Complex and complicated systems
What makes a system ‘complex’?
There is no agreement on how the word ‘complex’ should be defined, but there is wide consensus that complexity can arise in systems that have one or more of the following properties:
Many heterogeneous components at many levels
Examples include cities, companies, markets, riots, universities, the internet, airlines, and armies.
All the systems you have encountered so far have been described by diagrams with relatively few elements. Could these methods be used to plan and manage the railway system into London, the Health Service, or the business strategy of a multinational company such as McDonald’s or Facebook? These systems have millions of components and they have have many levels of operation. In social systems all the individual people are different, and often these differences matter. For such systems the data represented by system maps and influence diagrams have to be stored in computers. With millions of interactions, the consequences of multiple causes have to be investigated by computers.
Examples include gossip, epidemics, copying, banker networks, Facebook friends, motorways, and families.
One of the great discoveries that has come to fruition in the 21st century is that much human behaviour takes place on, and is largely determined by, networks. The 18th and 19th century theories of economics are giving way to a network view of socio-economic behaviour. For example, classical economics assumes that individual people make buying choices based on perfect information of the market. In practice, many people who want to buy a new phone, computer or TV simply ask a few other people in their social networks.
Examples include house prices, opinion polls, critical tweets, copying others, bank crashes, and trending tweets.
Systems thinking tells us of the importance of feedback loops. When many thousands of feedback loops interact the outcome cannot be investigated by a pencil and paper analysis. Instead a computer must be used.
Adaptation to changing environments
Examples include business, opinions, agriculture, retraining, and urban renewal.
The distinction between a system and its environment is fundamental in systems thinking. One extraordinary capability of ‘complex systems’ is that they can completely reconfigure themselves as they adapt to changing environments.
There are many other reasons for systems being complex. These include co-evolving subsystems, reflexivity where people respond to predictions by doing the opposite, sensitivity to initial conditions as illustrated by weather systems, and path-dependence where history matters.
Complex versus Complicated
Often a distinction is made between complex systems and complicated systems. To illustrate this consider a clock. The clock may have many heterogeneous components, and all its parts have to work together as a network structure, and the catchment mechanism provides feedback control. However, generally a clock does not adapt to its environment by itself. As you will see in the next section, clocks are designed not to be sensitive to initial conditions. Although clocks may be complicated systems, they are not usually considered to be complex systems.