Opposing objectives

The front–loop of the adaptive cycle is very present in our daily experience, no wonder that it dominates our thinking as well. It’s the place where we are most comfortable, where we want to be. Continued growth and the accumulation of resources create an impression that all change is positive, that all change is progress: your business model is successful, the economy thrives, normal science is productive within the established paradigm, and society moves forward in harmony, … This is the change that we want, the change that we push. Why can’t that go on forever?

Well, Lance Gunderson and Crawford Holling point out that every complex adaptive system (and that includes the human systems I’m focusing on) develops through an adaptive cycle that has two distinctly different stages, a front– and a back–loop:

The front–loop stage is a slow, incremental phase of growth and accumulation. The back–loop stage is the rapid phase of reorganisation leading to renewal. The first stage is predictable with higher degrees of certainty. The outcomes following destruction and reorganisation in the back loop can be highly unpredictable and uncertain.

The front–loop evolves slowly over long periods of time, hence we have gained most of our experience –if not all– under these conditions. And because the front–loop remains predictable and generates growth it is a period that we simply must like. The back–loop on the other hand hits us unexpected, appears to be predominantly destructive, with highly uncertain outcomes, and we don’t have (a lot of) relevant experience. From a front–loop perspective, it’s hard to believe that this dark side of the adaptive cycle should be unavoidable or even necessary.

However, Gunderson and Holling consider that both stages are essential for any complex adaptive system. While the system grows and matures through the front–loop, it is the back–loop that allows the system to adapt. As a consequence, such a system actually has to handle two opposing objectives:

The first maximises production and accumulation; the second maximises invention and reassortment … The two different objectives cannot be maximised simultaneously; they can only occur sequentially. And success in achieving one tends to set the stage for its opposite. The adaptive cycle therefore embraces the opposites of growth and stability on one hand, change and variety on the other.

These two objectives are the trademark of complex adaptive systems. And that adaptability requires the ability to reinvent yourself in order to bounce back, it needs a capacity for experimentation, for trial and error, for creating and testing novel configurations until a promising alternative for the old system emerges. The back–loop is the time and space for such transformational changes: terrifying to many, but important to us all.

That still leaves the all-important question: How does all of this relate? The short answer is: it’s the interaction between efficiency and resilience that drives the adaptive cycle. The long answer takes a couple of steps: What we want – What we don’t see – What we need – How it works.

What we want

An established complex adaptive system goes through the growth and conservation phases of the front–loop. Especially conservation, i.e., the second half of the front–loop, is a maturation process in which the system parameters are well-known. In such conditions, further maturation is achieved by increasing the efficiency of components, processes, and their interactions. That invites optimisation as we know it in the business context or in technology development as well. And optimisation is enacted through defining (prescribing, standardising, norming, total-quality-managing, you name it …) the interdependencies between more and more parts of the system. The result of the desired efficiency gains is a continuously increasing connectedness within the system.

What we don’t see

Now, you might just shrug and say okay, the system becomes more connected, so what? The challenge, I’d respond, is that connectedness comes at an invisible price. First, every connection must be established and maintained, and that requires energy and attention, that ties up resources. So there is a natural limit to the level of sustainable connectedness. Secondly, and more importantly, a system with a finite number of components has a finite number of potential connections. When more and more of the potential connections are actually used to ensure the efficient functioning of the system, less and less potential connections remain available for alternative or back-up routes to iron out hick-ups and correct errors: the system becomes less elastic and more rigid. The system might still be quite stabile, and it doesn’t become fragile; but it develops an invisible brittleness. And the more rigid and brittle the systems grows, the smaller a trigger is sufficient to shatter the system: the bigger Goliath becomes, the smaller David can be. As the system lives grows and matures through the front–loop, it optimises all its internal interactions for efficiency. In the end, that system becomes a one-trick pony that perfectly performs the only trick it knows. At the same time, that system has become an old dog that cannot learn any new tricks. Regardless of your preferred animal analogy, such a system will fail in the face of novel challenges.

What we need

Entry: resilience. I’d define resilience as the system’s ability to maintain its core functionality even when exposed to external shock, the ability to bounce back: reshaped, restructured, redefined, but still able to perform. If you prefer, bounceback-ability as a less abstract, more intuitive term for the same concept. Resilience is the third dimension of the adaptive cycle (though not depicted in the lying eight), and it is the key to understanding the adaptive cycle. In fact, connectedness and resilience work in opposite directions. During the front–loop, we seek to increase potential (the vertical axis of the lying eight) by promoting growth. We accept the increase in connectedness (the horizontal axis of the the lying eight), but we do not see that resilience decreases at the same time (the hidden axis). Looking at the back–loop, we fear and loath the loss of accumulated potential (first axis), we see the reduction in connectedness (second axis), while again we don’t see the parallel increase in resilience (hidden axis). However, the restoration of adaptive capacity is the whole purpose of the back–loop. We need this increase in resilience in order to allow for the experimentation that ultimately ensures that the system can adapt.

How it works

The back–loop is triggered by an external event that exceeds the system’s ability to cope. It cannot deliver its full function any more. For as long as the triggering shock works, old connections within the system are destroyed, freeing up components and resources that had been tied up within the system. These components and resources become available to build alternative interactions. Resilience goes back up and experimentation is possible again. In these conditions, novelty shines through, many ideas and approaches can be tested. Many of those will fail, but the few that survive will actually start a new growth phase, seeking to absorb more and more resources, thus launching the next front–loop. This is the adaptive cycle moving between the two opposing objectives. And as Gunderson and Holling observed (see quote above): “Success in achieving one tends to set the stage for its opposite“. There is no end-state; a complex adaptive system will keep evolving. And throughout that evolution, innovation plays a role; or rather: innovation can play different roles, depending on the stage the adaptive cycle is currently in.

The roles of innovation

Most discussions about innovation are clearly situated within the front–loop: efficiency innovation and sustaining innovation – that’s what corporations focus on. But when you think about disruptive innovation, you’ll start seeing the back–loop as well. Disruptive innovation –as Clayton Christensen pointed out– is pursued by the entrepreneur who challenges the market incumbent. It’s the shock from the outside that sends the established system into the destructive part of creative destruction. And in the following back–loop conditions of trial and error, the challenger is far better suited to be creative and to prevail.

Innovation plays different roles along the adaptive cycle. Those roles exist in their own right, and it’ll be helpful for innovators to be consciously aware of their setting in order to pursue their goals successfully. I guess that’s yet another element of innovation literacy …