Lack of sustainability is, to a significant degree, the product of governance – our decision-making processes and structures favor non-sustainable outcomes. What does “sustainability governance” look like? The book Dynamic Sustainabilities (DS) has expanded my thinking about this.
The authors characterize traditional governance as “closing down” questions to conform to “planned equilibrium” thinking and an artificial world. What they propose is governance that “opens up” questions and actions to embrace more fully the challenges of a dynamic world. Well functioning Global Action Networks are governance arrangements that do this.
Particularly useful is a diagram the authors concocted titled “The Dynamic Properties of Sustainability”. Their basic argument is that we need governance structures that can address all four of the quadrants.
Most governance systems are designed to address shocks. Shocks come in two forms: ones with controllable (tractable) drivers such as fires that destroy buildings, that can be managed through “stability” responses such as building codes and fire response systems. Then there are intractable shock issues – ones that cannot be controlled. Some of these are episodic, such as floods that can evoke responses such as constructing dikes and restricting building on floodplains. The DS authors label these types of situations as warranting increased “resilience”: the problem can’t be eliminated, and ways must be found to live with it.
Our governance structures are much poorer at addressing stress issues – ones that arise over a longer period of time – in part because governments have election-cycle horizons. The DS authors distinguish between two types of action styles here, as well. One is with issues that require a durability response: they are controllable chronic changes, but where there is insufficient knowledge about how to control them. This is smog circa 1950. And then there’re the most challenging of all situations: those that require robustness. The development of an ice age is a good example of this – its drivers cannot be controlled, and responses require more fundamental change such as evacuating colder regions and changing crops.
This diagram very much reflects David Snowden’s one that describes “Sense-Making Domains” that distinguishes between simple-complicated-complex-chaos. Simple is associated with stability, complicated with durability, complex with resilience, and robustness with chaos.
The table arises from another one below that looks at the concept of “risk”. The insurance industry basically works in only one of the quadrants, labeled “risk”, where they have lots of data and well-developed frameworks to predict the occurrence of an issue such as a death (hence life insurance). We see that the government gets involved in flood insurance in part because the predictor models are weak although there’s lots of knowledge about (and experience with) floods.
To address smog required the development of conceptual frameworks to connect “dirty air”, “poor health” and emission sources. It required the development of impressive data sources and ways of measuring, tracking and controlling emissions. In the case of the ice age, there are enormous unknowns – theories abound (indicated by lack of consensual frameworks) and data (and experience) are sparse.
This all suggests that issues can evolve: for example, the smog issue moved from ignorance up to risk (hence lawsuits). The climate change challenge is facing this evolutionary crisis: can it move up to “risk” quickly enough?
The Role of GANs in Resilience, Durability and Robustness
So this is where Global Action Networks (GANs) come in. One of their seven core characteristics is “entrepreneurial action learners”. They work to “open up” issues by engaging diverse participants who have mutually challenging perspectives on an issue. Indeed, they reflect the five empowering design principles of the DS authors:
In the language of the DS authors, GANs are developing resilience and durability, and trying to transform robust issues into ones that can be addressed through one of the other action styles. Transparency International has taken the issue of corruption, and added both data and conceptual frameworks; the Global Reporting Initiative, the Global Compact and the Forest Stewardship Council are doing the same with their issues.
The DS authors work with four case studies, but they never do draw out governance lessons to the point of operationalizing. They take a bit of a detour into descriptions of “adaptive, deliberative and reflexive” governance – nice academic concepts, but again they don’t readily produce good organizing models. As well, I feel like their focus on “policy” solutions inhibits them.
Nevertheless, the book makes an important contribution. Its major point – that we need governance structures to address all types of knowledge situations if we are to address sustainability – is right on target. As they write: “’Sustainable solutions’ are thus those that offer stability, durability, resilience and robustness in specified qualities of human well-being, social equity and environmental quality.” Governments can’t do this, but the right governance arrangements can.