Jonathan A. Morell
This is the abstract of a paper I have in draft form. I’m looking for critique on any or all parts of it. If you are interested please send me email and I’ll send you a copy. Thanks in advance to all.
This article presents a case for more rigorous application of Complexity Science in our efforts to evaluate activity that seeks to bring about transformative change. It builds on the work that is already going on in the evaluation community. The argument begins by explaining the value of traditional if –> then logic and then shows why such logic is not appropriate for evaluating large-scale transformation change activities. Three constructs from Complexity Science are employed – sensitive dependence, emergence, and social attractors. The paper concludes with an explanation of why if –>then logic is recommended for small-scale change within transformation efforts, but that to evaluate transformation writ large, data from ifàthen evaluation must be embedded in, and interpreted in terms of, complex behavior. The argument is linked to a definition of transformation that is multidimensional, non-linear, characterized by two different kinds of tipping points, and measurable. The paper is built around a generic model of transformational change and shows how that model can be customized for specific transformation scenarios.