What Chicken Nuggets Taught Me About Using Data to Design
By Arianna McClain
It was dinnertime and my colleagues were staring into the freezer of a 48-year-old man named John. As IDEO designers, we were working with a client to develop a new line of healthy food products, and John was one of the people who had invited us into his kitchen for research.
What we saw surprised us: stacked boxes of frozen children’s organic meals. John was a bachelor with no kids, so why would he have kids’ meals in his freezer?
Simple: Because he wanted to eat healthy, and he believed that no company would make unhealthy food for kids.
In data research, John represents the classic “outlier” — a person who stands out from the other members of the group. As a behavioral scientist (or as some call me, a “data scientist”), I used to spend a lot of time cleaning data, throwing out the outliers like John, and looking at measures of central tendency, or how the majority of people behaved. But in my new role as a designer, I seek these outliers.
Outliers help me learn how different people use and perceive a product. They help me reframe the challenge, uncovering new opportunities for design. Their unexpected behaviors can indicate larger trends that can be explored and tested. With this project, for example, tuning into the outliers allowed us to explore the possibility of developing healthy food products that appealed to single men, and potentially created a whole new market opportunity for our client. Using data as inspiration rather than validation inspired us to go on a different path than if we just paid attention to the mean.
And that’s just one scenario. While working at IDEO, I’ve realized that scientists and designers can learn a lot from one another. It’s a two-way street, and there’s plenty of room for everyone. Here’s what I’ve learned.
1. Behind the numbers are real people
Companies are collecting as much data as they can about their consumers. They’re collecting people’s personal information; revealing the economics of human interaction; and in turn, designing products that affect people’s lives. Whether I am thinking about data ethics or design, I try not to forget that my datasets represent real people, like my mom. I ask myself, how would my mom feel about strangers knowing this about her? What was she thinking and feeling while this data was being collected? The same way I embrace people in real life, that’s how I treat their data: with respect, curiosity and humanity.
Designers, however, sometimes resist working with data because all they can see are soulless numbers. When I look at those same numbers, I see human behaviors, needs and motivations. That’s why I’ve come to believe that data should be a part of the design process from the beginning, the same way people are. Like in the story above, John could have just been an outlier. But when we learned his story, he was able to inspire us. Too often data is only viewed as the final step companies use to evaluate or validate a decision. By seeing data as people, designers can turn that data into valuable input for their design process. But data alone isn’t going to give you the depth you need to understand people.
2. Without stories, numbers tell us very little
On a recent healthcare project, when we asked people through a survey what was most important in choosing a healthcare provider, people chose “costs and coverage.” Had we taken this data at face value, we would have designed a solution that was wrong, like a cost calculator.
That’s because when we spoke to people to hear their stories and looked at the behavioral data from the healthcare site, we saw and heard something very different from what they reported in the survey and told us through their stories. Even before costs, people consistently first clicked on “Things you should know when choosing a provider.” And afterwards, they made their final decision by figuring out costs. By merging the insights, we were able to create a more valuable product by designing for that tension.
When clients provide us data or when we gather data, we use it to guide our qualitative research, directing us whom to speak with and what questions to ask to uncover the “why” behind the numbers. Listening to people’s stories then helps us uncover the emotions and motivations, leading us to truly innovative design.
It is through the use of both qualitative stories and quantitative data (surveys and behavioral data) that we are able to uncover needs that people may not even know they have. My colleague Matt Cooper-Wright, a designer at IDEO in London, found similar insights on a project we worked on together earlier this year.
3. Design better outcomes
At least once a week I get an email from a store or a website asking me to take a survey. Last week, I opened my email and mindlessly clicked through a survey while watching television and eating a bowl of cereal. Does anyone else do that? Let’s be honest, we’ve all distractingly filled out a survey, possibly in between bites of our dinner with Seinfeld on in the background. And that’s scary if companies use this data to make major decisions.
As a designer, I take the design in survey and measurement design seriously. What this means is that I design surveys based off real people, I ask survey questions to figure out what to design, and I try to design surveys people actually want to take.
Before I design surveys, I always talk to people. On a recent healthcare project, my team and I asked people how they picked their last doctor. We heard some people make decisions after speaking to one person while others spent weeks researching different providers. In contrast, when we ask this question on a 1 to 5 scale on a survey, most people didn’t end up choosing answers far off from center, and we ended up with a mean of 3.4.
How do you design based on a mean of 3.4? I’ve learned we can’t. That’s why I design surveys with max-diff question-types to force people to answer what is most or least important. I create binary answer choices. I avoid likert scales. This helps me capture the differences in diverse needs and opinions. I then follow-up with respondents to hear their stories and understand the full context for design.
But all this is moot if people don’t want to take the survey. I believe we get better data when people are engaged. I don’t want people to feel like we are thoughtlessly extracting personal information from them. I’d prefer to frame everything as a conversation, like one you’d have with a friend.
Let data feed design
Data is multifaceted. It is both an input and an output to the design process. It is a tool to learn from like a survey; and a material in which a product can be molded like Facebook. Too often data is only being considered an output, the exhaust companies tap to evaluate product performance.
I’m excited at the prospect of data becoming something more — for design to fully embrace data as a medium. I think that when designers start recognizing that data are people, we can start thinking about collecting, incorporating and analyzing data in new ways. Data will enable designers to ask smarter questions, understand people in new ways, create fundamental new value, and evolve an evidence-based process that adds an invaluable capability to our industry.
I’m excited to see where this conversation takes us, and look forward to seeing how the fields of design and data continue to grow together.
This is just the beginning.
Special thanks to IDEO colleagues Tina Barseghian, Zena Barakat, and Iain Roberts for helping me with this article.
