← Scrum Master Toolbox Podcast: Agile storytelling from the trenches
Scrum Master Toolbox Podcast: Agile storytelling from the trenches
Organizations as Ecosystems — Understanding Complexity, Innovation, and the Three-Body Problem at Work With Simon Holzapfel
00:40:45
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- [00:04]
A
Hey there, agile adventurer, just a quick question. What if, for the price of a fancy coffee or half a pizza, you could unlock over 700 hours of the best agile content on the planet? That's audio, video, E courses, books, presentations, all that you can think of. But you can also join live calls with world class practitioners and hang out in a flame war free and AI slop clean slack with the sharpest minds in the game. Oh, and yes, you get direct access to me, Vasko, your Scrum Master Toolbox podcast. No, this is not a drill. It's this Scrum Master Toolbox membership. And it's your unfair advantage in the agile world. So if you want to know more, go check out scrummastertoolbox.org membership. That's scrummastertoolbox.org Membership. And check out all the goodies we have for you. Do it now. But if you're not doing it now, let's listen to the podcast. Hello everybody. Welcome to this very special bonus episode. And joining us to explore ecosystems and organizations is Simon Holsapfeld. Hey Simon, welcome to the show.
- [01:25]
B
Thank you, Asuka. It's a great pleasure to be here and to be in your presence after years of reading your work.
- [01:31]
A
So Simon is an educator, a coach, and a learning innovator who helps teams work with greater clarity, speed and purpose. He specializes in separating strategy from tactics, enabling short cycle decision making and higher value workflows. Simon has spent his career coaching individuals and teams to achieve performance with deeper meaning and joy. He's also the author of an amazing newsletter on substack called Equinomist. Simon will explain what that word means, but before he explains. Today we're here to talk about a topic that I think many of you listen will find extremely interesting and enlightening. The topic is ecosystems, which are a specific kind of system. Simon will explain that in a minute. But first, Simon, what is that name of your newsletter on Substack?
- [02:25]
B
Sure, sure. So I chose the name Equanimist specifically as a mashup of two different things that too often do not go together, which is economics. And that's the nomics part. But the equine part is really about both equanimity, which is that condition of being at work, involved in one's life with a sense of balance, but also something like equality of humans within teams.
- [02:52]
A
And.
- [02:53]
B
And if we know one thing, it's that our future and our past are teamed. And so we need to think in terms of those sorts of things, the way Quantum is supposed to show and be Playful in mixing things up to find new ways.
- [03:06]
A
So one of the things that I find really interesting, especially now in the age of AI, is this focus on teams. Because I happen to believe that teams are what I call the unit of productivity, knowledge, work. Now, many people who listen to me and many of my past managers and even clients have not necessarily agreed with me. Even if on the service they might say they agree. When we see the decisions they make, they often make decisions that are more towards managing individuals like individual pieces in a chessboard. Now you bring to us a completely different perspective which I want to explore. But first we need to put some definitions on the table. So you talk about ecosystem. So in your own definition, what, what are ecosystems in the context of business and work? And why do you prefer to use that word instead of just systems?
- [04:01]
B
Excellent. Yeah, thanks. So the most basic decision fork there is about types of systems and the names that we give them. Complex adaptive systems are complex in nature and we can talk about what those rules are adaptive in that they evolve over time. That's different from a static system. I was really blessed in high school when my physics teacher brought Stella system modeling to our class. So we learned physics through systems. I didn't know anything about complex adaptive systems at that time, but by getting introduced to Systems as a 17 year old, when I then got into senior management roles and learned much more about what was going on, I'll use ecosystem because it's less technical than complex adaptive systems, which is off putting to many people. So ecosystem, complex adaptive system, two words for just the craziness of teams and life and business.
- [05:02]
A
And it's very important for us to realize that this word system is not used innocently. It is used as a result of an in depth and over many years analysis of what is happening in organizations. First to be said, systems came more from the engineering perspective, understanding that things connect in a certain way and you need to understand how they connect in order to understand the whole. But when you talk about systems that include people, you're talking about a different level. So when I hear you, the distinction in my mind is mechanical. Systems have a predictable, even if not statistical, what do you call it? That there's. That is that they are predictable but they don't always give you the same result necessarily. Right. They are stochastic. But then with, with people you have a completely different degree of freedom which is that people can in the moment, in real time adapt to what is happening so that their observation of the system has an impact on how the system behaves. Itself because everybody in the system is looking at perceiving and adapting at the same time, right?
- [06:20]
B
Yes. And that's where managers get confused. They forget it's the interactions amongst the team that are so powerful in both defining, setting the boundaries and what the team can do and the team sense of itself. And so too often managers in that overly individualistic way only focus on the individuals and they get less interested in the interactions, which is really where the magic comes from over time, as teams mature, et cetera.
- [06:51]
A
And that part, the interactions as you named it, is very important because a system does not have part behavior, if you will, meaning that you can analyze the behavior of all of the parts, but you will not be able to reconstitute the behavior of the system because you need to look at the system results in order to understand the system itself. And then the parts are putting all the parts together are not going to get you the behavior of the system. That is they are opaque to analytical insight. Right?
- [07:28]
B
Correct, Correct. And so the three body problem in physics describes why we can't do that. When you have three nonlinear functions working at the same time within a system, you have almost no ability to predict its future state beyond just some of the shortest time series.
- [07:45]
A
This is very interesting for me because now with the age of AI we are starting to see kind of this individualization of work turned all the way up to 11 ie managers now think I can just tell a person to work with a bunch of AIs and they can do whatever a team would do. But now it's only one person that I need to manage.
- [08:08]
B
So goes the thought. But I think that's. And it'll be interesting to see over time. I mean one thing we know is humans and their tools always do things that we don't expect. So I'm very much out of the business. I'm trying to guess where any of this is going. I'm just looking at the people around me, the leaders, the people I'm trying to help on a day to day business, their organizations not worry about what's the far future going to be. Let's focus on how's our team now. Are there AIs that can help us with our bottlenecks really keeping it much closer to where the humans are and not getting lost in our heads when it's easier to dehumanize frankly any piece of the system and the people. And so by keeping it close and that's really what coaches do, and especially leaders who learn to coach understand about their people, that makes AI useful, an adjunct, but not a rep. I mean, AI still can't do complex reasoning of the sort that humans can do just reading basic facial cues. And again, this is where the technology is now. But to your point, yeah. To try to take a team, decompose it into a bunch of AIs and then one human. That's like Taylorism of a different sort. It's just, it's.
- [09:18]
A
We need to explore that. We need to explore that because when you said Taylorism, of course the thing that comes to mind is predictability, control, which is. And of course planning, which is everything that Taylor was about in terms of production in manufacturing and other more, let's call it, it's complicated, maybe, maybe even simple type of work. But then when we start doing knowledge work, whether it is software development, as most of our listeners would be doing, or something else, but you know, that involves different interactions, different people making decisions in real time based on information available, and we start having this problem. Right. Like many of the managers that we now work with, still believe in the planning and control ideas that Taylor was promulgating at the beginning of the 20th century. So tell us a little bit about your own journey, Simon. How did you come to this idea of ecosystems or complex adaptive systems? What was something that you used to believe about planning and control that you've completely changed your mind about?
- [10:26]
B
Yeah, yeah, great. So, you know, my journey through sort of agility and this sort of stuff was really unusual in that I was just a hardcore nerd from the beginning. And like I mentioned, like, I've always been interested in systems. So I was actually a classroom history teacher, an economics teacher for about 10 years, and so came to see what it means to lead to help groups figure things out quite differently. It was working with teenagers initially and it was just clear to me that over time, as I wanted to get better at what I did, I had to think this is not just about the content anymore. This is how do I work with a bunch of humans to help them get better together. So planning, for example, it used to be I would come into class with a lesson plan, doop, doop, doop, doop, doop, minute by minute agenda. And then what I realized is that would just completely squash those questions that would often emerge from the class or the team about various things that weren't necessarily the core of what we were doing. But, but we're highly relevant, maybe because of a news event, maybe because of anything. So to me, planning is still essential. There's no world in which is randomly walking around the workplace is a good plan. However, because of the need to create novel solutions, you have to create space for that novelty emerge from somewhere. And that's where planning over planning and really focusing too much on the tactical execution and wanting to control that wastes time. Leaders need to really. And so when I work with teams and leaders in particular, I'm like, no, no, the team does the tactical execution. As the leader, your job is to spend the time charting the where are we going, why do we need to go there? And then letting the team sort out the how. So planning really has a strategic level and a tactical level. And so now I think about getting the tactical stuff to the team and let them make those decisions locally while I work with a leader to make sure that the team is aligned with those other bigger picture things. So that's kind of a long rambling.
- [12:33]
A
I think that's a great insight. Right. And if we go back to the classroom as an example, when the teachers already know everything they want to say and they have this minute by minute agenda, the best they can perform is at the level of their planning. But when they are ready to accept what is coming in, incorporate that, build on that, they get more motivated students and the minimum they can do is to deliver the knowledge they already knew they could deliver. But they'll probably achieve much more. I remember, I'm sure you do, and most people listening to us, that there's always in our school history that one teacher who somehow got us excited about what we were learning, right?
- [13:16]
B
And go, that's exactly it. And once that flame is lit, people will do amazing things, they'll do surprising things, novel behaviors emerge because purpose and tools arrive at the same time. And it really wasn't until the learning educational Agile framework, LEAF L EAF framework, that I really started to lock this together. When I met a guy, Jeff Burstein, at the Boston University Agile Innovation Lab, and I realized, whoa, there's a practitioner out here who's like decades ahead of me in understanding this, but he was coming from the world of, you know, Fortune 500 businesses and coaching those people. So we were able to kind of mash up, you know, the two things to take, you know, what we know works in education, but then marrying it and sort of building off of it to sort of more industrial professional solutions.
- [14:11]
A
You talked about the word there that I want to explore a bit more because I think it informs also how we talk about systems, which is the concept and the word of emergence. Can you unpack that for us?
- [14:22]
B
Sure. So an emergent Property is a property of a complex adaptive system that is not particularly foreseeable. Because I don't know your audience too well, I'll just say there's tons of good books and at the end I could kind of give just a short annotated bibliography of some of the places they can go. There's great YouTube content by systems Innovation Group, so if you follow The Systems Innovation YouTube channel, that would be really stop number one. Great short videos. Very cool. If you want to understand emergence at a much greater level than I can sort of stumble through right now. But it's essentially emergences, these properties that can't be predicted in advance. And knowledge work is all about creating things that haven't existed before. So emergence is what we rely on. And so if we try to squash it and control it too much, it's just never going to happen.
- [15:16]
A
You know what is funny is that I see people, I mean, not everybody, but some people working with AI and experiencing emergence, you know, a first person basis, like they're seeing it happening with them. Like you ask a question, the AI comes up with an idea you never thought about, with a source you never heard about. That's emergence right there. And they benefit from this in a very practical manner. But then when we go to the work environment, we shriek when we hear the word emergence. I mean, some people will confuse emergence with chaos. Those are completely different things, by the way. And chaos has a specific definition within the world of systems, which we can talk about in a second. But how have you, especially when coaching leaders and teams, how have you incorporated this idea that emergence is not only a condition of complex adaptive system, but actually it's a good thing that we can take advantage of. How do you bring that to their consciousness?
- [16:19]
B
Yeah, yeah, yeah. So usually what I'll do is I'll start with a senior leader by trying to read their comfort level so I don't get into any sort of deep stuff until we've really built some rapport. So we'll talk about their favorite teachers, their most hated teachers, and I'll really try to bring them back to moments in time that were pivotal in their own development, for good or for bad, and then try to let them reintroduce themselves as the manager that they would want to be now, as against those previous things that they've experienced and say, ooh, what if? And then I'll just kind of bring in coaching questions and sort of suggest ways so that they never feel, or my intentions, they never feel diminished by the questions, by the coaching. But they also feel kind of a little bit uncomfortable because I'm pushing them to think a little bit differently. If they've got a strong math background, we'll start talking about narrow tail or standard distributions and fat tails. If they're a technical person, they don't want to talk about feelings, they want to talk about math. So I'll start with them, with the math. If they're a more humanities type person, we'll start on the humanity side of things. What are some little narrative chunks that they can think of about their team, about their product, about their whatever. And we try to get into the water of emergence and complexity slowly so that again, it doesn't feel like you're jumping in, you know, you're doing a high dive, but you're getting into it incrementally so that the manager feels safe in taking non standard risks, which in a standard business environment puts them at risk because they're doing things that are again, not entirely planable, not entirely knowable. And so, and Clayton Christensen wrote about this decades ago, this tension between innovating and then exploiting the innovation. And it's that sort of. And to come back to ecology, there's the exploit versus explore tension that always exists in a company. And once companies, especially if they're public companies driven by short term shareholder value, have to work in this very particular way that works against emergence because you've got to do things on the shareholders expectation timetable, which is not how innovation emerges. And there's just this difficult thing that has to get sorted out.
- [18:38]
A
Yeah, in fact, that's not how innovation emerges is a simpler way to talk about something that we talked about in prep. You called it innovation arrives stochastically. Now that's a big idea. And we'll translate that in a minute. So walk us through. What do you mean by that phrase innovation arrives stochastically and how that influences the way you talk about planning and the way you work in your own work with planning and control.
- [19:09]
B
Yeah, for sure. So in a case like that, I'll ask the person or the team to write down the two or three locations they were at when they've had some of their best ideas simply by noticing the locations. We notice the stochastic ness of arrival. Might be the shower, might be on a bike ride, might be sitting in traffic, might be at your desk, but often not. And so once we just locate those places, then we can get into the scary word stochastic in a more commonsensical way. And that's really what I try to do on my substack is just take these things, expose people to these ideas, try to make them safe, break them down to try new ways. Because we see so much misery, so much disengagement at work and at school. These don't have to be there. If we can get our managers to think like farmers taking care of the environment, as opposed to the farmer who goes out and yells at his seeds to grow.
- [20:08]
A
I recently read a book, it's called Seeing like the State by James C. Scott. And he talks about these systems that were put in place that tried to improve the human condition but did worse. So they made things worse. And we're talking about genius doing this. He has an example which I really love, and I'm sure that you will appreciate the example of forests. So forests, when they are chaotically grown, they are never chaotically grown. They just look chaotic to us because we don't understand how they work. But when we are on the outside and we look at them and say they're chaotic. So natural growth forests, they are incredibly resilient. They have large amounts of diversity, plant and animal and insect diversity. And then they started in the 1700s, late 1700s, early 1800s, mostly in Germany, but then also in France, they started to farm forests. And farming forests is basically like looking at the forest as just a farm, right? Like you have these crops, they are long term crops, obviously, but you have these crops and then you try to maximize the yield of the land. So basically you want to have a good tree. And there is a definition for what the good tree is per square meter or square mile. You have a certain number of good trees and that's the yield, that's what you want to do. And what they discovered, unfortunately, too late, one generation later, is that the way they were trying to optimize the yield of the land actually destroyed the ability for the land to produce the trees that they wanted to produce, right? So when we think about this idea of control, when we think about this idea of accepting the stochastic emergence, which is what you talk about, stochastic just basically means that it's predictable in large data set, but not predictable in the moment. At that moment, you can't predict it, but you know that you will come up with ideas if you just give yourself enough time, right? So that's what stochastic means. So that also highlights for us that when we try to force the reasonable approach to managing a system on a system that is naturally complex like nature, we often end up with a situation that leads to a much Worse outcome. And when I think about your stochastic emergence and also the concept of ecosystems, I can't help but think that that's also part of your message. Right, like that we are trying to over constraint something that has a natural dynamic that cannot be controlled.
- [22:55]
B
Yes. I think the technical word in medicine is iatrogenic, which means unintentionally causing harm through intervention. I should say that just as a personal bias. I was raised in a Zen Buddhist household. The idea in Zen is naturalness and creating space for naturalness to emerge. Trying to maybe use fewer words, show more with your hands and body, do less with your mouth, those sorts of things. That's very hard for the manager to do. The manager is told the more you talk, the better. Not so. Because again, if you trust your team, if you've got the right people, they'll figure it out. You need to resource them and not worry so much about the micromanagement of those, again, interactions within and amongst the team.
- [23:48]
A
And let's dive into that team system because I think the metaphor you used a moment ago, this three body problem, which is a physics puzzle, can actually be a very insightful metaphor to analyze how teams work. Walk us through that mapping.
- [24:05]
B
So I'll show you a visual here that will not work for your listeners, but if you're a viewer. So these are just. This is from my former life. I used to, because I was headmaster of a school, I had to wear a tie every day.
- [24:20]
A
Simon is holding a bunch of ties in his hand.
- [24:24]
B
Yeah, specifically three different ties.
- [24:27]
A
Different colors. Yeah, different colors.
- [24:29]
B
And so I'll bring this in and I'll say, look, this is your system right here. These things represent whatever your system is. And you're moving these three things through time at different rates with different dynamics. If any of these pieces behaves totally normally, that's fine, you can predict what's going on. But because there's nothing that's not a three part system in a business. So we'll say, okay, this is R and D, this is manufacturing, this is sales. And once you can just use something like this and say, look, this is insane, don't think you can master this, work with it. Understand it's a system. But as we know from systems, most of the outputs, most of the variability is due to the system itself, not to any given agent. So we can depersonalize the whole thing. People aren't good, people aren't bad. Systems can be improved, systems have features and bugs. But when you can depersonalize it and make the three body problem, not a personal failure, but how the world is. Then the team can relax, then the stochasticness that's going to be there doesn't feel like an emergency every time, but it's something we can sort of joke about and laugh about and just be curious about together.
- [25:43]
A
And in fact, you've been exploring some of that with your latest post on Substack. You've been reviewing some of Deming's work and some of his ideas, and he was a huge proponent of this idea that the. I think he's quoted as saying 95% of the productivity of a system is linked to the system itself, not the performance of the individuals. Yes. How do you explain that to a manager that has been brought up mostly engineers, of course, in an analytical culture, like for example, going through university, where only the analytical understanding of the world is taught and even fostered.
- [26:22]
B
Yep, yep. And so again, until I know that person's biography, history, those individual path dependencies, I don't know where I'm going to start with them. But once I understand their technicalness and I'll often ask, like, what did you love when you were 14 or 15 years old? And we'll often start. And this is something that frankly therapists do because you've got to get them to de. Like to release. They've got to open up if the only thing that they've got in their own mind is analytical chops. That's a brittle, brittle, brittle contribution. Everyone can learn to listen better in low fear conditions. Everyone can learn these things. So to the question of how do I do it? I can tell you where I'm going with that person. I don't know what the particulars will be until I know that particular person. That's kind of a non answer. But what we're really trying to do is just get them to open up to possibilities. So if they're very analytical, frankly, what I'll do is I'll bring in statistical stuff and we'll just talk about, oh, what is the off model variable that you discarded with your current mental model.
- [27:34]
A
Yeah. So I have a specific question because this is a question I always face, right? Like I've written about no estimates and I'm kind of the no estimates guys these days and I get such a waste of time. But when I introduce the idea of just looking at what the system is producing and using that as information, I get a lot of pushback. Right. Like for example, if I say, hey, we can just count the number of stories we complete per sprint and the Answer will be, yeah, but not all stories are the same, which is true. It's completely valid and that's why it makes sense. But then when you look at the system, that is when you look at what a team is able to produce in any random sprint, you will see that there's some variation, but mostly they deliver the same amount of stories, no matter what the size of the stories are. But how do you bring that ability to understand? Because one of the things that is really, really difficult for me to understand and kind of tackle in this kind of arguments is this ability that people have to be both very analytical and rational. And then when we go to statistics, which is completely analytical and rational, it's just not deterministic. Right.
- [28:48]
B
And that's it.
- [28:49]
A
Then when we go to statistics, people kind of lose that, that ability to reason and being analytical.
- [28:56]
B
Yeah, yeah, yeah. And it's, I mean you're so right that that's what it is. And it's like eight times out of ten that's exactly the path and you're like, and you get to this shut down moment where that person is like, nah. And then, you know, and it's very hard. One of the other things that I'll do is I'll bring in this image and again, this depends on trust. Can I share? Can I screen share?
- [29:21]
A
Yeah, we will have to describe everything for our listeners, but go ahead.
- [29:25]
B
Okay. Okay. Well then let me skip that as an example. But there are specific telltales physiologically that any person can notice about themselves in a given moment. There's a wonderful new book and I would really recommend this book to anyone who's managing people who are in their first 10 years or so of work. And it's called 10 to 25, as in age 10 to 25. And the guy's name I think is Jaeger. I forget his name. It's a wonderful, wonderful book and it's very useful for managers because there are some nice visuals in the book that let the manager, and let me have a conversation with the manager, say, ooh, you, you know, and I'll just use the little, the charts in there to help them locate themselves in their style and say, let's see if you did. And I'll just have them run experiments on hold your tongue once in a meeting to the manager, ask questions instead of statements, just, just simple things like that. So they can just begin to think, ooh, maybe I don't, I manager don't have to be, you know, Captain America and know everything because generally those managers have Developed this idea that they must be some sort of superhuman person who can solve the three volley problem, otherwise they wouldn't be a manager. And it's just a lie. It's just.
- [30:45]
A
In fact, I think Hulk is a great metaphor because as a manager you, you both need to be strong. The Hulk and you need to be analytical and be able to think and stop. Which is the non Hulk version of the Hulk.
- [30:59]
B
Bruce Banner.
- [31:00]
A
Yeah, the Bruce Banner. And people forget that Bruce Banner and the Hulk are different entities. They have completely different motivations, completely different rules. And when they think they. When we think that we can put those together, we start to understand that it's not possible. Right. You can't be analytical. I give value to knowledge, to reason and then never have doubts.
- [31:27]
B
Exactly. That would be insane. No scientist would ever agree. And when managers say we want scientific management, they don't actually.
- [31:35]
A
Well, it gets worse actually. Because when we talk about these things with leaders and with teams, then the answer that comes back very often, and this is perhaps when that shutdown moment happens, is that I don't care. I just to give the board, I just need to give the board a number and we need to commit to a plan. Yeah, yeah, that great thing right there. Right. And then when you, when you think about it, it's like, okay, but you can't at the same time be open to innovation and possibilities and have the plan that you will execute to a T and know already all of it in advance.
- [32:13]
B
Yeah, exactly. And again, but it would be insane to think you could do that. And yet so much of our management literature from the past has these awful ideas about this sort of all knowing manager, the philosopher king. It's just not how the world of knowledge works anymore. It's just too complex. There's too much chaos. Markets are too movable. Consumer taste vary too much people's preferences for how they work. It's just there's no way to try to wrap your arms around it and stay sane. And we see this in burnout and leaders all the time. I mean it's a largely self induced.
- [32:47]
A
Problem, I would say even. And when I do coach entrepreneurs, mostly like in individual entrepreneurs, so people who have their own businesses and they need to make decisions and some of them are struggling with the possibility of burnout and so on. And I do encourage people to look at this as information that something is not working well. And when I say something is not working well, it's not that you did something wrong, it's that the systems we have put in place are not giving us the results that we wish. And as a manager, and this is why I like Deming's approach as a manager, our goal is to constantly evaluate the performance of the system, not the people, the system. Because we can always put better systems in place, we can always improve existing systems. But you can't tell people what to do. It's not possible. People have tried it for a few thousand years, probably ten or more thousand years, it doesn't work right. You can't tell people what to do and expect that to happen exactly as you told them.
- [33:51]
B
In the same way that if you think that when you were 12 or 13 years old, if every time your parent opened their mouth they were yelling at you, you wouldn't want to be there, you would withdraw. Just don't be that parent. Don't be that manager. It's not that hard.
- [34:03]
A
Don't be that manager. That's such a great phrase. Don't be that manager. All right, Simon, we're getting close to the end, but before we go, what's a resour? And we'll for sure we'll put the link to the Economist, Simon's newsletter on substack. Be sure to check it out. But what's one resource could be a book, an article, a video that you think people need to check out if they want to understand more about complexity, about systems and of course also ecosystems, for sure.
- [34:32]
B
So as a nice summary of sort of where have we been, where are we, where are we going in this area? Eric Beinhocker's book called the Origin of Wealth is wonderful. I'm about three quarters of the way through it now and I would really recommend that as a very approachable and well researched piece. So that would be one thing I referenced earlier. If you're interested in systems, it's called Systems innovation. It's a YouTube channel. It's incredibly good, just brilliant stuff. I love their stuff that, you know, for the more curious, open minded manager, go there, have fun. What you could actually do if you're a manager is see if you can get anyone in your team to watch any of the videos and then tell you something about it.
- [35:21]
A
Yeah, absolutely. That's a great way to start exploring systems together, by the way.
- [35:25]
B
You've got to get it out of yourselves and make it not personal.
- [35:28]
A
And we need to create the language, right? Because people, they come from university with a certain language in their mind. For, for anyone who's been a project manager like myself, we create the project management language in our minds, but we need to start Creating this complex adaptive system or ecosystems, language in our minds as well.
- [35:48]
B
Yeah, precisely. And it is an ecosystem in that there's no bound to your business if you have customers. You're an inherently open system with tons of degrees of freedom. When you have lots of degrees of freedom in a system, it gets harder.
- [36:01]
A
It's like the three body problem, only.
- [36:03]
B
A lot more exactly at so many dimensions. And this is where the Beinhocker book is nice, because it, you know, it helps people understand how did we get these bad ideas to begin with? And they weren't bad ideas at the time, to be Frank. In the 19th century in particular, this economic idea of models and systems are biased towards equilibrium made sense because in the Newtonian world, in the pre quantum world, that was a reasonable place to start. And economists in particular aspired to be like physicists and scientists, but they made some assumptions about the math of systems based on their current knowledge. That has just proven to be not the case. So they weren't dumb or wrong. We just need to evolve our understanding of.
- [36:49]
A
And if we believe that science can evolve, we can certainly believe that the science of management can evolve as well. Right?
- [36:56]
B
Yes. Yes. And we can have more fun in the process by just accepting that stochasticness is random. I'll just. I don't know if this is how PG this is, but your podcast, if you imagine, would you want to know the number of seconds or minutes it would take in a sort of consensual, loving encounter to know when that would end? Would you want to know? Oh, today is going to be 7 minutes and 16 seconds and in advance? Hell no. That would be awful.
- [37:26]
A
Right.
- [37:26]
B
So like, the most basic things that we love and care about in terms of connection, they don't arrive on a schedule.
- [37:33]
A
They don't arrive on a schedule. Right. Simon, everybody can go and check out the Economist on substack. The link will be in the show notes. But where else can people find you and learn more about you and the work that you're doing?
- [37:46]
B
I'm on LinkedIn and that's really about it.
- [37:51]
A
And Substack, don't Forget.
- [37:52]
B
Oh, yeah, LinkedIn and Substack. Yeah, those would be the places. I've only been doing substack for like six months now, but I love it. I would really highly recommend that ecosystem as a place to find lots of cool, interesting ideas and conversation.
- [38:05]
A
Yeah. And that is definitely an ecosystem to explore. Simon, it's been a pleasure. Thank you very much for your generosity with your time and your knowledge.
- [38:13]
B
Absolutely. It's a pleasure. Thank you for doing what you've been doing for these years, decades. It's really, it's been an inspiration. I can't wait to have a reason to go to Helsinki and hope to visit you and have a beverage in person at some point.
- [38:24]
A
Absolutely. All right. I hope you liked this episode, but before you hit next episode, here's the deal. This podcast is powered by people like you, the members who wanted more than just inspiration. They wanted real tools and real connection to people who are practicing agile. Every day we're talking access to over 700 hours of agile Gold, CTO level strategy talks, Summit keynotes, live workshops, E courses, Deep Dive interviews, books, and if you're into no estimates, we got the pioneers of no Estimates in those Deep Dive interviews as well. Agile Business Intelligence, creating Product Visions, coaching your product owner courses, you name it. You'll get invites to monthly live Q&As with agile pioneers and practitioners, plus a private Slack community which is free of all of that AI slop you see everywhere. And of course, without the flame wars. It's a community of practitioners that want to learn and thrive together. It's the best place to connect with community and learn together. So if this podcast has helped you before, imagine what you will get from this podcast membership. So head on over to scrummastertoolbox.org membership and join the community that's shaping the future of Agile. We have so much for you, so check out all the details@scrummastertoolbox.org membership because listening is great, it's important. But doing it together, that's next level. I'll see you in the community.
- [40:17]
B
Slack.
- [40:20]
A
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