The world is complex, meaning that there are countless agents interacting with each other in ways that are, more often than not, hidden from view – hidden connections. Their complex interactions lead to emergent behaviour rather than predictable outcomes.
But efforts to understand complexity have often relied on this assumption – that what is complex can be reduced to simpler subsets that are easier to model, and that when re-aggregated will produce results that approximate the real world.
Thomas Hobbes, one of the founders of modern political philosophy, argued that all phenomena, including human activity, could be reduced to bodies in motion and their interactions. This assumption gave birth to modern science. It led to the tendency to dissect the world and to favour explanations framed at the lowest level of scale – down to the atomic level, and even beyond, to quantum sub-atomic levels, to the Higgs Boson, the “god particle”.
This approach is called reductionism. It is rooted in the belief that complex phenomena can be analysed in component – and simpler – parts. When the properties of these parts have been analysed separately, it is then possible to understand the properties of the whole in terms of the properties and the interactions of these components.
Reductionism has been central to the revolution in scientific thinking. But despite the enormous importance of this approach, and its incalculable contributions to human progress, a critical shortcoming is that it diverts attention away from the complex interactions among the components in the system. This gives the false impression that investigating the organisational features of things at a holistic level is less informative than investigating the properties of the components.
The limitations of reductionist theory
Indeed, outside the realm of science, reductionism has not been as effective in explaining phenomena in such areas as ecology and economics. For example, the economist Paul Ormerod wrote that “in orthodox economic theory, the agents involved in any particular market … are presumed to be able to both gather and process substantial amounts of information efficiently in order to form expectations on the likely costs and benefits associated with different courses of action, and to respond to incentives and disincentives in an appropriate manner. … The one thing these hypothetical individuals do not do… is to allow their behaviour to be influenced directly by the behaviour of others … and their tastes and preferences are assumed to be fixed, regardless of how others behave.”
What Ormerod is saying is that traditional economics does not take into sufficient account the complexity of the real world. The foundational assumption – that agents or people behave in a rational way and are not influenced by the behaviour of other agents – does not explain the effects of complexity in today’s economic systems. Intuitively, we know that the contrary is true, that people are influenced by the behaviour of others. The herd mentality that drives markets into bull or bear frenzies reflects this condition. In the real world, taking terminology from complexity science, agents – people – are not independent actors. They are interdependent – interacting and influencing one another in complex and emergent ways.
The counterbalancing effect of complexity science
However, it is only quite recently that this reductionist bias has been counterbalanced by efforts to study the overall properties of complex systems. The sciences of the twenty-first century have begun to turn away from just focussing on micro properties. They are beginning to look at problems of complexity, acknowledging that the principles governing the properties of higher-level entities are often quite distinct and unrelated to those of the components that constitute them. The Santa Fe Institute was a pioneer in this approach.
Stephen Hawking said “I think the next century (the 21st century) will be the century of complexity”. New tools are needed to deal with this complexity. Conventional efforts to model complex systems, like the Club of Rome’s model of economic and population growth, have often gotten it badly wrong. They use mathematical formula to link parts of a complex system together, wrongly or naively assuming that these parts interact with each other in a Newtonian fashion, with clear link between cause and effect. Unfortunately, we now realise that complex systems defy such deterministic analytical models. Indeed, a real challenge is to discern when systems are complex, and when they are merely complicated.
Complexity science abjures reductionism for the study of how systems interact with systems, how agents interact with agents, and then how these lead to emergent rather than causal results. Complexity science tools include agent-based modelling, which examines how autonomous agents interact with one another and influence system behaviour. These tools, applied to economics and to other areas like urban planning, provide fresh useable insights that deterministic models have failed to produce.
The logic of horizontal collaboration
Horizontal collaboration is imperative for solving the big challenges of today.
Some of the biggest challenges that governments face today involve the emergent outcomes of complexity. They include wicked problems such as climate change, population and urbanisation. There are many stakeholders, but they have conflicting perspectives, different opinions and divergent interests. Please one and you upset many others. Solve one problem and another will arise.
No single government agency is really equipped to deal with such wicked problems on its own. Professor Scott Page of the University of Michigan, who was in Singapore recently, argues that diverse teams are better able to solve such wicked problems, because each person offers a different perspective, a different mental model, and therefore a different representation of the problem.
The exploitation of diversity in government as part of the process of tackling the wicked problems of complexity is analogous to breaking down academic silos in universities. In Singapore, we call this the Whole-of-Government approach.
However, the Whole-of-Government approach has to overcome the deeply-ingrained bureaucratic instinct to operate within silos, rather than horizontally across organisational silos. This is a big hurdle, because it requires a fundamental change of mindset, into a culture in which officers consider the spill-over effects of what they do and their impact on the policies and plans of other agencies. This mindset also requires a willingness among agencies to work together to achieve common outcomes.
This mindset is so important to good governance in a complex operating environment that the Whole-of-Government approach is a priority of the top leadership in the Singapore Public Service. Today, there are inter-agency platforms that have been established to share information among ministries, statutory boards and other agencies, in order to take in different ideas and insights, so that wicked problems can be viewed in their manifold dimensions. Coordinating bodies now deal with cross-agency strategic issues, like the National Climate Change Secretariat and the National Population & Talent Division.
The logic of breaking down silos extends beyond government into working with citizens to jointly understand and solve problems. For example, the Urban Redevelopment Authority recently held an exhibition of its 2013 Draft Master Plan to gather feedback from the public in order to fine-tune plans for Singapore’s urban development. The exhibition attracted about 2,000 visitors daily and was organised with a website and iPads to obtain public feedback.
Another example is Our Singapore Conversation, a year-long process involving more than 600 dialogue sessions and nearly 50,000 participants. This process surfaced fresh insights for government – and for citizens – such as the desire for broader definitions of success or greater assurance about health care and retirement, that would otherwise have been much more difficult to obtain.
Designing a new approach
The “design approach” is another way of dealing with complexity. It is not about fashion. The Singapore government is now experimenting with the design approach which puts its planners and policy-makers into the shoes of the stakeholders – in the people and private sectors – to gain better insights into the impact of policies and plans. The design approach, in which we think from the view of end-users, whether it is someone with disabilities or a mother with triplets, will help us better design policies and their delivery to the customer. I would argue that it is conceptually not dissimilar to interdisciplinary collaboration, and I would take this one step further and argue that its logic is rooted in complexity. This, collaboration with citizens and a continued push towards a Whole-of-Government approach towards solving wicked problems are what we need to tackle Singapore’s complex challenges.
Peter Ho is a Senior Advisor at the Centre for Strategic Futures, Singapore. This essay is an excerpt of his speech at the opening of the NTU Complexity Institute, March 3, 2014.
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