This episode is hosted by Boundaryless Conversation Podcast host Simone Cicero with co-host Stina Heikkila.

The following is a semi-automatically generated transcript that has not been thoroughly revised by the podcast host or by the guest. Please check with us before using any quotations from this transcript. Thank you.

Simone Cicero:
Hello, everyone. So, we are back at the Boundaryless Conversation podcasts. I’m here today with my usual co-host, Stina.

Stina Heikkila:
Hello, I’m very excited to be here.

Simone Cicero:
And today we have — we seem to have a lot of legends coming on our podcast. And today, I cannot really contain my enthusiasm for having with us today, Simon Wardley!

Simon Wardley:
Hello. Well, can I just say it’s an absolute delight to be here. Thank you, both of you for inviting me to this. It has been ages since we’ve spoken, so thank you.

Simone Cicero:
Thanks, Simon. I’m really looking forward to exposing more people to your work that has been so foundational to, I must say, most of the things I’ve been doing in the last decade, including platform design toolkit and the entrepreneurial, ecosystem-enabling organization. So, I’m really looking forward to dive deeper into your latest insights. So, first of all, I mean, let’s just start to maybe from an overview of some of your thinking. And I was excited to read recently a tweet; your tweets are legendary, I would say, but this one was really, really synthetic, and really powerful. You know, and when you mentioned four layers, I would say, of the conversation, you mentioned society, economy, business and technology. And you said on society, we need to have this we versus me discussion. On the economy, we need to start learning from China. On business, we need to focus on doctrine. And on technology, we need to go serverless. So, maybe you can double click on these four topics, four layers, quickly as an introduction to your latest thinking for our listeners, and I’m sure we can beat on top of that.

Simon Wardley:
Sure, absolute pleasure. Fundamental to all of this is the concept of mapping. It’s quite important to understand the landscape that you exist with it before you make choices. It’s important to use it as a mechanism for communicating your assumptions, to challenging each other, and the assumptions that we make. A lot of the world in those sorts of layers use stories. I’m quite well known for being somewhat harsh about stories. And the problem with stories is they are connected to storytellers. So, inevitably, they are highly political instruments. So, when you challenge a story, you’re actually challenging the person, which is why you convert this stuff to maps where possible, because now we can have a conversation. And when I’m challenging, I’m challenging the map, not the past. So, mapping out a landscape, these are all maps of capital. And it doesn’t matter whether we’re talking just about things, and activities that we do, or practices or data or knowledge, or even ethical values. I mean, they’re all forms of capital that can be mapped. So, they all have the same sort of common properties in terms of they evolve through different stages.

And so when you look at the tech landscape, if you start mapping what’s going on in the tech landscape, of course, we’re focused on often lower-end systems like infrastructure, and those have evolved and become more utility-like. So, the basic stages of evolution is a four-stage process is genesis, custom-built, products, and commodity utility. And those are just labels for those different stages. If you’re talking about practices, novel, emerging good and best data starts as our model, divergent convergent the model. So, if you start mapping out technology, you see a lot of things are industrialized. And as they industrialize, we move up the stack. And that has two impacts. First, we get something called the coevolution of practice. So, when we think about things like computing from servers to utility with cloud, we got things like DevOps, and that became the new practice compared to the old architectural practice. And so that continues to evolve.

And then if you go above that layer, you — above infrastructure, above operating system, you have things like the runtime. And the runtime itself is shifting from product to stacks like LAMP and .NET to more utility forms, including things like Lambda. And so the reason why I say go serverless is — when you map out your map from the user and the user needs and what they require. And obviously, you want to put your effort and resources as close to the user as possible. And so nowadays, with the runtime becoming a utility, which is the whole serverless space, that’s where you want to be focused. I mean, it’s a bit like when you focus on building a car, you think about the user and their interaction with the car, you don’t put all your effort focusing in terms of nuts and bolts, those are just lower order systems. So, the first thing tech, go serverless is because that’s what’s currently industrializing becoming more of a utility, that’s where you should be 10 years ago. Of course, Infrastructure as a Service, what we call cloud, where you wanted to be. But now, you need to be thinking further up the stack.

Business, focus on doctrine. One of the things you learn from maps, are there are various forms of patterns. Some of them are very context-specific. So, it depends upon how evolved something is. And so a classic example of this is if you think about project management, then for the novel and new, you use something like lightweight Extreme Programming agile. When it’s more like custom product development, you use different methods, like Scrum, MVP, what you would call lean, and when it becomes more commodity, you would use things like Six Sigma. And the reason for that is the characteristics of the thing has changed. So, it’s gone from a world where deviation is desirable, i.e. change is constant to a world where you want to minimize deviation, and that’s why you need polar opposite methods.

Now, that leads to something called one-size-doesn’t-fit-all. And that turns out to be a universally useful pattern. So, while the methods are context-specific, the pattern of one size doesn’t fit all turns out to be universally useful. And it doesn’t matter whether I’m talking about project management or purchasing methods, or finance, you need to use multiple techniques, depending upon how evolved something is. So, creating something novel and new is different from managing a utility. Well, there’s about 40, different forms of doctrine. And — well, there’s more than 40. But in that table, there’s a list of 40 and I organized them into basic phases of how you would go around doing this. And the sort of phase one, things are pretty simple.

Understand your users, turns out that’s fairly universally useful, understand the chain of components. So, understand the details of — when you’re building something, understand what’s involved, understanding how evolved that thing is. So, understand what is being considered as a world of difference between managing something custom-built, and something which is more of a commodity, challenge assumptions, that turns out to be universally useful as well. So, there’s 40 of those, and most companies are pretty, pretty poor at them. And they are actually linked to adaptability of an organization. So, you’ve got one side, the bottom layer, which is like considering the tech and where you should focus, and then you’ve got these doctrines, these principles, which is around how you should, almost structure, organize yourself, how you should manage things.

Now, mapping isn’t just limited to single companies or individuals, you can do it at the nation-state level as well. So, when you start mapping out larger-scale systems and economic systems, and I did a piece of work many, many years ago, looking at China and USA. China has some interesting places. I mean, it’s obviously an amazing country in some incredible companies with quite stunning organizational models coming out of China. But at a national level, it uses very much a mixed economic model. So, very much encouraging, the government acting as a venture capital firm at one to use of special economic zones to industrialize existing components to the point of nationalization of what is a utility. And this all, for me, stems back to Deng Xiaoping and it doesn’t matter if the cat is black or white, as long as it catches mice. So, it’s all about using what is pragmatic and practical and understanding the context, and using appropriate economic tools and methods for that. So, that’s one of the things that I think at a nation-state and a competition level we need to learn from.

I suspect this year, which happens to be the 100th anniversary of the CCP, that China will also be — start its program to tackle inequality. It’s been doing a program to tackle poverty, taking 850 million people out of poverty, but it will tackle the issue or start to tackle the issue of inequality. And that’s actually important for economic competition. Unfortunately, in the West, we tend to be very much sort of one size fits all methods. We have some interesting beliefs, not backed up by anything. In fact, the reverse is usually the case, things like the trickle-down effect. So, we suffer terribly from inequality. And that actually impacts our ability as a nation to compete. And so then that takes us up another level, which is into the question of society because I said, you can map out ethical values. And if you map out the beliefs of a nation, you’ll find that just like science, just like physical things, they’re built on many, many different components, which have evolved over time.

And I use this to look at mapping out culture because one of the problems with culture is no one could quite explain it to me what culture was. And I started to look into the subject and came across various quotations, which pointed to the fact that anthropologists have spent 100 years trying to define culture, and no one can agree quite what it is. And they’re the experts in their field. And then I came across the work of Margaret Mead, and fabulous work, by the way. And Margaret Mead talked about how language is part of culture, and that creates a problem because if language is part of culture, then you won’t be able to use language alone to model culture. And that’s girdles in completeness there. So, what I did in start mapping it out, and of course, that meant I had to map out ethical values and then start to map out all the other components. Things like power, symbolism, the safety, competition, a whole range of different structures. And it turned out that what was at the top of this map, the anchors of the map were concepts of me and we.

So, me as — we’re all, shall we say, partly me, partly we, so we’re all about the self, and we’re all about the collective. And of course, there’s a balance between the two. And one of the things that was very noticeable was the balance that nation states, the difference between them. So, some, some cultures are very much me focused, and some cultures are much more we focus. And so the example would be China and Confucianism. And that seemed to have an impact in various different areas, and that has probably come to the fore with the whole pandemic, where we’ve — those countries, which tended to have a more Confucian type attitude, seem to have reacted in different ways and potentially more successful than other nations. So, that led to this whole discussion of should we not at a society level: a. identify what our core values are? I mean, really identify them and have that discussion about what is the balance of me and we? Have we actually got that right? So, I suppose, those are the four things. I use maps in terms of looking at technology, I use maps, in terms of working out doctrine, and how businesses should operate. I use maps for nation-state competition and looking at different economic systems. And I also use maps for looking at cultural systems and society itself.

Simone Cicero:
Well, there was so much in the first answer, but I should have expected with the initial question that I raised. So, first of all, I mean, a quick thought that I would like to exchange with you before maybe going deeper into some of the important aspects that we mentioned also in the preparation. So, it looks like, to me at least, that your work has always been also focused on explaining how progress, and I would say innovation and evolution works in markets now. And so, for example, when you refer to the stages of evolution and the ethics that competition has on market, you know, driving componentization and you know, climbing chains and so on. It looks really, I will say to some extent, a techno-driven process of innovation that we are all used to. And also we look at technology, we look at how technology and markets generate this kind of continuous process of technological innovation, componentization, and so on.

On the other hand, that was the end of your first answer, you were looking into more, I would say, socio-political, or socio-technical decisions that, to some extent define, for example, some political choices, or sometimes as we have seen in China, to some extent, the subjugation of technology to the political will and power of the people in that case or in general of these governments or bureaucracies or whatever. So, I’m curious to know from you, if you have thoughts about how these two things connect. Is culture this — your work and culture, the point where these two aspects connect: the aspects between your self-defined idea of technological progress and our choices, in terms of our choices in terms of politics, or organizational politics and culture and choices, personal ones. So, is this cultural aspect really the point where these two conversations on the, I would say political and technological connect.

Simon Wardley:
So, if I start with the point of me, me is about individuality, it’s about agency, and it’s about power. But now, obviously, power requires power over something. So, there’s different forms of power; relationship power, social, structural, high rising hierarchical power, and that depends upon being a member or part of some collective. Now, when we talk about we, it’s about us having control over our environment. Of course, that also depends upon a collective. Now, the collective itself, I mean it’s in competition with other collectives. So, critical to this is the concept of success and the success of our values.

So, we define, when we think about a collective, it has certain beliefs and values, values and beliefs are the same thing. I mean, and we define success by the spread of our beliefs and our values. And that’s connected to other things like behavior, enablement systems, how we market, how we sell, propaganda, whatever it happens to be. So, if you think about two systems in competition, I mean, the US, I mean, a lot of the values of the US, or beliefs of the US, such as democracy, are somewhat supported by success economically, and then creates a problem if another nation is more economically successful, it undermines the beliefs and the ideas of those beliefs.

So, when you start looking at that success, of course, that requires competition with another collective, and that’s linked to doctrine itself. So, when I talk about the 40 universally useful principles of doctrine, they’re connected to how well you compete if you’re good at the doctrine, you understand users, the needs, you understand the landscape, as in you understand the value chain, how involved components are, you can play the game better. And of course, that’s all linked to the landscape itself. And the landscape is that mix of practice, data, knowledge, technology, all these components evolving. So, yes, there is a direct link from technology all the way through to adopter and all the way through competition, all the way through the values and beliefs of the system; all the way to the concept of me and we. And there are many other components involved, but these are all interconnected systems.

Now, they’re going to have divisible these systems is a completely different question. I mean, landscapes — understanding a landscape also doesn’t tell you what to do. All this is a mechanism of looking at the environment. And within these landscapes, you’ll find all sorts of wonderful feedback loops, which can be positive and negative. So, if your collective is being successful, help spreads your values and encourages safety or the belief of those people within that collective that somehow they’re safe against other collectives. And of course, if it’s going wrong, then that becomes a negative cycle. And our sense of belonging starts to reduce in that collective. So, it’s — as bizarre as it might sound, I mean, you can — our ability to effectively understand the technology landscape and perform the right sort of actions and build the right set. Sort of companies will impact our sense of belonging and safety within the collective. So, these are, yes, all interconnected.

Now, when it comes to the political side, I mean, a lot of that is to do with a balance between me and we. And so it’s interesting, China, very much Confucian culture, so really strong focus on the we. And that may also be why it is quite enabled, I suppose, to use mixed methods in managing its economy. Whereas in the West, we tend to be much more focused on me, individualism, liberalism, which potentially may limit our choices. Certainly, in our choices of economic systems, we tend towards more of the let the free market run everything. Which in certain areas, as things evolve, there are certain times where you want the free market to run freely, so in late custom, product stages. But when it becomes more commodity, utility, you want it regulated, government-controlled, even nationalized. And when you talk about the genesis of genuinely novel and new activities, you often want the government acting as a venture capital firm. Companies tend to be good at applied research rather than core research. So, all of these things are interconnected with each other. Does that make sense?

Simone Cicero:
Yeah. I was, furiously chatting with Stina in the background and sharing some ideas for where to go next. And I was fascinated by this idea that you presented that success is success of our values. And also many times we discussed about, for example, for one organization, what does it mean to thrive? What is the purpose to some extent? So, I think this idea of success for our values is really clear in explaining that. And in the background, I was thinking about the seemingly switch and evolution we are living these days. Now, from a globalization, further globalization perspective, which means, essentially, you uniforming values. And so having an idea of success, that is more, I would say, widespread and more common across the world, and maybe between China and the US, for example. And this has been accelerating innovation fairly a lot in the last, probably two decades, especially in the industries that were not subject to strong regulations, and you know, in the digital world, for example.

On the other side, now that we are living through this so-called decoupling, this idea, but in general, I mean, it’s not just the decoupling of the US and China, it’s a matter of regionalization, or what we are seeing its — the economy’s apparently starting to re-regionalize. We know for example, on the podcast we had Nicolas Colin, that spoke about this idea that we used to think about digital as a global thing, but in reality, it’s not. It’s much more regional than we thought, especially now. And that’s also pointed at Ben Evans has been raising a lot lately. So, we see this regionalization and so to some extent, a clash of values. I don’t know to what extent but at least to some extent, a clash of values. And so maybe we can think about, to some extent, a reduction of the rate of innovation.

So, my question would be, what if we look into markets and organizations, from this point of view of our world where values are increasingly less uniform and much more clashing? What does it mean for the organization? So, for example, in our podcast, we have been discussing a lot, how the priorities of organizing may change from efficiency to more resilience or not. So, for example, embracing more distributed structures when maybe global players need to play an interplay with local, regional, or even city size players like collectives of people or even smaller businesses. So, in general, the question would be, in this perspective, and if you agree with this perspective, what do you see in terms of evolution of the organizational model and the market model, and these connections with all these thoughts that I just wrapped up in a question?

Simon Wardley:
Yes, yes, I do. So, there is two different threads there. One is the issue of sovereignty, and one is the development of principles and doctrine. So, values are our beliefs. Principles are these universally useful patterns, which everybody really should follow. And they start very simply with those ideas of focusing on the user, focusing on user needs, knowing the details, having a bias towards data, challenging assumptions, and so forth. But where do they come from? And this is where we’ll make, hopefully, all the connections. So, one of the things that happens is that as technology evolves, so you start off with — talking about activities, so we start with genesis, custom-built products, and commodity utility. As technology evolves, you often get coevolution of practice. And so to give a recent example, we’ll go back to cloud, the shift from computer as a product to computers as a utility, which is cloud. And we had a shift of practice, from those practices built with computer as a product, so they were based upon the characteristics of computers as a product, one of them being high lead time to recovery.

So, we had a, you know, disaster recovery test, lots of capacity planning, and plus one. And it shifted to utility, where we suddenly had another set of characteristics, including low MTTR, low mean time to recovery. So, if you wanted a new server, you didn’t have to wait months, you could have it in seconds. And so we started to do distributed systems designed for failure, chaos engines, and this is all around 2006–2009. And that was all put into the whole term DevOps. I mean, even things like continuous deployment. I mean, we couldn’t do continuous deployment in the past when you’re waiting three months for a server to turn up. So, what you get is, as technology evolves, you get this coevolution of practice. And some of those practices are context-specific, specific to an industry. But some of them are universally useful. And those ones end up in the doctrine table.

Now, there’s a whole bunch of technology that’s currently evolving at the moment. And as a result of which, we’re seeing 43 different potential areas of change that are going on. Everything from reusability resource management, resilience is another area, reduction of waste is another area, radicalization, protectionism, mobilization, manipulation of perception; there’s a whole bunch: 43. And some of those will turn out to be universally useful, they’ll end up in that doctrine table. Now, the successful organization, often people think, oh, it’s about technology, it’s actually about the principles. I mean, if you took all the technology away from Amazon, and gave it to somebody else, give Amazon 10 to 15 years, they’d be back in the same position they are because they have a really good set of principles.

And the same with Haier, for running their organization. And because of that, it makes them highly adaptable. And it gives them high levels of awareness. I mean, I love the book, Reaching Cloud Velocity, which I think that’s AWS’s second ever book. There’s several reasons, A, it’s a great book. And secondly, it’s got 17 pages of mapping in it. And their use of models like ILC, etc, within their book. So, having those principles in place enables your organization to adapt, cope with basically a constant change. And that leads all the way to things like cell-based structures, and models, like pioneer, settler town planner, which is a specific model of multiple attitudes in the organization. But of course, you can’t do those more advanced things, until you’ve done the basics of having challenging assumptions, having a common language, understanding user needs. Because otherwise, you’re applying structures to environments You don’t understand.

Okay. So, what you’ve got is technology changes, creates changing practice, some of those practices turn out to be universally useful. And when we talk about a change of practice, they have a common meaning. For example, DevOps and ITIL have a common meaning in terms of architectural type practice, but they’re different competencies. I think there’s a — I just mentioned that also because there’s some wonderful work by Elizabeth Shove on social practice theory, which is always worth exploring.

Now, technology evolves, it causes practices evolves, some of those practices are universally useful. They go into doctrine. How well you’re good at doctrine depends upon influences, how adaptable your organization is. And that organization or a collective could be a company, it could be a church, it could be a football club, it could be a nation-state itself. And so if you think about nation-states or any collective, that’s where we define our collective by the values, not the principles, the values, the beliefs that we have here, here are the things that we believe it. And there’s like seven universally, beliefs that we know of.

You know, respect for property, respect for rule of law, they appear in all collectives, in all cultures that we’re aware of. But a lot of them are specific to, shall we say that there’s quite a bit of variance in those beliefs, and some are more, shall we say, more localized. And some of them, there are aspects of universality, some of them are less evolved than others. So, there’s only about seven of which are really common through all collectives. And, of course, we define success of the collective by how we spread our values and our beliefs and so if our beliefs aren’t spreading, then we’re not being very, very successful. And, of course, the success of any collective depends upon the principles that’s in the doctrine we follow as well. So, those are interconnected.

And so this then leads me over into the whole area of sovereignty. You see if I map out something like the automotive industry, so we start with the user wants to get from A to B, and that requires a bunch of things, including maybe potentially a car. And a car requires a bunch of other components, and in there, maybe information systems and AI. And AI requires simulation training systems. Well, the interesting thing is the beliefs of a collective are usually embedded in the training systems for the AI. So, you can, when you map out the automotive industry, you can map out the nation collective and its beliefs and connect the two together. So, we often talk about ethics and AI. And it’s interesting, because you’ve got Beijing AI principles, and you’ve got the US AI principles being developed, ethical principles, this case by AI. And so the question you always ask yourself is the trolley question. I mean, a car’s coming along, you can hit four people or hit one person, who do you hit? Well, if you’re in a society, which values people, the collective, the we, then it’s tough for one person. But what if the one person super-wealthy and the four people are employed? Well, if you’re in a society, which values the individual, the me, and maybe has a heavy connection to wealth, maybe the decision you make is different. Now, this is where we get to the whole me versus we discussion.

So, what’s this got to do with sovereignty? Well, when we understand physical sovereignty, we use a map to understand the landscape and it’s from that understanding the landscape is where we set our boundaries, and which bits do we want to control, etc. When it comes to things like digital sovereignty, you can map out the digital space. And it’s a question of deciding, which of the bits that we wish to control? Where are the boundaries that we actually wish to set? What do we want to protect? Unfortunately, most discussions about digital sovereignty don’t use maps at all. They rely on stories. It’s a bit like trying to do physical sovereignty, with stories, without any understanding of maps, and borders, or anything else. So, it’s mostly, to be honest, a lot of blah, blah, blah, and a lot of things like, oh, we got to protect data and everything else. To which the obvious question is what data? Why? Where is the boundary setting? Just people can’t answer that question.

So, from my point of view what, you’re the connections, it’s so much easier to show this with a map. It’s always interesting to try to do this purely verbally. But, the connection between sovereignty and nation-state competition, what we want to control that really needs us to understand the landscape to determine where the boundaries that we wish to place, what are the components that we wish to own or at least express sovereignty over. And in terms of the collective, not only do we not understand the digital landscape that we’re competing in, talking about the West here generally. We also tend to be quite poor at the doctrine, the basic principles by which we operate. And that doctrine, of course, is evolving all the time. So, in certainly commercial companies, some are far behind. I mean, I find it quite amusing that people are talking about things like understanding users and user needs and understand your value chain in 2021. I mean, you really should have been doing that over a decade ago.

So, some are not only far behind, they’re getting further behind because that doctrine doesn’t stand still. Just like the map, when the components on the map evolve, new practices appear as well. So, we’re seeing this at an organization, and at all levels of collectives, again, it doesn’t matter whether you’re a church or a group, or a nation-state or an organization. And so it’s interesting to watch China because it clearly has — seems to have a better understanding of the landscape. Some of the games that it plays in terms of understanding its supply chain, what it wants to protect, indicated as what we would call fairly high levels of situational awareness. Some of its companies clearly have a good understanding of doctrine. In fact, some of the leading companies in the world in terms of organizational practice, you mentioned Haier. For me, that would be a classic example.

And in terms of technology, the underlying technology, if you look at the plans of China 2025, and other plans, it’s been making good economic bets, based upon industrializing technology, and that that requires high levels of situational awareness, a bit like Amazon, and the whole ILC type of innovate leverage commoditize model requires strong understanding of the landscape you’re operating in. Now, most of us are blind to this, we don’t understand our landscape. We certainly don’t understand the principles involved. We certainly don’t understand sovereignty, and how to actually do this. And most of us rely just on stories.

Simone Cicero:
You know, let me try to highlight a few points for our listeners, because I think this conversation was really awesome in terms of resonating with some of the conversation we had so far. So, one thing that I get from this, and you mentioned, for example, social practice theory, and doctrine as becoming a universal — being the set of universal useful patterns. The question we were debating, with Stina in the background, it was, you know, where this question, is democracy outdated, then?

So, let me explain what I mean. You know, for example, Ben Evans, as I said before, he’s talking about the next s-curve being the excuse of regulation. You know, we don’t expect such a dramatically different technology coming up. It’s really about regulating as the internet pervades society and everything we do. And we also had another conversation recently with Rita McGrath where we ended up actually agreeing that it’s going to be very much — more important, the duality, the relationship between the policymakers, regulators, and the business sector, you know. And it’s really, it looks like when you mentioned social practice theory and doctrine in the context of politics, and you criticize the use of stories, it’s like you say you’re advocating for policy making, that is much more about socializing decisions through evidence or to analysis. Versus policymaking that is much more story-based and much less grounded in insights.

Simon Wardley:
Fabulous question. So, one of the things I use maps for is what I call pre-mortem. So, to explain pre-mortem, what we do is we map out a space and use the map to look at what we should do, what we intend to do. And then we go into it. And then we do post-mortem analysis using the map. So, how did the map change and how did we succeed or not succeed? And that maps become not only a mechanism of communication, what we want to do, and challenge, people being able to question without challenging the person, challenging the map, but they also become a point of learning about a particular environment.

So, it’s out of that use of maps, that many of the patterns have occurred, and some of those patterns are economic patents, there’s about 30 of those common economic patents. There’s about — these are like the rules of the game, 40 on — oh, it’s eyes more than that now, 40 odd bits of doctrine, then there’s context specific gameplay and you’re into a100 different forms of those, which most people are fairly oblivious to. So, when you say about learning from data, I absolutely agree it’s a good idea. It’s a bit like the military. Yeah, you understand the battlefield. You learn from the battlefield and your actions and your opponent’s actions. And that’s how you improve your strategy, or the way you deal with future problems.

Now, when it comes to this whole issue of democracy in the end of democracy, and all these sorts of ideas, okay. Democracy is a belief. And unfortunately, what we had is a collection of beliefs, which have been — formed various parties’ self-interest being bundled together. One of those is the economic system, and a particular form of the economic system and democracy. So, you typically hear the — Oh, you can’t have capitalism without democracy. You can’t have democracy without capitalism, and they’re sort of tightly coupled together. Well, this is plainly not true. And this is about as true as trickle-down effects. I mean, the democratic system is a system of representation. And there’s no reason why we cannot use mixed economic models and so more context-specific models with a democratic system.

But because we’ve tightly coupled those in certain areas, there’s become this belief that in order for democracy to succeed, capitalism has to succeed. Well, actually, no, capitalism doesn’t have to succeed. We can have a more context-specific refined model than just purely market. And at the same time, we can quite happily have democracy in the way we think of democracy. Probably the problem is also linked to a misunderstanding of how economic systems tend to work. So, one of my favorite examples of this, it’s Pascal’s triangle, actually. So, that’s this triangle, that triangle, which if you remember, yeah, in the early math starts off with one, then the next line is one, one, then it’s one, two, one. And it’s all about permutations. So, for example, if I toss a coin twice, it might come up heads, there’s one head, there’s two different varieties of head tails as in head tails, tails, head, and there’s one tail, tail.

Now, if I throw a coin in the air, and if it comes up heads, I double my wealth, and if it comes up tails, I only have 60%. So, I lose 40% of my wealth, and you have four people throw it, then one person is going to go heads, heads, so they’re going to end up with four times the wealth, two people are going to go with a variation of heads, tails, they’ll end up with 1.2 times their wealth, and the one unlucky person will end up with 0.36 of their wealth. And if you add those all up, it’s just that 6.76, roughly divided by four, 1.6. What it means is people starting off with $1, each $4, they’ve ended up in total, with 6.76, off the top of my head, which is, well, on average, we’ve gone from one to 1.5 dollars.

But the average person, and if you look at the four people or three of them, are now below the average wealth, and one of them has got a lot of wealth. And this is a power law. And if you do it ranges of 63 million, what you get is a massively unequal system, where a few people are incredibly wealthy, and most people are below the average. And some people are extremely — a lot of people are extremely poor. And to create that sort of inequality, you just need one thing, which is luck. You can make it even worse with things like inheritance, and you can make it worse with return on capital expenditure being proportional capital. So, what I mean by that is, the more capital you have, the better return you get for every dollar.

And so what’s interesting is when you look at power-law distributions and you add those other factors, they sort of mimic what goes on in reality. Now, when we look at things like hard work and talent, which are more Gaussian distributions, they don’t mimic reality itself. And so the brutal honesty is we run around telling everybody we live in a meritocracy and hard work and talent really matter. We’re negligible compared to luck, inheritance, and return on capital investment, which is why we have an incredibly unequal system with a lot of poor social mobility.

Now, at a national level of competition, that creates a problem. And that problem is if the people running your system are not those defined by talent and hard work, but are those defined by luck, return on capital investment being proportional to capital, i.e., how much money you begin with in inheritance. We don’t necessarily end up with the best people in charge. So, but we like to tell people it’s a meritocracy, or certain people in charge like to tell people they are meritocracy. Because if you’ve got several billion, you don’t want to know that it’s not to do with your work and hard work and talent, you’d like to think it is. You can’t stand it if somebody tells you it’s mostly luck, inheritance, and return on capital investment.

So, we have this wonderful situation where we’ve tied up democracy with our economic system. We tell each other myths about our economic system is based on meritocracy, which quite clearly, plainly it isn’t. And so now we’re facing a culture which is becoming more economically successful. It is, though it’s being focused on reducing poverty, it will — it’s already present, she’s already signaled it’s going to attack the issue of inequality. So, we end up with this wonderful system whereby their economic system, once they start to tackle inequality may not only be ahead but accelerating, and a much more equal system to which we say, “Well, obviously, the problem is democracy. And we’ve got to get rid of that and be more something else.

But the problem isn’t democracy. The problem is the economic system, tendency to one size fits all rather than more contextual approaches. Government as a venture capital, use of nationalization where necessary, use of free-market, as necessary, and tackling the issues of inequality. Because the meritocracy is not what existed. So, that’s what we should do, tackle the inequality, tackle the return on capital investment, tackle the issue of luck, push the system towards a system — and you’ll have to do this with things like redistribution — where talent and hard work are the primary drivers of success. So, that’s where you’d have to start. And then you’d also have to tackle this issue of one size fits all. Which means you need to move to a more mixed economic model, knowing when to act as a venture capitalist, and when the government should act in nationalization, when the market should run free, and all — do both those things, you’ve got to have a pretty decent understanding of the landscape. We don’t have any of that. So, I am sure we’re just going to blame democracy. But the problem isn’t democracy.

Stina Heikkila:
Wow, super interesting. Let’s see if I can turn this question the way I wanted to. So, you’re talking about, well throughout the conversation about these collectives, so I actually have like two questions, I think. One thing is the scale of these collectives, you know, we arranged the conversation from businesses to nation states, but I’d love to hear more how you — how do you see this clarity of collectives, as the entities who organized activities in — we can say in an economic space, for instance. And the second question is, so we, as you might know, we just recently released a new white paper, on platform ecosystem thinking. And in that, we have a broad hypothesis. Let’s say that in the current context of where we see a lot of this sort of fragmentation, in digital markets and so on, that this would drive a push, essentially, also to micro-entrepreneurship. And especially, we’re drawing out these broad lines on something that is called the — we refer to as the economy of essentials.

So, where citizens essentially come together and form new sort of collectives, if we use these terms, to provide for themselves, basic sort of services that have become let’s say, commoditized and they are able to do so with low transaction costs. So, this is something that you know, we have mentioned, and it would be interesting to see if we can tie this to the picture that you just formed, if essentially, are we going to more or less of imposed principles from the top, and stories towards something much more self-organized?

Simon Wardley:
Interesting. So, one of the — if I look at the universally, my doctrine table, which is that list of universally useful principles, not context specific ones, which will come out of mapping, I mean, you’ll find in the later phases of that doctrine table, and this stuff can all be found online. You know, think small teams, and a later one is, there’s no single culture. And a later one is designed for constant evolution. So, use of cell-based structures. So, if you take a system and you break it down into smaller components, those components ideally provided by smaller teams. Now, when we say smaller teams, depends on what specifically you mean. When we talk about the genesis of novel and new activities, I mean, you can be talking to teams of two or three, once you’re talking about some things which are more evolved, it could be, you know, Amazon famously uses the two-pizza model. Of course, things which eventually end up as utility like structures, even though it may be a small component, you can sometimes have a slightly larger teams than that.

So, the idea that we will break down into smaller components, well, you’re seeing that anyway, with companies like Amazon, with companies like Haier as well. But this is a question of distribution of our production and power. This also features in this whole sort of discussion about hybrid cloud. One of the things I’d expect to see is because everybody talks about, well, the future is going to be in a much more hybrid cloud, maybe smaller providers, etc. Well, not necessarily. The cloud, maybe well distribute, it may be Amazon everywhere, it may be Alibaba everywhere. And what you’ve got is a distribution of provision, but centralization of power over that system. And it’s the same thing with production in terms of distribution of production into ever smaller teams. But again, centralization of power, as in all these teams work for Amazon or all these teams work for Alibaba, or Haier or whoever we’re talking about.

So, I do understand the ideas. I mean, certainly, once you have components services, the more components services, more utility like services you have, it becomes far easier for people to build novel and new things on it. But at the same time, that’s part of the whole ILC model, which I better explain. As things industrialized to a utility, you provide as a service, people build things on top. And like computer’s a utility, people might go and build, I don’t know, kit internet, or I don’t know, some other ridiculous service and some people might build big data on it. And if you provide a utility service, you can mine the metadata, the consumption of your API to determine what’s becoming successful. And so you leverage the entire ecosystem to swap future patterns, which you then commoditize to new component services, and everybody cheers, except for the people, you’ve just industrialized who complain you’ve eaten their business model. And the net effect of this, however, is the company at the heart of this gains from the benefits of efficiency providing economies of scale, providing utility services. It gains from apparent rates of innovation, because of everybody building on top, creating new services, and it gains in benefits of customer focus because mining metadata to spot the patents that are becoming useful gives that to everyone.

So, that company simultaneously increases in rates of innovation, customer focus, and efficiency; does all three simultaneously. And that will grow as the ecosystem grows. So, what you’re getting there is centralized power. But of course, the provision of it may be a whole bunch of small cells, so you’ve got decentralized production. It’s not one big department of 10,000 people, it’s lots of small teams building this stuff. And you may also get distribution of provision. So, you set up in multiple different regions, maybe with different teams as well. So, you get layers of distribution, and layers of centralization. So, do I expect to see lots of small teams building things ever more quickly and ever more interestingly, on these small utility-like services? Yes.

And then I expect that to be copied or to be acquired ever more rapidly, which then leads you to the question, well what is the nation-state perspective and role in this? Well, Alibaba, I mean, China’s going through the process of nationalizing it because it’s now a more core common utility like service to others. And, obviously, from a nation-state perspective, if you believe in the — if your focus is on the use of mixed economic models, and what’s appropriate where, you would tend towards high regulation of or nationalization of those things, which are called utility, simultaneously, at the same time, as while encouraging investment and venture capital, as a government for the novel and new.

So, will we see small teams building new things? Yes. Will I suspect they will be acquired or copied more quickly? Yes. And do I expect to see more centralization of power? Yes. And to which people often argue to say, well, what we want to do is we want to break up companies like Amazon. And that’s great, as long as you control China, because if China doesn’t return the favor with Alibaba, and there is no reason to believe it will, then they will gain the benefits of innovation, customer focus efficiency all proportional to the ecosystem. So, they will accelerate ahead, and we will just get further behind. So, that’s the space you’re in.

Simone Cicero:
That’s resonating with the work that recently we have been debating with Sangeet Choudary on states as a platform, and also the work that — the strategy that some nations like China, for example, are using to — when they develop these kinds of infrastructures, as commodities, to some extent, also exert certain cultural influence. So, I think this all resonates together. This conversation in general was pretty much, really confirming and double-clicking, again, on to some of the questions that we have been touching upon the last time, in the last year So, Stina, maybe you want to ask a final question before we move on?

Stina Heikkila:
Well, maybe it could be good as a sort of wrapping up to talk about what do you think is important for people listening to our podcast, who are interested in the platform ecosystem and their evolution? What is important to keep in mind in this current moving and looking forward in this space?

Simon Wardley:
I absolutely love the whole sort of focus on building platforms, the whole focus on using ecosystems, but I — a word of warning, a word of caution. It’s really important to understand your landscape before you embark on this. First of all, there are different forms of ecosystems. One is more of the ILC model where you’re providing services and getting others to build. One is all the way to the other end, which is more than just the general alliance. But if you’re building something which is genuinely novel and new, the genesis of something, the last thing you want to do is start exposing that as an API because it limits your ability to change the thing and so it reduces your rate of innovation. If you look at somebody like Amazon, or you look at China, for example, China concentrates a lot and so does Amazon on a industrializing pre-existing activities.

So, shifting them from product to utility, and that’s where particular ecosystem models like ILC all makes sense. So, I suppose my first word of caution would be understand your landscape before you — landscapes won’t tell you what to do but they’ll help. You should be able to have a discussion, you have to apply thought to it, but understand your landscape before making a decision. I am sure there’s a lot of people who have ran out there and open-sourced things or without truly understanding what they’re doing or trying to build ecosystems and spaces where or the wrong sort of ecosystem in the wrong space because they simply didn’t understand their landscape. So, that’s my first thing is understand your landscape.

My second thing is, it doesn’t matter what collective you are, an individual all the way up to a nation-state. If you want to be able to communicate in space without the political games, if you want to be able to challenge without the political games, if you want a mechanism of learning, then you too also need to understand your landscape.

Simone Cicero:
That’s a great way to resonate and close also this conversation because we used to say always that platform thinking and systems thinking needs to be outside in it really needs to be about what they are trying to do — with they I mean the ecosystem players — more than what you think about. And I think, you know, when you say you need to understand your landscape first, it’s really about setting up your structure so that you can then use your ecosystem as a future sensing engine, as you said. But if you don’t understand the landscape first, you’re never going to sense the future. That’s a key point. So, Simon, I mean, the conversation was crazy. I need to relisten to that maybe a couple of times before writing the notes. But first of all, I would like to ask you, if people want to look more into your work, where they should look into, apart from your amazing Twitter handle?

Simon Wardley:
Medium.com/Wardleymaps, you’ll find this map 600 pages of a book that’s on there. List.Wardleymaps.com, which is an awesome list that connects to all sorts of different places where there’s stuff about Wardley Maps. Just Google search Wardley Maps, you’ll find lots. And then there’s lots of books out there. Ducati has published a pretty large book on Wardley Mapping, the Knowledge Part One, it’s quite a thick tome. Art of Strategy, which has lots of mapping concepts within there, that’s by Eric. You’ve got Reaching Cloud Velocity, that’s AWS. You’ve even got things like From Intention to Action: A Plan for Digitization, that’s Puerto Rico, Giancarlo, that’s a lot of mapping in there or lots of chunks of mapping in there. So, you’ll find it in all sorts of places. And there’s even people teaching it at Peking, Moscow Institute of Technology, Harvard Kennedy, David Gray’s teaching up there Exeter, so it’s spreading. So, where do you find more? Just search for Wardley mapping online. I’m sure you’ll find a lot of resources.

Simone Cicero:
Right. And I think this is a witness of your heritage that is so wide. I mean, most of the map cam community, people can also look up the videos online. So, I think recognizing that your work of mapping was really foundational to many, many strategies and researchers, and business owners and entrepreneurs worldwide. So, thanks very much, Simon. It was amazing.

Simon Wardley:
Thank you. It’s been a pleasure, absolute delight. And it’s always difficult to do this just with words, I have this desperate need to show a map.

Simone Cicero:
Right, right. Right. And I think Stina will help me with figuring out all the pictures that we need to put into these notes. That will be great. Stina, do you want to say something more?

Stina Heikkila:
No, just to echo the thank you and yeah, I think this is great that the practice is growing. And we’ll keep checking out for new updates that we can draw benefit from.

Simon Wardley:
I must admit, it’s wonderful to see it spread because it’s all creative commons. I mean, the only thing I will mention is that all maps are imperfect there. By the nature of being a map, it has to be an imperfect representation of a space. I mean, even geographic maps in order to be a perfect map of France, you’d have to be one to one scale, which means you’d have to be the size of France as a map. So, all maps are imperfect. And secondly, they’re all models, so they are all wrong. But despite being imperfect and wrong, maps tend to be — people find them quite useful, and particularly for communication, learning, and challenge. And hopefully, one day someone will come up with a better map.

Simone Cicero:
Right. I totally echo this. So, our listeners, please, first of all, map then do more creative commons work and catch up soon.