: the souls you are mess. You are doomed.
47:47
Speaker 4: So in the last you know, since twenty twenty two,
47:50
Speaker 4: really when it was starting, it seems to be it
47:52
Speaker 4: was getting more broader, more broad use. Yeah, are you
47:56
Speaker 4: seeing the corporate communication better obfuscated because of AI?
48:04
Speaker 1: Down? Going down?
48:07
Speaker 3: There's another problem? You ready for the next problem? Oh?
48:12
Speaker 2: Yeah? Loving it?
48:14
Speaker 3: Leadership, What is your Socratic reasoning score? Do you do
48:20
Speaker 3: Socratic reasoning or do you do linear thinking? Did you
48:23
Speaker 3: go to school and go you know what? When I
48:26
Speaker 3: got those four multiple choice questions, I easily discounted too,
48:31
Speaker 3: and I have fifty percent shot at least when getting
48:33
Speaker 3: these two right, and I got those answers in ten seconds.
48:36
Speaker 3: I was always turning in my test fast. It's linear thinking.
48:41
Speaker 4: In the in the Navy, we called it recognizing right
48:44
Speaker 4: answer when told.
48:45
Speaker 3: So obedience yes, very good? Wow, Chris, what did you
48:51
Speaker 3: do in the Navy?
48:52
Speaker 4: By the way, I was a well lots of things.
48:56
Speaker 4: I was a reactor operator on a Blisk missile submarine.
49:01
Speaker 2: Which I got in a lot of trouble.
49:05
Speaker 3: Again, which which one I've actually been on the USS
49:09
Speaker 3: San Diego.
49:11
Speaker 4: Uh USS Henry and Jackson gold Crew. It was one
49:14
Speaker 4: of the tridents out of uh out of near kids
49:19
Speaker 4: appen the Kids Up sub based banger up in Kids
49:23
Speaker 4: Up Peninsula in Washington State.
49:25
Speaker 3: Wow, Okay, damn, that's pretty cool.
49:29
Speaker 2: Cool.
49:31
Speaker 4: I actually credit I credit the system's thinking to the
49:35
Speaker 4: Navy training, so the the recover Navy, the ability to
49:45
Speaker 4: do macro and micro thinking almost at the same time,
49:48
Speaker 4: and to be able to freely move.
49:50
Speaker 3: You mean, you can't go to home depot if something's wrong.
49:56
Speaker 4: So it's uh, yes is the short end or let
50:00
Speaker 4: let let me bypass off the long answer that I
50:02
Speaker 4: want to.
50:03
Speaker 2: Give for that. Yeah, yeah, totally.
50:06
Speaker 4: Going from musical theater to nuclear power was probably really
50:13
Speaker 4: really good for me.
50:16
Speaker 3: Yes, I would say so, yeah, musical the musical theater
50:21
Speaker 3: would be more change the rules and then living inside
50:25
Speaker 3: of what you did is a there is a lot
50:28
Speaker 3: of obedience to that structure, but boy, there's a lot
50:31
Speaker 3: of loopholes. You've got to survive you have a goal,
50:35
Speaker 3: you have an out, you have a mission m h
50:38
Speaker 3: and it it requires very different thinking. So going back
50:42
Speaker 3: David to that, where are we today when we look
50:45
Speaker 3: at leadership and we have a factory model in place,
50:50
Speaker 3: there's a lot of danger that there's not adaptability. So
50:55
Speaker 3: when suddenly the valve starts leaking and you're two thousand
50:58
Speaker 3: feet below the surface and you say, well, I don't
51:01
Speaker 3: see anything in the in the specs about what to
51:04
Speaker 3: do with that leaking valve, so I guess I'll just
51:07
Speaker 3: ignore it. That would be shallow coping in a very
51:11
Speaker 3: bad environment, right, And so that's what's happening with which is.
51:17
Speaker 2: Which is what? Sorry for the interruption exactly what happened
51:20
Speaker 2: to three mile.
51:21
Speaker 3: Islands m oh dot topack that one a little bit
51:26
Speaker 3: for the.
51:26
Speaker 1: For the for the younger generation, Chris.
51:30
Speaker 2: So, there was an island, it was three miles long.
51:32
Speaker 4: No, there was a reactor power a commercial power plant.
51:38
Speaker 4: And just to simplify it and flatten some things, they
51:43
Speaker 4: had an issue in their alarm system like a whatever
51:49
Speaker 4: it was, some electrical thing and alarm was erroneously going
51:52
Speaker 4: off and it was actually a problem with the alarm system.
51:55
Speaker 2: They bypassed that alarm.
51:58
Speaker 4: They got used to the blinking of that light, they'd
52:02
Speaker 4: silence the annoying buzz.
52:05
Speaker 2: But the trouble is that actually went to a leak sensor.
52:11
Speaker 4: That when they actually started getting a slow leak, that
52:17
Speaker 4: sensor that was supposed to detect it, they.
52:19
Speaker 2: Had bypassed it, and I would never actually fixed that problem.
52:23
Speaker 4: So it ended up masking and allowing that the massive
52:28
Speaker 4: loss of coolant leak and the environmental impact of the
52:31
Speaker 4: rest of that. You all down to, all down to
52:34
Speaker 4: just battle electrical and electronic maintenance practices is really what
52:38
Speaker 4: it came down to.
52:39
Speaker 3: Damn. Yeah.
52:43
Speaker 1: Yeah, to your point, Christopher, going back what you said
52:46
Speaker 1: about leadership is obviously what I'm passionate about leadership developing
52:50
Speaker 1: people having this place and I think, you know, we're
52:52
Speaker 1: coming out of a world even in our educations, I
52:55
Speaker 1: might argue, where we come out of we kind of
52:57
Speaker 1: trained people to be in this you obedient model, Hey,
53:01
Speaker 1: go through this, be that, this, get into the get
53:04
Speaker 1: get into the cog. Instead what we're seeing and that's,
53:08
Speaker 1: you know, because we don't need people that are not
53:10
Speaker 1: just gonna I mean, there's gonna be emplementaries. Don't get
53:13
Speaker 1: me wrong, But what you're saying, what I'm hearing you say, Christopher,
53:15
Speaker 1: is you know, looking at the folks that can actually
53:19
Speaker 1: be willing to change the rules and understanding that it's
53:22
Speaker 1: not just for changing the sake of rules. We're not
53:24
Speaker 1: just trying to like you know, but it's for a
53:26
Speaker 1: real purpose. It's because we were looking at where we
53:29
Speaker 1: want to go and it's not being shortsighted like you're
53:32
Speaker 1: just living highlighted, Chris. We're like, oh, this is annoying,
53:35
Speaker 1: you know, no, And to me, that's really powerful, Christopher.
53:39
Speaker 1: And I think businesses, I think you've highlighted this before
53:42
Speaker 1: when we were talking businesses that aren't thinking about that,
53:44
Speaker 1: not allowing for that to change the rules to adjust. Hey,
53:47
Speaker 1: just get in line, just make this. This is the
53:49
Speaker 1: way it is. We're seeing, like you said, that decline
53:52
Speaker 1: going down there, and if you're just using AI, it's
53:55
Speaker 1: just amplifying that that way of thinking and approaching some things.
54:00
Speaker 3: The last forty years, you could argue, the last four
54:03
Speaker 3: you could call it nineteen eighty with every year, you know,
54:08
Speaker 3: you go to the mall, it's like a little bit
54:10
Speaker 3: this new store. You know, Hey, I put money in
54:13
Speaker 3: the stock market and we're rich. Like, there's a lot
54:16
Speaker 3: of things that really went pretty well over the last
54:19
Speaker 3: forty years. Then we started to get into these big
54:21
Speaker 3: hiccups and we're now in a cycle of permanent hiccups. Decentralization, complexity,
54:30
Speaker 3: lots of things like you know, why is Nike stock
54:34
Speaker 3: so bad? There used to be such a cool company.
54:37
Speaker 3: There's so many things that have just kind of, you
54:41
Speaker 3: would argue, come off the rails. And so these are
54:46
Speaker 3: very much environmental problems. You know, you can go from
54:49
Speaker 3: demographic winter, labor participation, money, oh my gosh, there's so
54:56
Speaker 3: many things. But as a business, if you were designed
55:00
Speaker 3: for consistent, continuous efficiency gains, then suddenly, you know, putting
55:08
Speaker 3: a five percent improvement on something that doesn't matter anymore
55:12
Speaker 3: doesn't mean anything. Like it's how you have to step
55:18
Speaker 3: back and go, okay, it's you have to think more
55:21
Speaker 3: like a Jamie Diamond than you do think like somebody
55:25
Speaker 3: creating efficiencies. These efficiencies don't work in the new environment,
55:32
Speaker 3: and that's the whiary we're facing. A lot of that
55:36
Speaker 3: that that old system does not exist, and a lot
55:39
Speaker 3: of it does have to do with demographic winter, especially
55:43
Speaker 3: in the United States.
55:46
Speaker 1: Yeah, There's a great book I read called ten X
55:49
Speaker 1: is Easier than to X Christopher about thinking of incremental
55:53
Speaker 1: thinking versus this bigger move And I think to your point,
55:57
Speaker 1: we need that bigger move that they that tenets thinking,
56:01
Speaker 1: because honestly, the effort that's involved just to get like
56:03
Speaker 1: you said, a five percent of minimal intern is like,
56:06
Speaker 1: you know, we can actually do a lot more. But
56:08
Speaker 1: if we're not thinking about this, really we're not. This
56:11
Speaker 1: is where I feel like AI gets this into trouble
56:13
Speaker 1: when we're thinking this is the answer and it's not,
56:15
Speaker 1: because it's about how how do we think? How do
56:17
Speaker 1: we approach these problems like you're saying, and what's the culture?
56:21
Speaker 1: What's going in there? And so why I ask you
56:23
Speaker 1: both about the baseline looking at this is because if
56:25
Speaker 1: we don't have a baseline, an understanding, and just a
56:27
Speaker 1: really honest assessment of where we're at, it's really hard
56:30
Speaker 1: to make than any meaningful movement forward, you've got to
56:33
Speaker 1: have a reality check and then you can actually do
56:36
Speaker 1: something about it. But if you don't have that reality check,
56:38
Speaker 1: you're you're kind of screwed. I mean you're just like, well,
56:41
Speaker 1: we're in this bubble and this is why I wanted
56:43
Speaker 1: to have you both on the podcast, because you're both
56:46
Speaker 1: voices that are coming in and holding the mirror to
56:48
Speaker 1: clients and others and saying, hey, let's look at the
56:50
Speaker 1: reality and let's actually do something much better and healthier
56:53
Speaker 1: over the long run. I know we're getting into the podcast,
56:56
Speaker 1: so I want to go longer. But I know we
56:58
Speaker 1: don't have to wrap it up here. So I would
57:00
Speaker 1: ask you guys both of these questions. Because we've covered
57:03
Speaker 1: a lot here in the podcast. But if I'm the
57:06
Speaker 1: business owner, if I'm that leader, and here's an opportunity,
57:11
Speaker 1: you guys have given me some great information, what would
57:13
Speaker 1: you recommend that I do as a business owner leader?
57:17
Speaker 1: And I'll start with coming with you Chris Westling first,
57:19
Speaker 1: and I'll come to Christopher. But what would you say
57:21
Speaker 1: you know to do so that I can assess my baseline,
57:25
Speaker 1: look at how I'm thinking approaching things, and move in
57:27
Speaker 1: a much more productive and effective not necessarily efficient, but
57:31
Speaker 1: really truly an effective way that I really feel good
57:34
Speaker 1: in that I can then actually truly lean into the
57:36
Speaker 1: AI and actually have it helped me. But Chris, I'll
57:38
Speaker 1: start with you first.
57:41
Speaker 2: Well, what I'm going to do.
57:42
Speaker 4: At the end of this there's such good, so much
57:45
Speaker 4: good stuff that came out from from Chris.
57:48
Speaker 1: Chris.
57:50
Speaker 4: I'm going to take the transcript of this podcast and
57:54
Speaker 4: I'm going to generate a new number of frameworks based
57:57
Speaker 4: on the references and the terms that he's mentioned, and
58:01
Speaker 4: I'm going to use a large language model, probably Claude,
58:06
Speaker 4: and I do it on my phone with a hands
58:09
Speaker 4: free while I'm walking around, and I'm going to have
58:11
Speaker 4: a dialogue with Claude and have Claudia.
58:17
Speaker 2: Interview me and sort of ask me questions.
58:20
Speaker 4: And I'm going to dialogue in there, and I'm going
58:21
Speaker 4: to look for I'm gonna I'm gonna look for patterns.
58:25
Speaker 2: I'm not gonna look for answers.
58:25
Speaker 4: I'm gonna look for better questions, which is kind of
58:29
Speaker 4: what I'm is the value I have. And then based
58:33
Speaker 4: on what comes out of that, and I have this
58:35
Speaker 4: hardwired into what I do, I'm going to apply a
58:40
Speaker 4: falsification framework to it. There's a scientist by the name
58:44
Speaker 4: of Popper back in the nineteen thirties came up with
58:46
Speaker 4: this hypothesis testing falsification thing, and it asked the question,
58:53
Speaker 4: what's the least amount of information I need to falsify
58:57
Speaker 4: whatever this hypothesis is. And I have that framework running
59:03
Speaker 4: automatically on me when I do research for on clients,
59:10
Speaker 4: when I'm prepping for meetings and people have websites, the
59:14
Speaker 4: falsification framework is looking at the stats and the information
59:17
Speaker 4: that they have on their websites, and it just sort
59:20
Speaker 4: of catches. It gives it gives me better questions. It
59:23
Speaker 4: catches me, and that so.
59:27
Speaker 2: I'm going to you know, take this transcript, come.
59:31
Speaker 4: Up with the better question, come up with better questions.
59:34
Speaker 2: Based on this transfer. See what I ask.
59:37
Speaker 1: Chris and any of those you know need the transcripts,
59:41
Speaker 1: you can message me. You can also this is on
59:43
Speaker 1: YouTube or your favorite podcast platform. You should be able
59:46
Speaker 1: to get that as well. But if you need help,
59:48
Speaker 1: let me know. I'm happy to share. Christopher, how about you,
59:52
Speaker 1: what would you encourage our listeners to take action on
59:55
Speaker 1: with this information we've talked about today?
59:58
Speaker 3: Just call up David Are and get him to talk
1:00:03
Speaker 3: you through what's the next step and what are you
1:00:06
Speaker 3: ready for? Besides that, who realize that what you're measuring,
1:00:21
Speaker 3: it's not always the complete picture. There's a lot of
1:00:24
Speaker 3: hidden variables and to kind of go back to what
1:00:28
Speaker 3: Chris talked about his Navy world. You could spend all
1:00:33
Speaker 3: your time looking at the past to try to predict
1:00:35
Speaker 3: the future. You can look at the present to know
1:00:39
Speaker 3: situationally where you are. But it's only radar and sonar
1:00:43
Speaker 3: that gives you some indication of the future. And it's
1:00:48
Speaker 3: not that they're predictors of the future. They're just predicting
1:00:50
Speaker 3: where you'll be sometime in the future, where something might
1:00:54
Speaker 3: exist in the future or present. And realize that in business,
1:01:01
Speaker 3: it's not a lot of there's not a lot of
1:01:03
Speaker 3: signal there currently, and a lot of that signal is
1:01:08
Speaker 3: not physical objects, it's people and making decisions. So if
1:01:14
Speaker 3: you have radar and sonar on decision making of your company,
1:01:17
Speaker 3: of your supply chain, of your customers, it's like having
1:01:22
Speaker 3: radar and the other analogy to where is your business?
1:01:28
Speaker 3: So you really don't need radar. If it's a clear
1:01:30
Speaker 3: day and there's a straight river, a nice straight river
1:01:36
Speaker 3: and wide banks in the distance, you're going down, I
1:01:41
Speaker 3: don't even know what that would be the Saint Lawrence,
1:01:43
Speaker 3: see what maybe, But if it's foggy and the river
1:01:48
Speaker 3: is very curvy, and suddenly this thing called AI just
1:01:52
Speaker 3: stepped on the gas. You better get some radar and sonar.
1:02:00
Speaker 3: Think about what that means to your business.
1:02:05
Speaker 1: Yeah, well, I so appreciate you Christopher sharing Chris Westling
1:02:09
Speaker 1: being on the podcast with us. If you guys have
1:02:12
Speaker 1: questions for them or common please leave them wherever you
1:02:15
Speaker 1: are listening with us, up Apple, whatever the case might be.
1:02:22
Speaker 1: YouTube will make sure you gets back to both Christopher
1:02:25
Speaker 1: and Chris. Of course, connect with them on LinkedIn. We're
1:02:29
Speaker 1: all connected there and all their information, their websites, all
1:02:31
Speaker 1: that good stuff is there. I hope today's conversation really
1:02:34
Speaker 1: inspired you to look at leadership, how we're communicating the
1:02:37
Speaker 1: health of your team, the culture, how you're processing and
1:02:40
Speaker 1: making the decisions on technology. Of course, I'd love to
1:02:44
Speaker 1: connect with you too, David Carson under the steward your
1:02:47
Speaker 1: business and our team helping you and moving forward, Like
1:02:50
Speaker 1: Christopher said, helping your team and developing you, becoming more
1:02:53
Speaker 1: sustainable in your efforts to build and grow your team.
1:02:56
Speaker 1: I want to thank you both for being here and
1:02:58
Speaker 1: help everybody come back on the Business Round Mee podcast.
1:03:01
Speaker 1: Until next time, be well, thanks guys, thank you, Thanks
1:03:04
Speaker 1: so