ABSTRACT
Problems are best understood from a multiplicity of perspectives. Different types of information and the methodologies used to gather them are like the lenses of a camera.1 They each have their own biases and strengths. Some types of information, like some types of lenses, are good for close-up pictures, while others provide a macrostrategic overview. Some lenses are useful for capturing fast moving action while others are useful for portraits. Like lenses, the information used to assess fragility processes brings a country into sharp relief. They allow the viewer to appreciate both uniqueness and similarity. Used together, different lenses provide a more complete and balanced picture than any one lens could on its own. In this chapter, after focusing on large sample structural data analysis in Chapters 4 and 5, we identify a complementary form of information gathering, known as events monitoring, or dynamic data analysis, that together with fragility profiles can provide a fuller picture of country performance. When events are analyzed over time, events monitoring gives analysts an indication of a country’s current trajectory, and some context within which to understand unfolding developments. Typical questions for those who need day-to-day, weekly and monthly information about a country’s performance include: where and what are the emergent sources of instability? How do recent events and trends affect policy formation and implementation? Are our policies having a measurable impact? We show how profiling and events monitoring can be used to answer these questions. Using CIFP data to 2006 we provide profiles of three fragile states: Afghanistan, Haiti, and Zimbabwe, and place them in the context of selected countries drawn from regional profiles. It will be shown how this information can provide context and nuance and serve as a basis for identifying trends in performance. The chapter unfolds in four parts. First the relationship between dynamic data analysis and the development of country monitoring tools is discussed. Then we present our events-based monitoring methodology. Third, we present profiles that are quantitatively evaluated and systematically assessed to identify general trends of relevance to fragility. We conclude with a summary of how dynamic data analysis can improve the quality of decision making.
