Getting Evidence Used

Date
5-6 March 201
Time
09:00 - 11:00

Presentations

Data, evidence and access to information: how are they used to make decisions about humanitarian response?

Judith Randel, Development Initiatives, and Annette Were Munabi, Development Research and Training, Uganda


Generating more and better evidence alone will not lead to more evidence-based decisions. Evidence is one among many considerations in the decision-making processes that result in humanitarian funding allocation. This lively session focused on findings from Development Inititives’ preliminary research on incentives and disincentives for evidence-based decision-making and the real and often legitimate constraints and influences in a variety of governments.

Does evidence drive decision-making in food security crises? Examining the “response analysis” question

Daniel Maxwell, Tufts University


In 2004, a study investigating food security responses in emergencies concluded that most programs were not based on evidence, often ignored information and analysis where it existed, relied on a narrow range of programming options, and had little impact on actually reducing food insecurity (Levine and Chastre 2004). Since then, a major effort has gone into improving food security analysis, with many new tools for situational analysis, assessment, monitoring and evaluation, etc. This session examined whether, after a host of changes, improved analysis is now driving the decision-making in choosing among these various response options.

Cracks in the machine: is the humanitarian system fit for purpose?

Peter Walker, Tufts University


We understand more about why humanitarian crises might happen, evolve and recede. But less progress has been made on understanding why the aid system is so slow in taking up and using evidence based policy and practice.This session examined five features of the aid system and architecture – inertia, utility of data, compliance regimes, dominant narratives and longevity of crises – and asked whether they are inhibiting its ability to move to an evidence based model.