Blackboxing unknown unknowns through vulnerability analysis

By Joseph Guillaume

Author - Joseph Guillaume
Joseph Guillaume (biography)

What’s a productive way to think about undesirable outcomes and how to avoid them, especially in an unpredictable future full of unknown unknowns? Here I describe the technique of vulnerability analysis, which essentially has three steps:

  • Step 1: Identify undesirable outcomes, to be avoided
  • Step 2: Look for conditions that can lead to such outcomes, ie. vulnerabilities
  • Step 3: Manage the system to mitigate or adapt to vulnerable conditions.

The power of vulnerability analysis is that, by starting from outcomes, it avoids making assumptions about what led to the vulnerabilities. Continue reading

Designing scenarios to guide robust decisions

By Bonnie McBain

Bonnie McBain (biography)

What makes scenarios useful to decision makers in effectively planning for the future? Here I discuss three aspects of scenarios:

  • goals;
  • design; and,
  • use and defensibility.

Goals of scenarios

Since predicting the future is not possible, it’s important to know that scenarios are not predictions. Instead, scenarios stimulate thinking and conversations about possible futures. Continue reading

Agent-based modelling for knowledge synthesis and decision support

By Jen Badham

Jen Badham (biography)

The most familiar models are predictive, such as those used to forecast the weather or plan the economy. However, models have many different uses and different modelling techniques are more or less suitable for specific purposes.

Here I present an example of how a game and a computerised agent-based model have been used for knowledge synthesis and decision support.

The game and model were developed by a team from the Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD), a French agricultural research organisation with an international development focus. The issue of interest was land use conflict between crop and cattle farming in the Gnith community in Senegal (D’Aquino et al. 2003).

Agent-based modelling is particularly effective where understanding is more important than prediction. This is because agent-based models can represent the real world in a very natural way, making them more accessible than some other types of models. Continue reading

Managing uncertainty in decision making: What can we learn from economics?

By Siobhan Bourke and Emily Lancsar

Siobhan Bourke (biography)

How can researchers interested in complex societal and environmental problems best understand and deal with uncertainty, which is an inherent part of the world in which we live? Accidents happen, governments change, technological innovation occurs making some products and services obsolete, markets boom and inevitably go bust. How can uncertainty be managed when all possible outcomes of an action or decision cannot be known? In particular, are there lessons from the discipline of economics which have broader applicability? Continue reading

Idea tree: A tool for brainstorming ideas in cross-disciplinary teams

By Dan Stokols, Maritza Salazar, Gary M. Olson, and Judith S. Olson

Dan Stokols (biography)

How can cross-disciplinary research teams increase their capacity for generating and integrating novel research ideas and conceptual frameworks?

A key challenge faced by research teams is harnessing the intellectual synergy that can occur when individuals from different disciplines join together to create novel ideas and conceptual frameworks. Studies of creativity suggest that atypical (and often serendipitous) combinations of dissimilar perspectives can spur novel insights and advances in knowledge. Yet, many cross-disciplinary teams fail to achieve intellectual synergy because they allot insufficient effort to generating new ideas. Here we describe a brainstorming tool that can be used to generate new ideas in cross-disciplinary teams. Continue reading

Toolboxes as learning aids for dealing with complex problems

By Stefan Hilser

Stefan Hilser (biography)

How can toolboxes more effectively support those learning to deal with complex societal and environmental problems, especially novices such as PhD students and early career researchers?

In this blog post, I briefly describe four toolboxes and assess them for their potential to assist learning processes. My main aim is to open a discussion about the value of the four toolboxes and how they could better help novices.

Before describing the toolboxes, I outline the learning processes I have in mind, especially the perspective of legitimate peripheral participation. Continue reading