Over the years I have written, lectured, and done workshops about how (and when) Evaluation should draw from Complexity Science. Over that time my beliefs have evolved with respect to what aspects of Complexity Science matter, and how evaluation methodologies can be applied to understand program activity and the consequences of program action. This post … Continue reading Complexity in Evaluation: My Latest Thinking on What Matters
The primary objective of this series is to provide evaluators with the capability to apply constructs from Complexity Science to evaluation practice. This objective is bookended with two others. The first is to give evaluators a broad conceptual understanding of Complexity. The other is to provide an appreciation of how Complexity can influence how we conceptualize pattern, predictability, and the reasons for change. Our intention is to accomplish the primary goal within each case that is presented. The "bookended" goals will be achieved over time, as readers see the relevance of complexity in multiple cases.
I’m arguing for a culture of data use that resonates with what we know about information use and decision making.
Recently I was asked to prepare a brief presentation for people in the prediction business – planners and evaluators whose work was preoccupied with some form of the question: If I do this, what will happen? The audience brought a traditional if > then logic to the way they answered this question. They knew that … Continue reading Two Complexity Constructs to Reorient the Logic of Planning and Evaluation
Jonathan A. Morelljamorell@jamorell.com 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. Abstract This article presents a case for more rigorous application … Continue reading A Complexity-based Plan for Evaluating Transformation
This is the title of a blog post I wrote for the International Evaluation Academy. The blog opens with: Evaluators need to know more about complexity because the programs they evaluate often exhibit complex behaviors. Without understanding complexity, evaluators cannot construct models, develop methodologies, and interpret data in ways that accurately describe what programs are … Continue reading Why do Evaluators Need to Understand Complexity?
In recent years, the evaluation community has been looking to “complexity” as a source for addressing these difficulties.
I am involved in a project that involves helping people make a single choice among multiple technologies. They must commit to one, so there is no waffling. This is one more of many such exercises that I have been involved in over the course of my career, and I have never been fully satisfied with any of them. On an intuitive level, everyone knows they cannot make the best choice, but everyone thinks that they should be able to. I finally figured out why they cannot. I don’t mean that people are not smart enough. I mean that it is impossible. The behavior of complex systems makes it impossible.
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.