Understanding Complexity with Dave Snowden - OrgDev Episode 92

Hi, welcome to the org dev podcast. So if we can't predict with any certainty what will happen in our organizations, we can't control them and we can't agree on what's true, how do we lead? And that's the kind of question Dave Snow has been, it's career exploring. From Kinevin to Estrine mapping, his work challenges how we think about change complexity and what it really means to make sense of the world around us. Dave is the creator of the Kinevin framework and originated the design of SenseMaker, the world's first distributed ethnography tool and a new way of waving risk and strategy together called RAS. He's a lead author of managing complexity in times of crisis, a field guy for decision maker and he divides this time between two roles, founder and chief scientific officer of the Kinevin company and founder and director of the Kinevin Centre. His work is internationally nature and covers government and industry looking at complex issues relating to strategy and organizational decision making. He's pioneered a science-based approach to organizations during unantipopology, neuroscience and complex active systems. Dave's whole position is an extraordinary professor at the University of Pretoria and Stellanbosch as well as visiting professor at the University of Harle. The Kinevin company, formerly known as Collative Edge, was founded in 2005 by Dave Snowden and Dave has had a fascinating journey starting out studying theoretical physics and philosophy which has helped shape its approach. And interestingly, he was also C-level leader IBM, probably one of the most interesting organizations to study there are, which gives him fascinating insights into how organizations work. So Dave, thank you so much for joining us and we're literally the last people or the second from last call before we go and holiday today. So thank you so much for making time. It's great to have you with us Dave, thank you. So, Garen's kind of outlined what you do but just bring that to life a little bit more, tell us a bit about the roles you have and what does that involve. Okay, so we're a small company and we want to keep it small, we're an action research group. But I think the unique aspect of what we do is we totally reject the idea of using cases to create practice which dominates management science and there are a couple of reasons for that. One is, and this is my physics background talking, no social scientist ever has enough data to form any valid conclusion anyway, which doesn't mean there is value in it, but you never have enough data. The other problem is, and this isn't most social science, but what you see in management science is a consultant or an academic will go and interview 10 or 15 companies, they'll believe what they're told, which is really stupid. Every time I put ethnographers in to check what exactly to say about their company, they get completely different results, but they believe what they're told and then they assume that qualities they can identify from those cases, which are actually emerging properties, they're something which is emerged, they actually think they have causality. This is called the confusion of correlation with causation and they create really easy recipes. So here's 15 cases, here's a recipe, do these things, you two will be successful. It's the foundation of all the big consultancies. Now, let's say there are many problems with that. One is that you can't trust what you get told, you don't get enough data, but also a confusion to many issues. One is the confusion of correlation with causation. So for example, if any country wants to increase the number of Nobel Prizes it wins, it doesn't need an educational system, all of these to do is increase dark chocolate consumption. Because dark chocolate consumption per head of population directly correlates with Nobel Prizes for head of population for the last 50 years. It's a bigger data set and I've ever seen any management consultancy report, so go and eat chocolate. Now the one which I think is causally peaks in attempts to commit suicide by drowning, correlate with a release of Nicolas Cage movies, but I can see a reason for that. Go on with the population site and you'll see it. The other big problem, this is a massive issue in organizational development and you can see it in behavioral approaches, which are becoming increasingly discredited, is they confuse an emergent property with something which has causal aspects. So for example, you notice that innovative people are very creative, so you start to run creativity programs. You convert an office into primary colored children's toys and don't take me there. The reality is creativity and innovation are both emergent properties of starvation, pressure and perspective shift. And so the fact that you can identify characteristics of leaders, those characteristics aren't causal, they've arisen from multiple interactions over time. And I think there's a major issue on this. You can see it in leadership development theory and all sorts of theories. You see it in agile, you can have an agile mindset and people decide they define ideal behavior. And that is just the wrong way of going about it. So we take a very different approach. We spend about five, six, sometimes ten years playing around an initial or a problem. And we look into physics, chemistry, biology, anthropology, philosophy. And then things start to come together. And then one day it all sort of looks right. It's a bit like the theoretical physics. One day's the mass looks beautiful. Then you hand it over to the experimental physicists who kind of like get it right. And then when they get bored, they give it to the engineers. So that's kind of like the approach we adopt. So to give you the most simple example on that, if you give radiologists about your x-rays and ask them to look for anomalies. And on the final x-ray you put a picture of a gorilla, which is 48 times the size of a cancer nodule. 83% of radiologists will not see it, even otherwise physically scant it. And the 17% who do see it come to believe they were wrong when they talk with the 83% who didn't. And 100% of non-radiologists do not see it. It's called the "inattentional blindness" and it's part of what we are as a species. And then the minute you realize that, any approach which says if I give everybody the right information, they have the right training, the right competencies, they will make the right decisions is completed out of the belonging, which doesn't mean that you shouldn't give them training and competencies. But fundamentally you've got to find the 17%. Now some of our work for example is to find the 17% before they talk with the 83% who didn't. And I could go into other things, you know, that once you get above about seven people, dynamics of silos come into play which don't it sort of seven or five. So there's a whole body of natural science we can draw on. And I think to sort of conclude this, the big difference between natural science and social science and yeah, now I've got a background in that as well. Social science tends to provide explanatory but not predictive capability and it's very powerful as something. Natural science creates predictive because the experiments have been subject to repeated experiments by third parties, you've got peer review. And it's interesting if you look in psychology at the moment, you got what's called the experimental crisis in that people have tried to repeat the experiments and they failed. And a whole body of OD practice, you know, falls at that point. It's a long answer, but that's the essence of the approach. We've used the term complexity science to describe kind of the field you're working. If somebody's not under not heard that phrase before in kind of leadership context, how would you explain it? What it is and why it matters. Okay, so first you don't confuse it with systems thinking. Systems thinkers have tried to address complexity, but their theoretical models really all derive from Ashbees theory of information. Complexity science, the clue is in the second word, has a very different background. It comes from physics and chemistry from biology and then got applied to economics and that's where there's some overlaps, but actually the big fight in the Macy conference between baits and then Ashbees sort of is one of the bifurcation points. We can go to that more detail if you want. So complexity science deals with systems which are inherently uncertain where there is no linear relationship between cause and effect. Yeah, so the same thing will only happen again the same way toys by accident. And one of the ways that I get executives to understand that is there's a famous phrase which you see over the congressional report on 9/11 role commissions of inquiry, all of these things and it says why didn't we join at the dots? So something goes badly wrong and with the benefit of hindsight everybody says we should have joined at the dots and they can see the causal links. Okay, so this is a fun exercise. You give people four dots. You point that with four dots there are six linkages that conform between the dots. Yeah, the square and the diagonals which means if you take dots and linkages in any combination as a pattern there are 64 possible patterns. So you say with four dots how many possible patterns are there? Then wait and you give them like a minute to do it, all right? Yeah, ideally you get them to write it on a piece of paper and hold it up because most executives are lying bastards when it comes down to what they think they got the answer right? And I've had guesses as low as 150 most people start in the thousands. It's actually just under 3.4 trillion. If I work to four it's just under 4.8 quadrillion. And there's an old Chinese story about that. A Chinese say just for a reward by the Indian emperor for teaching him chess said I have a one screen of rice on the first square of the chess board double it thereafter. Right? There wasn't enough rice in India to satisfy the demand. So the question is how many dots are there in the human system? How many possible patterns are there? Everything is deeply entangled with everything else and critically hindsight doesn't lead to foresight. And the concept of entanglement is key because in a complex adaptive system and this also has major implications for OD connections matter more than things. And anybody with teenage children knows that yeah when when your children hit puberty it really matters who their friends are because they just come out of your influence and now another influence that and those interactions will shake them. Far more than anything else. So complexity deals with multi connected simp systems systems which don't have linear relationships to encores an effect but they we can measure patterns we can measure dispositional states we can influence their direction and we can observe regularities to other examples to illustrate complexity and to hope if they there's another little exercise you can do is again people to understand complexity physically is really useful so the dots is one. The other is get 20 or 30 people. stand up in a room and ask them to identify their best friend and their worst enemy. Before you do that, you say, "Don't look at anybody, don't say anything," and you can choose people at random. But it's worth videoing because they always do choose their best friend and their worst enemy so you can study it later. Sorry, that would be an ethical, but you could. And then you say, "Organise yourself so your best friend protects you from your worst enemy." And the group dissipates over the room. Then you switch the rule and you say, "Protect your friend from your enemy" and the group comes together instantly in the middle. It's a really powerful demonstration because nobody predicts it. So when an antelope spots a predator, they identify another antelope by the pattern on its bum. That's why they're so vivid. And they position themselves between the predator and the other antelope. So the herd stays together, even though it doesn't have a goal or a purpose in sense of a destination. Now, that is one of the ways a complex system works. And some of the stuff we're doing at the moment is how do you create alignment without goals? Because under conditions of extreme uncertainty, goals could be dangerous. And people keep talking about North stars as if they were destinations when it's meant to be an navigation ape. But that's another matter. The other example, which we've just launched something on, is if you look at bees swarming, there's a temperature trigger in the hive, which means the worker bees hatch out in the queen. And then a group of the worker bees go with that queen and hang off the nearest branch. Then individual worker bees fly out to try and find a new hive location. They fly back to the swarm and they do a figure of eight dances called the Wackel Dance. And the plane of the figure eight angle to the Sun indicates the destination. And the intensity of the dance says how good a place it is. And there are other bees which disrupt the dance of some bees. And that's important statistically. It creates variation. And after two or three days, the entire swarm suddenly goes to one destination by agreement. And it's always the best of all the destinations which have been investigated. I can let you have the papers on this. Now that's an optimization without directing intelligence entirely defined by interactions, not by attitudes, motivations, beliefs or anything else. So some of the stuff we're now doing, for example, is present a problem to the whole workforce, get them all to interpreted, then go through a series of iterations over a very short period of time until we know the consensus and we know the outliers. And we can do that in a day as opposed to three months of staff consultation and communication exercises. And that's the real power that complexity science gives you. It's the ability to do significantly more with less resources, because you're working with the natural contours of the system, rather than trying to impose a mechanical or engineering metaphor onto an organic system. And that's a real shift for organizations, isn't it? Who used to that kind of top down? We set goals. We cascade them. How do they start to make the shift? Yeah. Ironically, it wasn't the case in scientific management. So the great privilege of teaching leadership with Peter Druckert for a few years, which is a lot of pleasure. Partly, because the first time I met him, I was keynote in a conference and he spoke after me, and I made the mistake of criticizing Taylor and I got beaten up. It wasn't quite the I. New Fedric Taylor speech, if you remember it from that one, American lecture, but it was pretty close to that. Either way, decided that was rescuable. I was a puddle of humiliation on a stage in the hotel down in California, inside the Ego. Took me out for dinner and then we taught together, which was a huge privilege. Basically, if you go back to scientific management, this is Taylor et al. Everybody forgets what they were replacing. So we look at time and motion now. We say, "Oh my God, that's terrible." But before that, the accident rates in factories were appalling. It was near slave labor. Yeah, it was a huge improvement. And if you retailer, you had a very strong ethical driver behind what he was doing. But what he never did was to abandon apprentice models of management. So the assumption was people would grow up in a firm that there might be some new blood from time to time. But we know, for example, to understand a social system takes four or five years of social interaction at scale. So they understood that. And their management model was a military one. Now, again, people who I do a lot of work with military, fascinating stuff going on in Ukraine in the moment I'm back there in January, but fundamentally, military models are highly adaptive. They're not hierarchical, a weapons sergeant outpoints a brigadier in some respects. So they're highly adaptive in their distributed and their role-base, not personality-based, which is really important. What happens in the 80s and 90s with the popular introduction of systems, thinking through systems dynamics and then things like business process re-engineering is we moving to a world where we think the entire world is ordered and can be planned and structured. People's authority is just taken away. Like, you know, it's all a spreadsheet. Yeah, this is what you can do. You've got no judgment to involve. And really, that's the stuff which is coming to the end then. But engineering models of management are not flexible, whereas military are. And I think that's the big flip we're moving on to. We're now starting to see, and these things happen very quickly when they happen. They happen in one or two years. And COVID started to trigger it. That's when we wrote the guide with the European Union. First ever, government publication based on complexity theory, by the way. And then after the Trump election, from that point onwards, nobody believes the world is predictable anymore. So what we're now in a position where that sort of people are now looking for tools and methods, which assume you haven't got certainty and you can't control outcomes. But the critical thing, this is the really fascinating thing about complexity, you can understand and manage the present. And if you understand the present, you've actually got more control over the future than if you try and set goals. Because you know what can happen. It's called the science of canon-can't. Quote. You know what can change and what can't change. And you also know whatever has the lowest energy gradient is probably what's going to happen. Yeah, modern theories of evolution look at energy minimization rather than the survival of the fittest. And you've got some fascinating experience at IBM, which is often described as the mother of all bureaucracies. Yeah. And I think that's one of the-- The government field dynamic and user centric. You sort of share some insights about how organizations work and often how the world of the sea level leader is often not how others actually understand it to be. And there's often a lot of frustration directed towards sea level leaders. But is there's often a lack of understanding in terms of the complexity in organizations that are-- How have I kind of sort of informed your work? It's a mixture. So I mean, IBM for me to quote Dickens was the best of times in the worst of times. Yeah, I mean, IBM to again to quote Richards and the William stories and Violeta Elizabeth Bloch. When it's good, it's very, very good and when it's bad, it's awful. When I joined it, it was quite interesting. Senior VP's almost had a competition as to who could employ the most disruptive maverick. It was like a state of symbol. So that gave me infinite opportunities for employability. And I was hidden in the round in error. You need to understand some people in IBM, they're round in error every quarter. It's quarter of a million dollars. If it's less than, I think it's round you down to zero or Dick. Right? So they didn't transparency, lack of transparency, it allowed them to experiment. And by the way, that's a key issue. Too much transparency, you destroy innovation. No transparency, you get corruption. There's kind of like a golden mean to quote Aristotle between the two. So IBM gave me a job in which I could do whatever I wanted as long as I have set the right people. And I achieved my targets endlessly on that. Was that your job description? It was, and it was funny. I mean, my boss, he was, he always worked out targets retrospectively. He was a very civilized guy. You'd sit down at the end of the year and you agree what your targets would have been at the start of the year, based on what you both agreed to achieve. And HR for some reason didn't like that. So he decided to teach them a lesson. So I got $X,000 for every vice president of IBM who demanded in writing I was fired and $Y,000 for every director. HR went ballistic, but he said, look, we acquired data sciences to create a services business. We were the foundation for what became IBM Global Services. The strategy says we will disrupt traditional IBM senior people and we have to protect people from the disruption. So he said it's a strategic goal. It's measurable. I've got authority, but I've done it. And they never ever made him set a target again. He taught them a lesson on that. It was a great target for it. But the great thing about IBM is you could go into a client and you could do something risky because you were IBM. A lot of the stuff I developed, I couldn't have developed as a standalone company, but I could develop within the context of IBM. That was its great strength. It's great weakness was the bureaucracy. And the key thing in IBM, and this taught me a lot as well, is informal networks, matter-than-formal systems. So the first thing any two IBM people will do when they meet is try and work out which social network you're in. Because those are trusted. Yeah, and those networks make things happen for you. The formal system doesn't. So that was one aspect of IBM, but then the sea level issue, I mean, I was sea level before I joined IBM, I was strategy. I mean, you sit at your table and three people or five people come into you with well prepared PowerPoint slidesets that they worked on for the past three months in areas where they have deep expertise where you've got no bloody idea what the basis of their sciences. They present proposals and you meant to choose between them. It's bad enough if you have to do it individually, but if you have to do it in a board meeting it's even worse, because whatever you do, if it doesn't work, you can get blame for. People don't understand that pressure. They also don't understand that at sea level. You've got demands on you from stakeholders from other people that you can't communicate. Yeah, I mean, the characteristic of a good CEO is the ability not to suffer pressure and always appear, you've always got to appear confident. You can't appear vulnerable because you're in that role. It's not super heroous, super heroine time, is you've got to hold the ship together. And one of the things we developed in Cannevin, for example, is to help those executives is, okay, you've got five proposals, test which is coherent and which isn't. Coherence test is a lower level than it's right. So I can agree, for example, your idea is coherent, even though I think you're wrong. Yeah, so that reduces conflict in decision making. And every coherent idea, you say, okay, three months, here's $10,000, go away and see what happens if you try your idea. And then you see what happens. And that's called safe-to-fail approach. which is a key complexity technique. And I think we need to start to understand, and that's what we're doing with Swarm Compass, we're getting the hold of the workforce involved in determining what's viable before people commit their reputation to it. And I think we kind of know in organisation, because we do hear the phrase, "It's safe to fail," but often it's truly not. So how do you sort of create the conditions? Because a big part of this is creating the conditions, isn't it? Where people feel able to take those kind of calculated risks and then see what happens? You basically target the managers, they're 40% of your probe. We call them probes, not experiments. That gets the right attitude. 40% of your probes don't fail. You failed. Now, that's actually quite fascinating when you do it. I mean, somebody in IBM when I did it in Denmark said, "But they'll just create some not-some-stupid projects to achieve the target." And I said, "Well, that's what I'm hoping they'll do." And what happened is the stupid projects generally succeeded. Well, they pound-found people they thought were idiots and gave them some money for a change, right? And then suddenly discovered that those people are actually in the world differently from other people. But the key thing is you do them together and you do them collectively. So, you do the coherence test, you agree things are coherent, you agree that you don't all agree what's the right thing. And you say, "Right, we're now going to run five or seven or eight probes and that will change the space and then we'll know what the right thing is to do." So, and this is more of a research method. It's not competition as to who's right or wrong. It's a research method to understand what's viable. And this is different to a pilot because I think you sort of talked about the fact that often it's like the Hawthorne effect, where it doesn't matter what's in the pilot, it will create some form of change. And that's the problem with it. So, again, you'll never see anybody in the Kinevin Code talk about behavior or how you should be. What we do is we create processes which are likely to generate it, which actually means we can scale and we're not making moral judgments. And I had this argument with Amy Edmondson the other day where it wasn't an argument I disagreed with her, got patronized and when I replied, got ignored, all right? So, that's what happens when you fight with Harvard professors. I think the psychological safety movement is become terribly oppressive. It's becoming a sort of reverse form of oppression within the system. And it's like adult development theory, which norabates and has rightly called out as eugenic, which privileges people have reached the higher levels of enlightenment. In fact, the language, if you look at it, even Keegan, is the more respectable end, is the language of North Atlantic, green, yeah, enlightenment thinking. Yeah, this is our ideal, have you achieved it by implication I have? And all of that is kind of like to my mind deeply manipulative. If you actually get people together working together in small groups, they sort this stuff out for themselves. So, give another example. One of our methods, and complexity methods, generally hit multiple goals with one intervention, which is also powerful. So, you've got several problems like how do you take on new employees? And how do you do innovation? Right, simple thing. We take somebody who's just joined the company. We put them in a partnership with somebody who's about to retire from the company. This is called a transgenerational pair. Now, we've done it in communities, by the way, with teenagers and retired people. And that draws on something called young driver syndrome, in that young recently qualified drivers see things that experience drivers don't advise aversa. Yeah, we've done it with newly qualified doctors with experienced consultants. They see the world differently, but they've got enough in common. So, I've got young, bright and naive, with old, wise and cynical. And by the way, the cynics of the people in the organisation who care, if somebody calls you a cynic as far as I'm concerned, it's a compliment. Because you're not just being compliant. And then we put them in a trio with somebody who's identified as fast-track management. I mean, somebody who's on the track to be a senior manager, who's got a reputation to build. So I throw 15 of those trios at a problem for a month. Some of them will see gorillas, which they won't do if I do a tiger team where I have everybody together with authority. But also what I'm building is networks between young people in the organisation and old people. And I gather in the stories from the old people before they leave, which is the most valuable form of knowledge out. So I'm doing multiple things in the same way. We do the same in IT. We take young bright coder with experienced cynical systems architect. And user trained to talk to IT people. It's a lot easier to train users to talk to IT people and train IT people to understand users. And instead of sending out a systems analyst to interview people who will go out with a whole series of assumptions. And users don't know what to ask for in IT these days either, because they don't know what IT can do for them. It's moving so quickly. So we put those, you know, 20 of those trios to work for a month. And then we synthesise what they come up with. That's a much better requirements documentation. But I've also built social networks between users and IT people, which will carry forward into the project and de-risk it. Now again, you see what we're doing is we're creating a process which generates a result. We're not saying what result we want. We're not saying to old people you need to listen to youth. Well, yeah, everybody tells them that. I remember being told that. I now know that they were right, but I didn't know it at the time. Yeah, admonitions to be good have zero effect on any human being who's competent to survive in an organisation anyway. They just feed it back to you. It's interesting because it also does a thing to the organisation as well, doesn't it? One of the things I've sort of enjoyed getting ready for this podcast is looking at some of the terminology. One of the things you talk about is epistemic justice. Yeah. Yeah, so you got, well, please describe it better than I could. But it's about viewpoints of personas that are more represented than others. And that little mechanism like this would go some way to sort of. Yeah, but that's a much bigger issue. So I mean, Beth is one of our consultants, all right? She has a wonderful way of saying it. She said, "The illustration of epistemic injustice is old men are called philosophers where old wise tell tales." So the way you describe something in digitimises people. And one of the many advantages about being Welsh is we grown next to the English so we've recognised the phenomena. I mean, interesting just to tell you on that, my grandmother was subject to something called the Welsh knot. So in the middle of the 20th century, the English passed the law which said Welsh was an uncivilising influence on the Welsh and had to be eliminated. And so if my grandmother spoke Welsh in school, she had a wooden badge hanging around the neck which had WN written on it, which was for Welsh knot. She'd had to catch one of her friends speaking well and whoever wore and hand over the knot and whoever wore them not at the end of the day got thrashed by the teacher. And interestingly, it was the same happening to indigenous people in Australia and Canada at exactly the same period, Tyson and I'd call her, I'd talk about this the other day. And then they created an interview right, Tuffy was a Welshman, Tuffy was a cheat to reflect that. So Tuffy is a real insult. I mean, we can use it in Wales, but you English use it, that's not all. And the right to have your voice heard is key. And the critical thing here, and I think this is where AI is going down a really bad path at the moment, is the algorithm is interpreting what you wrote down. Now that has a problem because you can write down less than 10% of what you know anyway, focus on text and tokens is problematic. Secondly, what that text means is for you to interpret not for the AI. Or not for an academic or not for an expert. So a huge aspect of our work is to allow people to interpret their own experiences into what's called higher abstraction metadata, which is the primary unit of analysis. And as you can see, a lot of our methods put young people with older people in small groups, so their voice is heard. We don't say you should listen to the voice, we create a process where which that happens. So that's a really key concept in what we do. And it's one of the reasons why we're now starting big research programme we'll launch in next week or the week after to look at the balance between AI and human reasoning. So we're going to audit all the decisions that make you making your company identify the balance between human and machine reasoning. In fact, the way between what's called abductive logic and inductive logic. AI is inductive, humans are abductive. And then identify what our inductive capability human beings have to practice for five years before they create the abductive capability. There are things AI can do better than us, but if we don't do them, we never get the higher capacity. And then we're going to create an audit tool, so that's something we're going to run over the next six months. Because at the moment, the real danger with AI, and it's been coming over the last 30 years, it starts with systems thinking and the excessive focus on information, and information in signal form, which then became tax form, is that we're reducing human intelligence to the ability to process text. So in a knowledge management community, they don't talk about knowledge, they just talk about text. I mean, they call in it knowledge, but if it's not written down, they don't believe it exists. And that's deeply, deeply problematic. So at the moment, the danger with AI is we're meeting it halfway. And fascinating, a big issue for small consultants on this, by the way, is the big consultants again really hit, because the whole race on Dertra for the last, well, not all of them, but for the last three decades, is to be repurposed existing text for new clients at huge margins. Well, AI can do that better. So I have a simple heuristic at the moment. If anybody says AI is made to some more productive, that probably indicates they were doing a bad job in the first place. I think you also said that it should be mandatory that all software and Gs had ethics training as well. Yeah, wrote an article on that. Well, they're making decisions without any understanding of the implications. And the real scary thing, I had this in Sweet Georgia, Browns in Washington with Peter Thiel once, my one encounter with him. And I remember walking out of the meeting and saying, "You're not in moral, you're in moral." And that's far more scary. [MUSIC PLAYING] And you touch the band decision making there as well. And one of the things that's sort of fascinating is you talk about the fact that decision making doesn't bring out the best in an individual and often just and therefore the way in which decisions are designed actually bring out the worst things is actually there's much more sophisticated ways of doing it. Well all good decision makers actually have people with them they trust. I mean I've yet to see an executive who didn't carry two or three people around with them between employment. So any intelligent person has already worked like that but we do know some basic scientific facts on this comes from biology. The primary decision that there's a sexual pair which is nurture more than less than decision making. There's the small hand in party or extended family which is normally about five in terms of active decision makers. Maybe slightly bigger in numbers but never more than seven. And there are things called deems which are collective groups for about 20 and the deems tend to hold together in summer when there's plenty and compete with other deems. Then in winter they came together in what are called macro deems which are groups of 500 or so because now they got to cooperate to survive not compete. There's a lesson in that for economics by the way. And that's where Gerber and others argue monument building came from you have to have a task that you agree to do together otherwise you'll fight. Now we've actually built that into a lot of peace and reconciliation work. So you make decisions differently in different groups and the interesting is once you go above seven decision makers people fall back into their silos. So I was working recently on an NHS triage issue so we have doctors we have nurses we have ambulance drivers we have hospital administrators they all want to improve things but nobody will depart from their silos because that's the respect. If I take one person from each silo and put them in five or six parallel teams they innovate. So some of the really radical stuff which we announced yesterday is to actually allow roll based combinations. So if I've got six roles not people but roles and I accept the seventh role which is completely anonymous so I don't know who it is that creates what's called a panoptic and effect. And if you've got an unseen observer you're honest and those groups of seven can spend many or make decisions without seeking approval. Now what that allows me to do is basically to let a thousand flowers bloom to go back to the seventies all right I can actually have a very small amount of money allocated to lots of people doing experiments and then the real money can follow to the things which work rather than to people who say they can make things work. Now that's one of the most radical things we've created and I'm really excited by that we know in the NHS we could take 50% of the bureaucratic cost out of a hospital and we could have faster decisions made in the field with higher retention and medical staff. It's going to take two years to get people to listen to us on that. I was going to ask that the kind of the radical some of the more radical approaches how do you get people to engage with that how do you get kind of almost a mission to do the work. So I mean there's two ways if you're working in industry you go and find the early adopters and the trouble is they tend to be oil companies, farmer companies and military and intelligence so it's yeah if you want to do novel things get used to working with people who do so things other people consider evil. Now but I've taught just war theory at West Point so I quite like those guys because they know they're going to have to kill people so they worry about it or it's people who don't have to do it just rely on them but that's a story for another day. So there's always people there who will do something novel for the first time. Yeah and this is more across in the cas and this is where you build your early reference sites and to be quiet as you don't want to be overformed you want to be working with the clients so you jointly collaborate to develop stuff. When the market switches which is has on complexity then you start to create product because people are now buying what it will do for them not how it does. Now medical research is different it may be about to change in the states we're talking in California at the moment because the sudden withdrawal of funding is creating a crisis and they got a look in your ways of doing things. But generally medical research we're going to be holding an invitation only seminar next year for people in the health sector who get the basic science and what we'll be doing is constructing controlled finance experiments to test these ideas out from which we can publish papers because until we do that you will not get mass adoption in the NHS even though it can make a big big difference straight away. So you have to understand your markets and the way you work I think. One thing as we sort of shape in the system I think one of the things that's already stood out for me as well is you talk about you know you can't predict change but you can create a vector of direction almost as well. And then that sort of introduces the world of constraints and constructors and not all constraints are the same as well. So people that are actually relatively new to feel what is a little bit of a definition of how they actually work within an organization. If I work in a complex system there are kind of like what I know always doing is I'm trying to manage for emergence. So as things interact with other things properties will emerge which can't be predicted from the parts. That's the key concept of emergence. So there are four things I can manage in a complex system. One I called Actance, sorry this comes from the Tours Acton Network Theory though I've modified it a bit. So an Actant is anything with agency in the system. You know process philosophy argues the same thing but I'm not worried about that to be honest yeah. So Actance can be Actors i.e. people or roles. Yeah they can be constraints and constraints can connect things or they can contain things. Then you get Constructors which is a really important concept. A Constructor changes things but doesn't itself change in the act of changing them. So it can be so for example a software object is a Constructor. A Ritual is a Constructor. Now a Contagion also works with Constructors. So Constructors give you stability within a complex system. So when we're doing what's called Estero map and your affordance mapping we identify all the actance in play in it on an organization in its market. And we can do that in a workshop which is the best way to get started but then we use software to get it in its scale. And then we map that material onto a grid between energy costs of change and time to change. And there's a key principle we use on this if people can't agree what something is or they can't agree where it's placed they break it down into a leagree. There's no discussion there's no argument there's no dialogic there's no facilitation if you don't agree break it down until you agree. This gets to all in complexity is called the optimal level of granularity. And then on that grid we identify the stuff which is kind of like top right on that the energy cost of change and the time to change is so high realistically is not going to change but I may need to monitor it and monitors become key because monitors give me weak signs of failure of a constraint or early signs of emergence. And stuff in the bottom left is highly volatile so it can you know use the expression turn on the dime which means it's quite dangerous. And then and this takes half a day to do in the second half day because we normally do this overnight to give people time to absorb it. We come up with actions to change the energy cost of changing things but we don't necessarily try and change them. So what we're doing is we're changing the landscape so it's more favorably disposed to what we want to achieve before we try and intervene. So that's called a stride mapping and that uses act and I've introduced a concept of monitoring. The other key thing in complexity is the interactions. So one of the ways you change things is change the interactions and I can use some examples of that. And of course some actants can be made so solid that they won't change and some interactions can be ritualized so they won't change and that's called scaffolding. That's called the aims framework. Actants interactions monitor scaffolding. Now the key thing on this and it's really upset some people is in a complex adaptive system. None of the actants has any knowledge of the whole. So if anybody says we need to think holistically they do not understand complexity theory and then are in a very bad place because you can't and you shouldn't. Remember the bees? None of the bees are thinking holistically because a minute somebody tries to do that they impose their view of the world on the system and therefore they miss things which they would otherwise need to pay attention to. The other thing the stride map gives you is now an alternative to scenario planning because it says what can change easily and that's what's most likely to happen. But because we build it bottom up without discourse, without dialogue, without argument we got an objective assessment of the situation. Now I was just thinking a lot of the leaders we work with the kind of state of overwhelm. What advice would you give them? What's one small practice or one small thing they can start? Oh, the best thing they can start. Complexity theory is for lazy managers. Okay. And they can consultants because you start trying to control everything and you just say I'll change the actants, I'll change the actrants, I'll see what happens. And if I like it I'll give it more energy. I mean complexity theory is a gift for senior executives because it gives them time to monitor the whole. Well yeah because I think it's not the definition I think you sort of talk about that the Latin route of complicated and complex thing. Yeah, complicated is folded complexes entangled. Something which is folded can be unfolded and folded again, it doesn't change. Something was entangled so are you calm. Look at a fish in that on the side of a harbour. The fisherman can entangle it but you can't. Well come walking with me, I've got one route this week which I know is going to evolve bramble bushes and therns and woodland and I am not looking forward to it because everything is entangled. I've got a machete somewhere in the car and it may take with me. I mean it's a big question but when you look back at your career so far what are some of the biggest lessons you've learned that you can't carry with you? Oh it's just you're in bright at the time. I mean I was lucky as well I mean I had a very secure home life. That makes you, yeah we know that's a subject with risk taking but it was also intensive. I mean my father was born you know as he was a son of a small farmer quite abuse physically and everything else as a kid because farmers sons were and one day his father got a bad vet spill so he went down to the school and said which of my kids is bright enough to be a vet so that was hiked out of being a apprentice to be a carpenter and sent to Glasgow veterinary school. And ended up as a veterinary officer to the Blues and Royals regiment in Kashmir during the Second World War, so working class ex-Northemblen farmers suddenly in the pipe to British aristocracy. So he learnt a lot from that. And my mother was born above a whorehouse in Cardiff Docks and fought away out through education. She was studied German, first class honours in that, but she decided if she could study German, she'd do it in Germany. So she went to Hanover University in 1947, which meant she had to wear a passport around her neck so she wouldn't get raped by British soldiers. So I grew up in a house so where education was everything. And argument was everything. I mean, if we liked you, we argued with you. If we were being polite, you needed to worry about it. And that was huge because, and you know, I debated. I know that probably the most seminal thing I think in my life was debating. So I still remember at the age of 11 walking to the front of the classroom on Friday and got given a card and it said you support capital punishment. And my mother was then leading the North Wales Labour Party campaign against capital punishment. So this is a teacher being wicked, all right? I had to speak for seven minutes without preparation for something I profoundly disagreed with. We did that every week from the age of 11 to 18. And those are so any good at it got formally taught rhetoric. That made us journalists. It made us confident. You didn't, you read everything, but you know what we're going to hit with. And you became hypercritical because arguing for things you don't believe in means you've got to be critical. You see my point about process? Nobody told us how to behave, but in those days, the grammar school threw out generalists. Now part of the problem we got in society at the moment is there are hardly any generalist list. Everybody's a deep specialist and that T-shaped generalist stuff is nonsense. If you're deep in one field, you just can't really get the other fields. Generalists are shallowing everything. So I think generalist education, yeah, basically taking the view of whatever I wanted to do it with, with the work out and generally it did. And by the way, more people should do that. A particularly work for American companies, by the way, I worked that pretty fast. American companies are very authoritarian. So if your boss tells you to do something, you do it. I didn't do that. I just told them no. So I have the world record. I didn't fill out the time sheet for seven years. I just refused. I used to spend time sheets, not worth my time. Every year this little band of six would come up and say, I've been told to fill out your time sheet. So I'd let him have my diaries. Defiance is a wonderful tool when you use it. So because you're talking about the importance of disagreement, people coming together in organizations, they all had different perspectives on it. And let that nonsense about everybody's views are equally valuable. So they're not. How do you create conditions in organizations where people feel able and have permission or give themselves permission to actually have the discussion? They're required. You do it by micro interactions. You put out small groups to allow them to make decisions, sort it out between themselves. Yeah. Trusts will arise from working together. Yeah. You basically do swarm compass. You pull the entire workforce backwards and forwards continuously and anonymously and see what patterns are sustainable. This concept that you have to empower people to speak out in order to learn, well, it's a nice idea, but it's never going to happen. Nobody in their right mind is going to, it's like, you know, you've ever seen those facilitators say, oh, nup to your biggest failure to show you trust the group. Everybody's got a well-rehearsed failure, which shows how bright they are anyway. All of this, you know, ideal behavior stuff, interesting characters people who play the game rather than people who are genuine. And you just touch on that just just one second moment because you talk to you in, I was watching a keynote that you were giving where you sort of gave an example about how you can, so for things like whistle blowing or things like speaking out against things that have happened, is often sort of seen as too difficult and career whatever. I mean, the other evidence is whistle blows get punished and people know that. So you got that problem. The other problem you got is nobody wants to cry wolf. So we've seen that with engineers, you know, they'll look at something we had this in Boeing and say something smells wrong here, but it's not serious enough for them to report it because they don't want an investigation and we prove wrong. And it came home to me about two years ago. So I was speaking at an agile conference in Eastern Europe. So I was opening keynote, a woman's book after me, if she came off the stage, the third keynote who was pretty notorious, to be honest, we all know him, slapped her on the bottom and said, well, then, last I'll see you in the bar later tonight. So I thought we finally got him, right? Because there's a general rule amongst those of us who know him that you never like women on their own in a room with him. Yeah, he's notorious. And I remember going to the one she said, no way am I reporting that. I'll be subject to secondary abuse when it's when you confront him. Then all these makes all kind of on me, it's not worth my life. Now I found that because I did a lot of investigation on this and in the big authority firms, people will not report racism or sexism until it's so serious they've got no alternative. And actually, if you've seen the morning show, is it a really good illustration of that? Somebody gets things and then he starts to feel they're entitled to things, nobody feeds back negatively. So then they become an abuser. And we know that nobody will report fraud until they're absolutely certain of it. Nobody will report safety issues until they know it's a real problem. So what we do, and this is done with sense maker, is people can report something as a micro issue. The higher abstraction metadata we developed in painting, it comes in then because that's non non judgmental. It's purely descriptive. So they identify the thing they use descriptive metadata. We destroy any identity and we destroy the content apart from some key words. And look for a pattern in multiple micro reports and we create an auditable report that says you got an emerging program here, go and deal with it. Now that doesn't involve the company in investigating cases. This is weak signal detection. It says you've got an emergent problem here, go and investigate. And by the way, we do that for business opportunities as well. There may be a new opportunity here, but you're not spotting it because nobody's certain. And again, that's something which came out of a whole body of work. One question I was asked as well is you know, you're intensely well read. How do you invest in your own learning and development? How do you make time for it? What do you do? Oh, I lots of argue with people on social media. That's how people don't realise just how much I enjoy myself. I guess read a lot. And I chase references down. I've got one big advantage, young dyslactic. So the negative is I can't learn foreign languages. I can't pronounce a word from the text. I have to hear it 15 or 20 times and use a mental trick to lapse it. But it means I read a book two pages at a time. Literally, I just go through it like that. And I pick up the overall pattern. And some books get put on one side and I need to read them in detail, but I have used four different colored pens. I wasn't diagnosed with dyslexia when I was young. So I developed coping mechanisms to read it. A line of the time takes a lot of effort. And eclectic. So I'm the moment I've just packed to go up to the North Wales. And I've got a book on the history of intelligence which goes back to pre-Roman periods. Yeah, that's history. I've got five science fiction novels and I've got a couple of really heavyweight stuff on anthropology and biology. And so re-declactically. And don't worry if you don't always understand it. Yeah, you'll pick it up. Then you'll apply stuff. And talk with lots of people from lots of different backgrounds and don't be afraid to argue with them. The good people like an argument. The people who can't cope with an argument, you probably waste of time anyway. And is there a particular book or a podcast or something that you would recommend to other people? Is there one stand out? No. Recessfully. I refuse to do that on broad principle. Go and read a lot. See a lot. But read outside your discipline. If somebody's kind of just taken their first steps into this area, what advice would you give them? Finding intractable problem, finding a problem people can't solve with conventional excuses and come and talk with people like us and we can probably help you. Don't go after the low-hanging fruit because conventional techniques can deal with that. Yeah. So go for something really, really sticky and tricky. Okay, which is frustrating people. So for example, what we're doing with Swarm Compass is how the hell do you consult the whole of your workforce within a day and get results back? So you don't have to wait months while we do that. Thank you very much for taking the time to talk to us. We've really enjoyed it. There's lots for people to take away and digest. And I think you've just helped just help people think about things through a different lens and challenge some of the perceived wisdom that's all too prevalent out there. So thank you very much for the time and it's been a delight.