Weeknotes Ten:6? – Ethics of Comfort Zones, Hard/Soft Everywhere

What’s your comfort zone?

We’re reaching End of Epic stage; that emergence from a strung out thought-converse-trial-show-repeat cycle over the last few months, stretching back into valentines and pancakes. Initial contexts remain documented like dusty photos. Assumptions have come and gone. Where you end up is a test of your old map, not your walking shoes.

Last week I was moving into ‘focus’ mode, which is that part of the epic just before the end game, when things either come together well, or blow apart like dandelion seeds. Fine line, making sure there’s the right amount of emphasis. No hard deadline except our own. From experience I know things can slip at this stage. I’m still learning to trust the team too – we’re playing with new approaches to UX. Things may be ok. But, rather safe than sorry. The hard part of being a hit pushy: you’ll never really know if being pushy helped or not. Like that bit with the vase, in that film. The Matrix.

Pushiness is an art I’m still getting my head around. Take 1-1s and mentoring, for instance. People have their comfort zones. But I’d wager all real, quality learning comes when you’re off kilter and outside your zone. Focuses the mind, makes you pay attention. Memories are formed in these moments that stick with you forever.

So there’s an ethical question there. How do you know how much to move people out of their comfort zone? How much is too much? Should you push for discomfort of you know it’ll benefit someone, but they haven’t agreed to it? Is it enough just to let them they’re supported?

Related note: Currently reading ‘Deep Simplicity‘ by John Gribbin on chaos and order. He uses the term ‘order on the edge of chaos’, relating to how Things (structure, abstractly) emerge from entropy, and how certain interactions within a system produce this emergence. Planets forming from gravitational wells. Life forming from chemicals.

I’m captivated by this. It seems relevant. That meeting point of influences, that ‘decisive moment’, to borrow from Cartier-Bresson. Isn’t this the subtle art of leadership – knowing where and when to act in order to produce effectiveness? And, just as importantly, when not to act. Know strength/yang, but maintain weakness/yin, says the Tao Te Ching. Push sparingly.

‘Deep Simplicity’ refers to this as catalysis, to draw on chemical reactions. An instigation, a point of interjection. Controlling the arm of time through a single elbow.

Related: a brief Twitter thread on how skills aren’t inherently “hard” or “soft”, but rather that skills can be carried out with harder and softer approaches, depending in need.

Steve Halliday posted:

Winner of the worst term in leadership award: “soft skills” No, they ain’t soft. They are people skills. They are business critical skills.

@SteveHalliday0

My follow-on thoughts:

Was thinking about it the other day, and about the overlap between code and team management. Couldn’t draw a clear distinction except that flesh is soft, and servers are hard. But where does that leave software?

It’s not that there is no “soft/hard” skill dichotomy. Maybe a yin/yang approach is more apt though, where “soft” = more passive, listening, and “hard” = active/doing. Both apply to all skills though.

Eg. Listening is “traditionally” thought of as “soft”, but actually you can have both soft and hard forms of listening.
Soft: Quieting the mind, being aware of the moment/situation/person.
Hard: Actively asking for feedback and eliciting questions/responses.

Whereas, say, software engineering might be a traditionally ‘hard’ skill? But…
Soft: Observing and understanding the flow of information and logic needed for efficiency.
Hard: Deciding class and interface names, setting spec in stone, making tests pass, fixing syntax errors.

Which is to say, softness/hardness is less to do with particular skills, and more to do with your own approach to whatever you’re doing.

An Unweeknote

Like meditation, weeknoting is something hardest to do when you most need to do it. The brain doesn’t work like that, and so we descend into spiralling into hell, with no way back from the dark.

OK, so it’s not been quite that bad for me. But I have stopped weeknoting, and mostly because I’ve just been busy on some biggish things. Life – in work and out – has had enough going on, and sometimes it’s totally fine to dodge the guilt bullet, and just not do something. So I took the weeknote pressure off and silently omitted it from my routine. I played games and saw people and sorted out hard drives and watched bad DVDs, like a normal person. Sometimes I wonder about my life. I’m not quite sure which version is real.

Anyway, the joy of a break in routine is that the time off often lets you see things differently. So a break can also be very valuable. Try it – if you practice anything like a musical instrument or a martial art, something involving physical memory, then take a week or two off – the body and brain can be truly wondrous at absorbing the practice you’ve done, and replaying fresh ideas to invigorate your routine. Absence makes the heart grow bolder.

A few things have bubbled up for me, in my absence. I’m planning on gradually writing them up, but possibly not in the usual weeknotes rhythm. So in good time, and soon.

How do we think about the datas?

Disclaimer: This is not thought-out blog post like you might find on the real internet. This post is fueled by a few extra hours of sleep, black instant coffee, and a general interest and enthusiasm for the data debate which I haven’t had in years. This is a post to sort out some of my own thoughts before being able to engage more fully.

I also really really liked the idea of writing a blog post in response to a blog post. It feels like 2005 all over again.

Context: Dan Barrett, UK Parliament’s Head of Data and Search, has posted a couple of posts about the difficulty of talking about data – part 1 and part 2, with ensuing Twitter conversation.

This gave me wobbly memories going 7 years back, when ‘open data’ was getting ‘hot’ and trying to find its way in the world. Self-interested plug: I went back and dug out my old post, “Open Data” needs to die to see if it was still relevant. Some of it seems to be, namely the need for context, the semantic quibbling that goes on.

(The idea of “agile data” is a new idea for me though – this makes a lot of sense for my own job, and has a rich depth waiting to be explored.)

Perhaps this bit from the old post gets at some of the difficulty:

Many people with useful, everyday data and databases really don’t think in terms of data. Because the data is about stuff they know, they think of it as “information”. Maybe even a “resource”. But ask them what “data” they have and they’ll probably give you a back-up of their website.

Is the term ‘data’ just too vague to be useful? If you had a magazine all about Data, then what would it cover? Databases, database design, relational data, non-structured data, data dumps, big data, personal data, data security, — yeh, even my eyes are glazing over with the word now. Would I buy it? No, probably not.

Does the word “data” need to die?

No – emphatically not. I think it does mean something to me, as a computer scientist engaged in data on a daily basis. It is the raw material that underpins everything I do. BUT it’s hard for me to say that ‘data’ is this, that or the other.

On a daily basis, data for me covers not just the stuff we make available on Local Insight, but anything we’ve decided to commit to a database for the purpose of structuring it, processing it, linking to it, etc. As a second order, I also consider all of our files to be data, just structured in a different way.

So maybe there are two ways that we think about data (and yes, I think a lot of the confusion is now just how we explain what data is, but how we make sense of the term. And this is, in a sense, just a semantic argument. But it needs to be a semantic argument if we’re talking about how to talk to each other). Two ways that often conflict with each other:

  1. Bits stored in computers. As in, 0s and 1s that give the computer something to do. Data in its ‘purest sense’. This is so generic it hurts, and yet it forms a useful distinction between analogue processing, which, let’s face it, is pretty much how humans like to think. “It looks like rain” is much easier to think than “It has 47% chance of raining.”
  2. Structured information. This is different to ‘pure information’ – it is taking the content that underpins information, and gives it structure – shape, consistency, and something predictable which allows us -and others – to work with it more easily. At this point, this stuff that sits at the point that information and data intersect has become the stuff of science.

This distinction is possibly useful because everyone has different backgrounds – data and computing and digital and tech are still really divided when it comes to skillsets aross society as a whole.

I don’t like putting people into one camp or the other, but broadly speaking, I think it takes fairly specialist skills to understand Data as #2, whereas having a vague idea of #1 is more of a default, and without that training, it’s easy to think of structured data as just 0s and 1s.

OK I’m out of words for now. I wanted to get this down as a thought-clear cos I think there are some really interesting questions coming out of it, and I also want to go back and re-read the other points floating around.