A Complexity-Based Plan for Evaluating Transformation

Abstract 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. Three constructs from complexity science are employed – sensitive dependence, emergence, and social attractors. The paper argues that if–then logic is recommended for small-scale change within transformation efforts, but that to evaluate transformation writ large, data from if–then evaluation must be embedded in, and interpreted in terms of, complex behavior. Methodologies for evaluating within this framework are presented. The argument is linked to a definition of transformation that is multidimensional, non-linear, 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. It also shows how evaluation with respect to complexity can be accomplished with methodologies that are well known and well-practiced in the evaluation community

Contribution Analysis and Estimating the Size of Effects: Can We Reconcile the Possible with the Impossible?

While contribution analysis provides a step-by-step approach to verify whether and why an intervention is a contributory factor to development impact, most contribution analysis studies do not quantify the ‘share of contribution’ that can be attributed to a particular support intervention. Commissioners of evaluations, however, often want to understand the size or importance of a contribution, not least for accountability purposes. The easy (and not necessarily incorrect) response to this question would be to say that it is impossible to do so. However, in this CDI Practice Paper written by Giel Ton, John Mayne, Thomas Delahais, Jonny Morell, Barbara Befani, Marina Apgar and Peter O’Flynn, we explore how contribution analysis can be stretched so that it can give some sense of the importance of a contribution in a quantitative manner. The first part of the paper introduces the approach of contribution analysis and presents ideas to capture the change process in theories of change and system maps. The second part presents research design elements that include ranking or quantitative measures of impact in the verification of the theory of change and resulting contribution story

A Complexity-Informed Methodology for Interdisciplinary Dialogues: Key Questions and Challenges for Theory, Research and Practice on Modes of Thinking (In) Complexity

The study of complex systems has led to deep transformations in our modes of thinking, challenging our conceptions of reality and, with them, our roles and possibilities for action as agents in a complex world. A variety of modes of thinking co-exist within the fuzzy boundaries of the domain of complexity studies. Different modes of thinking complexity and of thinking ‘in’ complexity (enacting its principles) can be distinguished in the literature, even though they are not always explicitly identified. Despite the seminal calls of Edgar Morin for the development of more generalised modes of complex thinking, this is still an underdeveloped area of research and practice under the scope of Complexity Studies. This paper aims to make a contribution to the understanding of complexity and complex systems by offering a discussion around the complexity of the modes of thinking complexity. We report both the process and the outcomes of an interdisciplinary workshop aimed at identifying key theoretical, empirical, methodological and pragmatic challenges and questions pertaining to how we think, build, coordinate and practise different modes of thinking complexity and of thinking in complexity (thinking complexly). The workshop adopted a collaborative and dialogical approach organised by a methodology grounded in a theoretical framework for the practice of complex thinking. The methodology was designed to support complex relational dialogues and facilitate emergence (e.g. of new ideas; approaches; levels of understanding; solutions) in the collective discussion. We conducted a mixed-method evaluation of both the process and contents of the discussion using a combination of inductive qualitative thematic analysis and network analysis. The results point towards new areas for interdisciplinary research and practice, signposting domains that have been under explored within the realm of complexity studies and complexity sciences