Complex & Adaptive
A refresher
Friends,
I hope that all is well with you and yours, and that this e-mail finds you on a boat with shoddy connection, in the tropics, three months after I sent it.
Now accepting keynotes for 23Q4-24Q2
Every year, I create three main presentations. For 2023, they are:
Delusions of determinism: Why planning for success leads to failure
Regression toward the meme: Why modern leadership continues to fall into old traps
Under pressure: Retail in a new financial era
If you want to book me for your event, workshop, or corporate speaking slot, just send me an email. To make sure I am available, however, please do so at your earliest convenience; my schedule is filling up fast - and I will be raising my prices at the end of the year.
More information can be found here.
A couple of updates before we go-go
The first webinar will take place mid October, either before or after WPP Stream (I will know by next week). If you want to take part, you need to let us know so that we might email you the link on the day in question.
Given the time commitment required on our end, please only sign up for the webinar if you actually intend to show up. One of the major drawbacks of free events is that there is no cost associated with skipping them last minute, even though there is a cost associated with preparation.
But really, you should join. A lot will be revealed about the new book, and you will all get to meet Steve properly. Minds will be blown.
Item of the week arbitrary time period
As many will be aware, I consider Stuart Kauffman to be one of the great thinkers of our age; his mind stands out even among the geniuses at Santa Fe. Now at the ripe age of 84, he has published yet another paper (together with Andrea Roli) and is calling it his perhaps most important to date. That is saying something.
In A Third Transition in Science, the pair argue that the theory of the adjacent possible (which is a scientific keystone in adaptive strategy and ABCDE) fundamentally alters what we believe to know about the world. It is a fascinating read.
We can neither define nor deduce the evolving phase space: we can use no mathematics based on set theory to do so. We cannot write or solve differential equations for the diachronic evolution of ever-new adaptations in a biosphere. Evolving biospheres are outside the Newtonian paradigm. There can be no theory of everything that entails all that comes to exist. We face a third major transition in science beyond the Pythagorean dream that ‘all is number’ echoed by Newtonian physics. However, we begin to understand the emergent creativity of an evolving biosphere: emergence is not engineering.
Moving on.
A refresher on complexity
Not a higher state of complicatedness
As soon as we leave kindergarten, our teachers start telling us that for every question, there is a correct answer. They also tell us that we should know it. If we do not, well, we should have studied harder; we should have done our homework.
Eventually, we leave for business school, college, university, and later perhaps for an MBA program. Inevitably, our professors tell us that for every question, there is a correct answer. They also tell us that we should know it. If we do not, well, we should have studied harder; we should have done our homework.
Once employment beckons, we enter our working lives under the impression that there will be a correct answer to every challenge we may face. Should we find ourselves not knowing it, we need but to collect more data, study harder, and do our homework. Eventually, the correct answer will reveal itself.
Or so we think, because that is how we have been taught to think.
The scientific fact that it may not strikes us as utterly bewildering. If it were true, it would shatter the fabrics that hold our world view together. The idea that strategy is a tool with which to solve problems? Wrong. The promise of guaranteed outcomes if we merely follow the latest recipe? False. The suggestion that we, and we alone, may control our fate? Nope.
Yet that is what complexity science - a cutting-edge scientific field with numerous Nobel prize winners in its ranks - teaches us. Just as how quantum theory took Newtonian mechanics from certainty to probability, complexity scientists have been able to prove that the linear causalities that traditional strategic doctrine relies on simply do not exist.
In short, complexity theory can be said to refer to the study of complex adaptive systems (CAS). Complexity is not, contrary to popular belief, a higher state of complicatedness. The etymological root of the word is the Latin word plexus, which means braided or entwined. Complexus thus translates to “braided together”. Adaptive refers to the system’s ability to learn, change and alter its behavior. System is, in effect, a network of connections.
In other words, complexity theory has to do with, as Murray Gell-Mann once put it, the intricate inter-connectivity of elements within a system, and the system and its environment. Examples of such systems include ecologies, social networks, the brain, the immune system, economies, markets, and firms.
CAS have a few key features that make them distinctively different from ordered systems.
There is no linear material causality – the system is not causal, but dispositional (i.e., disposed to behave and evolve in a certain way). Doing A does not lead to B, but can lead to all kinds of things, and the size of the output is typically unrelated to the size of the input.
Example conclusion: we can never guarantee an outcome, merely nudge the firm away from a situation in which every outcome is equally likely.
Unlike ordered systems which are context-free, CAS are context-specific, rendering universal rules impossible. Given that contexts shift, what worked in one may also not work in another, nor is it certain that what was once correct will not become false.
Example conclusion: a strategy that worked for one organization at a given time is unlikely to work for another, or even the same organization at a different time.
The behavior of a CAS is emergent and only visible in retrospect – it comes out of self-organization, not external control, and cannot be predicted by study of individual parts.
Example conclusion: most heavyweights in strategic management history should be read out of interest, not in search of instruction.
In CAS, due to the above, the whole is different to the sum of its parts, and one can therefore neither take a single part and aggregate it into the whole nor take the whole and reduce it into a single part.
Example conclusion: no company can be said to have succeeded because of any one thing (e.g., flywheel, customer obsession, a particular strategy, etc.), nor is an employee representative of the whole department any more than the department is representative of the whole firm or the firm representative of the whole industry.
CAS are embedded into other CAS.
Example conclusion: teams are embedded into departments, which are embedded into firms, which are embedded into industries and so on. Expecting everyone, every step of the way, to execute a strategic plan precisely as intended is setting oneself up for failure.
In CAS, the relationships between parts (agents) are more important than the individual parts themselves.
Example conclusion: strategic management is less about managing people than managing connections between people.
I am fully aware that first encounters with complexity science may be difficult to take in. Does it mean, for example, that we cannot know anything? Well, yes and no. We cannot predict in detail what will happen regardless of how much data we collect, which means that strategies are better drawn in mud than etched in stone. Making the best of the messy present (or “maximizing its evolutionary potential”, to use technical language) becomes much more sensible than fooling oneself into thinking that there will come a tomorrow when the mess is no more.
But complexity also explains why things so rarely go according to plan, why we fail to spot the technologies that eventually disrupt us, why there will always be uncertainty, and why not everything that makes sense works while not everything that works makes sense.
Importantly, this is not all to say that everything is complex. Humans can create ordered systems; the person preparing your Big Mac does not experiment with it to see what will happen. However, in the field of work that so many of us do, assuming complexity is much safer than assuming order. Even though it is the opposite of what historically has been done.
Until next time, have the loveliest of weekends.
Onwards and upwards,
JP
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