Change, change, change!
So many clichés about change, so much ado about a big thing, so many ways to look at it and so many barriers to it!
And just so it’s clear: I’m talking about social change (see some pictures about this concept), i.e. change that involves humans and their behaviour, as opposed to changes in e.g. engineering or information systems.
The much desired and (our most loathed) change is at the centre of a lot of agile KM and also development work. We want to understand it, track it, make it happen, or stop it. As a formula. In a box. 100% fail-proof.
The bitter deceit…
Perhaps because we may be overlooking one of the most important dimensions of (social) change: it is the bizarre fruit of the dance of time and space along various factors. There is no direct and pure causality between activity A and change X. Complexity theories have helped us understand this intricacy. But not necessarily helped us find ways to address this.
Here’s a shoot post about a change management toolkit of sorts: Using hidden dynamics to realise how to look at and work around change, with four lighthouses on our journey: scaling, pacing, staging and patterning.
Social change has both roots and branches across space and time. Understanding scaling is a precondition to achieving change. What other geographic scales are at play in a change dynamics? What could be other beneficiaries or victims of change: other teams? Organisations? Projects? Communities? Districts? Regions? Think upstream-downstream, centre-edges, power groups/marginalised groups What mechanisms are intentionally or involuntarily titillating other scales? What are the tradeoffs and what is the aggregate ‘return on investment’ then?
Similarly, what could be long term as opposed to short term changes or effects? We tend to apply a tunnel vision to the scales we are focusing on, but understanding how a given initiative brings about change that affects people differently over time helps us get a bigger picture of the change we are looking at. This is at the centre of the reflection on time scales in social learning for climate change.
Of course we cannot predict all these changes, but joined-up thinking such as collective visioning exercises give us glimpses of these longer term changes… Don’t consider change without careful attention for scales.
Considering longer term effects begs us to examine the speed at which we hope change will happen and the one at which it really happens. As much as a common breathing pace brings people together, pacing activities according to the local context’s normal pace also raises chances for change – remember organic, civic-driven KM?. No need to rush, you might be leading the pack but no one may understand you. Going too slow on the other hand may jeopardise potential for change, time has to be just right. And our pace affects this…
No ‘intended’ social change happens overnight – unless by some miracle all elements are just ready for it and one extra drop takes care of it (ha! the results of edge effects Alice McGillivray is brilliantly talking about). So no change happens in a fingersnap.
And because of the complex interdependencies, no change is likely to happen at (extended) scale right on. Pacing helps us find the right rhythm of each activity, staging activities helps us align them. It gives us liberty to use effective safe-fail probes (more about that in the video below): We can thus explore how change happens in smaller iterations, using the feedback from each iteration to inform the next loop of activities. Like gardening, this is the key to let change grow and become part of the local fabric’s dynamics. Staging is the drip irrigation of change…
The last but not the least dynamic of the four, and for good reasons: The complexity of social change requires us to sharpen our senses and (ideally collectively) recognise patterns that make up change. Both in the centre of our attention and at the edges… With patterning we can identify the fractals of change, and by continually doing so we can recognise where in the bigger picture of change a certain fractal belongs.
How do you do patterning? Through learning conversations around a theory of change of sorts, and whether formalised or not, continually exploring the ramifications of that change.
In a lot of agile KM projects – and more conspicuously in a majority of development projects – we tend to zero in on specific changes induced by a given initiative. But we are chasing a fish pack and the way the fish pack shapes and shifts, moves and mixes, appears and disappears tells us much about that ever elusive change. Scaling, pacing, staging and patterning are instruments at our disposal to understand the fish better and, occasionally, to fish it better.
Since change might look like a shark, we might as well be apprehend it better, don’t you think?
Related blog posts: