What is it that adaptive cycles could tell us about innovation? Which new perspective could they give us? Could they actually serve as a common backdrop, a “unifying field theory” that covers all dimensions of innovation? That could incorporate the relevant aspects of technology, business, and society? I’m curious to learn more about the ups and downs in human systems, and to find out whether there are phases when such systems are more responsive to change, more vulnerable to shock, or more receptive to innovation.
With that ambitious objective in mind, let’s take a very first basic look at adaptive cycles. As presented by Lance Gunderson and Crawford Holling in their foundational work on the transformations in natural and human systems, adaptive cycles essentially fall into four phases: growth, conservation, release, and reorganisation.
At this first glance, there’s not a lot to this concept. But as we dive into the descriptions of each phase, the utility of the adaptive cycles to explain the behaviours of complex adaptive systems will become evident.
Let’s start with the growth (or exploitation) phase. As the system overcomes the recent disturbances and settles into a new structure, it starts to absorb the available resources, experiencing a period of rapid growth. In this phase, the systems’ components are only loosely connected, and overall governance is weak. Success depends on the ability to adapt easily to a wide variety of conditions, and to get along well with the uncertainty and the lack of external guidance. The focus is on small geographical areas and fairly short time lines. The fledging system grows by absorbing more resources, while its interal structure and and the connections between its components evolve comparatively slowly. Judged from a distance, this period might seem as the calm after the storm, as the rapid growth occurs well below the surface.
The transition to the conservation phase comes gradually. The growth of the system through accumulation of resources continues, but the growth rate slows down. At the same time, but far less visible than the system’s growth, the interconnections between the components become tighter. This increasing connectedness results in stronger internal regulation and growing interdependencies between components, so that the system can operate more efficiently than before, but in a smaller range of conditions. This is a period of optimisation, in which the flexibility and variation of the growth phase are increasingly replaced with stability and rigidity. In the end, the system achieves near-optimal performance within very narrowly defined conditions. However, the associated loss of adaptability makes the system highly susceptable to external shock. All that it takes …
… to abruptly move to the release phase is a small trigger event, a disturbance that disrupts the interconnections between the components within the system. This disruption sends shockwaves through the system, shattering its stability, destroying its functionality, releasing the resources it had accumulated. This decomposition can occur very rapidly, taking considerably less time than the growth and conservation phases. But once the initiating disturbance runs out of steam, the decomposition of the system and the release of its accumulated resources will come to an end. In fact, “release” is a fairly euphemistic term for the level of destruction that is often perceived, especially in human systems, as the deeply disconcerting loss of the old certainty and order. However, release is the necessary precondition …
… for the reorganisation (or renewal) phase to occur. The transition from the release phase might again be very quick, in fact too fast to see them as two separate phases, but still: Phoenix must burn to ashes before it can rise again. After the destruction of the old, the new can take shape. There are only very few connections or constraints, but lots of resources: this is the time of invention and experimentation; the time when uncertainty is seen as an opportunity rather than a threat; the time when change is easy to achieve. Reorganisation is the phase of redefining the system, its function and boundaries. Such a reconfiguration might employ the same components, or only a subset, or some new components, or a combination thereof; but either way, the emergence of this new system is the beginning of another cycle, leading over to another growth phase.
These four phases define the adaptive cycle that complex adaptive systems go through. Now, the descriptions of those phases already indicate that this cycle is far from a smooth ride. On the contrary, the adaptive cycle is a genuine roller coaster, especially if you consider the speed of change. While growth and conservation are rather extended periods of gradual, slow developments, release and reorganisation are comparatively short periods of dramatic transformations. As Gunderson and Holling express it in their Synopsis:
Life proceeds through uneven rhythms of change
– slow periods of gradual change and sudden surprises.
This insight is essential for adaptive cycles in human systems like societies, business models, or technologies. No matter how much we’d want growth and (at least the beginning of) conservation to go on forever, they’ll inevitably come to an end, and we’ll go through release and reorganisation, whether we like it or not. Hence I am convinced that we’d better develop an awareness of where you are in the cycle, so that we can try to act accordingly. However, Gunderson and Holling give us an idea regarding the limitations of our sense for time:
Human problem solving seems better attuned to processes
that do not exceed the length of a human generation
and the duration of human institutional or cultural memory.
Here, the authors build a direct bridge to our innovation skills – that’s basically saying that we are blind to the (very) long-term effects our actions might have … This idea certainly merits some further consideration, but let’s park it for a while. Before diving any deeper I’d like to take a step back to see how much of the concept of adaptive cycles resonates with my earlier considerations on technology, business, and society as human systems. That’ll be the topic of the upcoming post …
Well ‘great’ minds. I have been looking at Adaptive Pathways
http://paul4innovating.com/2015/08/05/anticipating-disruption-by-preparing-adaptive-pathways-to-respond/
Thanks a lot, this offers good context.
I hope that I can identify some of underlying reasons that help decide which pathways are more promising than others. Awareness of your system status is only the starting point, there’s a lot more to explore …