Data analysis

There are a variety of data collection and analysis methods available to those conducting evaluations and impact assessment.

However, their suitability for use is determined by a number of factors, such as the timing of the evaluation (ex-ante, interim or ex-post), the nature of the specific activities being evaluated as well as the evaluation questions addressed.

Descriptive statistics are the most common approach applied, while case studies – to understand contexts and developments over time – are performed less often possibly due to the increased resources they require, although they can provide detailed explanations of how and why policy measures work (or not). More sophisticated, quantitative approaches such as econometric analysis and network analysis are used more selectively. The most important pro-active data collection is done through interviews and participant surveys.

Overall, the methodological approaches applied are tailored to the evaluation issues addressed and impacts to be covered. For example, evaluations interested in strategy development and policy issues more generally look at consistency and vastly use interviews and other qualitative methods such as focus groups or document search. Evaluations more concerned with effectiveness rely on (often simple) statistical analysis of data collected through surveys and interviews. Those evaluations more concerned with efficiency and project level issues, in turn, tend to look for added value / additionality and rely on surveys, interviews and, less broadly, though, on case studies.