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Integrating analysis and synthesis, the systems approach is widely used and successful in natural science and engineering, for example systems engineering. It is most effective in treating complex phenomena, for it:
The systems approach is effective not only for understanding or designing physical systems but also for abstract construction in mathematics and theories. Instead of a physical module, a “subsystem” can be a concept within a conceptual scheme and its “interfaces” can be relations to other concepts in the scheme. The “object” in object-oriented computer programming is an examples. A mathematical symbol that represents a complex concept hides information.
In natural sciences, analyses and concepts are sometimes approximate. Scientists carve nature at its weak joints – to use Plato’s metaphor – and refine their approximations step by step. Isaac Newton explained: “By this way of analysis we may proceed from compounds to ingredients and from motions to the forces producing them, and in general from effects to their causes and from particular causes to more general ones, till the argument end in the most general. This is the method of analysis; and the synthesis consists in assuming the causes discovered and established as principles, and by them explaining the phenomena proceeding from them and proving the explanation.” [Opticks, Query 31].
Several confusions about the systems approach occur in the philosophical and sociological literature. The first is to confuse it with the system-level approach, which treats a large system as a unit without delving into lower-level subsystems. An example of the system-level approach is economist W. W. Rostow’s model of economic growth, which treats a national economy as a system that undergoes five historical stages: traditional society, preconditions for take off, take-off, drive to maturity, and the stage of high mass consumption. Another example is historian Thomas Hughes’s model of evolution of technical systems, which undergo the stages of invention, development, innovation, consolidation, reverse salient, inertia. The system-level is powerful and appropriate in many cases, but it macroscopic view misses most structures and dynamics of the system.
Some sociologists confuse a system with a “seamless web.” The confusion precisely misses a most important feature of the systems approach, modularity. The difference is apparent in issues of safety. A seamless web must be perfect, for it is unraveled by a tiny loose end. The effects of a minor local flaw propagating freely in a seamless web leading to system-wide collapse is one of the root causes of “normal accidents,” as Charles Perrow called it. To control such disastrous scenarios is a major reason for system modularity. Not seamlessness but good seams – mostly independent subsystems with interfaces that pass only the desired effects – is the mark of the systems approach. Confusing systems with seamless webs is a symptom of deficient analysis.
Analysis is also called reduction, and "reductionism" to scientists mean the importance of analysis. However, "reductionism" has also become a philosophical dogma asserting that a system is nothing but its constituents -- as you are nothing but your genes or neurons. Ideological reductionism, which slights synthesis, has engendered much debate in the philosophy of science.
The systems approach in a integral part of systems engineering. Besides the references cited there, see also:
Auyang, S. Y. 1998. Foundations of Complex-system Theories: in Economics, Evolutionary Biology, and Statistical Physics. New York: Cambridge University Press. (Section 6 examines analysis-synthesis in the sciences).
Simon, H. 1996. The Sciences of the Artificial, 3rd ed. Cambridge: MIT Press. (Gives probably the best arguments for the need for modularity).
Vincenti, W. G. 1990. What Engineers Know and How They Know It: Analytical Studies from Aeronautical History. Baltimore, MD: Johns Hopkins Press. (Chapter 1 lays out the successive decomposition of systems in engineering design).