I belong to multiple research groups on LinkedIn, mostly to stay apprised on topics of interest in those communities. A recent discussion in a market research group started when a member asked how other market research companies handle qualitative and quantitative responsibilities. In other words, do specialists focus on either qualitative or quantitative research, or do generalists handle both, and what is the value of each approach?
Great question, and I looked forward to the responses. As a specialist, I firmly believe that both qualitative and quantitative methods belong in the researcher's toolbox. I do think it's difficult, if not impossible, to be both broad and deep in both qualitative and quantitative research. Understanding when and how to use many tools is important, because if you only had one tool, you would be limited in applications: you wouldn't use a screwdriver to hammer in a nail. However, having a deep specialty in one set of tools shouldn't be seen as a limitation: even if I only had tools to address screws, I would know that a hammer is required for this situation and a hammer specialist could be referred.
The responses to the original question (is specialization or generalization better and why) were similar to my opinion in that researchers should be competent in both research approaches but personal proclivities and expertise will be heavier on one side than the other and work should be assigned accordingly. Two offshoots of the original question came up. One topic went further into specialization to discuss how specialized an individual could be, such as whether a quantitatively-oriented researcher is different from a programmer. The other offshoot I found more alarming: one poster ended her comment with "I don't think qualitative researchers work with "data". They work with ideas." Which was quickly followed by another comment from another poster:
"...you and I are among the Few [sic] in our view of the use of the term "data" in qualitative research. Apparently when we weren't looking, and without asking for our approval, which I for one would have withheld, the Many [sic] among users and purveyors of qualitative research started using "data" as if nothing had changed. Sigh!"
Sigh indeed. It is an old story but one that can still be told.
First, data, by definition, is information captured in numbers or characters. To say that ideas or words aren't data is to say that numbers aren't data. To define "data" as the output of quantitative research is an epistemological issue as opposed to a methodological question. *Why* certain techniques are used to collect data and how data is interpreted or analyzed to become meaningful may be what is in question here - and may be explored in a future blog post. For now, I'll gloss over epistemology to say if it is replicable, reliable and valid, it is scientific, and what is collected is indeed data, whether qualitative or quantitative.
Part of the larger question of "specialization or generalization", I think, has to do with how to best combine or deploy qualitative and/or quantitative methods. I'll give an example from a market research project I worked on in the past. We administered a large (n = over 1200) electronic survey with some open-ended (qualitative) questions in an attempt to understand purchase behavior (what products were chosen and how often) and decision drivers (why people chose products). An electronic survey was chosen as the collection method because of its relative low cost and ease to deploy. However, the data which came back didn't really answer the research questions. We got a lot of numbers that answered the quantitative questions (how many/how much of these products have you purchased in the past, etc.) but very little information to tell us why people behaved that way. If the focus was on why people behaved a certain way or made certain decisions, the research design should have been more qualitative in nature - and a survey is not a good way to collect qualitative information. Without a good research design, the end result was not as good as it could have been.
Also, I'm not entirely sure what type of qualitative research is under fire in this thread. From comments later in the thread, I interpret "qualitative" as "focus groups" rather than as describing a group of data collection methods which get at the *how* and *why* of human behavior.
Second, I do not agree with the second poster's opinion that "users and purveyors of qualitative research" were under some sort of obligation to get "approval" (from whom?) to use the term "data". I find this comment particularly divisive - as if one type of person has proprietary rights to data, research and analysis? Again, I think this stance goes back to an erroneous understanding of epistemologies - so maybe I should get on that blog post.
I did not comment on this discussion thread - mostly because I'm more of a lurker (observation methodology!) than an active participant in these groups, and partly because I preferred to wrestle with my episemological and methodological thoughts here.
Ultimately, a well-crafted research question will drive the selection of data collection and analysis methods. Any researcher, whether specialist/generalist or qualitatively/quantitatively oriented, should be able to understand the business problem at hand and translate that into questions that can be answered with data and analysis.
For a great source on qualitative and quantitative methods, please see Research Methods in Anthropology: Qualitative and Quantitative Approaches (2011) by H. Russell Bernard. I used an earlier edition in graduate school and still reference it today.
Hi, I'm Amy Goldmacher. I'm an anthropologist who works with individuals, teams, businesses and organizations, providing human-centered design and user experience research that drives product, service and experience innovation.