Thursday, March 15, 2007

Complexity for Regular Folks, Part 2

Well, i had this post half written, lost my connection to the internet and lost the whole thing. So, this is the second necessarily shorter version... And i am not an expert in any way, so if you have additions or corrections to this, please send 'em along.

Atractors and scalar invariance.

Attractors are the simple rules that determine the direction of a system, its stability, its general trend. There are three groups of attractors: single point, periodic, and strange.

Single point attractors pull the energy of a system to one point or goal. A magnet is one good example of a single point attractor. If you sprinkle iron filings or some pins on a peice of paper and then put a magnet underneath it, the filings and the pins will be drawn towards a single point--the magnet. Another example, from palaeontology (for my kids): Many of us have seen films of palaeontologists working to remove massive chunks of stone--everyone on the dig site is drawn towards the work, lends shoulders and hands to move the boulder. All of their energy is directed towards a single goal--removing the rock. Systems governed by single point attractors tend to produce heroic model management.

Periodic attractors oscillate between two points. We have many experiences of periodic attractors, seasonality in employment, rush hour, and the most common--breathing.
We can cope with and benefit from systems governed by periodic attractors. We can get clarity from goals based on our knowledge of the oscillation. And we can recruit and train heroic model leaders with skills in anticipating and navigating the fluctuations.

Strange attractors were first described in the 1960's by Edward Lorenz (Lorenz attractor and graph) as he puzzled out the mysteries of the weather. While local weather patterns seemed completely unpredictable, when Lorenz modelled more global weather data on a computer, an interesting regularity appeared. The equations consistenty produced graphs in the shape of butterfly wings. At a larger scale, there were obviously rules at play that produced a predictable pattern. What those rules were, however, was difficult to tell, hence the name strange.

Complex systems are shaped by strange attractors that can be governed by a few simple rules. For example the movement of flocking birds is governed by three simple rules: stay equidistant from your neighbour and other objects, maintain the same speed as your neighbour, head toward the centre of the group. These simple rules allow a flock of birds (or fish or bees) to be 50 times more sensitive to changes in their environment than any one individual. (So complex systems are not well suited to the heroic leadership model. They are governed by interdependence, and so need a more interdependent style of leadership.)

So, to recap, strange attractors affect the flow of energy in complex systems. Strange attractors are comprised of a number of simple rules that interact with one another to produce the visible results we can observe. Discerning what these rules are is supported by certain attitudes and behaviours that Westley et al delineate--and that i will chat about in another post (hopefully also drawing some links to Spiral Dynamics).

So what is scalar invariance? Scalar means scale, or size. Invariance means not variable, unchanging. So put together, scalar invariance means that complex systems tend to act the same whether you are looking at only a few individuals (the micro level) or a mass (the macro level). You can extrapolate the simple rules governing the attractors of large systems by looking at the parts of those systems. In very simple terms, you can see the whole in the parts. As Blake would say, "the world in a grain of sand."

Both of these characteristics of complex systems are important to those wanting to effect social change. Identifying the strange attractors, and then looking under the surface to find the rules governing the attractors will have more leverage than attacking the surface characteristics. And scalar invariance means that local knowledge and expertise can effect change with global impact. And that small-scale efforts and experiments

Which leads us to one last concept from chaos science: complex systems are highly dependent on initial conditions. I am linking this to concepts from Aikido. In Aikido we have a very simple math. All systems have an energy of 10. If someone is attacking you with a force of 7, you only need to respond with a force of 3 to complete the system. In dealing with complex systems, the attractors hold a lot of the energy of the system, so a small input of energy at the right place and time can have significant results on the outcome.

There is good news here for those of us looking for ways to influence change. No guarantees, but lots of possibilities.

There is a lovely little animated game using attractors that you can play over at thecleverest.
Strange Attractor equations and graphs.
Formal definition of attractor.
Interesting discussion with illustrations of the four attractors of chaos science with speculative parallels to consciousness.
Some very cool 3-D images of attractors and other fractals.
Good next step for those wanting more information on attractors and complexity theory: Attractors Everywhere.

Next: a few more additions to our growing list of skills and attitudes for thriving in complexity.

Wednesday, March 14, 2007

On hosting meaningful conversations

I am busy preparing a training manual on public speaking and public conversations for non-profit staff and volunteers. So, i have been musing a bit this morning on why i love facilitation when it is about hosting meaningful conversations.

What arose for me today was depth. I love asking the questions and holding the space for the questions that lead to depth. That let us get beyond the surface to the complexity that always is present. And i love it when that complexity gets unpacked, unfolded out in all its brilliance and unknowability. I love it when we get to a level of complexity where we must act out of the essence of who we are and not merely from what we know.

Friday, March 02, 2007

Complexity Theory for regular folks- pt 1

The subtitle for this post should probably be: And why should i care anyway??

Authors Brenda Zimmerman, Frances Westley and Michael Quinn Patton give a compelling and highly readable answer in their new book, "Getting to Maybe" (Random House Canada, 2006). The other really cool thing about this book is that two of its authors are Canadian. Woohoo!

The short answer to why care about complexity: because it's how the world works and perhaps more importantly to many of us--it's how little old us can change the world--from where we are--NOW.

I have been working away in my brain on a blog post about working on the edge. And the edge i have been working on is all about complexity. It is the rub i find everyday in my conversations with leaders of organizations, with other consultants and with my friends and neighbours. Most of us have been taught skills and conditioning to help us thrive in a complicated world. Those skills are all about organizing, managing, and controlling. We are increasingly frustrated when these skills don't produce the results we are looking for.

In my work and in my life i am constantly communicating that the world has changed. We now live in the midst of complexity. And that calls for a very different skill set. A skill set that is often at odds with the way we have worked and lived in the past.

Over the next little while i want to share with you some of the skills, competencies, and mindsets (and reactions to them) that i am seeing emerge. I will also share the insights i am gathering from reading , "Getting to Maybe". And i will try to make the science behind complexity theory accessible to those of you for whom the words strange attractor, iteration, fractal, and scalar are seldom found in your recreational reading.

To begin, the number one reaction i see when folks start to explore working in ways that meet the demands of complexity is fear. This fear can manifest as resistance, hostility, anger, disbelief, mistrust. I believe that the fear has two main sources: certainty and grief.

What do I mean by certainty? When we make decisions, we like to feel that we have based them on an adequate amount of data that we can trust. When working with complexity, we often have to make decisions before we have that perfect data--in order to benefit from emerging trends and patterns. This can feel very uncomfortable--like leaping from a ledge without knowing what is below you. Even if the jump is a relatively short one, we all want to know that we are going to be okay--and that is something we can't know until we've landed. Some skills to cultivate: comfort with risk, ability to function with paradox, flow, letting go, intuition, pattern seeking, trust.

What do i mean by grief? In the past few months i have had the chance to learn a lot about grief--especially about grief as it is experienced by children. And of course, we are all children. What i have learned is that change, ALL and ANY change evokes the grief response. Think about that. In all change there is a loss--even if there is also a gain. Now consider the pace of change in the past 30 years. Birgitt Williams says, "there is always grief in the room". What does grief look like? Resistance, denial, anger, depression. When folks begin to understand that clarity is no longer possible (replaced by more relative qualities like discernment) and that paradox, risk, and flow are the new names of the game-most of us are looking at a truckload of loss. Some skills to cultivate: compassion, openness, letting go, resting down, faith in others and self.

So what are the new skills, attitudes and competencies for living in a complex world? For starters, as Westley et al state, "Getting to maybe has almost nothing to do with certainty and everything to do with serendipity, conviction, risk taking, and faith." Not very popular words in the offices of the world.

I hope together we can explore more of these new ways of thinking, living, working--being--over the coming weeks and perhaps generate a great resource for us all.

In the next post i will take a look at some of the jargon of complexity. Strange attractors, and scalar invariance. And why would you care? Because attractors are the tipping points of the system and scalar invariance helps you spot patterns at the micro level that can promote change at the macro level. Can't wait, can you ;)