Blog

One of the most powerful smooth abilities we have at our disposal is the ability to work together to improve our designs while developing our own abilities and perspectives, regardless of how it is used or what it might be called.

Feedback is also one of the most underestimated equipment, and generally by assuming that we’re now great at it, we settle, forgetting that it’s a skill that can be trained, grown, and improved. Bad feedback can cause conflict in jobs, lower motivation, and negatively impact faith and teamwork over the long term. Quality comments can be a revolutionary force.

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 adjusted for isolated and distributed function settings?

On the web, we may find a long history of sequential comments: code was written and discussed on mailing lists since the beginning of open source. Currently, engineers engage on pull calls, developers post in their favourite design tools, project managers and sprint masters exchange ideas on tickets, and so on.

Design analysis is often the label used for a type of input that’s provided to make our job better, jointly. It generally shares many of the principles with comments, but it also has some differences.

The information

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

This equation, 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. If you keep the three components of the equation in mind, you’ll have a mental unit that can help you become more precise and effective.

Here is a reply that could be included in some feedback, and it might appear fair at first glance because it appears to merely fit the equation. But does it?

Not confident about the keys ‘ patterns and hierarchy—it feels off. Can they be altered?

Observation for style feedback doesn’t really mean pointing out which part of the software your input refers to, but it also refers to offering a viewpoint that’s as specific as possible. Do you offer the user’s viewpoint? Your expert perspective? A business perspective? 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.

Impact is about the why. 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 meant to provide open guidance by eliciting the critical thinking in the designer receiving the feedback. Notably, in Lara’s equation she provides a second approach: request, which instead provides guidance toward a specific solution. While that’s a viable option for general feedback, in my experience, going back to the question approach typically leads to the best solutions because designers are generally more at ease with having an open space to experiment with.

The difference between the two can be exemplified with, for the question 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. 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.

At this point in some situations, it might be useful to integrate with an extra why: why you consider the given suggestion to be better.

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 the question approach or the request approach can also at times be a matter of personal preference. I did rounds of anonymous feedback and I reviewed feedback with other people a while back when I was putting a lot of effort into improving my feedback. 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 changed teams. Surprise surprise, my next round of criticism from a specific person wasn’t very positive. 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 adapted my feedback for them 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. Yes, but also no. Let’s explore both sides.

No, this kind of feedback is effective because the length is a byproduct of clarity, and giving this kind of feedback can provide precisely enough information for a sound fix. Also if we zoom out, it can reduce future back-and-forth conversations and misunderstandings, improving the overall efficiency and effectiveness of collaboration beyond the single comment. Imagine that in the example above the feedback were instead just,” Let’s make sure that all screens have the same two forward and back buttons”. Since the designer receiving this feedback wouldn’t have much to go by, they might just make the change. In later iterations, the interface might change or they might introduce new features—and maybe that change might not make sense anymore. 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 style of feedback is not always efficient because the points in some comments don’t always need to be exhaustive, sometimes because certain changes may be obvious (” The font used doesn’t follow our guidelines” ) and sometimes because the team may have a lot of internal knowledge such that some of the whys may be implied.

The equation above is not intended to provide a predetermined template for feedback, but rather a mnemonic to reflect and enhance the practice. 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 tone

Well-grounded content is the foundation of feedback, 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 sustained change in people. It can be determined by tone alone whether content is rejected or welcomed.

Since our goal is to be understood and to have a positive working environment, tone is essential to work on. I’ve tried to summarize the necessary soft skills over the years using a formula that resembles that of the content receptivity equation.

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

The term “timing” describes the moment when the feedback occurs. To-the-point feedback doesn’t have much hope of being well received if it’s given at the wrong time. 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 later? Polishing work in progress? Each of these has unique needs. The right timing will make it more likely that your feedback will be well received.

Attitude is the equivalent of intent, and in the context of person-to-person feedback, it can be referred to as radical candor. That entails checking before writing to see if what we have in mind will actually help the person and improve the project overall. This might be a hard reflection at times because maybe we don’t want to admit that we don’t really appreciate that person. Although it’s possible, and that’s okay, it’s hoped not to be the case. Acknowledging and owning that can help you make up for that: how would I write if I really cared about them? How can I avoid being passive aggressive? How can I encourage constructive behavior?

Form is relevant especially in a diverse and cross-cultural work environments because having great content, perfect timing, and the right attitude might not come across if the way that we write creates misunderstandings. There could be many reasons for this: some words might cause particular reactions, some non-native speakers might not understand all the nuances of some sentences, and other times our brains might be different and we might perceive the world differently. Neurodiversity must be taken into account. Whatever the reason, it’s important to review not just what we write but how.

A few years back, I was asking for some feedback on how I give feedback. I was given some sound advice, but I also got a surprise comment. They pointed out that when I wrote” Oh, ]… ]”, I made them feel stupid. That’s not what I meant to say! I felt really bad, and I just realized that I provided feedback to them for months, and every time I might have made them feel stupid. 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 highlight because it’s quite frequent—especially in teams that have a strong group spirit—is that people tend to beat around the bush. It’s important to keep in mind that having a positive attitude doesn’t necessarily mean passing judgment on the feedback; rather, it simply means that even when you give difficult, or difficult feedback, you do so in a way that’s respectful and constructive. The nicest thing that you can do for someone is to help them grow.

We have a great advantage in giving feedback in written form: it can be reviewed by another person who isn’t directly involved, which can help to reduce or remove any bias that might be there. When I shared a comment with someone I knew,” How does this sound,”” How can I do it better,” or even” How would you have written it,” I discovered that the two versions had different meanings.

The format

Asynchronous feedback also has a significant inherent benefit: it allows us to spend more time making sure that the suggestions ‘ clarity and actionability meet two main objectives.

Let’s imagine that someone shared a design iteration for a project. You are reviewing it and leaving a comment. Let’s try to think about some factors that might be helpful to consider, as there are many ways to accomplish this, and context is of course a factor.

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 coming from a high-level perspective, or are you figuring out the details? Are there regressions? Which user’s point of view are you addressing when offering feedback? Is the design iteration at a point where it would be okay to ship this, or are there major things that need to be addressed first?

Even if you’re giving feedback to a team that already has some background information on the project, providing context is helpful. And context is absolutely essential when giving cross-team feedback. If I were to review a design that might be indirectly related to my work, and if I had no knowledge about how the project arrived at that point, I would say so, highlighting my take as external.

We frequently concentrate on the negatives and attempt to list every improvement that could be made. That’s of course important, but it’s just as important—if not more—to focus on the positives, especially if you saw progress from the previous iteration. 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. In the longer term, sharing positive feedback can help prevent regressions on things that are going well because those things will have been highlighted as important. 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.

Another way that you can improve your feedback is to depersonalize the feedback: the comments should always be about the work, never about the person who made it. 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.

In terms of actionability, one of the best approaches to help the designer who’s reading through your feedback is to split it into bullet points or paragraphs, which are easier to review and analyze one by one. You might want to break up the feedback into sections or even between several comments for longer pieces. Of course, adding screenshots or signifying markers of the specific part of the interface you’re referring to can also be especially useful.

One approach that I’ve personally used effectively in some contexts is to enhance the bullet points with four markers using emojis. A red square indicates that it is something I consider blocking, a yellow diamond indicates that it needs to be changed, and a green circle provides a thorough, positive confirmation. I also use a blue spiral � � for either something that I’m not sure about, an exploration, an open alternative, or just a note. 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 I’d have to reframe how I’d 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 think the page is solid, and this is good enough to be our release candidate for a version 1.0.
• � � 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 gives the impression that it’s a positive action because green is typically seen as a confirmation color. Do we need to explore a different color?
• Tiles—It seems to me that the tiles should use the Subtitle 2 style rather than the Subtitle 1 style given the number of items on the page and the overall page hierarchy. This will keep the visual hierarchy more consistent.
• � � Background—Using a light texture works well, but I wonder whether it adds too much noise in this kind of page. What is the purpose of using that?

What about giving feedback directly in Figma or another design tool that allows in-place feedback? 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.

One final note: say the obvious. We don’t say something because we sometimes think it’s obvious that something is either good or wrong. Or sometimes we might have a doubt that we don’t express because the question might sound stupid. Say it, that’s fine. You might have to reword it a little bit to make the reader feel more comfortable, but don’t hold it back. Good feedback is transparent, even when it may be obvious.

Asynchronous feedback also has the benefit of automatically guiding decisions, according to writing. Especially in large projects,” Why did we do this”? There’s nothing better than open, transparent discussions that can be reviewed at any time, and this could be a question that arises from time to time. For this reason, I recommend using software that saves these discussions, without hiding them once they are resolved.

Content, tone, and format. Although each of these subjects offers a useful model, improving eight of the subjects ‘ observation, impact, question, timing, attitude, form, clarity, and actionability is a lot of work to put in all at once. One effective approach is to take them one by one: first identify the area that you lack the most (either from your perspective or from feedback from others ) and start there. 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 Brie Anne Demkiw and Mike Shelton for reviewing the first draft of this article.

” Any post” you might have? is perhaps one of the worst ways to ask for suggestions. It’s obscure and unfocused, and it doesn’t give us a sense of what we’re looking for. Getting good opinions starts sooner than we might hope: it starts with the demand.

Starting the process of receiving feedback with a question may seem counterintuitive, but it makes sense if we consider that receiving feedback can be considered a form of pattern research. In the same way that we wouldn’t perform any studies without the correct questions to get the insight that we need, the best way to ask for feedback is also to build strong issues.

Design criticism is never 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.

And suddenly, as with any great research, we need to review what we got up, get to the base of its perspectives, and take activity. Iteration, evaluation, and problem. This 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 conclusion of a presentation are likely to garner a lot of different ideas, or worse, to make everyone follow the lead of the first speaker. And next… we get frustrated because vague issues like those you turn a high-level moves review into folks rather commenting on the borders of buttons. Which topic may be significant, so it might be difficult to get the team to choose the one you wanted to concentrate on.

But how do we get into this scenario? It’s a combination of various aspects. One is that we don’t often consider asking as a part of the input approach. Another is how healthy it is to leave the question open and assume that everyone else will agree. Another is that in nonprofessional debate, there’s usually no need to be that exact. In summary, we tend to undervalue the value of the issues, and we don’t make any improvements to them.

The work of asking good questions guidelines and focuses the criticism. It also serves as a form of acceptance, outlining your willingness to make comments and the types of responses you want to receive. It puts people in the right emotional state, especially in situations when they weren’t expecting to give opinions.

There isn’t a second best method to request comments. It simply needs to be certain, and precision may take several shapes. The concept of stage than level is a design for design criticism that I’ve found to be particularly helpful in my coaching.

” Stage” refers to each of the steps of the process—in our event, the design process. The kind of feedback changes as the person 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 comments into updated designs as the job has evolved. The layers of user experience could serve as a starting point for potential questions. What do you want to know: Project objectives? User requirements? Functionality? the content Interaction design? a system of information architecture UI design? Navigation planning? Visual design? Branding?

Here’re a few example questions that are precise and to the point that refer to different layers:

• Functionality: Is it desirable to automate account creation?
• Interaction design: Take a look through the updated flow and let me know whether you see any steps or error states that I might’ve missed.
• Information architecture: This page contains two competing pieces of information. Is the structure effective in communicating them both?
• User interface design: What do you think about the error counter at the top of the page, which makes sure you see the next error even if it is outside the viewport?
• Navigation design: From research, we identified these second-level navigation items, but once you’re on the page, the list feels too long and hard to navigate. Exist any recommendations for resolving this?
• Visual design: Are the sticky notifications in the bottom-right corner visible enough?

The other axis of specificity is determined by how far you’d like to go with the information being presented. For example, we might have introduced a new end-to-end flow, but there was a specific view that you found particularly challenging and you’d like a detailed review of that. This can be especially helpful from one iteration to the next when it’s crucial to highlight the areas that have changed.

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

Eliminating generic qualifiers from your questions like “good,” “well,” “nice,” “bad,” “okay,” and” cool” is a simple trick. For example, asking,” When the block opens and the buttons appear, is this interaction good”? is it possible to look specific, but you can identify the “good” qualifier and make the question” When the block opens and the buttons appear, is it clear what the next action is” look like?

Sometimes we actually do want broad feedback. That’s uncommon, but it can occur. 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’s clear that what you’re asking is open ended but focused on someone’s impression after their first five seconds of looking at it.

Sometimes the project is particularly broad, and some areas may have already been thoroughly explored. In these situations, it might be useful to explicitly say that some parts are already locked in and aren’t open to 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 further refinement but aren’t currently what matters most.

Asking specific questions can completely change the quality of the feedback that you receive. People with less refined criticism will now be able to provide more actionable feedback, and even expert designers will appreciate the clarity and effectiveness gained from concentrating solely on what’s needed. It can save a lot of time and frustration.

The iteration

Design iterations are probably the most visible part of the design work, and they provide a natural checkpoint for feedback. Many design tools have inline commenting, but many of those methods typically display changes as a single fluid stream in the same file. These methods cause conversations to vanish once they’re resolved, update shared UI components automatically, and require designs to always display the most recent version unless these would-be useful features were manually turned off. 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.

The asynchronous design-critique approach that I find most effective is to create explicit checkpoints for discussion. For this, I’ll use the term iteration post. It refers to a write-up or presentation of the design iteration followed by a discussion thread of some kind. This can be used on any platform that can accommodate this structure. 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 creates a rhythm in the design work so that the designer can review feedback from each iteration and prepare for the next.
• Decisions are always available, and conversations are also made accessible for future review.
• It creates a record of how the design changed over time.
• Depending on the tool, it might also make it simpler to collect and act on feedback.

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 ).

I don’t think there’s a standard format for iteration posts. However, there are a few high-level components that make sense as a baseline:

1. The goal
2. The layout
3. The list of changes
4. The querys

Each project is likely to have a goal, and hopefully it’s something that’s already been summarized in a single sentence somewhere else, such as the client brief, the product manager’s outline, or the project owner’s request. In every iteration post, I would copy and paste this, so I could do it again. The idea is to provide context and to repeat what’s essential to make each iteration post complete so that there’s no need to find information spread across multiple 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 design is then the actual series of information-architecture outlines, diagrams, flows, maps, wireframes, screens, visuals, and any other kind of design work that’s been done. In essence, it’s any design work. For the final stages of work, I prefer the term blueprint to emphasize that I’ll be showing full flows instead of individual screens to make it easier to understand the bigger 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 much different from creating a strong live presentation.

For an efficient discussion, you should also include a bullet list of the changes from the previous iteration to let people focus on what’s new, which can be especially useful for larger pieces of work where keeping track, iteration after iteration, could become a challenge.

Finally, as mentioned earlier, it’s crucial that you include a list of the questions to help you guide the design critique in the desired direction. Doing this as a numbered list can also help make it easier to refer to each question 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.

I want to highlight that even if these iteration posts are written and conceived as checkpoints, by no means do they need to be exhaustive. A post might be just a concept to start a conversation, or it might be a cumulative list of all the features that have been added gradually over the course of each iteration until the full picture is achieved.

Over time, I also started using specific labels for incremental iterations: 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. Everyone knows where to go to review things, and it’s simple to say” This was discussed in i4″ with each project.
• Unassuming—It works like versions ( such as v1, v2, and v3 ) but in contrast, versions create the impression of something that’s big, exhaustive, and complete. Exploratory, incomplete, or partial should be the definition of an argument.
• Future proof—It resolves the “final” naming problem that you can run into with versions. 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 areas that still need improvement and, in turn, require more iterations, such as” with i8 we reached RC” or “i12 is an RC” to indicate when it is finished.

The review

What typically occurs during a design critique is an open discussion that can be very productive between two people. This approach is particularly effective during live, synchronous feedback. However, when we work asynchronously, it is more effective to adopt a different strategy: 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 because of this shift, especially around these friction points:

1. It removes the pressure to reply to everyone.
2. It lessens the annoyance caused by swoop-by comments.
3. It lessens our personal stake.

The first friction is being forced to respond to every comment. Sometimes we write the iteration post, and we get replies from our team. It’s just a few of them, it’s simple, and there isn’t much to worry about. But other times, some solutions might require more in-depth discussions, and the amount of replies can quickly increase, which can create a tension between trying to be a good team player by replying to everyone and doing the next design iteration. This might be especially true if the respondent is a stakeholder or a person who is directly involved in the project and whom we feel we need to speak with. We need to accept that this pressure is absolutely normal, and it’s human nature to try to accommodate people who we care about. When we treat 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, responding to all comments can be effective.

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 might tag all the people who were involved in the previous discussion, but even that’s a choice, not a requirement.
• Another tactic is to formally acknowledge each comment in a brief response, such as” Understood. Thank you”,” Good points— I’ll review”, or” Thanks. These will be included in the upcoming iteration. 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 provide a quick summary of the comments before moving on. Depending on your workflow, this can be particularly useful as it can provide a simplified checklist that you can then use for the next iteration.

The swoop-by comment, which is the kind of feedback that comes from a member of a team or non-project who might not be aware of the context, restrictions, decisions, or requirements, or of the discussions from earlier iterations, is the second friction point. On their side, there’s something that one can hope that they might learn: they could start to acknowledge that they’re doing this and they could be more conscious in outlining where they’re coming from. Swoop-by comments frequently prompt the simple thought,” We’ve already discussed this,” and it can be frustrating to have to keep saying the same thing over and over.

Let’s begin by acknowledging again that there’s no need to reply to every comment. However, a brief response with a link to the previous discussion for additional information is typically sufficient if responding to a previously litigated point might be helpful. Remember, alignment comes from repetition, so it’s okay to repeat things sometimes!

Swoop-by commenting can still be useful for two reasons: first, they might point out something that isn’t clear, and second, they might have the power to fit in with a user’s perspective when they are seeing the design for the first time. Sure, you’ll still be frustrated, but that might at least help in dealing with it.

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 ). In the end, putting everything in aggregate form helps us to prioritize our work more.

Always remember that while you need to listen to stakeholders, project owners, and specific advice, you don’t have to accept every piece of feedback. You must examine it and come up with a rationale for your choice, but sometimes “no” is the best choice.

As the designer leading the project, you’re in charge of that decision. 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 stuck with me over the centuries. How do you generate solutions for scenarios you can’t think? Or create materials that are functional on products that have not yet been created?

Flash, Photoshop, and flexible pattern

When I first started designing sites, my go-to technology was Photoshop. I created a design for a 960px paint that I would eventually add willing to. The growth phase was about attaining pixel-perfect precision using set widths, fixed levels, and absolute setting.

All of this was altered by Ethan Marcotte’s 2010 post in A List Off entitled” Responsive Web Design.” I was sold on responsive pattern as soon as I heard about it, 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 new way to style

Making flexible or liquid websites has always been about removing restrictions and creating content that can be viewed on any system. It relies on the use of percentage-based design, which I immediately achieved with local 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%;}

Therefore with Sass but that I could use @includes to re-use repeated blocks of code and transition to more semantic premium:

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

Media questions

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

Media questions 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 screen sizes. If the goal of part libraries is modify, then this is a real problem because you can just use these components if the devices you’re designing for correspond to the viewport sizes used in the pattern library—in the process never really hitting that “devices that don’t already occur” goal.

Then there’s the problem of space. Media questions 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: our savior or a false dawn?

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 an important step in moving toward a form of component-based design that works at any size on any device.

In other words, responsive elements should be used to replace responsive layouts.

Container queries will help us move from designing pages that respond to the browser or device size to designing components that can be placed in a sidebar or in the main content, and respond accordingly.

My issue is that layout is still used to determine when a design needs to adapt. This approach will always be restrictive, as we will still need pre-defined 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 example, the dimensions of the container are not what should dictate the design, rather, the image is.

Without reliable cross-browser support for them, it’s difficult to say for certain whether container queries will be successful. Responsive component libraries would definitely evolve how we design and would improve the possibilities for reuse and design at scale. However, we might always need to modify these elements to fit our content.

CSS is changing

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 of this is that you don’t need to wrap any containers in rows. Without rows, content isn’t tied to page markup in quite the same way, allowing for removals or additions of content without additional development.

This is a big step forward when it comes to creating designs that allow for evolving content, but the real game changer for flexible designs is CSS Subgrid.

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. Meanwhile, Subgrid allows us to create designs that can adapt in order to suit morphing content. The above code can be implemented behind an @supports feature query even though Firefox is the only browser that supports subgrid at the time of writing.

Intrinsic layouts

I’d be remiss not to mention intrinsic layouts, a term used by Jen Simmons to describe a mix of contemporary and traditional CSS features used to create layouts that respond to available space.

Responsive layouts have flexible columns using percentages. 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”

Additionally, intrinsic layouts can mix and match both fixed and flexible units, letting the content choose how much space is taken up.

What makes intrinsic design stand out is that it not only creates designs that can withstand future devices but also helps scale design without losing flexibility. Without the requirement of having the same breakpoints or the same amount of content as in the previous implementation, components and patterns can be lifted and reused.

We can now create designs that adapt to the space they have, the content within them, and the content around them. We can create responsive components using an intrinsic approach without relying on container queries.

Another 2010 moment?

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

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. Nowadays, projects use existing tools and frameworks and are often improvements to existing websites with an existing codebase.

Another possibility is that I’m now more prepared for change. In 2010 I was new to design in general, the shift was frightening and required a lot of learning. Additionally, an intrinsic approach isn’t exactly new; it’s about applying existing skills and CSS knowledge in a unique way.

You can’t framework your way out of a content problem

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

And then there are design tools. We probably all used Photoshop templates for desktop, tablet, and mobile devices to drop designs into and show how the site would appear throughout our careers at some point.

How do you do that now, with each component responding to content and layouts flexing as and when they need to? This kind of design must take place in the browser, which is something I’m very fond of.

The debate about “whether designers should code” is another that has rumbled on for years. 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 implement 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?

Personally, I look forward to the day intrinsic design is the standard for design, when a design component can be truly flexible and adapt to both its space and content with no reliance on device or container dimensions.

Content should come first

Content is not constant. After all, to design for the unanticipated or unexpected, we must take into account changes in content, such as in our earlier Subgrid card illustration, which allowed the cards to make adjustments to both their own and 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. In the past, this was often achieved with Sass mixins but was often limited to switching from left-to-right to right-to-left orientation.

Directional variables must be specified in the Sass version.

$direction: rtl;$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 real estate.

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

However, now we have native logical properties, removing the reliance on both Sass ( or a similar tool ) and pre-planning that necessitated 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);}

The element in the figure above will be 50 % of its container as long as the element’s width doesn’t exceed 300px.

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

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

Now the element will be 50 % of its container as long as the element’s width is at least 300px. 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 separate content from markup, meaning the changes users make will not affect the design. By making plans for unanticipated changes in language or direction, we can begin to future-proof designs. And we can increase flexibility by setting desired dimensions alongside flexible alternatives, allowing for more or less content to be displayed correctly.

First, the situation

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

It’s a completely different design process for someone using a mobile phone and moving through a crowded street in glaring sunshine from a person 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 decision 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 provide choice.

Responsible design is important.

” There are parts of the world where mobile data is prohibitively expensive, and where there is little or no broadband infrastructure”.

On a 50 MB budget, I spent a day surfing the web.

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, in the real world, 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. 

There’s also native lazy loading, which indicates assets that should only be downloaded when they are needed.

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 return of media inquiries

Media questions 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. These checks allow us to provide options that suit more than one scenario, it’s less about one-size-fits-all and more about serving adaptable content.

The Media Queries Level 5 spec is still being developed as of this writing. It introduces some really exciting queries that in the future will help us design for multiple other unexpected situations.

For instance, a light-level feature allows you to alter a user’s style when they are in the sun or in the dark. Paired with custom properties, these features allow us to quickly create designs or themes for specific 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 questions like this go beyond choices made by a browser to grant more control to the user.

Expect the unexpected

In the end, we should always anticipate that things will change. Devices in particular change faster than we can keep up, with foldable screens already on the market.

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

A lot of the CSS discussed here is about moving away from layouts and putting content at the heart of design. There is so much 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 must 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.

Good design for the unexpected should allow for change, provide choice, and give control to those 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.

Laptops have trouble because between spoken and written speech, talk is more primitive. Machines must wrestle with the chaos of human statement, including the squabbling and pauses, the gestures and body vocabulary, and the dialect variations that can impede even the most skillfully created human-computer conversation. In the human-to-human situation, spoken language also has the opportunity of face-to-face call, where we can easily interpret verbal interpersonal cues.

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.

Spoken speech is not a pleasure in this regard. Besides the visual cues that mark conversations with emphasis and personal context, there are also linguistic cues and outspoken behaviors that mimic conversation in complex ways: how something is said, never what. Our spoken language reaches far beyond what the written word can ever deliver, whether it’s rapid-fire, low-pitched, high-decibel, satirical, awkward, or moaning. But when it comes to words interfaces—the devices we conduct spoken discussions with—we experience exciting difficulties as designers and content strategists.

Voice-to-voice relations

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 discussion in the following ways:

• we need something done ( such as a transaction ),
• we seek knowledge of anything ( some kind of information ), or
• we are social people and want someone to talk to ( conversation for conversation’s pleasure ).

A second talk from beginning to end that achieves some goal for the consumer, starting with the words interface’s initial greeting and ending with the user exiting the interface, also fits into these three categories, which I refer to as interpersonal, technical, and prosocial. Note here that a conversation in our human sense—a chat between people that leads to some result and lasts an arbitrary length of time—could encompass multiple transactional, informational, and prosocial voice interactions in succession. In other words, a voice interaction is a conversation, but it is not always just one voice interaction.

Purely prosocial conversations are more gimmicky than captivating in most voice interfaces, because machines don’t yet have the capacity to really want to know how we’re doing and to do the sort of glad-handing humans crave. Additionally, there is ongoing debate about whether users actually prefer the type of organic human conversation that starts with a prosocial voice and progresses seamlessly into new ones. In fact, in Voice User Interface Design, Michael Cohen, James Giangola, and Jennifer Balogh recommend sticking to users ‘ expectations by mimicking how they interact with other voice interfaces rather than trying too hard to be human—potentially alienating them in the process ( ).

A voice interface can also have two types of conversations we can have with one another that are both transactional and informational, each learning 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. Even when we walk up to the counter and place an order, the conversation quickly pivots from an initial smattering of neighborly small talk to the real mission at hand: ordering a pizza ( generously topped with pineapple, as it should be ).

Alison: Hey, how are things going?

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

Alison, can I get a pineapple-onion pizza in Hawaii?

Burhan: Sure, what size?

Large, Alison.

Burhan: Anything else?

Alison: No, that’s it.

Burhan: Something to drink?

Alison, I’ll have a bottle of Coke.

Burhan: You got it. It will cost about$ 15 and take fifteen minutes to complete.

Each progressive disclosure in this transactional conversation reveals more and more of the desired outcome of the transaction: a service rendered or a product delivered. Transactional conversations exhibit a few key characteristics: they’re direct, to the point, and economical. They quickly dispense with pleasantries.

Informational voice interactions

Meanwhile, some conversations are primarily about obtaining information. Alison might visit Crust Deluxe with the sole intention of placing an order, but she might not want to leave with a pizza at all. She might be just as interested in whether they serve halal or kosher dishes, gluten-free options, or something else. Even though we have a prosocial mini-conversation once more at the beginning to establish politeness, we’re after much more.

Alison: Hey, how are things going?

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

Alison: Can I ask a few questions?

Burhan: Of course! Go right ahead.

Do you have any halal options available on the menu, Alison?

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

Alison: What about gluten-free pizzas?

Burhan: For both our deep-dish and thin-crust pizzas, we can definitely make a gluten-free crust for you. Anything else I can answer for you?

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

Burhan: Anytime, come back soon!

This dialogue is radically different. Here, the goal is to get a certain set of facts. Informational conversations are research expeditions to gather data, news, or facts, or they are investigative quests for 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 Interfaces

Voice-based user interfaces use speech at the core to assist users in accomplishing their objectives. But simply because an interface has a voice component doesn’t mean that every user interaction with it is mediated through voice. We’re most concerned with pure voice interfaces, which depend entirely on spoken conversation and lack any visual component, making multimodal voice interfaces much more nuanced and challenging to deal with because they can lean on visual components like screens as crutches.

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

Though written conversational interfaces have been fixtures of computing for many decades, voice interfaces first emerged 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. We became familiar with the first real voice interfaces that could actually be spoken to without having to deal with overburdened customer service representatives as a result of the development of interactive voice response ( IVR ) systems.

IVR systems allowed organizations to reduce their reliance on call centers but soon became notorious for their clunkiness. These systems, which are commonplace in the corporate world, were primarily intended as metaphorical switchboards to direct customers to real phone agents (” Say Reservations to book a flight or check an itinerary” ), and it is likely that when you call an airline or hotel conglomerate, you will have the opportunity to have a conversation with one. 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 conversations than we’re used to in real life ( or even in science fiction ), despite being extremely repetitive and monotonous.

Screen readers

The invention of the screen reader, a tool that converts visual content into synthesized speech, was a development of IVR systems in parallel. For Blind or visually impaired website users, it’s the predominant method of interacting with text, multimedia, or form elements. Perhaps the closest thing we have today to an out-of-the-box delivery of content via voice is represented by screen readers.

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 growth of the web in the 1990s, the demand for accessible tools for websites exploded. Screen readers started facilitating quick 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 with the introduction of semantic HTML and especially ARIA roles in 2008, enabling speedy interactions with the pages. In other words, screen readers for the web “provide mechanisms that translate visual design constructs—proximity, proportion, etc. in A List Apart, writes Aaron Gustafson, “into useful information.” ” 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. The visual structures of websites and web navigation don’t translate well to screen readers, sometimes resulting in unwieldy pronouncements that name every manipulable HTML element and announce every formatting change. Working with web-based interfaces takes a cognitive toll for many screen reader users.

In Wired, accessibility advocate and voice engineer Chris Maury considers why the screen reader experience is ill-suited to users relying on voice:

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 before converting it to audio only after that. All of the time and energy that goes into creating the perfect user experience for an app is wasted, or even worse, adversely impacting the experience for blind users. ( )

In many cases, well-designed voice interfaces can speed users to their destination better than long-winded screen reader monologues. After all, users of the visual interface have the advantage of freely scurrying around the viewport to find information without getting too close to 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 assistants

Many of us immediately associate voice assistants with the popular subset of voice interfaces found in living rooms, smart homes, and offices with the film Star Trek or with Majel Barrett’s voice as the omniscient computer. Voice assistants are akin to personal concierges that can answer questions, schedule appointments, conduct searches, and perform other common day-to-day tasks. And because of their assistive potential, they are quickly receiving more attention from accessibility advocates.

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 ). It wasn’t until 2011 that Apple’s Siri finally entered the picture, making voice assistants a tangible reality for consumers.

There are a lot of variations in the programmability and customization of some voice assistants compared to others ( Fig. 1 ). As a result of the breadth of voice assistants available today ( Fig. 1 ). At one extreme, everything except vendor-provided features is locked down, for example, at the time of their release, the core functionality of Apple’s Siri and Microsoft’s Cortana couldn’t be extended beyond 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 allow for customization and extensibility. Amazon offers the Alexa Skills Kit, a developer framework for building custom voice interfaces for Amazon Alexa, while Google Home offers the ability to program arbitrary Google Assistant skills. Users today have the option to choose from among the thousands of custom-built skills available in the Google Assistant and Amazon Alexa ecosystems.

As businesses like Amazon, Apple, Microsoft, and Google continue to occupy their positions, they are also selling and open-sourcing an unheard array of tools and frameworks for designers and developers, aiming 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. I don’t prescribe any specific implementation approaches in this design-focused book, but in Chapter 4 we’ll get into some of the implications these variables might have on the way you build out your design artifacts.

Voice content

Simply put, voice content is content delivered through voice. Voice content must be free-flowing and organic, contextless and concise in order to preserve what makes human conversation so compelling in the first place. Everything written content is not.

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.

For many of us, our first foray into informational voice interfaces will be to deliver content to users. There is only one issue: any content we already have isn’t in any way suitable for this new environment. So how do we make the content trapped on our websites more conversational? And how do we create fresh copy that works with voice-activated text?

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. Back in 2002, well before the present-day ubiquity of voice assistants, technologist Anil Dash defined microcontent as permalinked pieces of content that stay legible regardless of environment, such as email or text messages:

An example of microcontent can be a day’s weather forecast [sic], an airplane flight’s arrival and departure times, an abstract from a lengthy publication, or a single instant message. ( )

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.

As microcontent, voice content is unique because it’s an example of how content is experienced in time rather than in space. We can instantly see when the next train is coming from a digital sign underground, but voice interfaces keep our attention occupied for so long that screen reader users are all too familiar.

Because microcontent is fundamentally made up of isolated blobs with no relation to the channels where they’ll eventually end up, we need to ensure that our microcontent truly performs well as voice content—and that means focusing on the two most important traits of robust voice content: voice content legibility and voice content discoverability.

Fundamentally, how voice content manifests in perceived time and space both affect the legibility and discoverability of our voice content.

Several wealthy runners had come to the conclusion that it was impossible to run a mile in less than four hours in the 1950s. 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 Roger Bannister surprised all on May 6, 1956. 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 presently knew that the four-minute hour could be accomplished thanks to this change in the standard. Bannister’s history lasted just forty-six days, when it was snatched aside by American sprinter John Landy. Finally, a year later, three runners all managed to cross the four-minute challenge in the same competition. 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 do a lot more when we think something is possible, and we only think it can be done when we see someone else doing it once more. As for man running speed, we also think there are strict guidelines for how a website should do.

Establishing requirements for a lasting web

The key environmental performance indicators for the majority of major industries 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 are not required to follow any specific environmental standards in the world of websites and apps, and we have only recently developed the tools and methods 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 item produces. We can’t measure the pollutants coming out of the exhaust valves on our devices. Our websites ‘ emissions are far away, out of mind, and out of sight when fuel and fuel are burned in 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 measures of coal pollutants:

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 wonderful example of how much energy is consumed and how much carbon is released. As a rule of thumb, the more files transferred, the more electricity used in the data center, telecoms systems, and end users products.

The easiest way to calculate data transfer for a single visit for web pages is to measure the page weight, which is the page’s transfer size in kilobytes when someone first visits the page. 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 the majority of technologies, including the web’s underlying technology 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 vague suggestions, much like speed limits while driving, so the goal should always be to come in 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 the page weight to compare it to competitors or the outdated website we’re replacing. 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 beyond the first visit and measuring page weight budgets for scenarios beyond this level of detail 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 actually provide direct information on carbon emissions and energy consumption, 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 power.

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” (gCO₂/k Wh ) is used to describe how much carbon dioxide is produced for each kilowatt-hour of electricity produced. 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, which combine energy from a variety of sources with different carbon intensity levels. 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 don’t have complete control over the energy supply of web services, we do have some control over where our projects are hosted. 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. Danish startup Tomorrow reports and maps the user-provided data, 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 ).

Having said that, we don’t want to locate our servers too far away from our users; however, it takes 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 from that location to the data center used by our hosting company by using the distance itself 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 look up the travel distance between London and San Francisco, 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 shorten the distance and the amount of energy needed 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 one step further and tailor the data more precisely to the unique 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 a layer of abstraction that isn’t as intuitive, carbon budgets do focus our minds on the main thing we’re trying to reduce, which 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 make it possible 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 know when your computer’s cooling fans start spinning so frantically that you suspect 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 principles into your design work in order to make tech that’s secure, how to persuade your stakeholders that this work is important, and how to respond to the critique that what we really need is more diversity. ( Spoiler: we do, but diversity alone is not the solution to fixing unethical, unsafe technology. )

The procedure for diverse safety

Your objectives when designing for protection are as follows:

• determine way your product can be used for misuse,
• 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 ). It’s a method I developed 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 basic areas of action:

• conducting exploration
• Creating tropes
• pondering issues
• Designing options
• Testing for security

The Process is meant to be flexible; in some situations, it didn’t make sense for groups to employ 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 an idea for making it better or simply want to give perspective of how it helped your group, please get in touch with me. It’s a living document, which I hope technicians may use as a practical and useful tool throughout their day-to-day tasks.

If you’re working on a product especially for a resilient team or survivors of some form of injury, such as an application for survivors of domestic violence, sexual abuse, or drug addiction, be sure to read Section 7, which covers that position directly and should be handled a bit different. The principles set forth here are for putting safety first when designing a more general product with a broad user base ( which, as we already know from statistics, will include some groups that should be protected from harm ). Chapter 7 is focused on products that are specifically for vulnerable groups and people who have experienced trauma.

Step 1: Conduct research

Design research should include a thorough analysis of how your technology might be used for abuse as well as specific insights into the experiences of those who have witnessed and perpetrated that kind of abuse. At this stage, you and your team will investigate issues of interpersonal harm and abuse, and explore any other safety, security, or inclusivity issues that might be a concern for your product or service, like data security, racist algorithms, and harassment.

broad 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 example, a team building a smart home device would do well to understand the multitude of ways that existing smart home devices have been used as tools of abuse. If your product involves artificial intelligence, be aware of the potential for racism and other issues that have been reported in other AI products. Nearly all types of technology have some kind of potential or actual harm that’s been reported on in the news or written about by academics. For these studies, Google Scholar is a useful resource.

Specific research: Survivors

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 avoid retraumatizing 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 important 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. While some survivors may not want to be paid, you should always make the offer in the initial ask. As an alternative to paying, you can donate to a group fighting against the violence the interviewee experienced. We’ll talk more about how to appropriately interview survivors in Chapter 6.

Abusers specifically: research

It’s unlikely that teams aiming to design for safety will be able to interview self-proclaimed abusers or people who have broken laws around things 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 after you’ve finished conducting it to create abuser and survivor archetypes. Archetypes are not personas, as they’re not based on real people that you interviewed and surveyed. Instead, they’re based on your research into likely safety issues, much like when we design for accessibility: we don’t need to have found a group of blind or low-vision users in our interview pool to create a design that’s inclusive of them. Instead, we base those designs on already-existing research to satisfy the requirements of this audience. Personas typically represent real users and include many details, while archetypes are broader and can be more generalized.

The abuser archetype is someone who views a product as a means of harm ( Fig. 5.2 ). They may be trying to harm someone they don’t know through surveillance or anonymous harassment, or they may be trying to control, monitor, abuse, or torment someone they know personally.

Someone who is being abused with the product is the survivor archetype. 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 )?

You may want to make multiple survivor archetypes to capture a range of different experiences. They may be aware of the abuse being occurring but not be able to stop it, such as when a stalker keeps tracing their whereabouts or when an abuser locks them out of IoT devices ( Fig. 5.4). Include as many of these scenarios as you need to in your survivor archetype. These suggestions will be used later when creating solutions to assist your survivor archetypes in achieving their objectives 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 details 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 example, if you uncovered an issue with security, such as the ability for someone to hack into a home camera system and talk to children, the malicious hacker would get the abuser archetype and the child’s parents would get survivor archetype.

Step 3: Brainstorm issues

After creating archetypes, brainstorm novel abuse cases and safety issues. You’re trying to identify entirely new safety issues that are unique to your product or service by using the term” Novel” in terms of things you’ve not found in your research. The goal with this step is to exhaust every effort of identifying harms your product could cause. You aren’t worrying about how to prevent the harm yet—that comes in the next step.

What other uses could your product be used for besides what you’ve already identified in 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 how your product would be used in an episode of the show—the most wild, awful, out-of-control ways it could be used for harm. Participants typically have a lot of fun when I lead Black Mirror brainstorms ( which is great because having fun when designing for safety! ). I recommend time-boxing a Black Mirror brainstorm to half an hour, and then dialing it back and using the rest of the time thinking of more realistic forms of harm.

After identifying as many opportunities for abuse as you can, you may still not feel confident that you have found every potential source of harm. A healthy amount of anxiety is normal when you’re doing this kind of work. 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 right, but instead of aiming for 100 % assurance, acknowledge that you’ve taken this step and have done everything you can, and pledge to keep putting safety first 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.

Step 4: Design solutions

You should now be able to identify potential harm-causing uses for your product as well as survivor and abuser archetypes describing opposing user objectives. The next step is to identify ways to design against the identified abuser’s goals and to support the survivor’s goals. This is a good idea to include this one alongside other areas of your design process where you’re offering solutions to the various issues your research has identified.

Some questions to ask yourself to help prevent harm and support your archetypes include:

• 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 help the user access support?

In some products, it’s possible to proactively detect harm is occurring. For example, a pregnancy app might be modified to allow the user to report that they were the victim of an assault, which could trigger an offer to receive resources for local and national organizations. Although this kind of proactiveness is not always possible, it’s worthwhile to spend a half hour talking about how your product could help the user receive help in a safe manner if any kind of user activity would indicate some form of harm or abuse.

That said, use caution: you don’t want to do anything that could put a user in harm’s way 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.

Ideally, safety testing happens along with usability testing. If you work for a company that doesn’t conduct usability testing, you might be able to use safety testing to deftly perform both. A user who uses your design while trying to use it against someone else can also be encouraged to point out interactions or other design details that don’t make sense to them.

You’ll want to conduct safety testing on either your final prototype or the actual product if it’s already been released. It’s okay to test an existing product that wasn’t created with safety goals in mind right away; “etrofitting” it for safety is a good thing to do.

Remember that testing for safety involves testing from the perspective of both an abuser and a survivor, though it may 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 most likely too closely connected to the product and its design at this point, just like other types of usability testing, 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.

Abuse testing

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

For example, for a fitness app with GPS-enabled location features, we can imagine that the abuser archetype would have the goal of figuring out where his ex-girlfriend now lives. With this in mind, you’d make every effort to discover the location of a different user who has their privacy settings in place. You might try to see her running routes, view any available information on her profile, view anything available about her location ( which she has set to private ), and investigate the profiles of any other users somehow connected with 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. Reverting 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.

Testing for Survivors

Testing for Survivors involves identifying how to give information and power to the survivor. It might not always make sense based on the product or context. 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.

However, there are cases where it makes sense. A survivor archetype’s goal would be to discover who or what causes the temperature change when they aren’t doing it themselves, for instance. You could test this by looking for the thermostat’s history log and checking for usernames, actions, and times, if you couldn’t find that information, you would have more work to do in step 4.

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 find? For your test, you would need to try 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. This concept comes from Design for Real Life by Eric Meyer and Sara Wachter-Boettcher. The authors noted that personas typically focus on happy people, but that happy people are frequently anxious, stressed out, unhappy, or even go through a bad day. These are called” stress cases”, and testing your products for users in stress-case situations can help you identify places where your design lacks compassion. More information about how to incorporate stress cases into your design can be found in Design for Real Life, as well as in many other effective methods for designing with compassion.

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 glad versions that are conceptual and that also connect related information, you can avoid that result.

I just had the opportunity to direct the CMS application for a Fortune 500 company. 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 articles 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 writers to produce original content and use it where necessary. But as the job proceeded, I realized that supporting material utilize at the range that my client needed required the whole group to identify a new pattern.

Despite our best efforts, we remained influenced by what we were more common with: design techniques. An holistic content strategy cannot rely on WYSIWYG equipment for design and layout, unlike web-focused material strategies. Our tendency to approach the material model with our common design-system thinking frequently led us to veer away from one of the main purposes of a material model: delivering content to audiences on various marketing channels.

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

We needed to explain to our designers, developers, and stakeholders that we were undertaking a very different task from their earlier web projects, where it was common for everyone to view content as visual building blocks that fit into layouts. The previous approach was not only more familiar but also more intuitive—at least at first—because it made the designs feel more tangible. We discovered two guiding principles that helped the team understand how a content model and the design processes we were familiar with were:

1. Instead of layout, content models must define semantics.
2. And content models should connect content that belongs together.

Semantic content models

Type and attribute names for semantic content models are used to reflect the content’s intended purpose and not its intended display. For example, in a nonsemantic model, teams might create types like teasers, media blocks, and cards. Although these types might make it simple to present content, they don’t aid in understanding the meaning of the content, which would have opened the door to the content presented in each marketing channel. In contrast, a semantic content model employs type names like product, service, and testimonial to allow for each delivery channel to interpret the content and use it as necessary.

When you’re creating a semantic content model, a great place to start is to look over the types and properties defined by Schema. a curated resource for type definitions that are understandable on platforms like Google search, type definitions .org

A semantic content model has a number of advantages:

Even if your team doesn’t care about omnichannel content, a semantic content model decouples content from its presentation so that teams can evolve the website’s design without needing to refactor its content. In this way, content can withstand irrational website redesigns.
• A semantic content model also gives you a competitive advantage. By adding structured data based on Schema. Using its types and properties, a website can provide hints to help Google understand the content, display it in search snippets or knowledge panels, and use it to respond to voice-interface user questions. Potential customers could access your content without ever visiting your website.
• Beyond those practical benefits, you’ll also need a semantic content model if you want to deliver omnichannel content. 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 easily displayed on a frequently asked questions ( FAQ ) page as well, but it could also be used by a bot that answers frequently asked questions.

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 content that should remain together so that multiple delivery channels can use it without needing to first put those pieces back together.

Write an essay or article about it. The unity of an article’s parts determines its meaning and usefulness. Would one of the headings or paragraphs be meaningful on their own without the context of the full article? Our well-known design-system thinking on our project frequently led us to want to develop content models that would divide content into distinct chunks to fit the web-centric layout. Similar effects could have been felt to an article that had its headline removed. Because we were slicing content into standalone pieces based on layout, content that belonged together became difficult to manage and nearly impossible for multiple delivery channels to understand.

Let’s examine how connecting related content can be used in a practical setting to illustrate. A complex layout for a software product page that included multiple tabs and sections was presented by the client’s design team. Our instincts were to follow suit with the content model. Shouldn’t we make adding any number of tabs in the future as simple and as flexible as possible?

We felt like we needed a “tab section” content type because our design-system instincts allowed for the addition of multiple tab sections to a page because they were so well-versed. Each tab section would display various types of content. The software’s overview or specifications might be available in one tab. A list of resources might be provided by another tab.

Our inclination to break down the content model into “tab section” pieces would have led to an unnecessarily complex model and a cumbersome editing experience, and it would have also created content that couldn’t have been understood 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. Furthermore, if the customer were to have no longer wanted to display this content in a tab layout, it would have been tedious to migrate to a new content model to reflect the new page redesign.

Our customer had a breakthrough when we realized that each tab’s specific information, such as the software product’s overview, specifications, related resources, and pricing, was intended to reveal a specific purpose. Once implementation began, our inclination to focus on what’s visual and familiar had obscured the intent of the designs. It wasn’t long after a little digging that it became clear that the idea of tabs wasn’t applicable to the content model. What was important was the meaning of the information that was intended to be displayed in the tabs.

In fact, the customer could have decided to display this content in a different way—without tabs—somewhere else. Based on the meaningful attributes the customer had desired to display on the web, we created content types for the software product. There were rich attributes like screenshots, software requirements, and feature lists as well as obvious semantic attributes like name and description. 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 those that follow, could comprehend and display this content.

Conclusion

In this omnichannel marketing project, we discovered that the best way to keep our content model on track was to ensure that it was semantic ( with type and attribute names that reflected the meaning of the content ) and that it kept content together that belonged together ( instead of fragmenting it ). These two ideas made it easier for us to shape 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 Google and other interfaces understand your content, remember:

• A design system isn’t a content model. Team members may be persuaded to combine them and have their content model resemble their design system, so you should guard the semantic and contextual integrity of the content strategy throughout the entire implementation process. This will enable each delivery channel to consume the content without the need for a magic decoder ring.
• If your team is struggling to make this transition, you can still reap some of the benefits by using Schema. Your website uses structured data from org. The advantage of search engine optimization is a compelling argument on its own, even if additional delivery channels are not in the works.
• Additionally, remind the team that decoupling the content model from the design will let them update the designs more easily because they won’t be held back 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 view content as the most important component of your user experience and as the most effective way to engage with your audience.

Here’s the key. You must engage stakeholders to determine high-risk conclusions and buried complexity, so that they can become just as motivated as you are to receive responses from users. Generally, you need to make them think it’s their plan.

By bringing the group up around two straightforward issues, I’ll show you how to collectively introduce alignment and cracks in the group’s shared understanding in this article.

1. What are the things?
2. What are the associations between those things?

A cross between panel design and analysis

These two issues correlate to the first two methods of the ORCA approach, which may be your new best friend when it comes to reducing speculation. Delay, what’s ORCA? Glad you asked.

ORCA stands for Things, Relationships, CTAs, and Values, and it outlines a process for creating good object-oriented user experience. My style philosophy is based on object-oriented UX. ORCA is an iterative strategy for synthesizing person study into an elegant fundamental foundation to help monitor and conversation design. My work as a UX designer has become more creative, productive, successful, fun, proper, and meaningful thanks to OOUX and ORCA.

The ORCA approach has four incremental shells and a staggering fifteen steps. In each round we get more precision on our System, Rupees, Computer, and As.

I occasionally refer to ORCA as a “garbage in, garbage out” procedure. To ensure that the observable design produced in the last round truly tests properly, the procedure needs to be fed by good research. However, the beginning of the ORCA process serves another function: it helps you buy the need for research if you don’t have a ton of study.

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

Getting back 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 reveal what this timeless comic so skillfully demonstrates:

This is one reason why so many UX designers are frustrated in their job and why many projects fail. Every decision-maker is confident in their own mental picture, which is another reason why we frequently can’t sell research.

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

However, how we go about doing this is crucial. 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 accept responsibility for their beliefs and understanding gaps, BAM! Suddenly, UX research is not such a hard sell, and everyone is aboard the same curiosity-boat.

Let’s say you have doctors on your staff. 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 issues? How do they use the current app”? Here’s the issue with that, though. 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 similar to the conversation you need to facilitate. Let’s listen in:

” Wait a sec, how frequently 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 position be considered a nurse practitioner?

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

Are caregivers included in this redesign, then?

” 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”?

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

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 most likely as a result of this, the software product will be more confusing, more complicated, and less intuitive.

The two questions

But how do we approach these types of contentious inquiries diplomatically, effectively, 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 things?
2. What are the associations between those things?

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

Work in preparation: Noun for 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.

In essence, look for nouns that are specific to the subject matter or industry of your project and use at least a few sources. I call this noun foraging.

Just a few excellent noun foraging sources can be found:

• the product’s marketing site
• the product’s competitors ‘ marketing sites ( competitive analysis, anyone? )
• the already-existing product ( check the labels )!
• user interview transcripts
• vision documents or notes from stakeholder interviews

Put your detective hat on, my dear Watson. Get resourceful and leverage what you have. Use those if all you have are a marketing website, some screenshots of the current legacy system, and access to customer service chat logs.

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

Consider, for instance, a library app. Is “book” an object?

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

What are some illustrations of this potential “book” object, for instance? Can you name a few? Check! The Alchemist, Ready Player One, Everybody Poops, OK!

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!

Focus on capturing the nouns that have SIP as you are noun foraging. 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 visiting your digital location to play with your dropdown! They are coming for the VALUABLE THINGS and what they can do with them. These 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.

I’d like to take a look at my own email client, which is Gmail. I’d then look at Outlook and the new HEY email. I would examine Hotmail, Yahoo, and even Basecamp and other’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 fictitious product as well, and then scroll down to see how closely our lists correspond. Just don’t get lost in your own emails! Rejoice 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 organizations
• attachment
• Google doc file / other integrated file
• newsletter? ( HEY views this in a different way )
• saved responses and templates

Scan your list of nouns and pick out words that you are completely clueless about. It might be a client or automation in our email example. 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 that I needed to clarify while working on my own projects in the past.

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

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

Facilitate an Object Definition Workshop

You could start your workshop by doing noun foraging; this can be done in concert. 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. Your friend here is affinity mapping!

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 enjoy showing screenshots of documents and screens that have all the highlighted nouns. 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. We’ll keep that a secret; you just need to let them know that you‘re looking for gaps in the team’s understanding so that you can demonstrate the need for more user research. Instead, go into the session optimistically, as if your knowledgeable stakeholders and PMs and biz folks already have all the answers.

Let the whack-a-mole question then start.

1. What is this thing?

Want to have genuine fun? At the beginning of your session, ask stakeholders to privately write definitions for the handful of obscure nouns you might be uncertain about. Have everyone then show their cards at once, and see if there are any variations (you will ). This is gold for exposing misalignment and starting great conversations.

As your discussion unfolds, capture any agreed-upon definitions. And when uncertainty sets in, quietly ( but clearly ) begin an “open questions” parking lot. � �

Here’s a fantastic follow-up to solidify definitions:

2. Do our users know what these things are? What is the name of this object?

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

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

Ask the group if they can agree to use only that term as they go along if a more user-friendly term comes up. This way, the team can better align to the users ‘ language and mindset.

Okay, let’s get to the next part.

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? How are they different if they are different from one another?

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

Stakeholder 1: Yes! Absolutely.

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.

Your expanding glossary of objects should continue to grow. 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 in any way connected to each other?

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 occur when the user is creating the saved response? Or when they apply the saved response to an email? What is the process behind that?

Listen. Capture uncertainty. When the number of “open questions” reaches a critical mass, pause to begin asking questions of 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 specific for someone who was unable to attend 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 query makes it easier for the team to concentrate on what your users are most interested in. 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 order these items either in small breakout groups or separately from the most important. Then, like you did with the definitions, have everyone reveal their sort order at once. Unsurprisingly, it’s not unusual for the VP to place something like” saved responses” at the top of the list while everyone else places it at the bottom. Try not to look too smug as you inevitably expose more misalignment.

I did this for a startup a few years ago. The three groups ‘ wildly different sort orders were displayed on the whiteboard.

The CEO nodded his head and said,” This is why we haven’t been able to move forward in two years,” taking a step back.

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 tried to figure out what two things are different, but this time, we wanted to ask the team about every possible relationship. For each object, ask how it relates to all the other objects. In what ways are the objects connected? Pull out your dependable boxes and arrows technique to see all the connections. Here, we are connecting our objects with verbs. I prefer to use simple statements like “has a” and “has many.”

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

• Can attachments be included in a saved response?
• Can a saved response use a template? If so, can the recipient override the template if an email uses a saved response with a 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. attached .jpg I’ve changed my professional photo and I want to alert everyone to update it”.

Effective responses might come directly from the workshop participants. Great! Capture that new shared understanding. However, as uncertainty arises, keep adding new questions to your expanding parking lot.

Light the fuse

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

Have the group reflect on the list of open questions before the workshop ends. Make plans for getting answers internally, then focus on the questions that need to be brought before users.

This is your final move. 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 approach, we are cornering our decision-makers into supporting user research because they themselves categorize questions as high-risk. Sorry, not sorry.

This 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 don’t force the user to choose any default responses. They should be open-ended.

Final words: Hold the screen design!

Seriously, if at all possible, if you never design screens again without first addressing these fundamental inquiries: 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 will give you the time and money to spend talking to your users and getting a clear understanding of what you are designing before you begin creating 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.

Wish you the best of luck! Now go sell research!