It is very common for people to use the idea of a "system" pretty freely when discussing their ideas, projects, and problems . Alas, they often have a pretty fuzzy idea about what a system is and how that perspective can be put to work. "Systems Science" offers a concise definition of a system that is easy to contrast with traditional analytics. In this post I'd like to start at the beginning and try to create a clear mental image of what systems science is and how it provides useful insights.
Let's start by recapping the paradigm that we're all familiar with -- traditional analytics. Then I'll introduce the Systemic perspective.
Traditional analytics, from before the time of the Greek philosophers, is based on a reductionist principle. This is the idea that to understand a thing we decompose it into its constituent parts and then further decompose those sub-parts and so forth until we reach something that cannot be further decomposed -- the "atoms" of the system. This produces the familiar hierarchical tree structure that appears so often in our world and is the result of this process. The idea is that once we have the atoms figured out we can assemble them to understand how each level of the hierarchy works. This perspective is so deeply ingrained into our thinking, institutions, and science that we aren't always aware of its influence. It leads directly to the saying that a "thing is the sum of its parts."
Traditional analysis is an undeniably useful way to organize, catalog, and index. But it does not describe how things work. Just try to understand how a firm works by examining an organizational chart, for example. Or how the body works by doing an autopsy and cataloguing the organs.
Systemic analysis employs a different approach. Instead of thinking about each component as a thing, we conceive it as a process. Accordingly, each component of the system has an input, an output, and a description of how the input is transformed into the output -- its function. Components are interconnected via their inputs and outputs to form the system. And, in the systems view, hierarchy exists such that each component can be broken down into a sub-system.
The specific pattern of interconnections is called the system structure. In most interesting real-life cases what the system does, its behavior, is more sensitive to the system structure than to the function of the individual components. As a result, in a systems analysis the focus is not so much on the details of the components but on the relationships between them. Because system behavior is dependent on the connections between components as well as the component themselves it's sometimes said that "a system is more than the sum of its parts."
By applying system science we can describe useful things about how a firm, market, or organism works and how it will behave over time. This is something traditional analysis can't do. This is why systems science is interesting. If we want analysis that provides insight into how the future will emerge from the present we need to apply a systemic approach.
