Complex Systems Design Overview
Channel: Systems Innovation
Date: 2014-12-16

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A brief overview to the area of complex systems design & engineering, discussing the key feature to this alternative paradigm with examples. 

Before we talk about the design of complex systems let’s start by thinking a bit about design itself and our traditional approach to it. Design and engineering are very broad and fundamental human activities and there are a lot of different definition for them, but at the heart of many of these definition is design as a process.
That is a process where we conceive of an original or improved solution to achieving some desired, optimal end state; we then identifying the set of factors and constrains within the given environment and lastly developing a model for the arrangement of a set of elements to achieving this desired end state, that is the design.
Thus whether we are engineering a bicycle, new production process for our factory or designing some health care service, we can say design is about the arrangement of elements within a system in order to achieve some optimal global functionality. Within engineering this optimal functionally is typically talked about and quantified in terms of the systems efficiency.
A design paradigm them is an overarching approach that consist of a set of basic assumptions and theories about how the world we want to engineer works, coupled with a complementary set of principle and methods with which to approach this design process.
Like many other areas our modern engineering paradigm inherits its theoretical foundation from modern science and in particular classical physics. A key method employed by both is that of reductionism.
Reductionism holds that a complex system is nothing but the sum of its parts, and that an account of it can be reduced to accounts of its individual constituents. The reductionist approach results in a vision of the world that is made up of isolated components that interact in a predetermined linear fashion, what is sometimes called the clock work universe, as when we put our reductions goggles on everything starts to look like little deterministic cog in a vast machine.
Thus the reductionist approach applied to engineering results in the decomposing or breaking down of whole systems into discrete components, that can be isolated and modelled using linear equations. The overall functionality of the system is then achieved by defining an
￼overarching top down plan as to how all these component fit back together.
In order to achieve this overall functionality of the system it is important that the elements can be constrained, that is to say they are relatively static and their behaviour can be predetermined and thus controlled.
The reductionist approach has worked well in the engineering of bridges, airplanes and skyscrapers, these systems are designed to be and we want them to be, stable, predicable and reliable. Reductionism works well when we are dealing with systems with a low level of inter-connectivity and inter-dependencies, where the components are static, controllable and the environment relatively unchanging.
But what happens when this is not the case? when we have to design information systems where the components are highly interconnected and interdependent, when we have to build sustainable cities with multiple stakeholders that all have their own agendas, or infrastructure systems that will have to operate in a changing uncertain future environment created by climate change.
In this case our basic assumption or design paradigm has to shift to one that is more focused upon the connections that integrate diverse components into systems as opposed to our traditional component based paradigm and this is where complex systems design comes in. So lets talk about the key features to this new design paradigm, all of which will be major themes through out the rest of the course.
Firstly complex systems are open systems; In traditional design and engineering we are dealing with things like chairs, bridges and buildings they have well defined boundaries, we can fully control all the elements within these boundaries and fully design the system, this makes them orderly and predictable.
With the design of complex systems what we are dealing with instead are open systems, think of electrical power grids, cities or the internet itself, a massively modular, distributed system, it has no defined boundaries, people and devices couple and decouple from the system, it is not random, but this world of complex systems in not so orderly it is to uses the catchy phrase “edge of chaos”, no one is in control and no one fully understands or can fully design these open systems.


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