Blog

This Person Does Not Exist is a website that generates human faces with a machine learning algorithm. It takes real portraits and recombines them into fake human faces. We recently scrolled past a LinkedIn post stating that this website could be useful “if you are developing a persona and looking for a photo.” 

We agree: the computer-generated faces could be a great match for personas—but not for the reason you might think. Ironically, the website highlights the core issue of this very common design method: the person(a) does not exist. Like the pictures, personas are artificially made. Information is taken out of natural context and recombined into an isolated snapshot that’s detached from reality. 

But strangely enough, designers use personas to inspire their design for the real world. 

Personas: A step back

Most designers have created, used, or come across personas at least once in their career. In their article “Personas – A Simple Introduction,” the Interaction Design Foundation defines personas as “fictional characters, which you create based upon your research in order to represent the different user types that might use your service, product, site, or brand.” In their most complete expression, personas typically consist of a name, profile picture, quotes, demographics, goals, needs, behavior in relation to a certain service/product, emotions, and motivations (for example, see Creative Companion’s Persona Core Poster). The purpose of personas, as stated by design agency Designit, is “to make the research relatable, [and] easy to communicate, digest, reference, and apply to product and service development.”

The decontextualization of personas

Personas are popular because they make “dry” research data more relatable, more human. However, this method constrains the researcher’s data analysis in such a way that the investigated users are removed from their unique contexts. As a result, personas don’t portray key factors that make you understand their decision-making process or allow you to relate to users’ thoughts and behavior; they lack stories. You understand what the persona did, but you don’t have the background to understand why. You end up with representations of users that are actually less human.

This “decontextualization” we see in personas happens in four ways, which we’ll explain below. 

Personas assume people are static 

Although many companies still try to box in their employees and customers with outdated personality tests (referring to you, Myers-Briggs), here’s a painfully obvious truth: people are not a fixed set of features. You act, think, and feel differently according to the situations you experience. You appear different to different people; you might act friendly to some, rough to others. And you change your mind all the time about decisions you’ve taken. 

Modern psychologists agree that while people generally behave according to certain patterns, it’s actually a combination of background and environment that determines how people act and take decisions. The context—the environment, the influence of other people, your mood, the entire history that led up to a situation—determines the kind of person you are in each specific moment. 

In their attempt to simplify reality, personas do not take this variability into account; they present a user as a fixed set of features. Like personality tests, personas snatch people away from real life. Even worse, people are reduced to a label and categorized as “that kind of person” with no means to exercise their innate flexibility. This practice reinforces stereotypes, lowers diversity, and doesn’t reflect reality. 

Personas focus on individuals, not the environment

In the real world, you’re designing for a context, not for an individual. Each person lives in a family, a community, an ecosystem, where there are environmental, political, and social factors you need to consider. A design is never meant for a single user. Rather, you design for one or more particular contexts in which many people might use that product. Personas, however, show the user alone rather than describe how the user relates to the environment. 

Would you always make the same decision over and over again? Maybe you’re a committed vegan but still decide to buy some meat when your relatives are coming over. As they depend on different situations and variables, your decisions—and behavior, opinions, and statements—are not absolute but highly contextual. The persona that “represents” you wouldn’t take into account this dependency, because it doesn’t specify the premises of your decisions. It doesn’t provide a justification of why you act the way you do. Personas enact the well-known bias called fundamental attribution error: explaining others’ behavior too much by their personality and too little by the situation.

As mentioned by the Interaction Design Foundation, personas are usually placed in a scenario that’s a “specific context with a problem they want to or have to solve”—does that mean context actually is considered? Unfortunately, what often happens is that you take a fictional character and based on that fiction determine how this character might deal with a certain situation. This is made worse by the fact that you haven’t even fully investigated and understood the current context of the people your persona seeks to represent; so how could you possibly understand how they would act in new situations? 

Personas are meaningless averages

As mentioned in Shlomo Goltz’s introductory article on Smashing Magazine, “a persona is depicted as a specific person but is not a real individual; rather, it is synthesized from observations of many people.” A well-known critique to this aspect of personas is that the average person does not exist, as per the famous example of the USA Air Force designing planes based on the average of 140 of their pilots’ physical dimensions and not a single pilot actually fitting within that average seat. 

The same limitation applies to mental aspects of people. Have you ever heard a famous person say, “They took what I said out of context! They used my words, but I didn’t mean it like that.” The celebrity’s statement was reported literally, but the reporter failed to explain the context around the statement and didn’t describe the non-verbal expressions. As a result, the intended meaning was lost. You do the same when you create personas: you collect somebody’s statement (or goal, or need, or emotion), of which the meaning can only be understood if you provide its own specific context, yet report it as an isolated finding. 

But personas go a step further, extracting a decontextualized finding and joining it with another decontextualized finding from somebody else. The resulting set of findings often does not make sense: it’s unclear, or even contrasting, because it lacks the underlying reasons on why and how that finding has arisen. It lacks meaning. And the persona doesn’t give you the full background of the person(s) to uncover this meaning: you would need to dive into the raw data for each single persona item to find it. What, then, is the usefulness of the persona?

The relatability of personas is deceiving

To a certain extent, designers realize that a persona is a lifeless average. To overcome this, designers invent and add “relatable” details to personas to make them resemble real individuals. Nothing captures the absurdity of this better than a sentence by the Interaction Design Foundation: “Add a few fictional personal details to make the persona a realistic character.” In other words, you add non-realism in an attempt to create more realism. You deliberately obscure the fact that “John Doe” is an abstract representation of research findings; but wouldn’t it be much more responsible to emphasize that John is only an abstraction? If something is artificial, let’s present it as such.

It’s the finishing touch of a persona’s decontextualization: after having assumed that people’s personalities are fixed, dismissed the importance of their environment, and hidden meaning by joining isolated, non-generalizable findings, designers invent new context to create (their own) meaning. In doing so, as with everything they create, they introduce a host of biases. As phrased by Designit, as designers we can “contextualize [the persona] based on our reality and experience. We create connections that are familiar to us.” This practice reinforces stereotypes, doesn’t reflect real-world diversity, and gets further away from people’s actual reality with every detail added. 

To do good design research, we should report the reality “as-is” and make it relatable for our audience, so everyone can use their own empathy and develop their own interpretation and emotional response.

Dynamic Selves: The alternative to personas

If we shouldn’t use personas, what should we do instead? 

Designit has proposed using Mindsets instead of personas. Each Mindset is a “spectrum of attitudes and emotional responses that different people have within the same context or life experience.” It challenges designers to not get fixated on a single user’s way of being. Unfortunately, while being a step in the right direction, this proposal doesn’t take into account that people are part of an environment that determines their personality, their behavior, and, yes, their mindset. Therefore, Mindsets are also not absolute but change in regard to the situation. The question remains, what determines a certain Mindset?

Another alternative comes from Margaret P., author of the article “Kill Your Personas,” who has argued for replacing personas with persona spectrums that consist of a range of user abilities. For example, a visual impairment could be permanent (blindness), temporary (recovery from eye surgery), or situational (screen glare). Persona spectrums are highly useful for more inclusive and context-based design, as they’re based on the understanding that the context is the pattern, not the personality. Their limitation, however, is that they have a very functional take on users that misses the relatability of a real person taken from within a spectrum. 

In developing an alternative to personas, we aim to transform the standard design process to be context-based. Contexts are generalizable and have patterns that we can identify, just like we tried to do previously with people. So how do we identify these patterns? How do we ensure truly context-based design? 

Understand real individuals in multiple contexts

Nothing is more relatable and inspiring than reality. Therefore, we have to understand real individuals in their multi-faceted contexts, and use this understanding to fuel our design. We refer to this approach as Dynamic Selves.

Let’s take a look at what the approach looks like, based on an example of how one of us applied it in a recent project that researched habits of Italians around energy consumption. We drafted a design research plan aimed at investigating people’s attitudes toward energy consumption and sustainable behavior, with a focus on smart thermostats. 

1. Choose the right sample

When we argue against personas, we’re often challenged with quotes such as “Where are you going to find a single person that encapsulates all the information from one of these advanced personas[?]” The answer is simple: you don’t have to. You don’t need to have information about many people for your insights to be deep and meaningful. 

In qualitative research, validity does not derive from quantity but from accurate sampling. You select the people that best represent the “population” you’re designing for. If this sample is chosen well, and you have understood the sampled people in sufficient depth, you’re able to infer how the rest of the population thinks and behaves. There’s no need to study seven Susans and five Yuriys; one of each will do. 

Similarly, you don’t need to understand Susan in fifteen different contexts. Once you’ve seen her in a couple of diverse situations, you’ve understood the scheme of Susan’s response to different contexts. Not Susan as an atomic being but Susan in relation to the surrounding environment: how she might act, feel, and think in different situations. 

Given that each person is representative of a part of the total population you’re researching, it becomes clear why each should be represented as an individual, as each already is an abstraction of a larger group of individuals in similar contexts. You don’t want abstractions of abstractions! These selected people need to be understood and shown in their full expression, remaining in their microcosmos—and if you want to identify patterns you can focus on identifying patterns in contexts.

Yet the question remains: how do you select a representative sample? First of all, you have to consider what’s the target audience of the product or service you are designing: it might be useful to look at the company’s goals and strategy, the current customer base, and/or a possible future target audience. 

In our example project, we were designing an application for those who own a smart thermostat. In the future, everyone could have a smart thermostat in their house. Right now, though, only early adopters own one. To build a significant sample, we needed to understand the reason why these early adopters became such. We therefore recruited by asking people why they had a smart thermostat and how they got it. There were those who had chosen to buy it, those who had been influenced by others to buy it, and those who had found it in their house. So we selected representatives of these three situations, from different age groups and geographical locations, with an equal balance of tech savvy and non-tech savvy participants. 

2. Conduct your research

After having chosen and recruited your sample, conduct your research using ethnographic methodologies. This will make your qualitative data rich with anecdotes and examples. In our example project, given COVID-19 restrictions, we converted an in-house ethnographic research effort into remote family interviews, conducted from home and accompanied by diary studies.

To gain an in-depth understanding of attitudes and decision-making trade-offs, the research focus was not limited to the interviewee alone but deliberately included the whole family. Each interviewee would tell a story that would then become much more lively and precise with the corrections or additional details coming from wives, husbands, children, or sometimes even pets. We also focused on the relationships with other meaningful people (such as colleagues or distant family) and all the behaviors that resulted from those relationships. This wide research focus allowed us to shape a vivid mental image of dynamic situations with multiple actors. 

It’s essential that the scope of the research remains broad enough to be able to include all possible actors. Therefore, it normally works best to define broad research areas with macro questions. Interviews are best set up in a semi-structured way, where follow-up questions will dive into topics mentioned spontaneously by the interviewee. This open-minded “plan to be surprised” will yield the most insightful findings. When we asked one of our participants how his family regulated the house temperature, he replied, “My wife has not installed the thermostat’s app—she uses WhatsApp instead. If she wants to turn on the heater and she is not home, she will text me. I am her thermostat.”

3. Analysis: Create the Dynamic Selves

During the research analysis, you start representing each individual with multiple Dynamic Selves, each “Self” representing one of the contexts you have investigated. The core of each Dynamic Self is a quote, which comes supported by a photo and a few relevant demographics that illustrate the wider context. The research findings themselves will show which demographics are relevant to show. In our case, as our research focused on families and their lifestyle to understand their needs for thermal regulation, the important demographics were family type, number and nature of houses owned, economic status, and technological maturity. (We also included the individual’s name and age, but they’re optional—we included them to ease the stakeholders’ transition from personas and be able to connect multiple actions and contexts to the same person).

To capture exact quotes, interviews need to be video-recorded and notes need to be taken verbatim as much as possible. This is essential to the truthfulness of the several Selves of each participant. In the case of real-life ethnographic research, photos of the context and anonymized actors are essential to build realistic Selves. Ideally, these photos should come directly from field research, but an evocative and representative image will work, too, as long as it’s realistic and depicts meaningful actions that you associate with your participants. For example, one of our interviewees told us about his mountain home where he used to spend every weekend with his family. Therefore, we portrayed him hiking with his little daughter. 

At the end of the research analysis, we displayed all of the Selves’ “cards” on a single canvas, categorized by activities. Each card displayed a situation, represented by a quote and a unique photo. All participants had multiple cards about themselves.

4. Identify design opportunities

Once you have collected all main quotes from the interview transcripts and diaries, and laid them all down as Self cards, you will see patterns emerge. These patterns will highlight the opportunity areas for new product creation, new functionalities, and new services—for new design. 

In our example project, there was a particularly interesting insight around the concept of humidity. We realized that people don’t know what humidity is and why it is important to monitor it for health: an environment that’s too dry or too wet can cause respiratory problems or worsen existing ones. This highlighted a big opportunity for our client to educate users on this concept and become a health advisor.

Benefits of Dynamic Selves

When you use the Dynamic Selves approach in your research, you start to notice unique social relations, peculiar situations real people face and the actions that follow, and that people are surrounded by changing environments. In our thermostat project, we have come to know one of the participants, Davide, as a boyfriend, dog-lover, and tech enthusiast. 

Davide is an individual we might have once reduced to a persona called “tech enthusiast.” But we can have tech enthusiasts who have families or are single, who are rich or poor. Their motivations and priorities when deciding to purchase a new thermostat can be opposite according to these different frames. 

Once you have understood Davide in multiple situations, and for each situation have understood in sufficient depth the underlying reasons for his behavior, you’re able to generalize how he would act in another situation. You can use your understanding of him to infer what he would think and do in the contexts (or scenarios) that you design for.

The Dynamic Selves approach aims to dismiss the conflicted dual purpose of personas—to summarize and empathize at the same time—by separating your research summary from the people you’re seeking to empathize with. This is important because our empathy for people is affected by scale: the bigger the group, the harder it is to feel empathy for others. We feel the strongest empathy for individuals we can personally relate to.  

If you take a real person as inspiration for your design, you no longer need to create an artificial character. No more inventing details to make the character more “realistic,” no more unnecessary additional bias. It’s simply how this person is in real life. In fact, in our experience, personas quickly become nothing more than a name in our priority guides and prototype screens, as we all know that these characters don’t really exist. 

Another powerful benefit of the Dynamic Selves approach is that it raises the stakes of your work: if you mess up your design, someone real, a person you and the team know and have met, is going to feel the consequences. It might stop you from taking shortcuts and will remind you to conduct daily checks on your designs.

And finally, real people in their specific contexts are a better basis for anecdotal storytelling and therefore are more effective in persuasion. Documentation of real research is essential in achieving this result. It adds weight and urgency behind your design arguments: “When I met Alessandra, the conditions of her workplace struck me. Noise, bad ergonomics, lack of light, you name it. If we go for this functionality, I’m afraid we’re going to add complexity to her life.”

Conclusion

Designit mentioned in their article on Mindsets that “design thinking tools offer a shortcut to deal with reality’s complexities, but this process of simplification can sometimes flatten out people’s lives into a few general characteristics.” Unfortunately, personas have been culprits in a crime of oversimplification. They are unsuited to represent the complex nature of our users’ decision-making processes and don’t account for the fact that humans are immersed in contexts. 

Design needs simplification but not generalization. You have to look at the research elements that stand out: the sentences that captured your attention, the images that struck you, the sounds that linger. Portray those, use them to describe the person in their multiple contexts. Both insights and people come with a context; they cannot be cut from that context because it would remove meaning. 

It’s high time for design to move away from fiction, and embrace reality—in its messy, surprising, and unquantifiable beauty—as our guide and inspiration.

Are you like me, reading about people fading away as they burn out, and feeling unable to relate? Do you feel like your feelings are invisible to the world because you’re experiencing burnout differently? When burnout starts to push down on us, our core comes through more. Beautiful, peaceful souls get quieter and fade into that distant and distracted burnout we’ve all read about. But some of us, those with fires always burning on the edges of our core, get hotter. In my heart I am fire. When I face burnout I double down, triple down, burning hotter and hotter to try to best the challenge. I don’t fade—I am engulfed in a zealous burnout. 

So what on earth is a zealous burnout?

Imagine a woman determined to do it all. She has two amazing children whom she, along with her husband who is also working remotely, is homeschooling during a pandemic. She has a demanding client load at work—all of whom she loves. She gets up early to get some movement in (or often catch up on work), does dinner prep as the kids are eating breakfast, and gets to work while positioning herself near “fourth grade” to listen in as she juggles clients, tasks, and budgets. Sound like a lot? Even with a supportive team both at home and at work, it is. 

Sounds like this woman has too much on her plate and needs self-care. But no, she doesn’t have time for that. In fact, she starts to feel like she’s dropping balls. Not accomplishing enough. There’s not enough of her to be here and there; she is trying to divide her mind in two all the time, all day, every day. She starts to doubt herself. And as those feelings creep in more and more, her internal narrative becomes more and more critical.

Suddenly she KNOWS what she needs to do! She should DO MORE. 

This is a hard and dangerous cycle. Know why? Because once she doesn’t finish that new goal, that narrative will get worse. Suddenly she’s failing. She isn’t doing enough. SHE is not enough. She might fail, she might fail her family…so she’ll find more she should do. She doesn’t sleep as much, move as much, all in the efforts to do more. Caught in this cycle of trying to prove herself to herself, never reaching any goal. Never feeling “enough.” 

So, yeah, that’s what zealous burnout looks like for me. It doesn’t happen overnight in some grand gesture but instead slowly builds over weeks and months. My burning out process looks like speeding up, not a person losing focus. I speed up and up and up…and then I just stop.

I am the one who could

It’s funny the things that shape us. Through the lens of childhood, I viewed the fears, struggles, and sacrifices of someone who had to make it all work without having enough. I was lucky that my mother was so resourceful and my father supportive; I never went without and even got an extra here or there. 

Growing up, I did not feel shame when my mother paid with food stamps; in fact, I’d have likely taken on any debate on the topic, verbally eviscerating anyone who dared to criticize the disabled woman trying to make sure all our needs were met with so little. As a child, I watched the way the fear of not making those ends meet impacted people I love. As the non-disabled person in my home, I would take on many of the physical tasks because I was “the one who could” make our lives a little easier. I learned early to associate fears or uncertainty with putting more of myself into it—I am the one who can. I learned early that when something frightens me, I can double down and work harder to make it better. I can own the challenge. When people have seen this in me as an adult, I’ve been told I seem fearless, but make no mistake, I’m not. If I seem fearless, it’s because this behavior was forged from other people’s fears. 

And here I am, more than 30 years later still feeling the urge to mindlessly push myself forward when faced with overwhelming tasks ahead of me, assuming that I am the one who can and therefore should. I find myself driven to prove that I can make things happen if I work longer hours, take on more responsibility, and do more. 

I do not see people who struggle financially as failures, because I have seen how strong that tide can be—it pulls you along the way. I truly get that I have been privileged to be able to avoid many of the challenges that were present in my youth. That said, I am still “the one who can” who feels she should, so if I were faced with not having enough to make ends meet for my own family, I would see myself as having failed. Though I am supported and educated, most of this is due to good fortune. I will, however, allow myself the arrogance of saying I have been careful with my choices to have encouraged that luck. My identity stems from the idea that I am “the one who can” so therefore feel obligated to do the most. I can choose to stop, and with some quite literal cold water splashed in my face, I’ve made the choice to before. But that choosing to stop is not my go-to; I move forward, driven by a fear that is so a part of me that I barely notice it’s there until I’m feeling utterly worn away.

So why all the history? You see, burnout is a fickle thing. I have heard and read a lot about burnout over the years. Burnout is real. Especially now, with COVID, many of us are balancing more than we ever have before—all at once! It’s hard, and the procrastinating, the avoidance, the shutting down impacts so many amazing professionals. There are important articles that relate to what I imagine must be the majority of people out there, but not me. That’s not what my burnout looks like.

The dangerous invisibility of zealous burnout

A lot of work environments see the extra hours, extra effort, and overall focused commitment as an asset (and sometimes that’s all it is). They see someone trying to rise to challenges, not someone stuck in their fear. Many well-meaning organizations have safeguards in place to protect their teams from burnout. But in cases like this, those alarms are not always tripped, and then when the inevitable stop comes, some members of the organization feel surprised and disappointed. And sometimes maybe even betrayed. 

Parents—more so mothers, statistically speaking—are praised as being so on top of it all when they can work, be involved in the after-school activities, practice self-care in the form of diet and exercise, and still meet friends for coffee or wine. During COVID many of us have binged countless streaming episodes showing how it’s so hard for the female protagonist, but she is strong and funny and can do it. It’s a “very special episode” when she breaks down, cries in the bathroom, woefully admits she needs help, and just stops for a bit. Truth is, countless people are hiding their tears or are doom-scrolling to escape. We know that the media is a lie to amuse us, but often the perception that it’s what we should strive for has penetrated much of society.

Women and burnout

I love men. And though I don’t love every man (heads up, I don’t love every woman or nonbinary person either), I think there is a beautiful spectrum of individuals who represent that particular binary gender. 

That said, women are still more often at risk of burnout than their male counterparts, especially in these COVID stressed times. Mothers in the workplace feel the pressure to do all the “mom” things while giving 110%. Mothers not in the workplace feel they need to do more to “justify” their lack of traditional employment. Women who are not mothers often feel the need to do even more because they don’t have that extra pressure at home. It’s vicious and systemic and so a part of our culture that we’re often not even aware of the enormity of the pressures we put on ourselves and each other. 

And there are prices beyond happiness too. Harvard Health Publishing released a study a decade ago that “uncovered strong links between women’s job stress and cardiovascular disease.” The CDC noted, “Heart disease is the leading cause of death for women in the United States, killing 299,578 women in 2017—or about 1 in every 5 female deaths.” 

This relationship between work stress and health, from what I have read, is more dangerous for women than it is for their non-female counterparts.

But what if your burnout isn’t like that either?

That might not be you either. After all, each of us is so different and how we respond to stressors is too. It’s part of what makes us human. Don’t stress what burnout looks like, just learn to recognize it in yourself. Here are a few questions I sometimes ask friends if I am concerned about them.

Are you happy? This simple question should be the first thing you ask yourself. Chances are, even if you’re burning out doing all the things you love, as you approach burnout you’ll just stop taking as much joy from it all.

Do you feel empowered to say no? I have observed in myself and others that when someone is burning out, they no longer feel they can say no to things. Even those who don’t “speed up” feel pressure to say yes to not disappoint the people around them.

What are three things you’ve done for yourself? Another observance is that we all tend to stop doing things for ourselves. Anything from skipping showers and eating poorly to avoiding talking to friends. These can be red flags. 

Are you making excuses? Many of us try to disregard feelings of burnout. Over and over I have heard, “It’s just crunch time,” “As soon as I do this one thing, it will all be better,” and “Well I should be able to handle this, so I’ll figure it out.” And it might really be crunch time, a single goal, and/or a skill set you need to learn. That happens—life happens. BUT if this doesn’t stop, be honest with yourself. If you’ve worked more 50-hour weeks since January than not, maybe it’s not crunch time—maybe it’s a bad situation that you’re burning out from.

Do you have a plan to stop feeling this way? If something is truly temporary and you do need to just push through, then it has an exit route with a
defined end.

Take the time to listen to yourself as you would a friend. Be honest, allow yourself to be uncomfortable, and break the thought cycles that prevent you from healing. 

So now what?

What I just described is a different path to burnout, but it’s still burnout. There are well-established approaches to working through burnout:

• Get enough sleep.
• Eat healthy.
• Work out.
• Get outside.
• Take a break.
• Overall, practice self-care.

Those are hard for me because they feel like more tasks. If I’m in the burnout cycle, doing any of the above for me feels like a waste. The narrative is that if I’m already failing, why would I take care of myself when I’m dropping all those other balls? People need me, right? 

If you’re deep in the cycle, your inner voice might be pretty awful by now. If you need to, tell yourself you need to take care of the person your people depend on. If your roles are pushing you toward burnout, use them to help make healing easier by justifying the time spent working on you. 

To help remind myself of the airline attendant message about putting the mask on yourself first, I have come up with a few things that I do when I start feeling myself going into a zealous burnout.

Cook an elaborate meal for someone! 

OK, I am a “food-focused” individual so cooking for someone is always my go-to. There are countless tales in my home of someone walking into the kitchen and turning right around and walking out when they noticed I was “chopping angrily.” But it’s more than that, and you should give it a try. Seriously. It’s the perfect go-to if you don’t feel worthy of taking time for yourself—do it for someone else. Most of us work in a digital world, so cooking can fill all of your senses and force you to be in the moment with all the ways you perceive the world. It can break you out of your head and help you gain a better perspective. In my house, I’ve been known to pick a place on the map and cook food that comes from wherever that is (thank you, Pinterest). I love cooking Indian food, as the smells are warm, the bread needs just enough kneading to keep my hands busy, and the process takes real attention for me because it’s not what I was brought up making. And in the end, we all win!

Vent like a foul-mouthed fool

Be careful with this one! 

I have been making an effort to practice more gratitude over the past few years, and I recognize the true benefits of that. That said, sometimes you just gotta let it all out—even the ugly. Hell, I’m a big fan of not sugarcoating our lives, and that sometimes means that to get past the big pile of poop, you’re gonna wanna complain about it a bit. 

When that is what’s needed, turn to a trusted friend and allow yourself some pure verbal diarrhea, saying all the things that are bothering you. You need to trust this friend not to judge, to see your pain, and, most importantly, to tell you to remove your cranium from your own rectal cavity. Seriously, it’s about getting a reality check here! One of the things I admire the most about my husband (though often after the fact) is his ability to break things down to their simplest. “We’re spending our lives together, of course you’re going to disappoint me from time to time, so get over it” has been his way of speaking his dedication, love, and acceptance of me—and I could not be more grateful. It also, of course, has meant that I needed to remove my head from that rectal cavity. So, again, usually those moments are appreciated in hindsight.

Pick up a book! 

There are many books out there that aren’t so much self-help as they are people just like you sharing their stories and how they’ve come to find greater balance. Maybe you’ll find something that speaks to you. Titles that have stood out to me include:

• Thrive by Arianna Huffington
• Tools of Titans by Tim Ferriss
• Girl, Stop Apologizing by Rachel Hollis
• Dare to Lead by Brené Brown

Or, another tactic I love to employ is to read or listen to a book that has NOTHING to do with my work-life balance. I’ve read the following books and found they helped balance me out because my mind was pondering their interesting topics instead of running in circles:

• The Drunken Botanist by Amy Stewart
• Superlife by Darin Olien
• A Brief History of Everyone Who Ever Lived by Adam Rutherford
• Gaia’s Garden by Toby Hemenway 

If you’re not into reading, pick up a topic on YouTube or choose a podcast to subscribe to. I’ve watched countless permaculture and gardening topics in addition to how to raise chickens and ducks. For the record, I do not have a particularly large food garden, nor do I own livestock of any kind…yet. I just find the topic interesting, and it has nothing to do with any aspect of my life that needs anything from me.

Forgive yourself 

You are never going to be perfect—hell, it would be boring if you were. It’s OK to be broken and flawed. It’s human to be tired and sad and worried. It’s OK to not do it all. It’s scary to be imperfect, but you cannot be brave if nothing were scary.

This last one is the most important: allow yourself permission to NOT do it all. You never promised to be everything to everyone at all times. We are more powerful than the fears that drive us. 

This is hard. It is hard for me. It’s what’s driven me to write this—that it’s OK to stop. It’s OK that your unhealthy habit that might even benefit those around you needs to end. You can still be successful in life.

I recently read that we are all writing our eulogy in how we live. Knowing that your professional accomplishments won’t be mentioned in that speech, what will yours say? What do you want it to say? 

Look, I get that none of these ideas will “fix it,” and that’s not their purpose. None of us are in control of our surroundings, only how we respond to them. These suggestions are to help stop the spiral effect so that you are empowered to address the underlying issues and choose your response. They are things that work for me most of the time. Maybe they’ll work for you.

Does this sound familiar? 

If this sounds familiar, it’s not just you. Don’t let your negative self-talk tell you that you “even burn out wrong.” It’s not wrong. Even if rooted in fear like my own drivers, I believe that this need to do more comes from a place of love, determination, motivation, and other wonderful attributes that make you the amazing person you are. We’re going to be OK, ya know. The lives that unfold before us might never look like that story in our head—that idea of “perfect” or “done” we’re looking for, but that’s OK. Really, when we stop and look around, usually the only eyes that judge us are in the mirror. 

Do you remember that Winnie the Pooh sketch that had Pooh eat so much at Rabbit’s house that his buttocks couldn’t fit through the door? Well, I already associate a lot with Rabbit, so it came as no surprise when he abruptly declared that this was unacceptable. But do you recall what happened next? He put a shelf across poor Pooh’s ankles and decorations on his back, and made the best of the big butt in his kitchen. 

At the end of the day we are resourceful and know that we are able to push ourselves if we need to—even when we are tired to our core or have a big butt of fluff ‘n’ stuff in our room. None of us has to be afraid, as we can manage any obstacle put in front of us. And maybe that means we will need to redefine success to allow space for being uncomfortably human, but that doesn’t really sound so bad either. 

So, wherever you are right now, please breathe. Do what you need to do to get out of your head. Forgive and take care.

One of the most successful soft skills we have at our disposal is opinions, in whatever form it takes, and whatever it may be called. It helps us collaborate to improve our designs while developing our own abilities and perspectives.

Feedback is also one of the most underestimated equipment, and generally by assuming that we’re already good at it, we settle, forgetting that it’s a talent that can be trained, grown, and improved. Bad comments can lead to conflict in projects, lower confidence, and long-term, undermine trust and teamwork. A revolutionary force can get quality feedback.

Practicing our knowledge is absolutely a good way to enhance, but the learning gets yet faster when it’s paired with a good base that programs and focuses the exercise. What are some fundamental components of providing effective opinions? And how can input be changed for workplaces where workers are located and distributed?

On the web, we may discover a long history of sequential suggestions: from the early weeks of open source, script was shared and discussed on email addresses. Designers and sprint masters discuss ideas on tickets, designers make comments in their favourite design tools, and so on.

Design criticism is frequently used as a term for a type of collaborative feedback that is provided to improve our work. So it shares a lot of the rules with comments in public, but it also has some variations.

The information

The content of the feedback serves as the foundation for every effective criticism, so we need to start there. There are many versions that you can use to design your content. This one from Lara Hogan is the one I privately like best because it’s obvious and actionable.

This calculation, which is typically used to provide feedback to users, even fits really well in a design critique because it finally addresses one of the main issues that we address: What? Where? Why? How? Imagine that you’re giving some comments about some pattern function that spans several screens, like an onboard movement: there are some pages shown, a stream blueprint, and an outline of the decisions made. You notice things that needs to be improved. You’ll have a psychological model that will enable you to get more accurate and effective if you keep in mind the three components of the equation.

Here is a reply that could be given as a part of some comments, and it might seem reasonable at a first glance: it seems to casually serve the elements in the equation. Does it, though?

Not sure about the hierarchy and styles of the buttons; it seems off. Can you change them?

Observation for design feedback also refers to providing a perspective that is as specific as possible, not just by pointing out which portion of the interface your feedback refers to. Do you offer the user’s viewpoint? Your expert perspective? From a business perspective? From the perspective of the project manager? A first-time user’s perspective?

I anticipate that one of these two buttons will go forward and the other will go back when I see them.

The why is the focus. Just pointing out a UI element might sometimes be enough if the issue may be obvious, but more often than not, you should add an explanation of what you’re pointing out.

I anticipate that one of these two buttons will go forward and the other will go back when I see them. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow.

The question approach is intended to give the designer some open guidance by provoking the designer’s critical thinking when they receive the feedback. Notably, Lara’s equation includes a second approach: request, which instead provides instructions for a particular solution. While that’s a viable option for feedback in general, for design critiques, in my experience, defaulting to the question approach usually reaches the best solutions because designers are generally more comfortable in being given an open space to explore.

For the question approach, consider the difference between the two:

I anticipate that one of these two buttons will go forward and the other will go back when I see them. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow. Would it make sense to unify them?

Or, for the request approach:

I anticipate that one of these two buttons will go forward and the other will go back when I see them. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow. Let’s make sure that all screens have the same pair of forward and back buttons.

In some situations, it might be helpful to include an additional reason why you think the suggestion is better at this point.

I anticipate that one of these two buttons will go forward and the other will go back when I see them. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow. Let’s make sure that all screens have the same two forward and back buttons so that users don’t get confused.

Choosing between the request and question approaches can occasionally be influenced by one’s personal preferences. I did rounds of anonymous feedback and reviewed feedback with other people before putting a lot of effort into improving it a while ago. After a few rounds of this work and a year later, I got a positive response: my feedback came across as effective and grounded. until I switched companies. Surprise surprise, one particular person gave me a lot of negative feedback. The reason is that I had previously tried not to be prescriptive in my advice—because the people who I was previously working with preferred the open-ended question format over the request style of suggestions. However, there was a person in this other team who had always preferred specific guidance. So I modified my feedback to include requests.

One comment that I heard come up a few times is that this kind of feedback is quite long, and it doesn’t seem very efficient. No, but also yes. Let’s look at both sides.

No, this style of feedback is actually efficient because the length here is a byproduct of clarity, and spending time giving this kind of feedback can provide exactly enough information for a good fix. Additionally, if we zoom out, it may lessen misunderstandings and back-and-forth conversations in the future, thereby increasing overall effectiveness and efficiency of collaboration beyond the single comment. Consider the example above where the feedback would be simply,” Let’s make sure that all screens have the same two forward and back buttons.” The designer receiving this feedback wouldn’t have much to go by, so they might just apply the change. In later iterations, the interface might change or new features might be introduced, and perhaps that change no longer makes sense. The designer might assume that the change is about consistency without the explanation, but what if it wasn’t? So there could now be an underlying concern that changing the buttons would be perceived as a regression.

Yes, this type of feedback is not always effective because some comments don’t always need to be thorough, some may be obvious because of the team’s internal knowledge, which may lead to some explanations of the whys.

Therefore, the equation above is intended to serve as a mnemonic to reflect and enhance the practice rather than a strict template for feedback. Even after years of active work on my critiques, I still from time to time go back to this formula and reflect on whether what I just wrote is effective.

The atmosphere

The foundation of feedback is well-rounded content, but that’s not really enough. The soft skills of the person who’s providing the critique can multiply the likelihood that the feedback will be well received and understood. It has been demonstrated that only positive feedback can lead to lasting change in people, and tone alone can determine whether content is rejected or welcomed.

Tone is crucial to work on because our goal is to be understood and have a positive working environment. Over the years, I’ve tried to summarize the required soft skills in a formula that mirrors the one for content: the receptivity equation.

Respectful feedback comes across as constructive, solid, and grounded. It’s the kind of feedback that, regardless of whether it’s positive or negative, is thought to be useful and fair.

Timing refers to when the feedback happens. If given at the wrong time, to-the-point feedback has little chance of receiving well. If a new feature’s entire high-level information architecture is about to go live when it’s about to be released, it might still be relevant if that questioning raises a significant blocker that no one saw, but those concerns are much more likely to have to wait for a later revision. So in general, attune your feedback to the stage of the project. Early iteration? Iteration that was later? Polishing work in progress? Each of these needs a different one. Your feedback will be received favorably if the right timing is chosen.

Attitude is the equivalent of intent, and in the context of person-to-person feedback, it can be referred to as radical candor. Before writing, it’s important to make sure the person we’re writing will actually benefit them and improve the overall project. Sometimes it might be difficult to reflect on this because we might not want to admit our deep appreciation for that person. Hopefully that’s not the case, but that can happen, and that’s okay. How would I write if I really cared about them? Acknowledging that and owning that can help you make up for it. How can I stop acting aggressively? How can I be more constructive?

Form is important in multicultural and cross-cultural workplaces because having excellent writing, perfect timing, and the right attitude might not be as effective if the writing style leads to miscommunications. There could be many reasons for this, including the fact that occasionally certain words may cause specific reactions, that non-native speakers may not be able to comprehend all thenuances of some sentences, that our brains may be different, and that we may perceive the world differently. Neurodiversity is a requirement. Whatever the reason, it’s important to review not just what we write but how.

I asked for some feedback on how I gave it a while back. I was given some helpful advice, but I also found a surprise in my comment. They pointed out that when I wrote” Oh, ]… ]”, I made them feel stupid. That wasn’t my intention at all! I just realized that I had been giving them feedback for months and that I had always made them feel foolish. I was horrified … but also thankful. I quickly changed my situation by adding “oh” to my list of replaced words (your choice between aText, TextExpander, or others ) so that when I typed “oh,” it was immediately deleted.

Something to keep in mind is that people frequently beat around the bush, especially in teams with strong group spirit. It’s important to remember here that a positive attitude doesn’t mean going light on the feedback—it just means that even when you provide hard, difficult, or challenging feedback, you do so in a way that’s respectful and constructive. The best thing you can do for someone is to encourage their growth.

Giving feedback in written form can be reviewed by someone else who isn’t directly involved, which can help to reduce or eliminate any bias that might exist. I found that the best, most insightful moments for me have happened when I’ve shared a comment and I’ve asked someone who I highly trusted,” How does this sound”?,” How can I do it better”, and even” How would you have written it” ?—and I’ve learned a lot by seeing the two versions side by side.

The format

Asynchronous feedback also has a significant inherent benefit: we can devote more time to making sure that the suggestions ‘ clarity of communication and actionability meet two main objectives.

Let’s imagine that someone shared a design iteration for a project. You are commenting on it while reviewing it. There are many ways to accomplish this, and context is of course important, but let’s try to think about some things that might be worthwhile to take into account.

In terms of clarity, start by grounding the critique that you’re about to give by providing context. This includes specifically describing where you’re coming from: do you know the project well, or do you just see it for the first time? Are you bringing in a high-level perspective, or are you just learning the ins and outs? Are there regressions? Which user’s point of view are you addressing when offering feedback? Is the design iteration at the point where it would be acceptable to ship this, or are there important issues that need to be addressed first?

Providing context is helpful even if you’re sharing feedback within a team that already has some information on the project. And context is a must when providing cross-team feedback. If I were to review a design that might be directly connected to my work, and if I had no idea how the project might have come to that conclusion, I would say so, highlighting my opinion as external.

We often focus on the negatives, trying to outline all the things that could be done better. That is obviously important, but focusing on the positives, especially if you saw improvement in the previous iteration, is even more crucial. Although this may seem superfluous, it’s important to keep in mind that design is a field with hundreds of possible solutions for each problem. So pointing out that the design solution that was chosen is good and explaining why it’s good has two major benefits: it confirms that the approach taken was solid, and it helps to ground your negative feedback. Sharing positive feedback can help prevent regressions in the long run because those things will have been identified as crucial. Positive feedback can also help, as an added bonus, prevent impostor syndrome.

There’s one powerful approach that combines both context and a focus on the positives: frame how the design is better than the status quo ( compared to a previous iteration, competitors, or benchmarks ) and why, and then on that foundation, you can add what could be improved. There is a significant difference between a critique of a design that is already in good shape and one that isn’t quite there yet.

Depersonalizing your feedback is another way to make it better: it should never be about the creator of the piece of art. It’s” This button isn’t well aligned” versus” You haven’t aligned this button well”. This can be changed in your writing very quickly by reviewing it just before sending.

One of the best ways to assist the designer who is reading through your feedback in terms of actionability is to divide it into bullet points or paragraphs, which are simpler to review and analyze one by one. For longer pieces of feedback, you might also consider splitting it into sections or even across multiple comments. Of course, adding screenshots or identifying markers for the specific area of the interface you’re referring to can also be very helpful.

I’ve personally used emojis to enhance the bullet points in some situations. So a red square � � means that it’s something that I consider blocking, a yellow diamond � � is something that I can be convinced otherwise, but it seems to me that it should be changed, and a green circle � � is a detailed, positive confirmation. A blue spiral is also used for either an exploration, an open alternative, or just a note for something I’m not sure about. However, I’d only use this strategy on teams where I’ve already established a high level of trust because it might turn out to be quite demoralizing if I deliver a lot of red squares and change how I communicate that.

Let’s see how this would work by reusing the example that we used earlier as the first bullet point in this list:

• 🔶 Navigation—I anticipate that one of these two buttons will go forward and the other will go back when I see them. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow. Let’s make sure that all screens have the same two forward and back buttons so that users don’t get confused.
• Overall, I believe the page is strong, and this is a good candidate for our version 1. 1.0 release candidate.
• � � Metrics—Good improvement in the buttons on the metrics area, the improved contrast and new focus style make them more accessible.
• Button Style: Using the green accent in this context, which conveys a positive action because green is typically seen as a confirmation color. Do we need to look for a different shade?
• 🔶Tiles—Given the number of items on the page, and the overall page hierarchy, it seems to me that the tiles shouldn’t be using the Subtitle 1 style but the Subtitle 2 style. This will maintain consistency in the visual hierarchy.
• Background: A light texture is effective, but I’m not sure if doing so will cause too much noise on this kind of page. What is the thinking in using that?

What about using Figma or another design tool that allows in-place feedback to provide feedback directly in Figma? These are generally difficult to use because they conceal discussions and are harder to follow, but in the right setting, they can be very effective. Just make sure that each of the comments is separate so that it’s easier to match each discussion to a single task, similar to the idea of splitting mentioned above.

Say the obvious, please. Sometimes we might feel good or bad about something, so we don’t say it. Or sometimes we might have a doubt that we don’t express because the question might sound stupid. Say it, that’s fine. Don’t hold it back, though, because you might need to change the phrasing a little to make the reader feel more at ease. Good feedback is transparent, even when it may be obvious.

Another benefit of asynchronous feedback is that written feedback automatically monitors decisions. Why did we do this, especially in large projects? could be a question that pops up from time to time, and there’s nothing better than open, transparent discussions that can be reviewed at any time. I advise using software to save these discussions so they can be hidden once they are resolved, for this reason.

Content, tone, and format are all there. Each one of these subjects provides a useful model, but working to improve eight areas—observation, impact, question, timing, attitude, form, clarity, and actionability—is a lot of work to put in all at once. One effective way to approach them is to start with the area you lack the most, either from your point of view or from other people’s feedback. Then the second, followed by the third, and so on. At first you’ll have to put in extra time for every piece of feedback that you give, but after a while, it’ll become second nature, and your impact on the work will multiply.

Thanks to Mike Shelton and Brie Anne Demkiw for their contributions to the initial draft of this article.

” Any feedback?” is perhaps one of the worst ways to ask for opinions. It’s obscure and unfocused, and it doesn’t give a clear picture of what we’re looking for. Great comments begins sooner than we might anticipate: it begins with the demand.

It might seem contradictory to start the process of receiving feedback with a problem, but that makes sense if we realize that getting feedback can be thought of as a form of design study. The best way to ask for feedback is also to build strong questions, just like we wouldn’t do any studies without the correct questions to get the insight we need.

Design criticism is not a one-time procedure. Sure, any great comments process continues until the project is finished, but this is especially true for layout because architecture work continues iteration after iteration, from a high level to the finest details. Each stage requires its unique set of questions.

Finally, we need to review what we received, get to the heart of its findings, and taking action, as with any great research. Problem, generation, and evaluation. Let’s take a closer look at each of those.

The query

Being available to input is important, but we need to be specific about what we’re looking for. Any comments,” What do you think,” or” I’d love to hear your mind” at the end of a presentation are likely to garner a lot of different ideas, or worse, to make people follow the lead of the first speaker. And finally, we become irritated because ambiguous queries like those can result in people who won’t comment on the boundaries of keys during a high-level flows review. Which might be a savory matter, so it might be hard at that point to divert the crew to the topics that you had wanted to focus on.

But how do we enter this circumstance? It’s a combination of various components. One is that we don’t often consider asking as a part of the input approach. Another is how healthy it is to keep the issue open and assume that everyone else will agree. Another is that there are frequently no need to be that exact in nonprofessional dialogues. In short, we tend to underestimate the importance of the concerns, so we don’t work on improving them.

Great questioning helps to guide and concentrate the criticism. It’s even a form of acceptance because it specifies what kind of feedback you’d like to receive and how you’re open to them. It puts people in the right emotional position, especially in situations when they weren’t expecting to provide feedback.

There isn’t a second best way to ask for opinions. It simply needs to be certain, and precision can take a variety of forms. A design for design critique that I’ve found especially helpful in my training is the one of stage over depth.

The term” level” refers to each stage of the process, specifically the design phase. The type of input changes as the consumer research moves forward to the final design. But within a single stage, one might also examine whether some assumptions are correct and whether there’s been a suitable language of the amassed input into updated designs as the job has evolved. The levels of consumer experience may serve as a starting point for future inquiries. What are your job goals, exactly? User requirements? Funnality? the glad Contact design? Data infrastructure Interface design Navigation style? Visual layout packaging?

Here’re a some example questions that are specific and to the place that refer to different levels:

• Features: Is it appealing to automate accounts creation?
• Interaction style: Take a look at the updated flowing and let me know if there are any steps or mistake states I may have missed.
• Information structures: We have two competing bits of information on this site. Does the construction work to effectively communicate both of them?
• User interface design: What do you think about the top-of-the-page problem counter, which makes sure you can see the following error even when the error is outside the viewport?
• Navigation style: From study, we identified these second-level routing items, but when you’re on the webpage, the list feels overly long and hard to understand. Exist any recommendations for resolving this?
• Are the thick alerts in the bottom-right corner of the page clearly apparent enough?

The other plane of sensitivity is about how heavy you’d like to go on what’s being presented. For instance, we may have introduced a new end-to-end movement, but you might want to know more about a particular viewpoint you found especially hard. This can be especially helpful when switching between iterations because it’s crucial to identify the changes made.

There are other things that we can consider when we want to accomplish more specific—and more effective—questions.

Eliminating generic finals from your issues like “good,” “well,” “nice,” “bad,” “okay,” and” cool” is a simple strategy. Asking,” When the stop opens and the switches appear, is this conversation excellent, for instance?” may seem precise, but you can place the “good” tournament, and transfer it to an even better query:” When the stop opens and the buttons appear, is it clear what the next action is”?

Sometimes we do want a lot of feedback. Although that is uncommon, it is possible. In that sense, you might still make it explicit that you’re looking for a wide range of opinions, whether at a high level or with details. Or perhaps just say,” At first glance, what do you think”? so that it is obvious that what you’re asking is open ended but focused on a person’s impression after their first five seconds of inquiry.

Sometimes the project is particularly expansive, and some areas may have already been explored in detail. In these circumstances, it might be helpful to state explicitly that some parts are already locked in and aren’t accessible for feedback. Although it’s not something I’d recommend in general, I’ve found it helpful in avoiding getting back into rabbit holes like those that could lead to even more refinement if what’s important right now isn’t.

Asking specific questions can completely change the quality of the feedback that you receive. Even experienced designers will appreciate the clarity and efficiency gained from concentrating solely on what is required, and those with less refined critique skills will now be able to offer more actionable feedback. It can save a lot of time and frustration.

The iteration

The most widely visible aspect of the design process is probably the design iteration, which serves as a natural feedback loop. Many design tools have inline commenting, but many of them only display changes as a single fluid stream in the same file. In addition, these kinds of design tools automatically update shared UI components, make conversations disappear and require designs to always display the most recent version, unless these would-be useful features were manually disabled. The implied goal that these design tools seem to have is to arrive at just one final copy with all discussions closed, probably because they inherited patterns from how written documents are collaboratively edited. That approach to design critiques is probably not the best approach, but some teams might benefit from it even if I don’t want to be too prescriptive.

Create explicit checkpoints for discussion is the asynchronous design-critique strategy that I believe works the best. I’m going to use the term iteration post for this. It refers to a write-up or presentation of the design iteration that is followed by a discussion thread of some kind. Any platform that can accommodate this type of structure can use this. By the way, when I refer to a “write-up or presentation“, I’m including video recordings or other media too: as long as it’s asynchronous, it works.

There are many benefits to using iteration posts:

It establishes a rhythm in the design process, allowing the designer to review the feedback from each iteration and get ready for the following.
• It makes decisions visible for future review, and conversations are likewise always available.
• It keeps track of how the design evolved over time.
• It might also make it simpler to collect and act on feedback depending on the tool.

These posts of course don’t mean that no other feedback approach should be used, just that iteration posts could be the primary rhythm for a remote design team to use. From there, there can be additional feedback techniques ( such as live critique, pair designing, or inline comments ).

There isn’t, in my opinion, a universal format for iteration posts. But there are a few high-level elements that make sense to include as a baseline:

1. The objective is.
2. The layout
3. The list of changes
4. The querys

A goal for each project is likely to be one that has already been condensed into a single sentence, such as the request for the project owner, the product manager, or the client brief. So this is something that I’d repeat in every iteration post—literally copy and pasting it. The goal is to provide context and repeat what is necessary to complete each iteration post so that there is no need to search for information in different posts. The most recent iteration post will provide all I need to know about the most recent design.

This copy-and-paste part introduces another relevant concept: alignment comes from repetition. Therefore, repeating information in posts is actually very effective at ensuring that everyone is on the same page.

The actual series of information-architecture outlines, diagrams, flows, maps, wireframes, screens, visuals, and any other design work that has been done is what the design is then called. In short, it’s any design artifact. In the final stages of the project, I prefer to use the term “blank” to indicate that I’ll be displaying complete flows rather than individual screens to make it simpler to comprehend the larger picture.

It might also be helpful to have clear names on the artifacts so that it is easier to refer to them. Write the post in a way that helps people understand the work. It’s not very different from creating a strong live presentation.

A bullet list of the changes made in the previous iteration should also be included for a successful discussion so that attendees can concentrate on what’s changed. This is especially useful for larger works of work where keeping track, iteration after iteration, might prove difficult.

And finally, as noted earlier, it’s essential that you include a list of the questions to drive the design critique in the direction you want. Creating a numbered list of questions can also make it simpler to refer to each one by its number.

Not every iteration is the same. Earlier iterations don’t need to be as tightly focused—they can be more exploratory and experimental, maybe even breaking some of the design-language guidelines to see what’s possible. Then, later, the iterations begin coming to a decision and improving it until the design process is complete and the feature is ready.

Even if these iteration posts are written and intended as checkpoints, I want to point out that they are not by any means required to be exhaustive. A post might be a draft—just a concept to get a conversation going—or it could be a cumulative list of each feature that was added over the course of each iteration until the full picture is done.

I eventually started using particular labels for incremental iterations, such as i1, i2, i3, and so on. Although this may seem like a minor labeling tip, it can be useful in many ways:

• Unique—It’s a clear unique marker. One can quickly say,” This was discussed in i4″ with each project, and everyone knows where to go to review things.
• Unassuming—It functions like versions ( such as v1, v2, and v3 ), but versions give the impression of something that is large, exhaustive, and complete. Iterations must be able to be exploratory, incomplete, partial.
• Future proof—It resolves the “final” naming issue that versions can encounter. No more files with the title “final final complete no-really-its-done” Within each project, the largest number always represents the latest iteration.

The wording release candidate (RC ) could be used to indicate when a design is finished enough to be worked on, even if there are some bits that still need work and, in turn, need more iterations:” with i8 we reached RC” or “i12 is an RC” to illustrate this.

The evaluation

What usually happens during a design critique is an open discussion, with a back and forth between people that can be very productive. This strategy is particularly successful when receiving live, synchronous feedback. However, when we work asynchronously, using a different approach is more effective: we can adopt a user-research mindset. Written feedback from teammates, stakeholders, or others can be treated as if it were the result of user interviews and surveys, and we can analyze it accordingly.

Asynchronous feedback is particularly effective around these friction points because of this shift’s significant benefits:

It lessens the need to respond to everyone.
1. It reduces the frustration from swoop-by comments.
2. It lessens our own worth.

The first friction point is having to feel pressured to respond to each and every comment. Sometimes we write the iteration post, and we get replies from our team. It’s simple, straightforward, and doesn’t cause any issues. Sometimes, however, some solutions may require more in-depth discussions, and the number of responses can quickly rise, which can cause tension between trying to be a good team player by responding to everyone and attempting the next design iteration. This might be especially true if the person who’s replying is a stakeholder or someone directly involved in the project who we feel that we need to listen to. It’s human nature to try to accommodate those we care about, and we need to accept that this pressure is completely normal. When responding to all comments, it can be effective, but when we consider a design critique more like user research, we realize that we don’t need to respond to every comment, and there are alternatives in asynchronous spaces:

One is to let the next iteration speak for itself. When the design changes and we publish a follow-up iteration, that’s the response. You could tag everyone in the previous discussion, but that’s just a choice, not a requirement.
• Another is to briefly reply to acknowledge each comment, such as” Understood. Thank you,”” Good points— I’ll review,” or” Thanks. In the upcoming iteration, I’ll include these. In some cases, this could also be just a single top-level comment along the lines of” Thanks for all the feedback everyone—the next iteration is coming soon”!
• Another option is to quickly summarize the comments before moving on. This may be particularly helpful if your workflow allows you to create a simplified checklist that you can use for the following iteration.

The second friction point is the swoop-by comment, which is the kind of feedback that comes from someone outside the project or team who might not be aware of the context, restrictions, decisions, or requirements —or of the previous iterations ‘ discussions. One can hope that they will learn something from them, starting with acknowledging that they are doing this and making their location more explicit. Swoop-by comments frequently prompt the simple thought,” We’ve already discussed this,” and it can be frustrating to have to keep coming back and forth.

Let’s begin by acknowledging again that there’s no need to reply to every comment. However, if responding to a previously litigated point is useful, a brief response with a link to the previous discussion for additional information is typically sufficient. Remember that repetition results in alignment, so it’s acceptable to repeat things occasionally!

Swoop-by commenting can still be useful for two reasons: they might point out something that still isn’t clear, and they also have the potential to stand in for the point of view of a user who’s seeing the design for the first time. Yes, you’ll still be frustrated, but that might at least make things better for you.

The personal stake we might have in the design could be the third friction point, which might cause us to feel defensive if the review turned into a discussion. Treating feedback as user research helps us create a healthy distance between the people giving us feedback and our ego ( because yes, even if we don’t want to admit it, it’s there ). And in the end, presenting everything in aggregated form helps us to prioritize our work more.

Remember to always remember that you don’t have to accept every piece of feedback, even though you need to listen to stakeholders, project owners, and specific advice. You have to analyze it and make a decision that you can justify, but sometimes “no” is the right answer.

You are in charge of making that choice as the designer who is in charge of the project. In the end, everyone has their area of specialization, and the designer is the one with the most background and knowledge to make the right choice. And by listening to the feedback that you’ve received, you’re making sure that it’s also the best and most balanced decision.

Thanks to Mike Shelton and Brie Anne Demkiw for their contributions to the initial draft of this article.

Although I’m not certain when I first heard this statement, it has over the centuries stuck in my mind. How do you generate solutions for scenarios you can’t think? Or create items that function on products that have not yet been created?

Flash, Photoshop, and flexible pattern

My go-to program when I first started creating platforms was Photoshop. I created a 960px paint and set about creating a design that I would eventually lose information in. Using set widths, fixed heights, and complete positioning, the development phase aimed to achieve pixel-perfect precision.

Ethan Marcotte’s speak at An Event Off and subsequent content” Responsive Web Design” in A List Off in 2010 changed all this. As soon as I learned about flexible style, I was convinced, but I was even terrified. The pixel-perfect models full of special figures that I had formerly prided myself on producing were no longer good enough.

My first encounter with flexible style didn’t help my fear. My second project was to get an active fixed-width website and make it reactive. You can’t really put responsiveness at the end of a job, which I learned the hard way. To make smooth design, you need to prepare throughout the style phase.

A novel method of style

Developing flexible or smooth sites has always been about removing limitations, producing material that can be viewed on any system. It relies on the use of percentage-based design, which I immediately achieved using native CSS and power groups:

.column-span-6 { width: 49%; float: left; margin-right: 0.5%; margin-left: 0.5%;}.column-span-4 { width: 32%; float: left; margin-right: 0.5%; margin-left: 0.5%;}.column-span-3 { width: 24%; float: left; margin-right: 0.5%; margin-left: 0.5%;}

Then with Sass so I could take advantage of @includes to re-use repeated slabs of script and walk up to more semantic premium:

.logo { @include colSpan(6);}.search { @include colSpan(3);}.social-share { @include colSpan(3);}

Media inquiries

The next ingredient for flexible design is press queries. Without them, content would shrink to fit the available space, regardless of whether it remained readable ( The exact opposite issue resulted from the development of a mobile-first approach ).

Media inquiries prevented this by allowing us to add breakpoints where the design could adapt. Like most people, I started out with three breakpoints: one for desktop, one for tablets, and one for mobile. Over the years, I added more and more for phablets, wide screens, and so on. 

For years, I happily worked this way and improved both my design and front-end skills in the process. The only problem I encountered was making changes to content, since with our Sass grid system in place, there was no way for the site owners to add content without amending the markup—something a small business owner might struggle with. This is because each row in the grid was defined using a div as a container. Adding content meant creating new row markup, which requires a level of HTML knowledge.

String premium was a mainstay of early flexible design, present in all the frequently used systems like Bootstrap and Skeleton.

 
1 of 7
 
2 of 7
 
3 of 7
 
4 of 7
 
5 of 7
 
6 of 7
 
7 of 7

Another difficulty arose as I moved from a design firm building websites for tiny- to medium-sized companies, to larger in-house teams where I worked across a collection of related sites. In those capacities, I began to work more with recyclable parts.

Our rely on multimedia queries resulted in parts that were tied to frequent window sizes. If modify is the goal of part libraries, then this is a real issue because you can just use these components if the devices you’re designing for match the window sizes in the design library, which prevents you from actually achieving the “devices that don’t yet occur” goal.

Then there’s the problem of space. Media inquiries allow components to adapt based on the viewport size, but what if I put a component into a sidebar, like in the figure below?

Container queries: A false dawn or our savior?

Container queries have long been touted as an improvement upon media queries, but at the time of writing are unsupported in most browsers. Workarounds for JavaScript exist, but they can lead to dependencies and compatibility issues. The basic theory underlying container queries is that elements should change based on the size of their parent container and not the viewport width, as seen in the following illustrations.

One of the biggest arguments in favor of container queries is that they help us create components or design patterns that are truly reusable because they can be picked up and placed anywhere in a layout. This is a significant step in the direction of a component-based design that can be used with any device, regardless of size.

In other words, responsive components to replace responsive layouts.

Container queries will enable us to design components that can be placed in a sidebar or in the main content and respond accordingly rather than designing pages that respond to the browser or device size.

My concern is that we are still using layout to determine when a design needs to adapt. This approach will always be restrictive because we will still require predetermined breakpoints. For this reason, my main question with container queries is, How would we decide when to change the CSS used by a component?

The best place to make that choice is probably not a component library that is disconnected from context and real content.

As the diagrams below illustrate, we can use container queries to create designs for specific container widths, but what if I want to change the design based on the image size or ratio?

In this instance, the container’s dimensions are not what should be used to dictate the design; rather, the image is.

It’s hard to say for sure whether container queries will be a success story until we have solid cross-browser support for them. Responsive component libraries would undoubtedly change the way we design them, and they would increase the possibilities for reuse and scale design. But maybe we will always need to adjust these components to suit our content.

CSS is evolving.

Whilst the container query debate rumbles on, there have been numerous advances in CSS that change the way we think about design. The days of fixed-width elements measured in pixels and floated div elements used to cobble layouts together are long gone, consigned to history along with table layouts. Flexbox and CSS Grid have revolutionized layouts for the web. We can now create elements that wrap onto new rows when they run out of space, not when the device changes.

.wrapper { display: grid; grid-template-columns: repeat(auto-fit, 450px); gap: 10px;}

The repeat() function paired with auto-fit or auto-fill allows us to specify how much space each column should use while leaving it up to the browser to decide when to spill the columns onto a new line. Similar things can be achieved with Flexbox, as elements can wrap over multiple rows and “flex” to fill available space. 

.wrapper { display: flex; flex-wrap: wrap; justify-content: space-between;}.child { flex-basis: 32%; margin-bottom: 20px;}

The biggest benefit of all this is you don’t need to wrap elements in container rows. Without rows, content is not tied to page markup in the same way, allowing for changes or additions to content without further development.

The real game changer for flexible designs is CSS Subgrid, which is a significant improvement in terms of designing designs that allow for evolving content.

Remember the days of crafting perfectly aligned interfaces, only for the customer to add an unbelievably long header almost as soon as they’re given CMS access, like the illustration below?

Subgrid allows elements to respond to adjustments in their own content and in the content of sibling elements, helping us create designs more resilient to change.

.wrapper { display: grid; grid-template-columns: repeat(auto-fit, minmax(150px, 1fr)); grid-template-rows: auto 1fr auto; gap: 10px;}.sub-grid { display: grid; grid-row: span 3; grid-template-rows: subgrid; /* sets rows to parent grid */}

CSS Grid allows us to separate layout and content, thereby enabling flexible designs. Subgrid also enables us to create designs that can change to fit changing content. Subgrid at the time of writing is only supported in Firefox but the above code can be implemented behind an @supports feature query.

Intrinsic layouts

I’d be remiss not to mention intrinsic layouts, the term created by Jen Simmons to describe a mixture of new and old CSS features used to create layouts that respond to available space.

Columns with percentages are flexible in responsive layouts. Intrinsic layouts, on the other hand, use the fr unit to create flexible columns that won’t ever shrink so much that they render the content illegible.

frunits is a statement that says I want you to distribute the extra space in this manner, but never that it should be smaller than the content inside.

—Jen Simmons,” Designing Intrinsic Layouts”

Intrinsic layouts can also make use of a mix of fixed and flexible units, letting the content choose how much space it occupies.

What distinguishes intrinsic design is that it not only creates designs that can withstand future devices but also helps scale designs without losing flexibility. Components and patterns can be lifted and reused without the prerequisite of having the same breakpoints or the same amount of content as in the previous implementation.

They now have the ability to adapt to the content both inside and outside of them. With an intrinsic approach, we can construct responsive components without depending on container queries.

Another 2010 moment, perhaps?

This intrinsic approach should in my view be every bit as groundbreaking as responsive web design was ten years ago. It’s another “everything changed” moment for me.

But it doesn’t seem to be moving quite as fast, I haven’t yet had that same career-changing moment I had with responsive design, despite the widely shared and brilliant talk that brought it to my attention.

One possible explanation for that might be that I now work for a sizable company, which is significantly different from the role I held as a design agency in 2010: In my agency days, every new project was a clean slate, a chance to try something new. Modern projects frequently improve existing websites with an existing codebase and use existing tools and frameworks.

Another could be that I feel more prepared for change now. I was new to design in general in 2010; the shift was frightening and required a lot of learning. Also, an intrinsic approach isn’t exactly all-new, it’s about using existing skills and existing CSS knowledge in a different way.

You can’t framework your way out of a content issue.

Another reason for the slightly slower adoption of intrinsic design could be the lack of quick-fix framework solutions available to kick-start the change.

Ten years ago, responsive grid systems were everywhere. With a framework like Bootstrap or Skeleton, you had a responsive design template at your fingertips.

Because having a selection of units is a hindrance when creating layout templates, intrinsic design and frameworks do not work together quite as well. The beauty of intrinsic design is combining different units and experimenting with techniques to get the best for your content.

Additionally, there are design tools. We probably all, at some point in our careers, used Photoshop templates for desktop, tablet, and mobile devices to drop designs in and show how the site would look at all three stages.

How do you do that right away, with each component responding to content and layout flexing as and when necessary? This type of design must happen in the browser, which personally I’m a big fan of.

Another ongoing debate centered on whether designers should code is ongoing. When designing a digital product, we should, at the very least, design for a best- and worst-case scenario when it comes to content. It’s not ideal to do this in a graphics-based software package. In code, we can add longer sentences, more radio buttons, and extra tabs, and watch in real time as the design adapts. Does it continue to function? Is the design too reliant on the current content?

I’m personally anticipating the day when a design component can truly be flexible and adapt to both its space and content without relying on the device or container dimensions.

Content first

Content is variable. After all, to design for the unknown or unexpected we need to account for content changes like our earlier Subgrid card example that allowed the cards to respond to adjustments to their own content and the content of sibling elements.

Thankfully, there’s more to CSS than layout, and plenty of properties and values can help us put content first. Subgrid and pseudo-elements like ::first-line and ::first-letter help to separate design from markup so we can create designs that allow for changes.

Instead of dated markup tricks like this —

 First line of text with different styling...

—we can target content based on where it appears.

.element::first-line { font-size: 1.4em;}.element::first-letter { color: red;}

Much bigger additions to CSS include logical properties, which change the way we construct designs using logical dimensions (start and end) instead of physical ones (left and right), something CSS Grid also does with functions like min(), max(), and clamp().

This flexibility allows for directional changes according to content, a common requirement when we need to present content in multiple languages. This was frequently accomplished with Sass mixins in the past, but it was frequently limited to a left-to-right or right-to-left orientation.

In the Sass version, directional variables need to be set.

$direction: rtl;$opposite-direction: ltr;$start-direction: right;$end-direction: left;

These variables can be used as values.

body { direction: $direction; text-align: $start-direction;}

—or as properties.

margin-#{$end-direction}: 10px;padding-#{$start-direction}: 10px;

However, with native logical properties, we can now avoid relying on Sass ( or a similar tool ) and pre-planning, which meant using variables throughout a codebase. These properties also start to break apart the tight coupling between a design and strict physical dimensions, creating more flexibility for changes in language and in direction.

margin-block-end: 10px;padding-block-start: 10px;

There are also native start and end values for properties like text-align, which means we can replace text-align: right with text-align: start.

Like the earlier examples, these properties help to build out designs that aren’t constrained to one language, the design will reflect the content’s needs.

Fluid and fixed

We briefly covered the power of combining fixed widths with fluid widths with intrinsic layouts. The min() and max() functions are a similar concept, allowing you to specify a fixed value with a flexible alternative. 

For min() this means setting a fluid minimum value and a maximum fixed value.

.element { width: min(50%, 300px);}

As long as the element’s width is not greater than 300px, the element in the figure above will cover 50 % of its container.

For max() we can set a flexible max value and a minimum fixed value.

.element { width: max(50%, 300px);}

As long as the element’s width is at least 300px, it will now cover 50 % of its container. This means we can set limits but allow content to react to the available space.

The clamp() function builds on this by allowing us to set a preferred value with a third parameter. Now we can allow the element to shrink or grow if it needs to without getting to a point where it becomes unusable.

.element { width: clamp(300px, 50%, 600px);}

This time, the element’s width will be 50 % of its container’s preferred value, with no exceptions for 300px and 600px.

With these techniques, we have a content-first approach to responsive design. We can’t change markup because content can’t be changed, so user modifications won’t have an impact on the design. We can start to future-proof designs by planning for unexpected changes in language or direction. Additionally, we can increase flexibility by specifying desired dimensions alongside adaptable alternatives, which will allow for more or less content to be displayed correctly.

Situation first

We can cover device flexibility by changing our approach, designing around content and space rather than catering to devices, thanks to what we’ve discussed so far. But what about that last bit of Jeffrey Zeldman’s quote,”… situations you haven’t imagined”?

It’s a lot different to design for someone using a mobile phone and walking through a crowded street in glaring sunshine than it is for someone using a desktop computer. Situations and environments are hard to plan for or predict because they change as people react to their own unique challenges and tasks.

This is why making a choice is so crucial. One size never fits all, so we need to design for multiple scenarios to create equal experiences for all our users.

Thankfully, there is a lot we can do to give people choices.

Responsible design

There are places in the world where mobile data is prohibitively expensive and where there is little or no broadband infrastructure.

” I Used the Web for a Day on a 50 MB Budget“

Chris Ashton

One of the biggest assumptions we make is that people interacting with our designs have a good wifi connection and a wide screen monitor. However, our users may be commuters using smaller mobile devices that may experience drops in connectivity while traveling on trains or other modes of transportation. There is nothing more frustrating than a web page that won’t load, but there are ways we can help users use less data or deal with sporadic connectivity.

The srcset attribute allows the browser to decide which image to serve. This means we can create smaller ‘cropped’ images to display on mobile devices in turn using less bandwidth and less data.

The preload attribute can also help us to think about how and when media is downloaded. It can be used to tell a browser about any critical assets that need to be downloaded with high priority, improving perceived performance and the user experience. 

Additionally, there is native lazy loading, which indicates that only the most crucial files should be downloaded.

With srcset, preload, and lazy loading, we can start to tailor a user’s experience based on the situation they find themselves in. What none of this does, however, is allow the user themselves to decide what they want downloaded, as the decision is usually the browser’s to make. 

So how can we put users in control?

The media queries are now being returned.

Media inquiries have always been about much more than device sizes. They allow content to adapt to different situations, with screen size being just one of them.

We’ve long been able to check for media types like print and speech and features such as hover, resolution, and color. Because of these checks, we can offer options that work for more than one situation. It’s less about one-size-fits-all and more about providing adaptable content.

As of this writing, the Media Queries Level 5 spec is still under development. It brings up some really intriguing queries that will eventually help us design for a number of other unanticipated situations.

For example, there’s a light-level feature that allows you to modify styles if a user is in sunlight or darkness. These features, which are enhanced by custom properties, make it simple to create designs or themes for particular environments.

@media (light-level: normal) { --background-color: #fff; --text-color: #0b0c0c; }@media (light-level: dim) { --background-color: #efd226; --text-color: #0b0c0c;}

Another key feature of the Level 5 spec is personalization. Instead of creating designs that are the same for everyone, users can choose what works for them. This is achieved by using features like prefers-reduced-data, prefers-color-scheme, and prefers-reduced-motion, the latter two of which already enjoy broad browser support. These features tap into preferences set via the operating system or browser so people don’t have to spend time making each site they visit more usable. 

Media inquiries like this go beyond choices made by a browser to grant more control to the user.

Expect the Unexpected

In the end, the one thing we should always expect is for things to change. With foldable screens already available on the market, devices especially change more quickly than we can keep up.

We can’t design the same way we have for this ever-changing landscape, but we can design for content. We can create more robust, flexible designs that increase the longevity of our products by putting content first and allowing that content to adapt to whatever space surrounds it.

A lot of the CSS discussed here is about moving away from layouts and putting content at the heart of design. There is a lot more we can do to adopt a more intrinsic approach, from responsive components to fixed and fluid units. Even better, we can test these techniques during the design phase by designing in-browser and watching how our designs adapt in real-time.

When it comes to unexpected circumstances, we need to make sure our goods are accessible whenever and wherever needed. We can move closer to achieving this by involving users in our design decisions, by creating choice via browsers, and by giving control to our users with user-preference-based media queries.

A good design for the unexpected should allow for change, give choice, and give control to the people we serve: our users themselves.

We’ve been conversing for many thousands of years. Whether to present information, perform transactions, or just to check in on one another, people have yammered aside, chattering and gesticulating, through spoken discussion for many generations. Only recently have we begun to write our conversations, and only recently have we outsourced them to the system, a system that exhibits a far greater affection for written communications than for the vernacular rigors of spoken speech.

Computers have issues because conversation is more important than written speech, between spoken and written. To have productive conversations with us, machines may struggle with the messiness of mortal speech: the disfluencies and pauses, the gestures and body language, and the variations in word choice and spoken dialect that is stymie even the most carefully crafted human-computer interaction. Speaking language also has the advantage of face-to-face contact, which allows us to view visual social cues in the human-to-human scenario.

In contrast, written language develops its own fossil record of dated terms and phrases as we commit to recording and keeping usages long after they are no longer relevant in spoken communication ( for example, the salutation” To whom it may concern” ). Because it tends to be more consistent, smooth, and proper, written word is necessarily far easier for devices to interpret and know.

This pleasure is not available in spoken speech. There are verbal cues and outspoken behaviors that mimic conversation in complex ways, including how something is said, never what. These are the nonverbal cues that ornament conversations with emphasis and emotional context. Whether rapid-fire, low-pitched, or high-decibel, whether satirical, awkward, or groaning, our spoken speech conveys much more than the written word had ever muster. As designers and content planners, we face significant challenges when it comes to tone interfaces, the machines with which we speak.

Voice-to-voice relationships

We interact with voice interfaces for a variety of reasons, but according to Michael McTear, Zoraida Callejas, and David Griol in The Conversational Interface, those motivations by and large mirror the reasons we initiate conversations with other people, too ( ). We typically strike up a dialogue as a result:

• we require something ( such as a transaction ),
• we want to know something ( information of some sort ), or
• We are sociable creatures, and we need a talk partner.

These three categories, which I refer to as interpersonal, technical, and prosocial, also apply to virtually every voice interaction: a solitary conversation that begins with the voice interface’s initial greeting and ends with the user leaving the interface. Notice here that a conversation in our individual sense—a chat between people that leads to some result and lasts an arbitrary length of time—could encompass many interpersonal, technical, and interpersonal voice interactions in succession. In other words, a voice interaction is a conversation, but it is not always just one voice interaction.

Most voice interfaces are more gimmicky than captivating in pure prosocial conversations because most people find it difficult to trust their machines to actually understand how we’re doing and to give them the kind of glad-handing we crave. There’s also ongoing debate as to whether users actually prefer the sort of organic human conversation that begins with a prosocial voice interaction and shifts seamlessly into other types. In fact, Michael Cohen, James Giangola, and Jennifer Balogh advise sticking to user expectations by imitating how they interact with other voice interfaces rather than trying too hard to be human, which could lead to alienation of them ( ).

That leaves two different types of conversations we can have with one another that a voice interface can also have easily, including one that is transactional and one that is informational, teaching us something new ( “discuss a musical” ).

Transactional voice interactions

When you order a Hawaiian pizza with extra pineapple, you’re typically having a conversation and a voice interaction when you’re tapping buttons on a food delivery app. The conversation quickly shifts from a brief smattering of neighborly small talk to ordering a pizza ( generously topped with pineapple, as it should be ) when we walk up to the counter and place an order.

Alison: Hey, how’s it going?

Burhan: Hello and welcome to Crust Deluxe! It’s chilly outside. How can I help you?

Can I get a Hawaiian pizza with extra pineapple, Alison?

Burhan: Yes, but what size?

Alison: Large.

Burhan: Anything else?

Alison: No, that’s it.

Burhan: Something to drink?

Alison: I’ll have a bottle of Coke.

Burhan, you know what. That’ll be$ 13.55 and about fifteen minutes.

A service rendered or a product delivered, as each incremental disclosure in this transactional conversation reveals more and more of the desired transactional outcome. Conversations that are transactional have certain characteristics: they are direct, precise, and cost-effective. They quickly dispense with pleasantries.

Informational voice interactions

In the meantime, some conversations are primarily about getting information. Though Alison might visit Crust Deluxe with the sole purpose of placing an order, she might not actually want to walk out with a pizza at all. She might be interested in trying kosher or halal dishes, trying gluten-free dishes, or something else entirely. Even though we have a prosocial mini-conversation once more at the beginning to establish politeness, we’re after much more.

Alison: Hey, how’s it going?

Burhan: Hello and welcome to Crust Deluxe! It’s chilly outside. How can I help you?

Alison: Can I ask a few questions?

Burhan: Of course! Continue straight ahead.

Alison: Do you have any halal options on the menu?

Burhan: Absolutely! On request, we can make any pie halal. We also have lots of vegetarian, ovo-lacto, and vegan options. Are you considering any additional dietary restrictions?

Alison: What about pizzas that are gluten-free?

Burhan: We can definitely do a gluten-free crust for you, no problem, for both our deep-dish and thin-crust pizzas. Anything else I can say to you to help?

Alison: That’s it for now. Good to know. Thank you!

Burhan: Anytime, please.

This is a very different dialogue. Here, the goal is to obtain a particular set of facts. Informational conversations are research expeditions to gather data, news, or facts in search of the truth. Voice interactions that are informational might be more long-winded than transactional conversations by necessity. In order for the customer to understand the key takeaways, responses are typically longer, more in-depth, and carefully communicated.

Voice-to-text interfaces

At their core, voice interfaces employ speech to support users in reaching their goals. However, just because an interface has a voice component doesn’t mean that every user interaction with it is mediated through voice. We’re most concerned in this book with pure voice interfaces because multimodal voice interfaces can lean on visual components like screens as crutches, which are completely dependent on spoken conversation and lack any visual component, making them much more nuanced and challenging to deal with.

Though voice interfaces have long been integral to the imagined future of humanity in science fiction, only recently have those lofty visions become fully realized in genuine voice interfaces.

IVR ( interactive voice response ) systems

Written conversational interfaces have been a part of computing for many decades, but voice interfaces first started to appear in the early 1990s with text-to-speech ( TTS ) dictation programs that recited written text aloud as well as speech-enabled in-car systems that gave directions to a user-provided address. With the advent of interactive voice response ( IVR ) systems, intended as an alternative to overburdened customer service representatives, we became acquainted with the first true voice interfaces that engaged in authentic conversation.

IVR systems made it easier for businesses to cut down on call centers, but they soon gained notoriety for their clunkiness. Similar to the corporate world, these systems were primarily created as metaphorical switchboards to direct customers to a real phone agent (” Say Reservations to book a flight or check an itinerary” ), and chances are you’ll have a conversation with one when you call an airline or hotel conglomerate. Despite their functional issues and users ‘ frustration with their inability to speak to an actual human right away, IVR systems proliferated in the early 1990s across a variety of industries (, PDF).

IVR systems have a reputation for having less scintillating conversation than we’re used to in real life ( or even in science fiction ), but they are great for highly repetitive, monotonous conversations that typically don’t veer from a single format.

Readers of screens

Parallel to the evolution of IVR systems was the invention of the screen reader, a tool that transcribes visual content into synthesized speech. For Blind or visually impaired website users, it’s the predominant method of interacting with text, multimedia, or form elements. Readers of screens represent perhaps the closest equivalent we have today to an out-of-the-box implementation of content delivered through voice.

Among the first screen readers known by that moniker was the Screen Reader for the BBC Micro and NEEC Portable developed by the Research Centre for the Education of the Visually Handicapped (RCEVH) at the University of Birmingham in 1986 ( ). The first IBM Screen Reader for text-based computers was created by Jim Thatcher in the same year, which was later recreated for computers with graphical user interfaces ( GUIs ) ( ).

With the rapid expansion of the web in the 1990s, there was an explosion in the demand for user-friendly tools. Thanks to the introduction of semantic HTML and especially ARIA roles beginning in 2008, screen readers started facilitating speedy interactions with web pages that ostensibly allow disabled users to traverse the page as an aural and temporal space rather than a visual and physical one. In other words, screen readers for the web “provide mechanisms that translate visual design constructs—proximity, proportion, etc. —into useful information,” according to Aaron Gustafson in A List Apart. ” At least they do when documents are authored thoughtfully” ( ).

Although incredibly instructive for voice interface designers, screen readers have a major flaw: they’re challenging to use and consistently verbose. Sometimes awkward pronouncements that name every manipulable HTML element and announce every formatting change are made because the visual structures of websites and web navigation don’t translate well to screen readers. For many screen reader users, working with web-based interfaces exacts a cognitive toll.

Chris Maury, an advocate for voice quality and voice engineer, examines why the screen reader experience is not appropriate for users who rely on voice in Wired:

I hated the way Screen Readers operated from the beginning. Why are they designed the way they are? It makes no sense to present information visually and then only to have that information translated into audio. All the time and effort put into creating the ideal user experience for an app is wasted, or worse, it has a negative effect on blind users ‘ experience. ( ) _ _ _

Well-designed voice interfaces can often be more effective than long-winded screen reader monologues in guiding users to their destination. After all, users of the visual interface have the advantage of freely scurrying around the viewport to find information without worrying about it. Blind users, meanwhile, are obligated to listen to every utterance synthesized into speech and therefore prize brevity and efficiency. Users with disabilities who have long had no choice but to use clumsy screen readers might find that voice interfaces, especially more contemporary voice assistants, provide a more streamlined experience.

Voice-overseers are

When we think of voice assistants (the subset of voice interfaces now commonplace in living rooms, smart homes, and offices), many of us immediately picture HAL from 2001: A Space Odyssey or hear Majel Barrett’s voice as the omniscient computer in Star Trek. Voice-overseers are are akin to personal concierges that can answer questions, schedule appointments, conduct searches, and perform other common day-to-day tasks. And they’re rapidly gaining more attention from accessibility advocates for their assistive potential.

Before the earliest IVR systems found success in the enterprise, Apple published a demonstration video in 1987 depicting the Knowledge Navigator, a voice assistant that could transcribe spoken words and recognize human speech to a great degree of accuracy. Then, in 2001, Tim Berners-Lee and others created their vision for a Semantic Web “agent” that would carry out routine tasks like” checking calendars, making appointments, and finding locations” (, behind paywall ). Apple’s Siri finally made voice assistants a reality for consumers until 2011 when they were available.

Thanks to the plethora of voice assistants available today, there is considerable variation in how programmable and customizable certain voice assistants are over others ( Fig 1.1 ). At one extreme, everything but vendor-provided features are locked down. For instance, when Apple’s Siri and Microsoft’s Cortana were released, they couldn’t extend their existing capabilities. There are no other means by which developers can interact with Siri at a low level, aside from predefined categories of tasks like sending messages, hailing rideshares, making restaurant reservations, and other things, which are still unavoidable today.

At the opposite end of the spectrum, voice assistants like Amazon Alexa and Google Home offer a core foundation on which developers can build custom voice interfaces. For this reason, developers who feel stifled by the limitations of Siri and Cortana are increasingly using programmable voice assistants that are capable of customization and extensibility. Google Home enables the programming of arbitrary Google Assistant skills, while Amazon offers the Alexa Skills Kit, a developer framework for creating custom voice interfaces for Amazon Alexa. Today, users can choose from among thousands of custom-built skills within both the Amazon Alexa and Google Assistant ecosystems.

As businesses like Amazon, Apple, Microsoft, and Google continue to occupy their positions, they’re also selling and open-sourcing an unheard array of tools and frameworks for designers and developers that aim to make creating voice interfaces as simple as possible, even without code.

Often by necessity, voice assistants like Amazon Alexa tend to be monochannel—they’re tightly coupled to a device and can’t be accessed on a computer or smartphone instead. In contrast, many development platforms, such as Google’s Dialogflow, have omnichannel capabilities that allow users to create a single conversational interface that then becomes a voice interface, textual chatbot, and IVR system upon deployment. In Chapter 4, we’ll explore some of the possible effects these variables might have on how you build out your design artifacts, but I don’t recommend any particular implementation strategies in this design-focused book.

Voice Content

Simply put, voice content is voice-transmitted content. Voice content must be free-flowing and organic, contextless and concise—everything written content isn’t enough to preserve what makes human conversation so compelling in the first place.

Our world is replete with voice content in various forms: screen readers reciting website content, voice assistants rattling off a weather forecast, and automated phone hotline responses governed by IVR systems. We’re most concerned with the content in this book being delivered auditorically, not as an option but as a necessity.

Our initial foray into informational voice interfaces will likely be to provide user content, for many of us. There’s only one problem: any content we already have isn’t in any way ready for this new habitat. How can we improve the conversational content on our websites? And how do we create fresh copy that works with voice movements?

Lately, we’ve begun slicing and dicing our content in unprecedented ways. Websites are, in many ways, massive vaults of what I call macrocontent: lengthy prose that can last for miles in a browser window while extending like microfilm viewers of newspaper archives. Microcontent was defined as permalinked pieces of content that stay legible regardless of the environment, such as email or text messages back in 2002, well before the present-day ubiquity of voice assistants.

A day’s weather forcast]sic], the arrival and departure times for an airplane flight, an abstract from a long publication, or a single instant message can all be examples of microcontent. ( ) _ _ _

I would update Dash’s definition of microcontent to include all instances of bite-sized content that transcends written communiqués. After all, today we encounter microcontent in interfaces where a small snippet of copy is displayed alone, unmoored from the browser, like a textbot confirmation of a restaurant reservation. The best way to learn how to stretch your content to the limits of its potential is through microcontent, which will inform both established and new delivery methods.

Voice content stands out as being unique because it illustrates how content is experienced in space as opposed to time. We can glance at a digital sign underground for an instant and know when the next train is arriving, but voice interfaces hold our attention captive for periods of time that we can’t easily escape or skip, something screen reader users are all too familiar with.

We need to make sure that our microcontent truly performs well as voice content because it is essentially composed of isolated blobs without any connection to the channels in which they will eventually end up. This means focusing on the two most crucial characteristics of robust voice content: voice content legibility and voice content discoverability.

Our voice content’s legibility and discoverability in general both depend on how it manifests in terms of perceived space and time.

In the 1950s, some members of the elite running group had come to accept the idea that it was impossible to run a hour in less than four hours. Riders had been attempting it since the later 19th century and were beginning to draw the conclusion that the human body just wasn’t built for the job.

But on May 6, 1956, Roger Bannister caught all off guard. It was a cold, damp morning in Oxford, England—conditions no one expected to give themselves to record-setting—and but Bannister did really that, running a mile in 3: 59.4 and becoming the first people in the history books to run a mile in under four hours.

The world then knew that the four-minute hour was possible because of this change in the standard. Bannister’s history lasted just forty-six days, when it was snatched aside by American sprinter John Landy. Finally, in the same race, three athletes all managed to cross the four-minute challenge. Since therefore, over 1, 400 walkers have actually run a mile in under four days, the current document is 3: 43.13, held by Moroccan performer Hicham El Guerrouj.

We accomplish a lot more when we think something is possible, and we only think it can be done when we see someone else doing it after all. As for human running speed, we also think there are the strictest requirements for how a website should do.

Establishing requirements for a green website

The key indicators of climate performance in most big companies are very well established, such as power per square metre for homes and miles per gallon for cars. The tools and methods for calculating those measures are standardized as well, which keeps everyone on the same site when doing economic evaluations. However, we aren’t held to any specific environmental standards in the world of websites and apps, and we only recently have access to the tools and strategies we need to do so.

The main objective in green web layout is to reduce carbon emissions. However, it’s nearly impossible to accurately assess the amount of CO₂ that a website merchandise produces. We didn’t measure the pollutants coming out of the exhaust valves on our laptops. Our websites produce far-away, invisible, and unremarkable emissions when they leave fuel and gas-burning power plants. We have no way to track the particles from a website or app up to the power station where the light is being generated and really know the exact amount of house oil produced. So what do we accomplish then?

If we can‘t measure the actual carbon emissions, then we need to get what we can estimate. The following are the main elements that could be used as carbon pollution gauges:

1. Transfer of data
2. Electricity’s carbon power

Let’s take a look at how we can use these indicators to calculate the energy use, and in turn the carbon footprint, of the sites and web applications we create.

Transfer of data

Most researchers use kilowatt-hours per gigabyte (k Wh/GB ) as a metric of energy efficiency when measuring the amount of data transferred over the internet when a website or application is used. This serves as a reliable indicator of how much energy is being consumed and how much carbon is being released. As a rule of thumb, the more data transferred, the more energy used in the data center, telecoms networks, and end user devices.

The page weight, or the page’s transfer size in kilobytes, can be most easily calculated for a single visit for web pages. It’s fairly easy to measure using the developer tools in any modern web browser. Frequently, any web application’s overall data transfer statistics will be included in your web hosting account ( Fig. 2.1 ).

The nice thing about page weight as a metric is that it allows us to compare the efficiency of web pages on a level playing field without confusing the issue with constantly changing traffic volumes.

A large scope is required to reduce page weight. By early 2020, the median page weight was 1.97 MB for setups the HTTP Archive classifies as “desktop” and 1.77 MB for “mobile”, with desktop increasing 36 percent since January 2016 and mobile page weights nearly doubling in the same period ( Fig 2.2 ). Image files account for the majority of this data transfer, making them the single biggest contributor to carbon emissions on a typical website.

History clearly shows us that our web pages can be smaller, if only we set our minds to it. While most technologies, including the underlying technology of the web like data centers and transmission networks, become more and more energy efficient, websites themselves become less effective as time goes on.

You may be aware of the idea of performance budgeting as a method for directing a project team to deliver faster user experiences. For example, we might specify that the website must load in a maximum of one second on a broadband connection and three seconds on a 3G connection. Performance budgets are upper limits rather than hazy ideas, much like speed limits while driving. As a result, the goal should always be to stay within budget.

Designing for fast performance does often lead to reduced data transfer and emissions, but it isn’t always the case. Page weight and transfer size are more objective and reliable benchmarks for sustainable web design, whereas web performance is frequently more about the subjective perception of load times than it is about the underlying system’s actual efficiency.

We can set a page weight budget in reference to a benchmark of industry averages, using data from sources like HTTP Archive. We can also use competitor page weight to compare the new website to the old one. For example, we might set a maximum page weight budget as equal to our most efficient competitor, or we could set the benchmark lower to guarantee we are best in class.

We could start looking at the transferability of our web pages for repeat visitors if we want to take it one step further. Although page weight for the first time someone visits is the easiest thing to measure, and easy to compare on a like-for-like basis, we can learn even more if we start looking at transfer size in other scenarios too. For instance, visitors who load the same page more frequently are likely to have a high percentage of the files cached in their browser, which means they don’t need to move all the files on subsequent visits. Likewise, a visitor who navigates to new pages on the same website will likely not need to load the full page each time, as some global assets from areas like the header and footer may already be cached in their browser. Moving away from the first visit and allowing us to determine page weight budgets for scenarios other than this one can help us learn even more about how to optimize efficiency for users who regularly visit our pages.

Page weight budgets are easy to track throughout a design and development process. Although they don’t directly disclose carbon emissions and energy consumption data, they do provide a clear indicator of efficiency in comparison to other websites. And as transfer size is an effective analog for energy consumption, we can actually use it to estimate energy consumption too.

In summary, less data transfer leads to more energy efficiency, which is a crucial component of lowering web product carbon emissions. The more efficient our products, the less electricity they use, and the less fossil fuels need to be burned to produce the electricity to power them. However, as we’ll see next, it’s important to take into account the source of that electricity because all web products require some.

Electricity’s carbon power

Regardless of energy efficiency, the level of pollution caused by digital products depends on the carbon intensity of the energy being used to power them. The term” carbon intensity” is used to describe how many grams of carbon are produced for every kilowatt-hour of electricity (gCO₂/k Wh ). This varies widely, with renewable energy sources and nuclear having an extremely low carbon intensity of less than 10 gCO₂/k Wh ( even when factoring in their construction ), whereas fossil fuels have very high carbon intensity of approximately ₂00–400 gCO₂/k Wh.

The majority of electricity is produced by national or state grids, where different levels of carbon intensity are combined with energy from a variety of sources. The distributed nature of the internet means that a single user of a website or app might be using energy from multiple different grids simultaneously, a website user in Paris uses electricity from the French national grid to power their home internet and devices, but the website’s data center could be in Dallas, USA, pulling electricity from the Texas grid, while the telecoms networks use energy from everywhere between Dallas and Paris.

Although we have some control over where our projects are hosted, we do not have complete control over the energy supply of web services. With a data center using a significant proportion of the energy of any website, locating the data center in an area with low carbon energy will tangibly reduce its carbon emissions. This user-provided data is reported and mapped by Danish startup Tomorrow, and a look at their map demonstrates how, for instance, choosing a data center in France will result in significantly lower carbon emissions than choosing a data center in the Netherlands ( Fig. 2.3 ).

However, we don’t want to move our servers too far away from our users because it requires a lot of energy to transmit data through the telecom’s networks, and the more energy is used, the further the data travels. Just like food miles, we can think of the distance from the data center to the website’s core user base as “megabyte miles” —and we want it to be as small as possible.

We can use website analytics to determine the country, state, or even city where our core user group is located and measure the distance between that location and the data center that our hosting company uses as a benchmark. This will be a somewhat fuzzy metric as we don’t know the precise center of mass of our users or the exact location of a data center, but we can at least get a rough idea.

For instance, if a website is hosted in London but the main audience is on the United States ‘ West Coast, we could calculate the distance between San Francisco and London, which is 5,300 miles. That’s a long way! We can see how hosting it somewhere in North America, ideally on the West Coast, would significantly lessen the distance and the amount of energy required to transmit the data. In addition, locating our servers closer to our visitors helps reduce latency and delivers better user experience, so it’s a win-win.

Reverting it to carbon emissions

If we combine carbon intensity with a calculation for energy consumption, we can calculate the carbon emissions of our websites and apps. A tool my team created accomplishes this by measuring the data transfer over the wire when a web page is loaded, calculating the associated electricity consumption, and then converting that data into a CO₂ figure ( Fig. ₂.4). It also factors in whether or not the web hosting is powered by renewable energy.

The Energy and Emissions Worksheet that comes with this book teaches you how to take it to the next level and tailor the data more accurately to the individual aspects of your project.

With the ability to calculate carbon emissions for our projects, we could actually expand our page weight budget and establish carbon budgets as well. CO₂ is not a metric commonly used in web projects, we’re more familiar with kilobytes and megabytes, and can fairly easily look at design options and files to assess how big they are. Although translating that into carbon adds an air of abstraction, carbon budgets do focus our minds on the main issue we’re trying to reduce, which also supports the main goal of sustainable web design: reducing carbon emissions.

Browser Energy

Transfer of data might be the simplest and most complete analog for energy consumption in our digital projects, but by giving us one number to represent the energy used in the data center, the telecoms networks, and the end user’s devices, it can’t offer us insights into the efficiency in any specific part of the system.

One part of the system we can look at in more detail is the energy used by end users ‘ devices. The computational burden is increasingly shifting from the data center to the users ‘ devices, whether they are phones, tablets, laptops, desktops, or even smart TVs, as front-end web technologies advance. Modern web browsers allow us to implement more complex styling and animation on the fly using CSS and JavaScript. Additionally, JavaScript libraries like Angular and React allow us to create applications where the” thinking” process is performed either partially or completely in the browser.

All of these advances are exciting and open up new possibilities for what the web can do to serve society and create positive experiences. However, more energy is used by the user’s devices as a result of the user’s web browser’s increased computation. This has implications not just environmentally, but also for user experience and inclusivity. Applications that put a lot of processing power on a user’s device unintentionally make them use older, slower devices and make their phones and laptops ‘ batteries discharge more quickly. Furthermore, if we build web applications that require the user to have up-to-date, powerful devices, people throw away old devices much more frequently. The poorest members of society are also under disproportionate financial burdens due to this, which is not just bad for the environment.

In part because the tools are limited, and partly because there are so many different models of devices, it’s difficult to measure website energy consumption on end users ‘ devices. The Energy Impact monitor inside the developer console of the Safari browser is one of the tools we currently have ( Fig. 2.5 ).

You are aware of the moment your computer’s cooling fans start spinning so frantically that you mistakenly believe it might take off when you load a website? That’s essentially what this tool is measuring.

It uses these figures to create an energy impact rating based on the percentage of CPU used and how long it took the web page to load. It doesn’t give us precise data for the amount of electricity used in kilowatts, but the information it does provide can be used to benchmark how efficiently your websites use energy and set targets for improvement.

This book will provide you with that plan of action. It covers how to incorporate safety concepts into your design work to create healthy technology, how to persuade stakeholders that this work is required, and how to respond to criticism that there isn’t really enough diversity. ( Spoiler: we do, but diversity alone is not the antidote to fixing unethical, unsafe tech. )

The procedure for ensuring equitable safety

When you are designing for health, your goals are to:

• detect the abuse potential of your product.
• style ways to prevent the maltreatment, and
• offer assistance for harmed people to regain control and power.

The Process for Inclusive Safety is a tool to help you reach those goals ( Fig 5.1 ). I developed this strategy in 2018 to better understand the different methods I used to create products that were designed with safety in mind. Whether you are creating an entirely new product or adding to an existing element, the Process can help you produce your product secure and diverse. The Process includes five main public areas of action:

• Conducting study
• Creating tropes
• Pondering problems
• creating answers
• Testing for health

The Process is meant to be flexible; in some situations, it didn’t make sense for groups to adopt every step. Use the parts that are related to your special function and environment, this is meant to be something you can put into your existing style process.

And once you use it, if you have suggestions for improving it or just want to give an overview of how it helped your staff, please get in touch with me. It’s a dwelling report that I hope will continue to be a helpful and practical tool that technicians can use in their day-to-day job.

If you’re developing a product especially for a defenseless group or victims of some kind of stress, such as an application for victims of domestic violence, sexual abuse, or drug habit, make sure to read Chapter 7, which specifically addresses the issue and should be handled a little bit different. The guidelines below are for evaluating safety when designing a more basic product that will have a large customer base ( which, we now know from data, will include specific groups that should be protected from harm ). Chapter 7 concentrates on goods made especially for those who have been traumatized and are susceptible.

Step 1: Do studies

A thorough examination of how your technology might be used to abuse people as well as a detailed study of the experiences of those who have survived and perpetrated that kind of abuse should be included in the design research. At this stage, you and your group does investigate issues of emotional damage and abuse, and examine any other safety, security, or inclusivity issues that might be a concern for your product or service, like data security, prejudiced algorithms, and harassment.

broad-based research

Your project should begin with broad, general research into similar products and issues around safety and ethical concerns that have already been reported. For instance, a team building a smart home device would be wise to comprehend the many ways that already-existing smart home devices have been misused as abuse tools. If your product will involve AI, seek to understand the potentials for racism and other issues that have been reported in existing AI products. Nearly all forms of technology have potential or actual harm that have been covered in academic writing or in the media. Google Scholar is a useful tool for finding these studies.

Survivors as a specific field of study

When possible and appropriate, include direct research ( surveys and interviews ) with people who are experts in the forms of harm you have uncovered. In order to gain a better understanding of the subject and be better positioned to avoid traumatizing survivors, you should first interview those who work in the area of your research. If you’ve uncovered possible domestic violence issues, for example, the experts you’ll want to speak with are survivors themselves, as well as workers at domestic violence hotlines, shelters, other related nonprofits, and lawyers.

It is crucial to pay people for their knowledge and lived experiences, especially when interviewing survivors of any kind of trauma. Don’t ask survivors to share their trauma for free, as this is exploitative. You should always make the offer in the first interview, even though some survivors might not want to be paid. An alternative to payment is to donate to an organization working against the type of violence that the interviewee experienced. In Chapter 6, we’ll discuss how to approach interviews with survivors.

Specific research: Abusers

It’s unlikely that safety-focused projects will be able to interview self-declared abusers or those who have broken laws in areas like hacking. Don’t make this a goal, rather, try to get at this angle in your general research. Attempt to understand how abusers or bad actors use technology to harm others, how they use it against others, and how they justify or explain the abuse.

Step 2: Create archetypes

Use your research’s findings to create abuser and survivor archetypes once you’ve finished conducting your research. Archetypes are not personas, as they’re not based on real people that you interviewed and surveyed. They are based on your investigation into potential safety problems, similar to how we design for accessibility: we don’t need to have identified any blind or vision users in our interview pool to come up with a design that is representative of them. Instead, we base those designs on existing research into what this group needs. While archetypes are broad and can be more generalized, real users typically represent real users and contain many details.

The abuser archetype is someone who will look at the product as a tool to perform harm ( Fig 5.2 ). They may be attempting to harm someone they don’t know by using surveillance or anonymous harassment, or they may be attempting to control, monitor, abuse, or otherwise torment someone they know.

The survivor archetype describes a person who is being abused with the product. There are various situations to consider in terms of the archetype’s understanding of the abuse and how to put an end to it: Do they need proof of abuse they already suspect is happening, or are they unaware they’ve been targeted in the first place and need to be alerted ( Fig 5.3 )?

To capture a range of experiences, you might want to create several survivor archetypes. They may know that the abuse is happening but not be able to stop it, like when an abuser locks them out of IoT devices, or they know it’s happening but don’t know how, such as when a stalker keeps figuring out their location ( Fig 5.4). In your survivor archetype, include as many of these scenarios as you need. You’ll use these later on when you design solutions to help your survivor archetypes achieve their goals of preventing and ending abuse.

It may be useful for you to create persona-like artifacts for your archetypes, such as the three examples shown. Focus on their objectives rather than the demographic information we frequently see in personas. The goals of the abuser will be to carry out the specific abuse you’ve identified, while the goals of the survivor will be to prevent abuse, understand that abuse is happening, make ongoing abuse stop, or regain control over the technology that’s being used for abuse. Later, you’ll think about how to help the survivor’s goals and the abuser’s goals.

And while the “abuser/survivor” model fits most cases, it doesn’t fit all, so modify it as you need to. For instance, if you found a security flaw, such as the ability for someone to hack into a home camera system and talk to kids, the malicious hacker would receive the abuser archetype and the child’s parents would receive the survivor archetype.

Step 3: Brainstorm problems

Brainstorm novel abuse cases and safety concerns after creating archetypes. ” Novel” means things not found in your research, you’re trying to identify completely new safety issues that are unique to your product or service. This step is intended to exhaust every effort put forth to identify potential harms your product might cause. You aren’t worrying about how to prevent the harm yet—that comes in the next step.

What other abuses could your product be used for besides what you’ve already discovered through your research? I recommend setting aside at least a few hours with your team for this process.

Try conducting a Black Mirror brainstorming session if you want to start somewhere. This exercise is based on the show Black Mirror, which features stories about the dark possibilities of technology. Try to figure out the most outrageous, horrible, and out-of-control ways your product could harm you in a show episode. When I’ve led Black Mirror brainstorms, participants usually end up having a good deal of fun ( which I think is great—it’s okay to have fun when designing for safety! ). I suggest that you time-box a Black Mirror brainstorm for the first half an hour, then dial it back, and then consider more realistic ways of harm the remaining half.

After you’ve identified as many opportunities for abuse as possible, you may still not feel confident that you’ve uncovered every potential form of harm. When you’re doing this kind of work, a healthy amount of anxiety is normal. It’s common for teams designing for safety to worry,” Have we really identified every possible harm? What if something is missing, then? If you’ve spent at least four hours coming up with ways your product could be used for harm and have run out of ideas, go to the next step.

It’s impossible to say 100 % assurance that you’ve done everything, but instead of aiming for 100 %, acknowledge that you’ve done it and will continue to prioritize safety in the future. Once your product is released, your users may identify new issues that you missed, aim to receive that feedback graciously and course-correct quickly.

4. Create solutions

At this point, you should have a list of ways your product can be used for harm as well as survivor and abuser archetypes describing opposing user goals. Next, it’s time to figure out how to design in accordance with the objectives of the identified abuser and the objectives of the survivor. This step is a good one to insert alongside existing parts of your design process where you’re proposing solutions for the various problems your research uncovered.

Questions to yourself should you ask yourself to protect your archetypes and to support them

• Can you design your product in such a way that the identified harm cannot happen in the first place? If not, what barriers can you place to stop the harm from occurring?
• How can you make the victim aware that abuse is happening through your product?
• How can you assist the victim in understanding what they need to do to stop the problem?
• Can you identify any types of user activity that would indicate some form of harm or abuse? Could your product provide support for the user?

In some products, it’s possible to proactively recognize that harm is happening. For instance, a pregnancy app might be modified to allow users to report that they were the victims of an assault, which could result in an offer to receive resources for local and national organizations. This sort of proactiveness is not always possible, but it’s worth taking a half hour to discuss if any type of user activity would indicate some form of harm or abuse, and how your product could assist the user in receiving help in a safe manner.

Nonetheless, be careful when doing anything that could harm a user if their devices are being monitored. If you do offer some kind of proactive help, always make it voluntary, and think through other safety issues, such as the need to keep the user in-app in case an abuser is checking their search history. In the next chapter, we’ll walk through a good illustration of this.

Step 5: Test for safety

The final step is to evaluate your prototypes from the perspective of your archetypes, who wants to harm the product and the victim of the harm who needs to regain control over the technology. Just like any other kind of product testing, at this point you’ll aim to rigorously test out your safety solutions so that you can identify gaps and correct them, validate that your designs will help keep your users safe, and feel more confident releasing your product into the world.

Safety testing should be performed along with usability testing. If you’re at a company that doesn’t do usability testing, you might be able to use safety testing to cleverly perform both, a user who goes through your design attempting to weaponize the product against someone else can also be encouraged to point out interactions or other elements of the design that don’t make sense to them.

If your final prototype or the finished product has already been released, you’ll want to conduct safety testing on both. There’s nothing wrong with testing an existing product that wasn’t designed with safety goals in mind from the onset —”retrofitting” it for safety is a good thing to do.

Keep in mind that testing for safety involves both an abuser and a survivor’s perspective, even though it might not make sense for you to do both. Alternatively, if you made multiple survivor archetypes to capture multiple scenarios, you’ll want to test from the perspective of each one.

You as the designer are probably too closely acquainted with the product and its design at this point, just like other usability testing techniques, and you know the product too well. Instead of doing it yourself, set up testing as you would with other usability testing: find someone who is not familiar with the product and its design, set the scene, give them a task, encourage them to think out loud, and observe how they attempt to complete it.

testing for abuse

The goal of this testing is to understand how easy it is for someone to weaponize your product for harm. You want to make it impossible, or at least difficult for them to accomplish their goal, unlike with usability testing. Reference the goals in the abuser archetype you created earlier, and use your product in an attempt to achieve them.

For instance, we can imagine that the abuser archetype would have the goal of determining the location of his ex-girlfriend right now in a fitness app with GPS-enabled location features. With this goal in mind, you’d try everything possible to figure out the location of another user who has their privacy settings enabled. You might try to follow her running routes, view any information she has on her profile, view any information she has made private, and check out the profiles of any other users who are connected to her account, such as her followers.

If by the end of this you’ve managed to uncover some of her location data, despite her having set her profile to private, you know now that your product enables stalking. Returning to step 4 and figuring out how to stop this from occurring is your next step. You may need to repeat the process of designing solutions and testing them more than once.

Survivor testing

Survivor testing involves identifying how to give information and power to the survivor. Depending on the product or context, it might not always make sense. Thwarting the attempt of an abuser archetype to stalk someone also satisfies the goal of the survivor archetype to not be stalked, so separate testing wouldn’t be needed from the survivor’s perspective.

There are times, however, when it makes sense. For example, for a smart thermostat, a survivor archetype’s goals would be to understand who or what is making the temperature change when they aren’t doing it themselves. If you couldn’t find the information in step 4, you would need to perform more work in step 4. You could test this by looking for the thermostat’s history log and looking for usernames, actions, and times.

Another goal might be regaining control of the thermostat once the survivor realizes the abuser is remotely changing its settings. Are there any instructions that explain how to remove a user and change the password, and are they simple to locate? For your test, this would involve trying to figure out how to do this. This might again reveal that more work is needed to make it clear to the user how they can regain control of the device or account.

stress testing

To make your product more inclusive and compassionate, consider adding stress testing. Eric Meyer and Sara Wachter-Boettcher’s Design for Real Life inspired this idea. The authors pointed out that personas typically center people who are having a good day—but real users are often anxious, stressed out, having a bad day, or even experiencing tragedy. These are known as” stress cases,” and analyzing your products to see if they respond to users in stressful circumstances can reveal areas where your design lacks compassion. Design for Real Life has more details about what it looks like to incorporate stress cases into your design as well as many other great tactics for compassionate design.

But how can a content management system ( CMS ) be set up to reach your current and future audience? I learned the hard way that creating a content model—a concept of information types, attributes, and relationships that let people and systems understand content—with my more comfortable design-system wondering would collapse my patient’s holistic information strategy. By developing willing versions that are conceptual and that also connect related information, you can avoid that result.

A Fortune 500 company recently tapped me to guide the CMS application. The customer was excited by the benefits of an holistic information plan, including material modify, multichannel marketing, and robot delivery—designing content to be comprehensible to bots, Google knowledge panels, snippets, and voice user interfaces.

A content type is essential for an omnichannel information strategy, and the model needed conceptual types, which are types of types that are categorized according to their meaning rather than their presentation. Our aim was to allow artists to create original content and use it where necessary. However, as the project progressed, I realized that the entire team had to be aware of a new design in order to support material reuse at the level that my customer needed.

Despite our best motives, we kept drawing from what we were more common with: design techniques. Unlike web-focused information strategies, an holistic information strategy doesn’t rely on WYSIWYG equipment for design and structure. One of the main objectives of a material model was to deliver content to audiences across multiple marketing channels, which is a tendency that we have to approach the material model with.

Two fundamental tenets must be followed in order to create a successful content type

We needed to explain to our designers, developers, and stakeholders that we were undertaking a very unique task from their earlier web projects, where it was common for everyone to view content as visible building blocks that fit into layouts. The past approach made the designs feel more recognizable and intuitive, at first, at least because it was more comfortable and also more intuitive. We learned two guiding principles that helped the team comprehend how a willing model and the design processes we were familiar with were:

1. Instead of design, content models may establish semantics.
2. And glad models may connect elements that belong together.

Conceptual material models

A conceptual content type uses form and attribute names that reflect the content’s intended purpose and not its intended display. For instance, in a nonsemantic design, groups may produce varieties like teasers, press blocks, and cards. These types may simplify the presentation of material, but they do not aid in understanding the meaning of the articles, which would have opened the door to the articles presented in each marketing channel. In comparison, a conceptual content type uses kind names like “product,”” service,” and “testimonial” to allow for each delivery channel to interpret and use the content as it sees fit.

A great place to start when creating a conceptual content type is by reviewing the types and qualities that Schema has defined. nonprofit, a community-driven source for type meanings that are comprehensible to platforms like Google search.

A semantic information model has many advantages:

A semantic articles design decouples content from its presentation, eliminating the need for teams to restructure the website’s design. This allows teams to develop the design without having to restructure its content. In this way, content may withstand problematic site redesigns.
• A conceptual content model also gives you an advantage in the market. by including structured, schema-based files. org’s forms and properties, a site can give hints to help Google understand the content, display it in research snippets or information panels, and use it to reply voice-interface customer questions. Potential customers could access your content without ever visiting your website.
• A semantic content model is also necessary if you want to deliver omnichannel content in addition to those practical advantages. Delivery channels must be able to comprehend the same content in order to use it across multiple marketing channels. For instance, if your content model provided a list of questions and answers, it could be used as a voice interface or by a bot to answer frequently asked questions ( FAQ ) pages.

For example, using a semantic content model for articles, events, people, and locations lets A List Apart provide cleanly structured data for search engines so that users can read the content on the website, in Google knowledge panels, and even with hypothetical voice interfaces in the future.

Content models that connect

Instead of slicing up related content across disparate content components, I’ve come to the realization that the best models are those that are semantic and also connect related content components ( such as a FAQ item’s question and answer pair ). A good content model connects pieces of content that ought to be preserved so that multiple delivery channels can use it without having to assemble those pieces separately.

Write an essay or article about it. An article’s meaning and usefulness depends upon its parts being kept together. Would one of the headings or paragraphs have any significance on their own if the entire article were not included? Our well-versed in designing systems frequently led us to want to develop content models that would break content into smaller pieces to fit the web-centric layout. This had a similar effect to an article that had its headline removed. Because we were dividing content into separate pieces based on layout, content that belonged together became challenging to manage and nearly impossible for multiple delivery channels to comprehend.

To illustrate, let’s look at how connecting related content applies in a real-world scenario. The client’s design team created a challenging layout for a software product page that included numerous tabs and sections. Our instincts were to follow the content model’s. Shouldn’t we make adding multiple tabs in the future as simple and flexible as possible?

We felt like we needed a content type called “tab section” because our design-system instincts were so well-known, so that multiple tab sections could be added to a page. Each tab section would display a variety of content. One tab might provide the software’s overview or its specifications. Another tab might provide a list of resources.

Our tendency to divide the content model into “tab section” pieces would have resulted in a cumbersome editing process, as well as unnecessarily complex content that couldn’t have been digested by additional delivery channels. How would a different system have been able to determine which “tab section” referred to a product’s specifications or resource list, for instance? Would that system have had to have used tab sections and content blocks to calculate this? This would have prevented the tabs from ever being rearranged, and it would have required adding logic to each other delivery channel to interpret the layout of the design system. Additionally, it would have been difficult to migrate to a new content model in response to the new page redesign if the customer had decided against displaying this content in a tab layout.

We had a breakthrough when we discovered that our customer had a specific purpose in mind for each tab: it would reveal specific information such as the software product’s overview, specifications, related resources, and pricing. Our desire to concentrate on the visually appealing and well-known had obscured the design’s purpose once implementation began. With a little digging, it didn’t take long to realize that the concept of tabs wasn’t relevant to the content model. What was important was the meaning of the content they were planning to display in the tabs.

In fact, the customer could have chosen to display this content elsewhere in a different manner, without tabs. In response to this realization, we created content types for the software product based on the meaningful attributes the client wanted to display on the web. There were obvious semantic attributes like name and description as well as rich attributes like screenshots, software requirements, and feature lists. The software’s product information stayed together because it wasn’t sliced across separate components like “tab sections” that were derived from the content’s presentation. Any delivery channel—including future ones—could understand and present this content.

Conclusion

In this omnichannel marketing project, we discovered that the best way to maintain the content model’s semantic consistency was by ensuring that it was semantic ( with type and attribute names that reflected the content’s meaning ) and that it maintained content that belonged together ( as opposed to fragmenting it ). These two ideas made it easier for us to decide what to do with the content model based on the design. Remember: If you’re developing a content model to support an omnichannel content strategy, or even if you just want to make sure that Google and other interfaces understand your content, keep in mind:

• A design system isn’t a content model. You should maintain the semantic value and contextual structure of the content strategy throughout the entire implementation process because team members might be tempted to combine them and to make your content model resemble your design system. Without the use of a magic decoder ring, every delivery channel will be able to consume the content.
• If your team is having trouble making this transition, Schema can still offer some of the advantages. org–based structured data in your website. The benefit of search engine optimization is a compelling argument on its own, even if additional delivery channels aren’t on the horizon at this time.
• Remind the team that separating the content model from the design will allow them to update the designs more quickly because they won’t be hindered by the cost of content migrations. They’ll be able to create new designs without compromising the compatibility between the content and the design, and they’ll be prepared for the upcoming big thing.

By firmly defending these ideas, you’ll help your team treat content the way it deserves as the most important component of your user experience and the best way to engage with your audience.

Do you find yourself designing screens with only a vague idea of how the things on the screen relate to the things elsewhere in the system? Do you leave stakeholder meetings with unclear directives that often seem to contradict previous conversations? You know a better understanding of user needs would help the team get clear on what you are actually trying to accomplish, but time and budget for research is tight. When it comes to asking for more direct contact with your users, you might feel like poor Oliver Twist, timidly asking, “Please, sir, I want some more.” 

Here’s the trick. You need to get stakeholders themselves to identify high-risk assumptions and hidden complexity, so that they become just as motivated as you to get answers from users. Basically, you need to make them think it’s their idea. 

In this article, I’ll show you how to collaboratively expose misalignment and gaps in the team’s shared understanding by bringing the team together around two simple questions:

1. What are the objects?
2. What are the relationships between those objects?

A gauntlet between research and screen design

These two questions align to the first two steps of the ORCA process, which might become your new best friend when it comes to reducing guesswork. Wait, what’s ORCA?! Glad you asked.

ORCA stands for Objects, Relationships, CTAs, and Attributes, and it outlines a process for creating solid object-oriented user experiences. Object-oriented UX is my design philosophy. ORCA is an iterative methodology for synthesizing user research into an elegant structural foundation to support screen and interaction design. OOUX and ORCA have made my work as a UX designer more collaborative, effective, efficient, fun, strategic, and meaningful.

The ORCA process has four iterative rounds and a whopping fifteen steps. In each round we get more clarity on our Os, Rs, Cs, and As.

I sometimes say that ORCA is a “garbage in, garbage out” process. To ensure that the testable prototype produced in the final round actually tests well, the process needs to be fed by good research. But if you don’t have a ton of research, the beginning of the ORCA process serves another purpose: it helps you sell the need for research.

In other words, the ORCA process serves as a gauntlet between research and design. With good research, you can gracefully ride the killer whale from research into design. But without good research, the process effectively spits you back into research and with a cache of specific open questions.

Getting in the same curiosity-boat

What gets us into trouble is not what we don’t know. It’s what we know for sure that just ain’t so.

Mark Twain

The first two steps of the ORCA process—Object Discovery and Relationship Discovery—shine a spotlight on the dark, dusty corners of your team’s misalignments and any inherent complexity that’s been swept under the rug. It begins to expose what this classic comic so beautifully illustrates:

This is one reason why so many UX designers are frustrated in their job and why many projects fail. And this is also why we often can’t sell research: every decision-maker is confident in their own mental picture. 

Once we expose hidden fuzzy patches in each picture and the differences between them all, the case for user research makes itself.

But how we do this is important. However much we might want to, we can’t just tell everyone, “YOU ARE WRONG!” Instead, we need to facilitate and guide our team members to self-identify holes in their picture. When stakeholders take ownership of assumptions and gaps in understanding, BAM! Suddenly, UX research is not such a hard sell, and everyone is aboard the same curiosity-boat.

Say your users are doctors. And you have no idea how doctors use the system you are tasked with redesigning.

You might try to sell research by honestly saying: “We need to understand doctors better! What are their pain points? How do they use the current app?” But here’s the problem with that. Those questions are vague, and the answers to them don’t feel acutely actionable.

Instead, you want your stakeholders themselves to ask super-specific questions. This is more like the kind of conversation you need to facilitate. Let’s listen in:

“Wait a sec, how often do doctors share patients? Does a patient in this system have primary and secondary doctors?”

“Can a patient even have more than one primary doctor?”

“Is it a ‘primary doctor’ or just a ‘primary caregiver’… Can’t that role be a nurse practitioner?”

“No, caregivers are something else… That’s the patient’s family contacts, right?”

“So are caregivers in scope for this redesign?”

“Yeah, because if a caregiver is present at an appointment, the doctor needs to note that. Like, tag the caregiver on the note… Or on the appointment?”

Now we are getting somewhere. Do you see how powerful it can be getting stakeholders to debate these questions themselves? The diabolical goal here is to shake their confidence—gently and diplomatically.

When these kinds of questions bubble up collaboratively and come directly from the mouths of your stakeholders and decision-makers, suddenly, designing screens without knowing the answers to these questions seems incredibly risky, even silly.

If we create software without understanding the real-world information environment of our users, we will likely create software that does not align to the real-world information environment of our users. And this will, hands down, result in a more confusing, more complex, and less intuitive software product.

The two questions

But how do we get to these kinds of meaty questions diplomatically, efficiently, collaboratively, and reliably? 

We can do this by starting with those two big questions that align to the first two steps of the ORCA process:

1. What are the objects?
2. What are the relationships between those objects?

In practice, getting to these answers is easier said than done. I’m going to show you how these two simple questions can provide the outline for an Object Definition Workshop. During this workshop, these “seed” questions will blossom into dozens of specific questions and shine a spotlight on the need for more user research.

Prep work: Noun foraging

In the next section, I’ll show you how to run an Object Definition Workshop with your stakeholders (and entire cross-functional team, hopefully). But first, you need to do some prep work.

Basically, look for nouns that are particular to the business or industry of your project, and do it across at least a few sources. I call this noun foraging.

Here are just a few great noun foraging sources:

• the product’s marketing site
• the product’s competitors’ marketing sites (competitive analysis, anyone?)
• the existing product (look at labels!)
• user interview transcripts
• notes from stakeholder interviews or vision docs from stakeholders

Put your detective hat on, my dear Watson. Get resourceful and leverage what you have. If all you have is a marketing website, some screenshots of the existing legacy system, and access to customer service chat logs, then use those.

As you peruse these sources, watch for the nouns that are used over and over again, and start listing them (preferably on blue sticky notes if you’ll be creating an object map later!).

You’ll want to focus on nouns that might represent objects in your system. If you are having trouble determining if a noun might be object-worthy, remember the acronym SIP and test for:

1. Structure
2. Instances
3. Purpose

Think of a library app, for example. Is “book” an object?

Structure: can you think of a few attributes for this potential object? Title, author, publish date… Yep, it has structure. Check!

Instance: what are some examples of this potential “book” object? Can you name a few? The Alchemist, Ready Player One, Everybody Poops… OK, check!

Purpose: why is this object important to the users and business? Well, “book” is what our library client is providing to people and books are why people come to the library… Check, check, check!

As you are noun foraging, focus on capturing the nouns that have SIP. Avoid capturing components like dropdowns, checkboxes, and calendar pickers—your UX system is not your design system! Components are just the packaging for objects—they are a means to an end. No one is coming to your digital place to play with your dropdown! They are coming for the VALUABLE THINGS and what they can do with them. Those things, or objects, are what we are trying to identify.

Let’s say we work for a startup disrupting the email experience. This is how I’d start my noun foraging.

First I’d look at my own email client, which happens to be Gmail. I’d then look at Outlook and the new HEY email. I’d look at Yahoo, Hotmail…I’d even look at Slack and Basecamp and other so-called “email replacers.” I’d read some articles, reviews, and forum threads where people are complaining about email. While doing all this, I would look for and write down the nouns.

(Before moving on, feel free to go noun foraging for this hypothetical product, too, and then scroll down to see how much our lists match up. Just don’t get lost in your own emails! Come back to me!)

Drumroll, please…

Here are a few nouns I came up with during my noun foraging:

• email message
• thread
• contact
• client
• rule/automation
• email address that is not a contact?
• contact groups
• attachment
• Google doc file / other integrated file
• newsletter? (HEY treats this differently)
• saved responses and templates

Scan your list of nouns and pick out words that you are completely clueless about. In our email example, it might be client or automation. Do as much homework as you can before your session with stakeholders: google what’s googleable. But other terms might be so specific to the product or domain that you need to have a conversation about them.

Aside: here are some real nouns foraged during my own past project work that I needed my stakeholders to help me understand:

• Record Locator
• Incentive Home
• Augmented Line Item
• Curriculum-Based Measurement Probe

This is really all you need to prepare for the workshop session: a list of nouns that represent potential objects and a short list of nouns that need to be defined further.

Facilitate an Object Definition Workshop

You could actually start your workshop with noun foraging—this activity can be done collaboratively. If you have five people in the room, pick five sources, assign one to every person, and give everyone ten minutes to find the objects within their source. When the time’s up, come together and find the overlap. Affinity mapping is your friend here!

If your team is short on time and might be reluctant to do this kind of grunt work (which is usually the case) do your own noun foraging beforehand, but be prepared to show your work. I love presenting screenshots of documents and screens with all the nouns already highlighted. Bring the artifacts of your process, and start the workshop with a five-minute overview of your noun foraging journey.

HOT TIP: before jumping into the workshop, frame the conversation as a requirements-gathering session to help you better understand the scope and details of the system. You don’t need to let them know that you’re looking for gaps in the team’s understanding so that you can prove the need for more user research—that will be our little secret. Instead, go into the session optimistically, as if your knowledgeable stakeholders and PMs and biz folks already have all the answers. 

Then, let the question whack-a-mole commence.

1. What is this thing?

Want to have some real fun? At the beginning of your session, ask stakeholders to privately write definitions for the handful of obscure nouns you might be uncertain about. Then, have everyone show their cards at the same time and see if you get different definitions (you will). This is gold for exposing misalignment and starting great conversations.

As your discussion unfolds, capture any agreed-upon definitions. And when uncertainty emerges, quietly (but visibly) start an “open questions” parking lot. 😉

After definitions solidify, here’s a great follow-up:

2. Do our users know what these things are? What do users call this thing?

Stakeholder 1: They probably call email clients “apps.” But I’m not sure.

Stakeholder 2: Automations are often called “workflows,” I think. Or, maybe users think workflows are something different.

If a more user-friendly term emerges, ask the group if they can agree to use only that term moving forward. This way, the team can better align to the users’ language and mindset.

OK, moving on. 

If you have two or more objects that seem to overlap in purpose, ask one of these questions:

3. Are these the same thing? Or are these different? If they are not the same, how are they different?

You: Is a saved response the same as a template?

Stakeholder 1: Yes! Definitely.

Stakeholder 2: I don’t think so… A saved response is text with links and variables, but a template is more about the look and feel, like default fonts, colors, and placeholder images. 

Continue to build out your growing glossary of objects. And continue to capture areas of uncertainty in your “open questions” parking lot.

If you successfully determine that two similar things are, in fact, different, here’s your next follow-up question:

4. What’s the relationship between these objects?

You: Are saved responses and templates related in any way?

Stakeholder 3:  Yeah, a template can be applied to a saved response.

You, always with the follow-ups: When is the template applied to a saved response? Does that happen when the user is constructing the saved response? Or when they apply the saved response to an email? How does that actually work?

Listen. Capture uncertainty. Once the list of “open questions” grows to a critical mass, pause to start assigning questions to groups or individuals. Some questions might be for the dev team (hopefully at least one developer is in the room with you). One question might be specifically for someone who couldn’t make it to the workshop. And many questions will need to be labeled “user.” 

Do you see how we are building up to our UXR sales pitch?

5. Is this object in scope?

Your next question narrows the team’s focus toward what’s most important to your users. You can simply ask, “Are saved responses in scope for our first release?,” but I’ve got a better, more devious strategy.

By now, you should have a list of clearly defined objects. Ask participants to sort these objects from most to least important, either in small breakout groups or individually. Then, like you did with the definitions, have everyone reveal their sort order at once. Surprisingly—or not so surprisingly—it’s not unusual for the VP to rank something like “saved responses” as #2 while everyone else puts it at the bottom of the list. Try not to look too smug as you inevitably expose more misalignment.

I did this for a startup a few years ago. We posted the three groups’ wildly different sort orders on the whiteboard.

The CEO stood back, looked at it, and said, “This is why we haven’t been able to move forward in two years.”

Admittedly, it’s tragic to hear that, but as a professional, it feels pretty awesome to be the one who facilitated a watershed realization.

Once you have a good idea of in-scope, clearly defined things, this is when you move on to doing more relationship mapping.

6. Create a visual representation of the objects’ relationships

We’ve already done a bit of this while trying to determine if two things are different, but this time, ask the team about every potential relationship. For each object, ask how it relates to all the other objects. In what ways are the objects connected? To visualize all the connections, pull out your trusty boxes-and-arrows technique. Here, we are connecting our objects with verbs. I like to keep my verbs to simple “has a” and “has many” statements.

This system modeling activity brings up all sorts of new questions:

• Can a saved response have attachments?
• Can a saved response use a template? If so, if an email uses a saved response with a template, can the user override that template?
• Do users want to see all the emails they sent that included a particular attachment? For example, “show me all the emails I sent with ProfessionalImage.jpg attached. I’ve changed my professional photo and I want to alert everyone to update it.” 

Solid answers might emerge directly from the workshop participants. Great! Capture that new shared understanding. But when uncertainty surfaces, continue to add questions to your growing parking lot.

Light the fuse

You’ve positioned the explosives all along the floodgates. Now you simply have to light the fuse and BOOM. Watch the buy-in for user research flooooow.

Before your workshop wraps up, have the group reflect on the list of open questions. Make plans for getting answers internally, then focus on the questions that need to be brought before users.

Here’s your final step. Take those questions you’ve compiled for user research and discuss the level of risk associated with NOT answering them. Ask, “if we design without an answer to this question, if we make up our own answer and we are wrong, how bad might that turn out?” 

With this methodology, we are cornering our decision-makers into advocating for user research as they themselves label questions as high-risk. Sorry, not sorry. 

Now is your moment of truth. With everyone in the room, ask for a reasonable budget of time and money to conduct 6–8 user interviews focused specifically on these questions. 

HOT TIP: if you are new to UX research, please note that you’ll likely need to rephrase the questions that came up during the workshop before you present them to users. Make sure your questions are open-ended and don’t lead the user into any default answers.

Final words: Hold the screen design!

Seriously, if at all possible, do not ever design screens again without first answering these fundamental questions: what are the objects and how do they relate?

I promise you this: if you can secure a shared understanding between the business, design, and development teams before you start designing screens, you will have less heartache and save more time and money, and (it almost feels like a bonus at this point!) users will be more receptive to what you put out into the world. 

I sincerely hope this helps you win time and budget to go talk to your users and gain clarity on what you are designing before you start building screens. If you find success using noun foraging and the Object Definition Workshop, there’s more where that came from in the rest of the ORCA process, which will help prevent even more late-in-the-game scope tugs-of-war and strategy pivots. 

All the best of luck! Now go sell research!