Why “soft” research is “hard”

Some of my colleagues like to talk about how research that involves programming is “hard”, while research that involves human subjects is “soft”. Similarly, some colleagues like to call exploratory (qualitative) research “soft” and confirmatory (quantitative) research “hard”. Soft and hard are often used as synonyms for easy and difficult, and this is plain wrong.

Pretty much any research worth its salt is difficult in some way, and working with human subjects makes it even more difficult. I find research methods like qualitative surveys, involving interview analyses, for example, much harder than the statistical analysis of some data or some algorithm design. The reason is the lack of immediate feedback.

While you can (and should) put quality assurance measures in place for your interview analyses, ranging from basic member checking to complex forms of triangulation, it might take a long time until you learn whether what you did was any good. So you have to focus hard in your analysis without knowing whether you are on the right track. It doesn’t get more difficult than this.

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