What Could Complexity Theory Ever Do For Us?

By Orit Gal & Greg Fisher

Over the past few years, the spillover of complexity theory from the natural into the social realms has intensified, instigating a whole range of new theories and insights about the manner in which complex human systems emerge, behave, and transform.  But, with a few honourable exceptions, complexity theory has struggled to make the leap from the academic community into the real world.  Could policy makers use ideas emanating from complexity theories, to design and implement better policies? Or, to paraphrase Eric Beinhocker, could complexity evolve from a Sunday afternoon thought into a Monday morning action?

The Origin of Wealth by Eric Beinhocker

Complexity experts have produced a growing array of books and articles presenting the added value of analysing social environments as complex systems, be it new understandings into the behaviour of markets; the manner in which tastes and preferences are shaped through network effects; the indirect impacts of infrastructure development; or the optimisation of knowledge retrieval. However, as might be expected from any emerging field, much of this new knowledge is still structured from an R&D perspective rather than an end-user’s point of view, thereby potentially slowing down adoption, integration, and learning. Put another way, the complexity community looks rather supply-side heavy and demand-side light.

Curiously, the problem of bridging the theory-policy gap is much more acute with complexity theory than other approaches because complexity puts a great deal of emphasis on uniqueness, both in time and space.  Idiosyncrasies matter, which means that some policy adopted in one area might not be appropriate elsewhere; and a policy implemented now might not work in the future (in the same area) because complex human systems are constantly evolving (unpredictably).  However, far from saying policy is pointless, it means that policy analysis has to be differently focused and any outcomes better tailored to a dynamic environment.

Helping to create the bridge from the theoretical to the practical will entail an end-user’s exploration into complexity, i.e. the people making decisions, designing action plans and leading implementation. Given the impressive strides already made in the field, this short article aims to answer the following: given a policy maker’s perspective, what could complexity ever do for us?

Policy-making: between design and outcome

Reforming the NHS? Developing new growth strategies? Fighting human trafficking? Or contemplating military intervention? It would be hard to find policy makers who wouldnt describe their challenges as complex, comprising of seemingly endless interrelated elements, actors and uncertainties. At the same time, the mere acknowledgment of life as complex is rather futile. The real question is whether complexity theory can provide decision-makers with an actual toolbox for better dealing with their challenges. We suggest that complexity based methodologies can contribute to policy makers on three main fronts – redefining end goals; providing new knowledge bases for both background research and implementation; and supplying new tools for policy design.


  1. Redefining the aims of policy: traditionally, we tend to think of policy in terms of problem solving. Any social or economic challenge is viewed as part of a complicated machine that can be improved through careful calibration. At the same time, complexity science depicts our social system not as a complicated machine but as a complex ecology. Ecologies cannot be calibrated, designed or controlled as there will always be too many dynamic elements, uncertain relations and consequences involved. They can however be transformed. Hence, from a complexity perspective, the aim of policy is to transform a social or economic challenge rather than “solve” it. While this might seem abstract or merely semantic, it holds huge practical ramifications. When planning a solution to a problem, the planner must be able to present an end-state as well as the backward-engineering steps for achieving it. Alternatively, if the aim of a policy is to continually disrupt forces and trends making up a given problem through iterative interventions, it no longer requires a clearly defined end-state and a “proven” path of cause-effect relations. What it does necessitate is a systemic direction. Such a shift from problem solving to transformation opens up a whole new realm of policy options, some of which might have made much sense to policy makers in the past, but were deemed “un-proven” or merely intuitive. A complexity approach can provide new tools for supporting such ideas through new sources of knowledge and implementation tools.
  2. New knowledge bases: perhaps the most advanced area so far, complexity based research provides new means for collating and making sense of social information. Advances made in network research and ‘big data’ have set the ground for the development of new indicators and real time data mining. For example, assessing indirect policy impacts in urban development projects, simulating alternative growth trajectories, and following the dispersion of various health concerns. Moreover, together with smarter and more dynamic organisational structures, such new knowledge bases also provide policy makers with new tools for implementation. These include the ability to run multiple pilots and experimentations, create new platforms for outreach and participation, and assess real time feedback. In fact, without such tools the strategic goal of transformation cannot be operationalised. Used effectively, the new knowledge bases will allow policy makers the actual resources needed to persistently adapt their moves so as to continuously maximize impacts and minimize negative effects.
  3. New methodologies for policy design: if policy objectives are to be seen as transforming or disrupting existing challenges then the manner in which they are designed will need to incorporate new rationales and modes of operation. To date, while complexity insights have been incorporated into a wide range of social challenges, coherent methodological frameworks for strategising have been developed mostly within the military. For example, Operational Design has emerged out of the integration between complexity principles and architectural theories on structures and space, providing militaries with new practical tools for operating within current conflict environments. It includes a structured process for policy development, starting with information gathering, systems framing, detecting rationales for action and organising the forces’ operations. Unless equivalent, practical methodologies are developed for policy makers in the civilian realms, complexity will not enter the day-to-day workings of governments.

Overall, while we would like to think of policy-making as a rational problem-solving exercise, in which problems are analysed, solutions based on reliable evidence gathering are modeled, authorised and translated into effective end-results, we also know that real life policy-making is a messy and fuzzy process involving only partial knowledge, political bargaining, egos, pre-conceived positions, chance events and unintended consequences. To a large extent, policy makers seem to have inevitably accepted this chasm between rational modeling on the one hand and messy decision-making and implementation on the other – i.e. the inevitable friction between theory and practice. We believe complexity theory provides a foundation upon which this chasm can be bridged, providing policy makers with more genuine and dynamic means for successfully creating the social impacts they seek. Building on this foundation will now require the joint efforts of complexity experts and policy practitioners i.e. to bring the supply-side and the demand-side much closer together.


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