This is the abstract for a book chapter I am writing on the evaluation of transformation. It is a draft and will undoubtedly change quite a bit by the time it is published.
This chapter draws from complexity science to present a metatheory of transformation that can be applied to discrete theories of change that are constructed to guide model building, methodology, and data interpretation for the evaluation of individual change efforts. The focus is on six specific behaviors of complex systems – stigmergy, attractors, emergence, phase transition, self-organization, and path dependence. These can be invoked singly or in combination to understand pattern, predictability, and how change happens. The importance of both “explanation” and “prediction” is woven into the discussion. A definition of “transformation” is offered in which a qualitatively new reality becomes the default choice that constitute a new normal. Indicators of transformation include measurable ranges (as opposed to specific values) for level of energy use and the time over which the change endures. Because complex systems behave as they do, the recommended theory of change is sparse – it has few well-defined elements or relationships among those elements. There is already good progress in the application of complexity to the evaluation of transformation. An argument is made that these efforts should be strengthened by deliberately incorporating what is known about complex system behavior, and that by so doing, both prediction and explanation would better serve the purpose of practical decision making.
Here is the entire chapter.