Complexity science has arguably proven itself most productive and relevant when dealing with non-linear systems, in particular what are called complex adaptive systems where non-linearity is largely the product of an ‘if/then’ logic possessed by the individual elements within the system, with the structure and order of the system as a whole deriving from the emergent patterns created by the interaction between the parts. This approach, called Agent-Based Modeling is an active area of research within many areas of social science from management and organization studies to economics and sociology, when combined with the capability of current computation it represents a powerful theoretical and practical framework for the social sciences.
The emphases on reductionism within traditional science, as opposed to holism within complexity science, may present itself as diametrically opposed but to think about science as fundamentally being an inquiry into the world around us, both physical and social, requires a broader framework than that presented by reductionist reasoning. Although reductionism may be a powerful mechanism within many domains of science the world is inherently complex and multidimensional requiring, in turn, a multi-dimensional and adaptive framework. The real challenge is not in developing one or the other, reductionism or holism, but the integration of the two to provide both a detailed analytical perspective and a broader vision for integrating this into a deeper understanding of the world we live in.