Attune to Timing and Flow

Principle 3: Attune to timing and flow

“An important aspect of complex systems, one that certainly complicates our understanding and modeling of such systems, is their temporal nature. Complex systems unfold in time, they have a history that co-determines present behavior and they anticipate the future. Moreover, as we know at least since the work of Prigogine, the behavior of complex systems is not symmetrical in time. They have a past and a future that are not interchangeable. This being ‘situated in time’ does not always receive adequate attention in our analysis of complexity.

The central notion at stake when we talk of time and complexity is that of ‘memory.’ Memory is the persistence of certain states of the system, of carrying something from the past over into the future. It is not merely the remembering of something in the past, as if belonging to that past, it is the past being active in the present.” – Paul Cilliers (2)

Time matters in human systems. The patterns we can observe today were shaped by the initial starting conditions of the system and many years of evolutionary change.

Complex systems can have causal interactions without being readily predictable. They also have dispositional states: their history and structure make some behaviors more likely than others. If we understand these dispositions and follow those ‘natural contours,’ the energy gradient for change is lessened.

An analogy I often use is elephant paths. There are two ways to design a garden or park. There is the ordered systems approach where we spend a lot of time and money up-front in the design: we survey the soil, observe the light, and design aesthetically pleasing vistas. When we finally open the gates to let in the first visitors, they almost immediately proceed to mar our beautifully designed gardens with elephant paths. Elephant paths, or desire lines, are informal paths that pedestrians prefer to take from one location to another rather than using a sidewalk or, in our case, the paved garden paths.

A more effective way to determine where our paths should go is to lay the lawn and then let people in and see where they naturally walk. We can then use those naturally emergent paths to guide us on where to put ours. Similarly, we can only really know how to intervene in a system once we understand the structure and dynamics of that particular system. That enables us to expend less energy in our attempts to create conditions for change. In contrast, recipe-based approaches waste much energy forcing solutions onto the system regardless of whether they fit the context.