Dr. Brené Brown is the author of The Gifts of Imperfection. Her work uses qualitative research to explore the human connection. She dubs her qualitative research stories as “just data with a soul.” Her work references the descriptive rather than the numeric aspect of qualitative knowledge. She discusses the power of vulnerability in her The Power of Vulnerability TED Talk.
When analyzing which is more significant – quantitative or qualitative data – many would say hands down it is quantitative data. That’s math and science, right? Real, measurable numbers. In fact Brené Brown in her talk comments that one of her professors stated “if you can’t measure it, it doesn’t exist.” Quantitative data can be precise, fast, and direct. Because of this seemingly clear definition of quantitative data, qualitative data ended up being positioned as the opposite. If quantitative data is reliable and discrete, qualitative data must be imprecise and fuzzy, right?
The importance of qualitative data is in building acceptance/validation. Qualitative data relates to the human experience. It builds empathy. Numbers aren’t significant until/unless they can be expressed in a qualitative manner. It’s all about the story and what it means to us.
Both are meaningful and required. Quantitative is how the world works. Qualitative is how we perceive the world working and what it means to us as individuals and societies.
As an exercise planner, one of my central pillars of design is to create a framework that will allow for the proper and effective collection of data of many types. Often, I require a mix of both quantitative and qualitative data to achieve my objectives, and more data give me more accurate outcomes and predictions!
For example, in an exercise testing an agency’s ability to shut down 75% of its transit stations within 30 minutes of an incident, data collectors can quantitatively assess whether the agency can achieve this goal by watching players respond during the exercise. However, determining “how well” the same agency succeeded or failed may require qualitative data that can’t be measured with a stopwatch. While the quantitative data is appealing and quite useful when answering the pass/fail question, qualitative data must be used to better assess the quality of what was observed.
Warning! There is a danger of focusing too narrowly on a single story, however. Chimamanda Adichie in her Danger of a Single Story – Ted Talk warns of the danger of only hearing “one narrative in a world of billions.” As managers of data, whether quantitative or qualitative, we must ensure that the tools we select match our goals and give us the best analysis possible without allowing our biases to predetermine the outcomes we think we want to see.
How do I know if a quantitative or qualitative approach is the best to solve my problem? The table below helps sort our which approach may be best:
|Use this approach if:||Quantitative||Qualitative|
|You believe that:||This is an objective reality that can be measured||There are multiple constructed realities|
|Your audience is:||Familiar with/supportive of quantitative studies||Familiar with/supportive of qualitative studies|
|Your research question is:||Confirmatory, predictive||Exploratory, interpretive|
|The available literature is:||Relatively large||Limited or missing|
|Your research focus:||Covers a lot of breadth||Involves in-depth study|
|Your time available is:||Relatively short||Relatively long|
|Your ability/desire to work with people is:||Medium to low||High|
|Your desire for structure is:||High||Low|
|You have skills in the area(s) of:||Statistics and deductive reasoning||Attention to detail and inductive reasoning|
|Your writing skills are strong in the area of:||Technical, scientific writing||Literary, narrative writing|
Sources for this article include:
- Investigating the Social World: The Process and Practice of Research by Russell K. Schutt
- Practical Research Planning and Design by Paul D. Leedy
—Written by Jeff Roth