Lisa works in Human Resources at Widgets, Inc. Lately, she’s heard rumblings that employees are unhappy with their supervisors, but she’s not sure why. Determined to find out what’s going wrong, she sets up one-on-one meetings with every single employee. Unfortunately, none of the meetings are helpful, because no one is willing to say anything negative about their supervisor out loud.
Frustrated, Lisa decides to send a survey instead—hoping that the anonymity of a survey will make employees feel more comfortable about sharing what they really think. She sits down to create her survey, however, and feels a little stuck and overwhelmed.
Okay, thinks Lisa, let’s start with the basics…
This type of question is known as an “open-ended” or “qualitative” question. It is called “open-ended” because the person responding to it is free to answer in any manner he or she chooses.
There are no response options specified. It is known as “qualitative” because responses are judged and measured by feel rather than by mathematics.
Lisa, anxious for her survey to be a success, thinks about how she’d answer this question about her own supervisor…
The great thing about this data is that if Lisa has no idea why people are upset with their supervisors, it gives them free reign to answer. For example, Lisa might not have thought to ask specifically about whether a supervisor fosters work-life balance—but this might emerge as a theme among responses.
There are, however, some problems with open-ended, qualitative questions…
1. Whaddya mean by that? Qualitative questions can be vague. What do I think about my supervisor? Are you referring to his management style? His fashion sense? His punctuality? His credentials? Re-writing open-ended questions to be more specific can help with that. For example: Please describe your supervisor’s management style.
However, questions may still linger when specific responses are not provided. It’d be much easier to answer the following question about supervisor management style:
This type of question is known as a “closed-ended” or “quantitative” question. It is called “closed-ended” because the person responding to it is constricted in the range of options he or she has to choose from as answers. It is known as “quantitative” because the response options can be converted to numbers. Why does that matter?
2. What on earth should I do with all this data? Figuring out what questions to ask is tough but figuring out what to do with the answers you get can be even tougher. With qualitative questions, you need to read all of the responses carefully in order to extract common themes. However, this process can be riddled with bias, as you often see only what you want to see in open-ended response answers. That’s why quantitative questions can be so great!
All you have to do is compute an average of the responses you get, a simple calculation in a spreadsheet with no hours of reading required. This also makes more complex analyses–like group comparisons–lightning fast. Simply compute an average for each group, compare, and you’re done!
3. What else is in it for me? The other thing to know about qualitative questions is that they take a really long time to answer. As a survey respondent, it’s much faster to choose one of five pre-formulated options than to have to take the time to write your own response. And, as we’ve mentioned before, keeping surveys short keeps respondents focused and interested. So not only will you get to ask more questions when you use quantitative questions, but it will also get you better data! Getting the most accurate data possible means that you’ll make the right decision every time.
So what’s the bottom line? Qualitative questions are a fantastic first step at exploring the minds of the people you want to survey, but they shouldn’t be your last. Using quantitative questions makes questions clearer, analysis simpler, and data quality better.
Take the time to think of specific quantitative questions to ask now—trust us, you’ll be glad that you did. As for Lisa, here’s hoping she figured out the right quantitative questions to ask to get the answers she needed.