Building blocks and open source organisations

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.

Financial Management

  • Mango has some great resources for NGO financial management

Child Protection and Safeguarding

Organisational Health

*See also: Easier tomorrow

Machine. Ecosystem. (5) – Duncan Green on systems thinking and development

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)

Machine. Ecosystem. (4) – Marc Andreessen on Systems Thinking

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.

Mrs D: empty moments

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.

AI and us: Kevin Kelly on ‘centaurs’

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

Machine. Ecosystem. (2)

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:

  • organisational history;
  • personalities on the team;
  • individual moods;
  • collective morale;
  • Team members’ stage of life and health;
  • interpersonal chemistry or rivalry;
  • changes in team members’ salaries or position;
  • ‘near’ factors like the closure of a favourite neighbourhood gathering spot;
  • the health of the wider economy;
  • government policy;
  • levels of outside interest and flows of money into or out of your sector

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

Fruitful thinking

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

Double time

There is never enough time.

There are theories about why we’re so bad at predicting how long things will take: the planning fallacy, Brooke’s law (admittedly a variation on the theme), and my personal favourite, Hofstadter’s law:

It always takes longer than you expect, even when you take into account Hofstadter’s Law.

Others have written helpful things about how to mitigate this problem.* I propose a simple experiment: allow double the time you think you’ll need for all of your tasks in the coming week.**

Let me know how it goes.

*One of the more helpful approaches is to ask how long similar tasks have taken in the past.

**Not including tasks where you know how long they’ll take – in those cases, you’re not estimating.***

***If in doubt, though, you don’t know.

Vision. Positioning. Execution. (4)

Execution

Being able to execute means being able to get the right things done at the right times. Good execution is a combination of:

  • Knowledge – do you know what to do and how to do it? This is a type of vision, but I include here for completeness.
  • Skill – are you able to do it? Skills need to be learned and practiced, and intuition improves with experience.
  • Will – are you committed? Do you make things happen and get stuff done? Skill doesn’t matter if you don’t take action.
  • Performance – how well do you do your part? Do you make the most of what you’ve got?
  • Bringing people with you – who else is involved? Are they ready?
  • Luck – do things go your way?

The Key

Having a strong will – strong enough that you consistently act on it – is the most important of these. Unless you’re committed and determined and actually show up, make things happen and get stuff done – nothing else matters.

Vision. Positioning. Execution. (3)

Positioning

Being ready in the right place at the right time makes everything easier.

Sometimes you need to position yourself for a better view – to improve your vision – before you can position yourself to do. If you can’t see properly, you can’t decide.

Once you’ve got a decent view you can move to position yourself with respect to whatever’s coming, gathering the resources that you need and giving yourself enough time and space to use them.

Good positioning – creating time and space and being prepared – ends up looking like skill in execution, and it sort of is. It’s a skill of its own – the skill of making the most of what you’ve got.

The more I practice, the luckier I get

You can never see enough, never have all the information to be perfectly prepared – you do what you can with what you have. But the better your vision and positioning is, the better you’ll be able to respond to opportunities that come your way by pure, dumb luck.

Running to stay still

Once you’re in position, you might have to work hard just to stay there. Sometimes this is necessary – and keeping moving is almost always better than staying still – but if you find yourself having to run constantly just to keep up you might be playing the wrong game or need to think again about where the best positions are.

Some questions about positioning:

  • Where am I now?
  • Where do I need to be, by when?
  • How do I get there?
  • What’s my next step, and the one after that – and what will make it easier for me to take them?
  • What types of relationships do I need, and with who?
  • What skills and attributes will I need once I’m in position, and how will I develop them?
  • What resources?
  • What else do I need to know?
  • Who is in position already that I can learn from – or need to be cautious of?

(These are all questions about vision, too.)

Recording and editing with Audacity – start here

I had another go with Audacity this weekend and came across this tutorial for absolute beginners.

David Taylor‘s introduction is clear and systematic. He tells you everything you need to know to record, edit and tidy up audio in a little over fifteen minutes – fifteen minutes very well spent.

I like that it assumes no prior knowledge, covered everything you need to know with some nice details, and ignored the rest… and treats you as a beginner but not an idiot.

I’m convinced. My recent adventure went far better than my first try, and Audacity will almost certainly be my tool of choice for making the next episode – or prototype episode – of the DC podcast.

Thank you David!

P.S. There’s an reference in the video to Son of Citation Machine, which looks like a good resource…