At the eleventh hour – just in time – in the dying, last-gasp seconds…
Find a way to ship.
At the eleventh hour – just in time – in the dying, last-gasp seconds…
Find a way to ship.
No doubt your organisation has lots of moving parts, many of which are specific to what you do.
But it’s probably also made up of generic components – accounts and inventory management, conditions of employment and contracts, safeguarding policy and procedures, communications manual – that you could drag and drop into another organisation with a bit of customisation.*
We have some way to go to good documentation at Saya Suka Membaca, but we’re getting ready to share them.
Let me know if you know any groups have good versions of these things and is sharing them… ideally bilingual in English and Indonesian!
There are only a few here, but it’s a start.
*See also: Easier tomorrow
Okay, so machines are simple, largely linear, and predictable, and systems are complex, adaptive and ‘dispositional’… but look a bit closer and the distinction gets blurry.
Most systems (individual people, markets, forests to name three) are combinations of sub-systems that are, at the end of the day, made up of simple units. And our machines – especially digital ones – are increasingly complex and interconnected. Even our simplest machines don’t really stand alone – they’re outgrowths of human activity, the product of networks of ideas, activities and resources that allow them to develop, grow, and – if they’re not maintained – fall into obsolescence and decay.
Kevin Kelly calls this the techium*, and describes it brilliantly in What Technology Wants:
Once [19th century economist Johann] Beckmann lowered the mask [of technology, by uniting various arts and sciences under the term technologie], our art and artifacts could be seen as an interdependent components woven into a coherent impersonal unity.
Each new invention requires the viability of previous inventions to keep going. There is no communication between machines without extruded copper nerves of electricity. There is no electricity without mining veins of coal or uranium, or damming rivers, or even mining precious metals to make solar panels. There is no metabolism of factories without the circulation of vehicles. No hammers without saws to cut the handles; no blades without hammers to pound the saw blades. This global-scale, circular interconnected network of systems, subsystems, machines, pipes, roads, wires, conveyor belts, automobiles, servers and routers, codes, calculators, sensors, archives, activators, collective memory, and power generators – this whole grand contraption of interrelated and interdependent pieces forms a single system.
When scientists began to investigate how this system functioned, they soon noticed something unusual: large systems of technology often behave like a very primitive organism. Networks, especially electronic networks, exhibit near-biological behaviour.Kevin Kelly – What Technology Wants (amazon)
In our organisations, this way of seeing helps us to think about the machines we buy buy of the networks of activity and supply that are necessary to maintain them and run them well – a way of thinking that’s probably automatic in the manufacturing and computer industries, but comes far less naturally in the social sector.
Something as simple as buying a new computer or printer isn’t just that simple. It’s introducing a new organism into an ecosystem, and will require our teams to do the work of acclimatising and adapting to make it really useful. The more complicated or relational a technology is – social media being a prime example – the further the adaptation and unintended consequences go.
*as distinct from specific technologies
The water breaks through because upstream – far enough up that there isn’t any stream – there’s a drip, drip, drip.
Enough drips to puddle, to pool and start to trickle and then to run: a rivulet, a stream to cool your feet in.
Further on* lakes, rivers, waterfalls, floods, torrents to burst banks and blow your socks off.
All it takes is gravity, time, and enough drips.
*in no particular hydrological order
A ‘system’ is an interconnected set of elements coherently organized in a way that achieves something. It is more than the sum of its parts: a body is more than an aggregate of individual cells; a university is not merely an agglomeration of individual students, professors, and buildings; an ecosystem is not just a set of individual plants and animals.
A defining property of human systems is complexity; because of the sheer number of relationships and feedback loops among their many elements, they cannot be reduced to simple chains of cause and effect. Think of a crowd on a city street, or a flock of starlings wheeling in the sky at dusk. Even with supercomputers, it is impossible to predict the movement of any given person or starling, but there is order; amazingly few collisions occur even on the most crowded streets.
In complex systems, change results from the interplay of many diverse or apparently unrelated factors. Those of us engaged in seeking change need to identify which elements are important and understand how they interact.
Unfortunately, the way we commonly think about change projects onto the future the neat narratives we draw from the past. Many of the mental models we use are linear plans – ‘if A, then B’ – with profound consequences in terms of failures, frustration, and missed opportunities [when the plan is thrown out by unexpected consequences within the plan, or by things that were never in it]. As Mike Tyson memorably said, ‘everyone has a plan ’til they get punched in the mouth.’
Let me illustrate with a metaphor. Baking a cake is a linear, ‘simple’ system. All I need to do is find a recipe, buy the ingredients, make sure the oven is working…
Baking a cake is also a fairly accurate metaphor for the approach of many governments, aid agencies, and activist organisations. They decide on a goal (the cake), pick a well-established method (the recipe), find some partners and allies (the ingredients), and off they go.
The trouble is that real life rarely bakes like a cake. Engaging in a complex system is more like raising a child. What fate would await your new baby if you decided to go linear and design a project plan setting out activities, assumptions, outputs, and outcomes for the next twenty years and then blindly followed it?
Deng Xiaoping said, “We will cross the river by feeling the stones under our feet, one by one.”Duncan Green – How Change Happens (amazon)
Think about it [systems thinking] through the lens of a new tech product, which is kind of the centre of what we do [at Andreesen Horowitz]… If you’re not a systems thinker basically you say “I’m going to build a really great product, and then I’m going to have a really great product, and it’s going to be great, because it’s a really great product.”
The systems thinking more is that that’s just the first step because it’s not just about the product. It’s about okay, now the product is going to enter into the marketplace, and there are going to be customers that are going to have a point of view on your product, and there are going to be competitors that are going to be trying to take you out with a better product. And you’ll put your product in retail, and the retailers are going to try to gouge you on price, and make your product uneconomic to manufacture, and the press is going to write a review of your product, and maybe the reviewer is going to have a really bad day and he’s going to say horrible, horrible things… and your employees are hard at work and they build the first product, and you assume they’re going to be with you to build the second product, and maybe they will, or maybe they won’t, because maybe someone else will hire them.
And so with any kind of creative endeavor, with anything we do in our world – and this is for products or for companies – they’re launching into technically what is called – there’s actually a mathematical term – a complex adaptive system – the world. And inherently it’s not a predictable system, it’s not a linear system, it doesn’t behave in ways that you can expect, kind of by definition. So they say “complex” because there are many, many dimensions and variables, and then “adaptive”, like it changes. Things change. So the introduction of a new product changes the system and then the system recalibrates around the product.
And so as a consequence, to launch a new tech product and have it succeed you have to have a keen awareness of all the different elements of the system. You have to have a willingness to engage in the entire system, and it’s a gigantic problem generally if you’re in denial about that, if you’re not willing to think in systems terms.Marc Andreessen on The Moment with Brian Koppelman*
*Full transcript here.
I’m a sucker for filling up spare moments with reading, listening, messaging. I like being in touch with people, and I love learning, so empty moments can feel like moments wasted.
But – and it’s a big but – it’s often in empty moments that your thoughts settle and clear. You make a connection between two thoughts, or have a new idea, or remember what it is you were really supposed to be doing today, or who it is you should be in touch with. You see the things around you more clearly.
You empty moments add value to your full ones by helping you to clarify, simplify and focus. And even if they don’t, they’re worth it on their own terms:
In people’s eyes, in the swing, tramp, and trudge; in the bellow and the uproar; the carriages, motor cars, omnibuses, vans, sandwich men shuffling and swinging; brass bands; barrel organs; in the triumph and the jingle and the strange high singing of some aeroplane overhead was what she loved; life; London; this moment of June.Virginia Woolf – Mrs Dalloway*
*Which I never thought I’d actually quote, and certainly not in an actual place.
In 1997 Watson’s precursor, IBM’s Deep Blue, beat the reigning chess grand master Garry Kasperov in a famous man-versus machine match. After machines repeated their victories in a few more matches, humans largely lost interest in such contests. You might think that this was the end of the story (if not the end of human history), but Kasparov realised that he could have performed better against Deep Blue if he’d had the same instant access to a massive database of all previous chess moves that Deep Blue had. If this database of tools was fair for an AI, why not for a human? … To pursue this idea, Kasparov pioneered the concept of man-and-machine matches, in which AI augments human chess players rather than competes against them…
You can play as your unassisted human self, or you can act as the hand of a supersmart chess computer, merely moving its board pieces, or you can play as a “centaur”, which is the human/AI cyborg that Kasparov advocated… In the championship Freestyle Battle 2014, open to all modes of players, pure chess AI engines won 42 games, but centaurs won 53 games. Today, the best chess player alive is a centaur. It goes by the name of Intagrand, a team of several humans and several different chess programs.
But here’s the even more surprising part: The advent of AI didn’t diminish the performance of purely human chess players. Quite the opposite. Cheap, supersmart chess programs inspired more people than ever to play chess, at more tournaments than ever, and the players got better than ever…
If AI can help humans become better chess players, it stands to reason that it can help us become better pilots, better doctors, better judges, better teachers.Kevin Kelly – The Inevitable
Yesterday’s post laid out several reasons benefits of understanding your organisation as a machine.* But many of the important parts of your organisation don’t behave in predictable or mechanistic ways. Your team’s culture, for example, is a affected by, for example:
In short, your organisation is a complex adaptive system within the complex adaptive system of the economy and the world as a whole.
Unlike complicated problems, complex problems cannot be solved, only managed. They cannot be controlled, only nudged. This is the domain of the butterfly effect, where a small change can lead to something big, and a big change can barely make a dent.Aaron Dignan
What this means is that trying to eliminate uncertainty or narrowly control outcomes is likely to be futile. Instead you need to ask which nudges will make your system more likely to produce good outcomes. You can think of projects and things you do as seeds with a chance of bearing fruit, and so widely – and position yourself to take advantage of opportunities that crop up in surprising places but seem to strengthen the system.
And as you think about the wider ecosystem and realise that you’re scarily dependent on ‘exogenous’ factors way beyond your control, you can think about how to nurture and protect the flows that you depend on, like flows of information or resources (including people and ideas) into and out of your organisation. How might building a network (for example) strengthen these flows, or tweak the system’s disposition in a way that’s in your favour?
*If you go deeper there are compelling arguments that even our machines are part of a living ecology – see Kevin Kelly‘s What Technology Wants and The Techium for jumping off point into this way of thinking