As a student, have you ever been told that your work was “too descriptive” and that you need to be “more analytical”? As a teacher, have you ever told your students that their work was “too descriptive” and that they lacked “analytical depth”?
But the question remains: what is analysis and what does it take to produce good analytical work
What is analysis?
Analysis is a process of transformation. Raw data and information do not have meaning per se. It is you who make meaning out of it, via the process of analysis.
Analysis is a creative process. What you create through analysis is a new discourse about the world, which helps people perceive the world in a different way, understand things that they did not know or did not understand before reading your research.
But how does it work? How does analysis make sense of the world, then? To summarise: by bringing focus, synthesising, naming, establishing patterns and relationships that will help other people in perceiving these patterns and relationships and thus understand the world differently.
A good metaphor for analysis is the work of astronomers and other stargazing lovers who identified constellations. The sky is full of stars. Nonetheless, some people drew patterns in the sky, named these patterns and even created stories around the shapes thus formed. This way of perceiving the sky is passed down from generations to generations, taught and written in books people, and people who learned them can’t help but seeing the constellations when they look at the stars.
Here are two definitions of analysis taken from methodology handbooks:
“Taken literally, ‘breaking up’ something complex into smaller parts and explaining the whole in terms of the properties of, and relations between, these parts” (Robson 2011: 412)
“The process of bringing order to the data, organizing what is there into patterns, categories and descriptive units, and looking for relationships between them; ‘interpretation’ involves attaching meaning and significance to the analysis, explaining the patterns, categories and relationships…” (Brewer 2000: 105)
These definitions highlight the double process involved in analytical work. On the one hand, the breaking down and simplification of a complex messy phenomenon; and on the other the building up of patterns between selected elements to produce a new synthetic way of interpreting the world.
In practical terms, the transcription of one hour of interview can take up to 40 pages. Thus, the transcription of 10 interviews amounts to 400 pages. You need to break down your material into manageable segments, and focus on certain elements and sacrifice others, in order to find out what is the most interesting knowledge you can produce out of this data.
Does that mean that everything goes?
The answer is NO. The idea that meaning is not inherent to the data, but the result of a process nurtured by both the researcher and the empirical material, does not imply that any kind of discourse you can create out of it is relevant for social science purposes.
Making explicit criteria of what we need to do to achieve good analysis can help us ensure we are on tracks regarding our analytical goals. To sum it up: the objective of analysis is to produce a convincing demonstration based on empirical evidence describing, explaining and interpreting a social phenomenon.
Criteria of analysis 101: The ‘wheel of analysis’
Each word of this definition has its importance. In the schematic ‘wheel’ below, I unpack the definition to make explicit the criteria of good analysis:
Let’s unpack further these criteria:
Each of us has natural strengths and weaknesses. For example, some of us will have no problem in expressing their argument with clarity but will struggle to bind their research topic. Others will provide a rich interpretation but without demonstrating how they reached these conclusions. It is important to identify which dimensions of analysis are your weaknesses or which ones you usually tend to neglect and work on them as a priority.