The Principle of the Five Why’s and How Can You Use It Better Listen to Others

Photo Credit: Trung Nhan Tran

The Five Why’s is a common technique among UX researchers and other qualitative researchers that has personally transformed my approach to conversations. UX researchers interview people all the time, and to understand what they think about something, they always make sure to ask five “why” questions about their opinion in order to get to the heart of their opinion on the matter. Humans often rush into assumptions and judgements about what the other person thinks, and this forces us to slow down and get to the heart of how they view the world. 

Let’s consider a classic UX research example. Say you just developed a great new app, and you wanted to see whether people actually find it useful. So, you observe several people using the app and ask them what they think. The first person says, “I find it frustrating.” This is really useful information, but obviously, more details would help even more. So, a natural response would be, “Why do you find it frustrating?” 

Say the person gives a quick answer like, “I find the interface confusing, so I can’t do what I want to do” or whatever their frustration might be. This gives you a better understanding of their frustrations, but you can dig even more. According to the Principle of the Five Why’s you should ask at least five follow-up questions about why (or in some cases, how) they feel the way they do. 

This allows you to hone in exactly what their underlying needs and expectations are and how well your product meets those needs for them. Now, technically, not all follow-up questions have to be “why”. The idea is that like, “why” questions, ask questions that nonjudgmentally help uncover the underlying reasons for the opinions. For example, in this scenario, I may next ask, “What about the interface do you find confusing?” or “What are you trying to do, and how is it preventing you from doing it?” Both of these are not “why” questions, but they help orient me to understand why the person feels frustrated. Sometimes you have to learn some basic data about what their experience was before you uncover the next level of detail about why they had that experience. 

I often use this principle in regular conversations as well. Too often people assume they know what the person is thinking and make assessments based on their initial judgements. Asking follow-up questions forces us to slow down and consider in-depth what that person is trying to communicate. After listening, one can still disagree with a person’s conclusions, but at least you will know why. In almost every situation, I have found at least some points of agreement even when I thought we had opposing, conflictual perspectives. 

It also calms you down. In tense conversations, we often simply react. Maybe we presume they meant something hostile and respond in turn. This helps us survive threats but clouds our ability to empathize with others and reason through their ideas. Asking questions allows us to pause and reflect for a few more moments on what else might be influencing where they are coming from. 

Feel free to try it in regular conversations, especially potential arguments or other tense conversations. Pause and ask a few “why” questions to understand the layers behind their thoughts before launching into your perspective on the matter. It will change the course of the conversation. Worst case scenario, by the end of it, you will still disagree with them just as much as you did initially, but often you will learn something and will discover a way to carry on nonconfrontationally in a way that involves both of you getting what you want. If you disagree, you have lost little by hearing them out and gained the ability to disagree productively since you now know exactly where the other person is coming from. 

Now in every interaction, you don’t have to literally ask five questions. That exact number may not fit every interaction. The spirit of the rule is to ask follow-up questions that force you to engage with the reasons underneath someone’s impressions. For me, I often ask follow-up questions until it feels uncomfortable, until I feel my thoughts well up so strongly within me that I am eager to jump in. Then, I ask just two more follow-up questions. In the unlikely event that I still think they are totally wrong by the end of those two questions, I can jump in with my perspective. This slows me down and forces me to practice more constraint and helps me see a path to empathize and/or disagree in a positive and productive manner.

Data Science Storytelling: Quantitative UX Research in Google Cloud with Randy Au (Part 2 of 2)

In this second part of my interview with Randy Au, he discusses the techniques he used to teach himself to code and his approach to programming and data science as a social scientist.

Here is Part 1 of our interview.

Prior to joining Google, he spent a decade as a mixture of a data analyst, data scientist, and data engineer at various startups in New York City and before that, studied Communications. In his newsletter, he discusses data science topics like data collection and data quality from a social science perspective. Outside of work he often engages in far too many hobbies, taken to absurd lengths.

Click here to learn more about the Interview Series this is a part of.

More about Randy:

Data Science Storytelling: Quantitative UX Research in Google Cloud with Randy Au (Part 1 of 2)

Randy Au, a Quantitative UX Researcher at Google, explains how he leverages his backgrounds in communication, statistics, and programming as a quantitative UX researcher in Google Cloud to analyze and improve Cloud Storage products.

Here is Part 2 of our interview.

Prior to joining Google, he spent a decade as a mixture of a data analyst, data scientist, and data engineer at various startups in New York City and before that, studied Communications. In his newsletter, he discusses data science topics like data collection and data quality from a social science perspective. Outside of work he often engages in far too many hobbies, taken to an absurd lengths.

Click here to learn more about the Interview Series.

More about Randy:

Data Scientist, Entrepreneur, and Artist: Interview with Emi Harry Part 2 of 3 (Interview #5 in the Interview Series)

This is the second part of my interview with Emi Harry as part of my Interview Series. In it, she discusses her experiences of racial discrimination in data science as a black woman, how she manages her dual background in data science and fashion, and how she leverages her storytelling and communication skills as a data scientist.  If you would like to start at the beginning of my interview with her, click here.

Links to the other two parts of the interview:

Emi Harry is the co-founder of Naina Tech Inc., a New York-based tech startup that is poised to launch an adaptive learning platform for early childhood education in the U.S. and Nigeria’s underserved communities. As a highly skilled data scientist and social entrepreneur, Harry is also on the board of Alula Learning, an EdTech learning management systems provider, and Manna, a health and nutrition company, both in Nigeria. She has had a diverse professional experience, having worked in the food, oil and gas, entertainment, and fashion industries in Nigeria, as well as the entertainment, non-profit, and education industries in the United States. Currently, she balances her time between working in tech, creative writing, and fashion designing.

Her educational qualifications include B.S. in Mathematics, University of Lagos, Nigeria; Master’s in Social Entrepreneurship, Hult International Business School, San Francisco; M.Sc. in Data Analytics/Science, Fordham University, New York, and is on track to earn a M.Sc. in Computer Science from Pace University New York.

To learn more about Emi Harry, check these out: