I see two genre of futuring. One is based on the belief that however uncertainly, we can envision a future and plan to get there. I call this the “Locksley Hall” approach, after a line in Tennyson’s poem Locksley Hall “For I dipt into the future, far as human eye could see, / Saw the Vision of the world, and all the wonder that would be.” The second genre relies on the behavior of complex systems and is much less sanguine about futuring. We plan; God laughs.
How do we Know? Some Interviews With Scientists
This section of my blog is an exercise in spreading knowledge about how scientists come to believe what they tell us. I want to explore whether scientists can explain their methods and deliberations well enough for us to make informed judgements about the worth of their messages.
Why does Evaluation need Complexity Science?
Why does Evaluation need Complexity Science? With implications for predictability, unpredictability, and methodology.
Six principles for applying complexity to the evaluation of transformation
Motivated by a survey I was asked to complete, I spent some time distilling my thoughts about how complexity can be applied to the evaluation of transformation. It came down to six principles. I have written a lot on this topic, so if anyone wants the gory details, just ask. Evaluators deal with complexity in … Continue reading Six principles for applying complexity to the evaluation of transformation
Complexity in Evaluation: My Latest Thinking on What Matters
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
Installment One of an Occasional Series: Applied Complexity – Tools for Understanding Programs and their Consequences
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.
Good Reasons Not to Use Data: The Problem of Tactics Outside of Culture
I’m arguing for a culture of data use that resonates with what we know about information use and decision making.
Two Complexity Constructs to Reorient the Logic of Planning and Evaluation
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
A Complexity-based Plan for Evaluating Transformation
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
Why do Evaluators Need to Understand Complexity?
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?
Evaluation Uncertainty 