If the collected data is to be converted into usable information, then it must be consolidated and interpreted.
If an overall picture needs to be produced from many different individual surveys or data from various sources and methods needs to be assessed, then the raw data first of all needs to be prepared accordingly. It is obvious how quantitative data is consolidated. The data is entered into tables or presented in the form of graphs. Quantitative data is analysed statistically. Consolidating qualitative data is a slightly more complex matter and depends on the type of analysis. Qualitative data can be analysed with various methods of content analysis. The results must be graded and assessed.
Analysing and interpreting the data forms the core of outcome and impact assessment. It is a matter of assessing the effects of the project on the basis of the comparisons that have been made and revealing potential weaknesses. Discussing the findings helps to explain or fill in contradictions or gaps in the data. Analysing data is an especially important element of participatory methods. It helps stakeholders to internalise and accept the conclusions, and their motivation to commit themselves to change increases.
The following are generally accepted standards that need to be adhered to:
External teams should be allowed to work freely. The organisation should not put any pressure on the assessment.
Differing perspectives within a team are disclosed and documented.
Sources of information are published and are reliable.
Data is meaningful and systematically checked.