If you ask most people who run a factory, or an organisation or a sports team, what they’re looking for is a taut, firm connection between and among everybody: everybody busy all the time. The reason that a bucket brigade is so much more efficient than people running back and forth and back and forth to the source of water is that it’s easier for people to efficiently pass the bucket from one to another than it is for them to run back and forth. You will put the fire out faster.
If you’ve ever seen an efficient juggling troupe or bucket brigade or a hockey line-up that’s passing, passing as it works its way down to the goal, it’s a thing of beauty. And so what we seek to achieve is that idea of synchronisation. But I’m here to tell you that you cannot maximise system efficiency by eliminating slack from the system. It feels like you should, but you can’t. And the reason you can’t is because of variability. Variability says that someone might be five minutes late for their appointment. Variability says there might be a custom order coming through that’s worth it for the organisation to take on. Variability says that some customers need to be treated differently from others. And when a system like that exists, when you have removed all of the slack, then when switching costs kick in, the whole system falls apart.
What’s the alternative? The alternative is a fire department with firemen who eat chili for three hours, waiting for the alarm to ring. If you were trying to get rid of slack what you’d do is say, “Let’s have exactly the right number of firemen so that when the average number of fires are happening, all of the fires are being addressed.” Which works great – except when the above number of fires show up. And when the above average number of fires show up, you don’t have enough firemen to go around.
And so what we have the opportunity to do as we organise our lives, as we dance with these systems, is to intentionally build slack into our systems. A buffer. A cushion. To avoid the emergency. Because in that buffer, we can work on the long term stuff. The firemen aren’t really eating chili… they’re using their downtime in a slightly productive way. But mostly what they’re doing is standing in reserve, waiting for when the emergency shows up so that they don’t have to say, “Oh, sorry your house burnt down.”Seth Godin – Akimbo Season 4 Episode 20: Systems Thinking
Akimbo Season 4 Episode 20 (July 10, 2019) – Systems Thinking
This is a great episode of riffs on how systems create – and constrain – possibilities, and the opportunities that open up when systems change. Featuring Mr Heinz and the fictional (!) Betty Crocker.
Akimbo Season 4 Episode 18 (June 26, 2019) – Find the others: Apollo 11 and the making of culture
This episode isn’t flagged as an episode about systems or systems thinking, but that’s really what this telling of the story of going to the moon is all about. We watch the Space Race grow out of the wreckage of the Second World War and unfold across a network of more-and-less-and-un- expected connections within the complex adaptive systems of science, science fiction, culture and politics. I loved it.
This is a great episode of Econtalk. Bertaud uses labour markets as a lens for thinking about cities. Helpful examples of emergent order and the challenges (impossibility?) of planning in complex adaptive systems.
Highlights (coming up) include:
- Discussion of the importance of culture and context in how cities develop;
- Bertaud’s explanation of his broader-than-usual understanding of labour markets;
- When planning and regulation is helpful and when it’s damaging;
- The trade-offs made by new arrivals in a city (and the danger of planners trying to decide these for them);
- The way that property markets can turn development costs into opportunities.
Some ideas for strengthening your connections within a group of people or scene:
- Have good, generous intentions. Show up to serve or share where it’s needed and wanted and because being part of this network is its own reward (you like the people, you like what they do), rather than for what you might get out of it.
- Start small – person by person. It’s helpful to think of the group as a network of people rather than as a a monolithic whole.
- Relationships and trust take time – but the right group settings or events can speed this up.
- First impressions always count – but not nearly as much as what you do and say consistently over time. People who know and trust you will interpret you generously and shrug off the clumsy mistakes that we all inevitably make as just that – understandable, human clumsiness. People who love you will stick with you through your real mistakes – the ones where you should have known better.
- Build on connections – friendships, relationships – that you already have.
- Lots of loose connections are helpful – relationships where you know them a bit, they know you a bit, and you share a general positive regard for each other. Each loose connection is like a single hook-and-loop in a piece of velcro – weak on its own, but strong when combined with many others. (see also: gecko feet)
- … but the 80/20 rule will be at work here – a few people will be very interested in your contribution, and a few of those will be people you have a good rapport with… and a few of those will be key for helping you to connect with others.
- Don’t worry too much about people who aren’t that interested in you or what you have to offer: they’re either genuinely not interested, or have something else on their minds, neither of which you can do very much about. Assume that you can’t do too much to influence them (apart, perhaps, if you can help them with their thing, the thing that’s on their minds) – but they might be influenced by the right sort of champion from within the network.
Problems gain (or lose) interestingness as their context and scale changes.
Take teaching a kids to read as an example. It’s almost inevitable that a child will learn to read given the following ingredients:
- A supportive family
- A strong reading culture at home
- A steady supply of good books
- A reasonable curriculum or methodology for teaching
- An well educated, motivated teacher (who could be a parent) who cares about the child who shows up consistently
- A safe, relatively comfortable, relatively calm environment
- An absence of specific learning difficulties
These factors form a strong, mutually reinforcing (and robust and self-repairing) network/system that makes learning to read more a matter of process than a problem, per se. If one or two of these ingredients are weak or missing, strength in another area will probably make up the difference. The outcome (learning to read) might take a bit more time, but it will happen.
But the more ingredients that are missing from the system – the looser or weaker the network – the harder (and more interesting) the problem becomes. It’s no longer a case of due process, but of finding a path and doing something new.
To be continued…
My first post about The Onion looked at interesting problems as systems of networked sub-problems, and suggested that our solutions will mirror this structure.
The Onion is also a good metaphor for the process of finding practical solutions: we work from solving the smallest problems in theory, outwards to technical solutions, before we finally build a (networked system of) practical solution that works consistently and at the scale we need.
1) Theoretical problem – theoretical solution
First we work out how – in theory – the problem might be solved. This might be a simple case of gathering information, because the theoretical problem has already been solved – as in the case for all the three problems above.
If the problem doesn’t yet have a theoretical solution, we’ll need to break the problem into smaller pieces, work out what’s missing, and treat the smallest unsolved piece as a new interesting problem. (see the example above: family health)
2) Technical problem – technical solution
Once we have a theoretical solution, the problem becomes a technical one: how do we apply the theoretical solution in the world, in this context, to make the solution actually work? The old saying about the difference between theory and practice holds true here. When we attempt to put our theory to work in practice we uncover buried assumptions and dependencies that make our theory impractical without major revision or lots of additional work to create the conditions in which it will work. So we have a choice: modify the context enough to make the theory work, or modify the theory to better suit the context. Often we do both.
Example technical problems:
Yikes, how to do I reduce the number of horrifically-bad-for-you things that my family eats on a regular basis?
In our context, what does a healthy diet look like?
Given that I can’t source organic kale in my neighbourhood, what are the alternatives?
How do I make kale-alternatives delicious?
Which components of a healthy diet are easiest to add to what we already do?
What habits can I encourage that will make it easier for my family to eat healthily?
3) Practical or scaleable solution
This is often the most overlooked part in solving an interesting problem: what is the ‘wrapper‘ of infrastructure and activity necessary to make the technical solution workable on an ongoing basis.
This is usually about the collection and coordination of scarce resources (time, money, people, other inputs) that are needed to solve the problem reliably.
This post is a sketch of a way of thinking about how problems work, and what we need to do to make our solutions (“the change we seek to make”) effective. It’s bit abstract – I’ll share a more concrete illustration in a later post.
We often talk about interesting problems as if they’re discrete units:
- How can I keep my family healthy?
- How can we split the atom?
- How can we help more children learn to read?
But all interesting problems really consist of little clusters or bundles (or networked systems) of problems – we just can’t always see what the problem-network looks like until we’ve spent some time working in it.
We can work our way down the problem hierarchy, reducing complexity as we ask smaller (and usually more easily solvable) problems.
Example theoretical problem:
How can I keep my family healthy?
What is a healthy diet? How can I make sure my family has access to it? How can I make sure that they eat it? What foods do they need to avoid, and how can I make sure they do?
What’s a healthy level of exercise?
What about emotional health?
In lots of cases, the sub-problems have sub-problems… and so-on.
We can also work our way further out too, from micro-problems to macro – for example, “How can I help other families to live healthier lifestyles?”
So we end up with a multi-layered set of nested-problems – ‘the onion’. And effective solutions will mirror this structure of solutions-within-solutions, with each layer creating the necessary conditions for the layers within it – more on this in an upcoming post.
*see also: the wrapper
This is a great introduction (or reminder) about emergent order in the complex adaptive system that is the economy.
If you haven’t thought much about economics, this series from the BBC is a first-rate introduction to a lot of key ideas about how markets work.
Each episode is about ten minutes long and features at least one interesting, often entertaining and sometimes surprising ‘thing’ to illustrate fundamental principles of economics.
There are lessons galore about how technologies take off and spread, change culture, transform the environment (human and physical) for both good and ill, and the unpredictable nature of emergent order and complex adaptive systems.
Seasons one and two are here at the BBC, and downloadable free wherever you get your podcasts.
There’s also a book (amazon).
Tim Harford is great – The Undercover Economist and More or Less (also on the BBC) are well worth checking out too.
Planning is essential in education, but it’s easy to fall into the habit of treating your session plan or presentation as a set of inputs for a machine: “If I do these things, and introduce this content, and prescribe this activity, this learning will result.”
But we know that groups of people, and especially groups of children, don’t work so predictably. The ‘perfect’ lesson plan a classroom is a Russian doll of one set of complex adaptive systems inside another inside another:
- The rapidly developing minds of children or teenagers…
- Nested in expectations and the social structures and groups-within-groups of kids-at-school culture…
- In the classroom culture shaped by a particular teacher – who is themselves a complex adaptive system of body, thoughts and emotions…
- Interacting with the wider culture of the school…
- All interacting with cultures local, national and international…
- And influenced by what’s going on at home, the weather, what they had for lunch…
In the face of this complexity, the first thing to do is recognise that what happens in our classroom is beyond our control, at least in the mechanistic sense of the word. Trying to impose precise control – of learning outcomes, of students’ behaviour – is a recipe for frustration and disappointment, if not damage.
The second thing is to start thinking about teaching and classroom management in terms of disposition and influence (and teachers can have a lot of influence):
- How can I make it more likely that the people I teach arrive on time and ready to learn?
- How I can I increase their disposition to be kind to each other, or to love this subject and to work hard?
- How can I make it more likely that they’ll do X, rather than Y?
Go to work. Take responsibility. Do the hard work of building a classroom culture that gets your students where they want to go (hint: you might have to start by showing them where it’s possible to go).
But don’t beat yourself up the next time it snows, and the lesson plan goes out the window as the kids pile up against the window to watch the world turn white.
A butterfly must have flapped its wings in New York.