Research Automation as
Technomethodological
Pixie Dust
Elizabeth F. Churchill

Yahoo! Research | [e-mail]

 

Like many people in these times of cost saving, I have lost my sense of humor. Why? Because what constitutes reasonable economizing—determining what costs are or are not optional— reveals some curious assessments of value. I am referring to human-centered research and the peculiar assumption that qualitative research methods— like qualitative interviewing and ethnographically inspired fieldwork—are too expensive to use in the design process during lean times.

Photograph by Garrett Nickell

There are plenty of companies willing to jump in and offer cut-rate services, but, as in all of life, one should be aware that “you get what you pay for.” Timothy de Waal Malefyt’s recent article in American Anthropologist details how corporations are turning to “multiple ethnographic vendors to compete for projects in bidding wars.” He states that “ethnographic companies and market research anthropologists no longer assume a solitary uniqueness for their practice but often distinguish themselves by branding.” He focuses on brand differentiation through evocation of inventiveness, demonstrated through technologies of data capture—

cell phones, video cameras and reporting platforms like blogs are all examples of novel, sexy “technomethodologies.”

The point of differentiation that interests me most is cost cutting; technologies of automation have always been coupled seductively with cost savings. There are plenty of companies competing for business by offering quicker, faster (often capitalized: FASTER) results— time is money and less time is money saved. So what can be cut or compressed in qualitative research planning and execution? How can qualitative research services remain effective while cutting costs?

1. Outsource the experience of being there. To do really good qualitative research, I personally believe there is no substitute for being there—actually interacting with people where they normally hang out and where they work/live/play. I do, however, realize that sending trained researchers into the field is not always possible. A popular solution is to outsource the data gathering to study participants; I call this the do-it-yourself approach to data gathering. The assumption is that by asking people to produce personal records of their actions, in situ,

documented with video, imagery, and text, we can outsource the work of “being there”—data straight from the horse’s mouth has authenticity. While I don’t doubt that some people are really good at reporting their experiences, when accounting for and recounting their actions, doing good “ auto-ethnogra-phy” is hard. It is not simply reportage of what happened.

It entails developing reflexive understandings of one’s own experience, and a consideration of the sociocultural milieu in which one is operating. If not conducted well, the results of the presented-self might not be reflective of participants’ actual everyday practice, instead revealing a neatly constructed, sampled view of some ideal of everyday life. Using this data to offer design recommendations may be on par with designing domestic spaces based on how people live in “at home” via reality-TV shows. Researchers that offer quality services stress the importance of iterative data analysis—they do not take recorded or reported raw data as uncontestable or final.

Less convincing are services that cut costs and increase efficient results by automating online interviews and

September + October 2009