In some sectors, lots of quantitative data is important. Think about climate change and climate science. Reports taken from major institutions such as the UN focus on macro data, numbers that summarize what is going with pollution and CO2 emissions at the country and international level. Marketing, and consumer affairs, while a completely different industry, also tends to like big numbers, and for good reasons—synthesizing big data means understanding trends at the national and sub-national level for what people are buying, whether its clothing, furniture, accessories, etc. From an economic standpoint, firms in this sector like to know what is selling and what isn’t, as this helps managers understand people’s behaviors at the macro level.
In research and academia, whether looking at the social science industry, such as the fields of psychology, poverty alleviation, mental health, or humanitarianism, ethnography and survey data is incredibly important. Instead of being concerned with macro data and big numbers (while they are still relatively important), researchers can be mainly engaged with micro data—data of the individual and the communities they belong to, and therefore being able to come up with good surveys allows researchers to understand communities of people, how they interact, what creates vulnerabilities, and what their stressors are in life. It’s even become a habit in the U.S. to take a survey on an iPad before your doctor’s appointment.
Qualitative Data’s Worth
Surveys are all about their design and reasoning for questioning in the first place. This means that the survey architect, or creator, has the power to ask very targeted, or also very broad lines of questioning. If you’ve ever taken a survey, you know exactly what these lines of questioning look like. Meyers Briggs surveys asks respondents very clearly to rate their “feelings” on a scale from 1 to 5 to derive how much empathy, defensiveness, positivity, negativity, introversion, and extroversion a respondent has with respect to how heavily each group of questioning is weighted.
Surveys like these, often taken online and when somebody has time, given that a potential respondent has voluntarily opted into taking the survey, probably means the respondent will answer the questions to the best of their knowledge, unless of course they feel threatened or biased—uncomfortable. But all in all, when individuals have a safe and regulated environment to take their survey in, the probability they will tell the truth goes way up.
Conversely, such as instances of the classic doctor’s office visit or the first time at a new therapists office, surveys and questionnaires can become very inaccurate very fast. This is because of a few reasons:
- The respondent feels stressed or under too much pressure to finish the survey
- The respondent doubts the survey has any real external validity
- The respondent doesn’t trust the institution that is providing the survey
- The survey questions are too broad and don’t pertain to the respondents/patients real problems
In academia and research roles, it is important to understand the environment your respondent is answering in. Qualitative data is highly dependent on the timing in which questions are asked, when they are asked, how the interviewer approaches subjects, and whether there is mutual trust between the individual or guiding institution giving out the survey and the respondent that is answering them. In big data, these things don’t matter as much because there is less interaction with humans. Calculating the profit of a company in a given year doesn’t necessitate much human interaction.
Different approaches for different audiences
It is amazing what good qualitative research can reveal then when the right approaches and methodologies and designs are used. Stories, and narratives about how community members view certain problems can provide highly valuable insights into problems that cannot be understood by looking at poverty metrics or the net worth of a group of individuals. These stories can show up in surveys and questionnaires that ask very specific questions.
It is possible to include on surveys questions that reveal such insights. One way is to move from the standard 1-5 scale of answers to including short sections where respondents can write, or type, their responses (or answer them verbally in person). When surveys are approached this way, new insights for researchers can prove highly valuable, and also lead to secondary research that strengthens primary research.
Dr. Palmer Morrel-Samuels, a social psychologist, backs up this train of thought by adding:
“Respondents often give higher ratings to questions that contain more words and require more time for reflection. Maintaining fairly equal question and section lengths provides the highest probability that you’ll obtain compatible survey responses across all questions.”