Improving analytical practices and skills
Over the last couple of years, the amount of data produced in humanitarian emergencies has increased drastically. In 2010 an average of 215 reports were produced per disaster - by 2014 this number had reached 800, according to Reliefweb statistics, and the numbers continue to grow (http://trends.rwlabs.org/).
With the increasing number of methodologies and tools for information management and data collection in humanitarian crises, the sense-making component has unfortunately been largely overlooked, as if displaying graphs and maps on a dashboard for users to interpret themselves were all there is to humanitarian analysis. Never before have we had so much information and been left with so many questions.
In December 2015, ACAPS launched a new multi-year research project on analytical thinking in humanitarian emergencies. The project, supported by the Centre for Disease Control (CDC), is focused on improving analytical practices and skills by:
- identifying best practices in data analysis from recent crises and building on them to systematise improved approaches
- evaluating how the tools developed in recent crises perform in different contexts
- distilling lessons learned into user-friendly frameworks, tools, guidance, and training materials.
We created this section to share the results of this research: documents, tools, and guidance will be posted here as they are developed.
Biases are normal processes designed to make decisions quickly. They are unconscious, automatic and non-controllable and there is no magical solution to overcome these reflexes.
However, knowing their effects, when and where they apply as well as some key structured techniques, can help mitigate their negative consequences. Systematically identifying their effects on your analysis is a habit that each analyst should possess.
Scientific Thinking in Humanitarian Analysis
Scientific thinking needs to be taught and cultivated so it becomes seemingly intuitive when humanitarians conduct analysis under pressure and tight deadlines.
Logical Reasoning in Humanitarian Analysis
The aim of logic is to develop a system of methods and principles that can be used as criteria for evaluating the arguments of others – and as guides in constructing arguments of our own. It is thus critically important for analysts to apply logical reasoning in order to provide good analytical products.
"Homo Analyticus" - Humanitarian Analyst Profile
Humanitarian analysts apply specific frameworks, structured techniques and analytical standards to review, evaluate and make sense of the often partial information available. They tailor their analysis to their end user’s specific questions (e.g., who are the affected groups most in need of assistance after the earthquake), contributing to the design and implementation of more efficient humanitarian programmes.
This document provides guidance for data analysts to find the right data cleaning strategy when dealing with needs assessment data. The guidance is applicable to both primary and secondary data. It complements the ACAPS technical note on How to approach a dataset which specifically details data cleaning operations for primary data entered into an Excel spreadsheet during rapid assessments.
Spotting Dubious Data
This technical brief provides practical guidance on how to interpret the context. It provides a list of common problems found in the numbers appearing in humanitarian reports and illustrates these problems with examples.
Find below a list of infographics illustrating some of the key concepts