Tuesday, January 17, 2012

Network-centric approaches to transforming systems

I've recently been nutting the value out of a great approach for working towards a long term vision within a complex system.  The approach was described as a 'network-centric approach to transforming systems' by John Blackburn.

I can't find much online, but John presented at a Collaboratory Melbourne meetup last November - these words are necessarily interpreted and regurgitated.

Applying a network-centric approach

It was described mostly in terms of organisational vision and capacity, but the principles fundamentally apply when:
  • we have a broad-scale, long-term objective that requires systemic transformation (e.g. carbon neutrality)
  • the system is complex (one we can't fully understand the operation of)
Transforming complex systems is a challenge because our understanding of them is never good enough to fully predict the outcomes of our actions.  This is why detailed, linear change plans will never work for this sort of change.  Nevertheless, we might know where we want (or need) to get to.  The network-centric approach starts by determining the key characteristics of the future you want to create (but not specific details).

Some change required is relatively simple, despite a complex context - for example increasing school attendance.  Traditional top-down policy implementation does not solve these because the context is too complex for a one-size-fits-all approach.  Nevertheless developing and prototyping local solutions (e.g. a design methodology) can make good progress because the extent of change required is more modest.

When transformation is needed, however, we need to use the system to catalyse changes - the extent of change required is too great for simple solutions, no matter how ingenious or well resourced they might be.  John referred to this as a 'pull' approach to working towards a vision.  In an organisational sense it was like implanting 'viruses' which disrupted the system to shift it onto a trajectory better aligned with the vision.  It isn't possible to know exactly what any given intervention will do, but persistently intervening can transform the system in ways that no amount of 'push' will achieve.

In other systems this intervention will take different forms, but the principle is the same: understand the characteristics you're aiming for, and intervene in ways that will disrupt the system and align it with those characteristics.  For example, trees planted along the bank of a river may hold the banks in place, encourage other greenery and plant life, and clean the water - much of which may be impractical to be created by force.

Apply to the individual

The Power of Pull was referred to that evening, and while it bears little resemblance to the content of the talk (unfortunately), it reinforces what I had been thinking - our 'careers' are sufficiently complex to approach them like this.  It might seem like we are in control and that a linear planning approach will work - this may be the case for some people. But in a highly networked, ever changing and unpredictable world, where job opportunities are more likely to open up by chance than design, it just doesn't work like that.

In part, that's the philosophy underpinning my employment policy and the way I'm going about sorting out my future in general - like this blog.

But what intervention?

What John didn't explain well was understanding what interventions to make.  Just because the impact can't be predicted doesn't mean all interventions are the same.  I'm still trying to nut that out, but I think that's where things get messy, and the simplicity of the approach breaks down.  I can't avoid the need to understand the structure of the system (e.g. that trees are an integral component of the river ecosystem, but that the kangaroos, while important, are secondary).  Your choice of action is only as good as your understanding of the system.  On the upside, if you can map them out then complex systems can have relatively simple interventions (Berlow TED talk - short but fantastic).

A complex system graph.  Times like these I'm grateful to be a mathematician!

On the other hand, your understanding might depend on actually getting off your backside and trying something. I guess that means I should get going!

John Baxter

No comments:

Post a Comment