The perennial curmudgeon H.L. Mencken is famously misquoted as saying: “For every complex problem there is an answer that is clear, simple, and wrong.” The ability to simplify is of course one of our strengths as humans. As a species, we might just as well have been called homo reductor—after all, to think is to find patterns and organize complexity, to reduce it to actionable options or spin it into purposeful things. Behavioural economists have identified a multitude of short-cuts we use to reduce complex situations into actionable information. These hard-wired tricks, or heuristics, allow us to make decisions on the fly, providing quick answers to questions such as ‘should I trust you?’, or ‘Is it better to cash in now, or hold out for more later?’ Are these tricks reliable? Not always. A little due diligence never hurts when listening to one’s gut instincts, and the value of identifying heuristics is in part to understand the limits of their usefulness and the potential blind spots they create. The point is, there is no shortage of solutions to problems, whether we generate them ourselves or receive them from experts. And there’s no dearth of action plans and policies built on them. So, the issue isn’t so much how do we find answers?—we seem to have little trouble doing that. The real question is, how do we get to the right answers, particularly in the face of unrelenting complexity?
There’s a nomenclature in the hierarchy of complexity as well as proper and improper ways of going about problem solving at each level. This is presented in the new publication “From Transactional to Strategic: Systems Approaches to Public Challenges” (OECD, 2017), a survey of strategic systems thinking in the public sector. Developed by IBM in the 2000s, the Cynefin Framework posits four levels of systems complexity: obvious, complicated, complex and chaotic. Obvious challenges imply obvious answers. But the next two levels are less obvious. While we tend to use the adjectives ‘complicated’ and ‘complex’ interchangeably, the framework imposes a formal distinction. Complicated systems/issues have at least one answer and are characterised by causal relationships (although sometimes hidden at first). Complex systems are in constant flux. In complicated systems, we know what we don’t know (known unknowns) and apply our expertise to fill in the gaps. In complex systems, we don’t know what we don’t know (unknown unknowns) and cause and effect relations can only be deduced after the fact. That doesn’t mean one can’t make inroads into understanding and even shaping a complex system, but you need to use methods adapted to the challenge. A common bias is to mistake complexity for mere complication. The result is overconfidence that a solution is just around the corner and the wrong choice of tools.
Unfortunately, mismatches between organisational structures and problem structures are common. For example, in medicine, without proper coordination, two specialists can work at cross-purposes on a single client. While the endocrinologist treats the patient’s hyperglycaemia (a complicated system) with pharmaceuticals and diet, the nephrologist might treat her kidney failure (also a complicated system) through a separate set of pharmaceuticals and dietary recommendations. Not only can these two pursuits be at odds (what may be good for the kidneys may be bad for blood sugar, for example), but both treatments can have effects on other systems of the body that may go unmonitored. Understanding these interactions and those of each treatment on the body’s individual systems as well as on the body as a joined up, holistic entity (which it certainly is) would be the broader, complex and more desirable goal.
The body politic may not be so different. Institutions have specific and sometimes rather narrow remits and often act without a broader vision of what other institutions are doing or planning. Each institution may have its specific expertise yet few opportunities for sustained, trans-agency approaches to solving complex issues.
Thus, top-down, command-and-control institutional structures breed their own resistance to the kind of holistic, whole-of-government approach that complex problems and systems thinking require. This may be an artefact of the need for structures that adapt efficiently to new mandates in the form of political appointees overseeing a stable core of professional civil servants. Also, the presence of elected or appointed officials at the top of clearly defined government institutions may be emblematic of the will of the people being heard. Structural resistance may also stem from competitive political cycles, discouraging candidates to engage in cycle-spanning, intertemporal trade-offs or commit to projects with complex milestones. In a world of sound-bites, fake news and scorched earth tactics, a reasoned, methodical and open-ended systems approach can be a large, slow-moving political target.
And that’s the challenge of approaching complex, ‘wicked’ problems with the appropriate institutional support and scale—there must be fewer sweeping revolutions or cries of total failure by the opposition. Disruption gives way to continuous progress as the complex system evolves from within. It is a kind of third way that eschews polarization and favors collaboration, that blends market principles with what might be called ‘state guidance’ rather than top-down intervention.
Global warming, policies for ageing populations, child protection services and transportation management are all examples of complex systems and challenges. To take the last example, in the US, traffic congestion is estimated to cost households USD 120 billion per year and 30 billion to businesses (OECD, 2016). But where to start? With a massive infrastructure building spree? Where would you add additional capacity? How much would you invest in roads, and how much in pubic transportation? What are the relative advantages of toll roads vs increases in gas or vehicle taxes? What are the likely effects of gas price fluctuations and the onset of fleets of electric, self-driving cars? What about the technologies that have yet to be invented? And what will be the impact of policies on income inequality, gender equality, the environment and well-being? Finally, how do you efficiently join up levels of government and all the stakeholders potentially involved?
Complex systems are hard to define at the outset and open ended in scope. They can only be gradually altered, component by component, sub-system by sub-system, by learning from multiple feedback loops, measuring what works and evaluating how much closer it takes you to your goals.
General Systems Theory (GST), that is, thinking about what is characteristic of systems themselves, sprang from a bold new technological era in which individual fields of engineering were no longer sufficient to master the breathtaking range of knowledge and skills required by emerging systems integration. That know-how gave us complex entities as fearful as the Intercontinental Ballistic Missile and as inspiring as manned space flight. Today, the world seems to be suffering from complexity fatigue, whose symptoms are a longing for simple answers and a world free of interdependencies, with clear good guys and bad guys and brash, unyielding voices that ‘tell it like it is’, a world with lines drawn, walls built and borders closed. Bringing back a sense of excitement and purpose in mastering complexity may be the first ‘wicked’ problem we should tackle.
In the meantime, we need to find a way to stop approaching complex challenges through the limits of our institutions and start approaching them through the contours of the challenges themselves. Otherwise too many important decisions will be clear, simple and wrong.