Blog

  • An Holistic Framework for Shared Design Leadership

    An Holistic Framework for Shared Design Leadership

    Picture this: Two people are having what appears to be the same talk about the same design issue in a conference room at your technical company. One is talking about whether the staff has the right abilities to handle it. The other is examining whether the solution truly addresses the user’s issue. Similar room, the same issue, and entirely different perspectives.

    This is the lovely, sometimes messy fact of having both a Design Manager and a Guide Designer on the same group. And you’re asking the right question if you’re wondering how to make this job without creating confusion, coincide, or the feared” to some cooks” situation.

    Fresh lines on an organizational chart have always been the standard solution. The Design Manager handles persons, the Lead Designer handles art. Problem solved, is that straight? Except that clear organizational charts are dream. In fact, both roles care greatly about crew health, style quality, and shipping great work.

    When you begin to think of your style organization as a style organism, the magic happens when you accept collide rather than fight it.

    The biology of a good design team

    Here’s what I’ve learned from years of being on both sides of this formula: consider of your design team as a living organism. The style manager has a focus on the internal safety, career advancement, team dynamics, and other aspects. The Lead Designer concentrates on the body ( the handiwork, the design standards, the hands-on projects that are delivered to users ).

    But just like mind and body aren’t totally separate systems, but, also, do these tasks overlap in significant ways. Without working in harmony with one person, you can’t have a good person. The technique is to recognize those overlaps and how to manage them gently.

    When we look at how good team really function, three critical devices emerge. Each requires the collaboration of both jobs, but one must assume the lead role in maintaining that system sturdy.

    Individuals & Psychology: The Nervous System

    Major caregiver: Design Manager
    Supporting duties: Direct Artist

    The anxious system is all about mental health, comments, and signals. When this technique is good, information flows easily, people feel safe to take risks, and the staff may react quickly to new problems.

    The main caregiver here is the Design Manager. They are keeping track of the team’s emotional signal, making sure feedback rings are good, and creating the conditions for people to develop. They’re hosting job meetings, managing task, and making sure no single burns out.

    However, the Lead Designer has a significant enabling position. They’re offering visual feedback on build development needs, identifying stagnant design skills in someone, and pointing out potential growth opportunities that the Design Manager might overlook.

    Design Manager tends to:

    • discussions about careers and career development
    • emotional stability and dynamics of the team
    • Overhead management and resource allocation
    • Performance evaluations and input mechanisms
    • Providing opportunities for learning

    Direct Custom supports by:

    • Providing craft-specific coaching for staff members
    • identifying opportunities for growth in style skills gaps
    • Giving design mentoring and assistance
    • indicating when staff people are prepared for more challenging problems.

    The Muscular System: Design & Execution

    Major caretaker: Lead Designer
    Supporting duties: Design Manager

    The skeletal structure focuses on developing strength, coordination, and talent development. When this technique is healthy, the team can do complicated design work with precision, maintain regular quality, and adjust their craft to fresh challenges.

    The Lead Designer is in charge of everything here. They are raising the bar for quality work, providing craft instruction, and ensuring that shipping work is done to the highest standards. They’re the ones who can tell you if a design decision is sound or if we’re solving the right problem.

    However, a significant supporting role is played by the Design Manager. They’re making sure the team has the resources and support they need to perform their best work, such as proper nutrition and time for an athlete recovering.

    Lead Designer tends to:

    • Definition of system requirements and design standards
    • Feedback on design work that meets the required standards
    • Experience direction for the product
    • Design choices and product-wide alignment are at stake.
    • advancement of craft and innovation

    Design Manager supports by:

    • ensuring that design standards are understood and accepted by all members of the team
    • Confirming that a direction of experience is being pursued
    • Supporting practices and systems that scale without bottlenecking
    • facilitating design alignment among all teams
    • Providing resources and removing obstacles to outstanding craft work

    The Circulatory System: Strategy &amp, Flow

    Shared caretakers: Lead Designer and Design Manager, respectively.

    The circulatory system is concerned with how the team’s decisions and energy are distributed. When this system is healthy, strategic direction is clear, priorities are aligned, and the team can respond quickly to new opportunities or challenges.

    True partnership occurs in this area. Although both roles are responsible for keeping the circulation strong, they both bring in different viewpoints.

    Lead Designer contributes:

    • The product fulfills the user’s needs.
    • overall experience and product quality
    • Strategic design initiatives
    • User needs based on research for each initiative

    Contributes the design manager:

    • Communication to team and stakeholders
    • Stakeholder management and alignment
    • Team accountability across all levels
    • Strategic business initiatives

    Both parties work together on:

    • Co-creation of strategy with leadership
    • Team goals and prioritization approach
    • organizational structure decisions
    • Success frameworks and measures

    Keeping the Organism Healthy

    Understanding that all three systems must work together is the key to making this partnership sing. A team will eventually lose their way despite excellent craftmanship and poor psychological security. A team with great culture but weak craft execution will ship mediocre work. A team that has both but poor strategic planning will work hard on the wrong things.

    Be Specific About the System You’re Defending.

    When you’re in a meeting about a design problem, it helps to acknowledge which system you’re primarily focused on. Everyone has context for their input.” I’m thinking about this from a team capacity perspective” ( nervous system ) or” I’m looking at this through the lens of user needs” ( muscular system ).

    It’s not about staying in your lane. It’s about being transparent as to which lens you’re using, so the other person knows how to best add their perspective.

    Create wholesome feedback loops

    The partnerships that I’ve seen have the most effective feedback loops between the systems:

    Nervous system signals to muscular system:” The team is struggling with confidence in their design skills” → Lead Designer provides more craft coaching and clearer standards.

    The nervous system receives the message” The team’s craft skills are progressing more quickly than their project complexity.”

    We’re seeing patterns in team health and craft development that suggest we need to adjust our strategic priorities, both systems say to the circulatory system.

    Handle Handoffs Gracefully

    When something switches from one system to another, this partnership’s most crucial moments occur. This might occur when a team’s ( nervous system ) needs to be exposed to a design standard ( muscular system ), or when a strategic initiative ( circulatory system ) needs specific craft execution ( muscular system ).

    Make these transitions explicit. The new component standards have been defined. Can you give me some ideas on how to get the team up to speed? or” We’ve agreed on this strategic direction. From here, I’ll concentrate on the particular user experience approach.

    Stay original and avoid being a tourist.

    The Design Manager who never thinks about craft, or the Lead Designer who never considers team dynamics, is like a doctor who only looks at one body system. Great design leadership requires both parties to be concerned with the entire organism, even when they are not the primary caregiver.

    Rather than making assumptions, one must ask questions. ” What do you think about the team’s craft development in this area”? or” How do you think this is affecting team morale and workload”? keeps both viewpoints present in every choice.

    When the Organism Gets Sick

    This partnership has the potential to go wrong, even with clear roles. Here are the most typical failure modes I’ve seen:

    System Isolation

    The design manager ignores craft development and only concentrates on the nervous system. The Lead Designer ignores team dynamics and concentrates solely on the muscular system. Both people retreat to their comfort zones and stop collaborating.

    The signs: Team members receive conflicting messages, work conditions suffer, and morale declines.

    Reconnect with other people’s goals in the treatment. What are you both trying to achieve? It’s typically excellent design work that arrives on time from a capable team. Discover how both systems accomplish that goal.

    Poor Circulation

    There is no clear strategic direction, shifting priorities, or accepting responsibility for keeping information flowing.

    The signs: Team members are unsure of their priorities, work is duplicated or dropped, and deadlines are missed.

    The treatment: Explicitly assign responsibility for circulation. Who is communicating with whom? How frequently? What’s the feedback loop?

    Autoimmune Response

    One person feels threatened by the expertise of the other. The Design Manager thinks the Lead Designer is undermining their authority. The Design Manager is allegedly misunderstanding the craft, according to the Lead Designer.

    The symptoms: defensive behavior, territorial disputes, middle-class teammates, etc.

    The treatment: Remember that you’re both caretakers of the same organism. The entire team suffers when one system fails. The team thrives when both systems are strong.

    The Payoff

    Yes, this model calls for more interaction. Yes, both parties must be able to assume full responsibility for team health. But the payoff is worth it: better decisions, stronger teams, and design work that’s both excellent and sustainable.

    The best of both worlds can be found in the combination of strong people leadership and deep craft expertise. When one person is ill, taking a vacation, or overburdened, the other can support the team’s health. When a decision requires both the people perspective and the craft perspective, you’ve got both right there in the room.

    The framework has a balance, which is crucial. You can use the same system thinking to new challenges as your team grows. Need to launch a design system? Both the muscular system ( standards and implementation ), the nervous system (team adoption and change management ), and both have a tendency to circulate ( communication and stakeholder alignment ).

    The End result

    The relationship between a Design Manager and Lead Designer isn’t about dividing territories. It’s about multiplying impact. Magic occurs when both roles realize they are tending to various aspects of the same healthy organism.

    The mind and body work together. The team benefits from both strategic thinking and craftmanship. And most importantly, the work that is distributed to users benefits both sides.

    So the next time you’re in that meeting room, wondering why two people are talking about the same problem from different angles, remember: you’re watching shared leadership in action. And if it’s functioning well, your design team’s mind and body are both strengthening.

  • Guilty Gear Strive Producer Ken Miyauchi Looks to the Fighting Game’s Future

    Guilty Gear Strive Producer Ken Miyauchi Looks to the Fighting Game’s Future

    Guilty Gear Strive, the 2021 battle match, had already become the best-selling name in the whole Arc System Works show’s record only one year after its launch. Guilty Gear Strive, which was released four years later, has sold more than 3 million copies international, with over 3.5 million people playing it…

    The first article on Den of Geek was Guilty Gear Strive Producer Ken Miyauchi Looks at the Fighting Game’s Coming.

    Guilty Gear Strive, the 2021 battle match, had already become the best-selling name in the whole Arc System Works franchise record only one year after its launch. Guilty Gear Strive, which was released four years ago, has sold more than 3 million copies international, with over 3.5 million people worldwide, and the popular video game is still gaining steam. Guilty Gear Strive was a major step opposition at Evo 2025, drawing in a sizable crowd of competitors and becoming a well-liked pull for viewers both in person and streaming the occasion online, a tradition that existed for many years at the Evolution Championship Series, or Evo.

    Guilty Gear Strive, in essence, has taken what was Arc System Works ‘ most cherished original brand to new heights of success and awareness. The post-launch DLC seasons of the game help to maintain the show’s continued growth and good response from the area for fighting games. Strive is wrapping up its third season with the franchise’s first-ever guest fighter from a recently established franchise. Den of Geek spoke with Guilty Gear Strive producer Ken Miyauchi at Evo 2025 to discuss everything Guilty Gear, including the surprise inclusion of Lucy Kushinada from the Netflix animated series Cyberpunk: Edgerunners as a crossover character in the fourth season.

    ” I really do appreciate that the success wasn’t just from us,” he said. It’s really about how the Guilty Gear community is supporting us, attempting to attract new players, and Ken Miyauchi-san says. This is our first time playing a game that has been in its fifth year and has been running for four years. Typically, what we’ve done is update the game by releasing a new version with a different title, like Guilty Gear Xrd Revelator and Guilty Gear Xrd REV2. There has been a lot of study and learning about how live service for fighting games should be conducted. We hope to improve our updates and live operations in the upcoming years by learning from those viewpoints.

    Guilty Gear Strive‘s inclusion of a guest fighter was born out of a desire to reach even wider audiences for the franchise, along with consistently high player engagement rates from regularly conducted player polls by Arc System Works. Interesting to note is that the developers thought about including a character from a completely different video game studio, CD Projekt Red. Arc System Works initially inquired about having a protagonist from The Witcher, but it was initially turned down by CD Projekt’s Cyberpunk 2077 franchise.

    cnx. cmd. push ( function ( ) {cnx ( {playerId:” 106e33c0-3911-473c-b599-b1426db57530″, }). render ( “0270c398a82f44f49c23c16122516796” ), }),

    Hidehiko Sakamura, our lead artist, is a huge fan of the Witcher series. According to Miyauchi-san,” We originally wanted to reach out to CD Projekt to see if we could include either Geralt or Ciri from The Witcher 3.” ” At the time, CD Projekt was actually working on The Witcher 4 at the time. They were revealing that there were a lot of changes occurring in Ciri. They didn’t want to distribute the IP at the time to various IPs to ensure that the series ‘ branding would remain consistent.

    With Miyauchi-san speaking directly with CD Projekt’s Japan country manager Honma Satoru, this early attempt to include Ciri or Geralt in Guilty Gear Strive sparked further discussions between Arc System Works and CD Projekt Red. With Satoru-san working on Cyberpunk: Edgerunners as a producer, he advised the Strive development team to also think about collaborating with CD Projekt’s ambitious sci-fi franchise. Before deciding Lucy Kushinada was the best fit for the Guilty Gear franchise, Arc System Works looked into whether other Cyberpunk characters might exist in Strive.

    ” We were considering possibly excluding Johnny Silverhand or V from the game. It’s difficult to characterize the game as a fighting game because the main character is the player, says Miyauchi-san. We ultimately decided to pick Lucy after looking into the characters and ultimately choosing a character from Edgerunners.

    Arc System Works is still working hard to maintain the popular game’s continued growth and stronghold in the fighting game community as a fifth season of DLC is confirmed at Evo 2025 and Guilty Gear Strive is set to be ported to the Nintendo Switch at the start of the year. Miyauchi-san has been talking about his observations of Strive closely with its director Akira Katano, despite there have been no officially confirmed plans for a sequel or standalone follow-up. What the two would do if given the chance to work on a potential new Guilty Gear title have naturally been a part of these discussions.

    We made a lot of experimentation attempts to see what might work better. We’re conducting a lot of post-mortem right now, looking at what really worked, what really wasn’t received well, and what was discussed in the community,” says Miyauchi-san. What could be improved is something we’ve discussed extensively internally if we have another chance to make a new Guilty Gear game.”

    PlayStation 5, PlayStation 4, Xbox One, Nintendo Switch, and PC are the current PlayStation 5 and PlayStation 4 users. The season 4 finale character, Lucy Kushinada, will be revealed on August 21. DLC for a fifth season is currently being developed.

    The first post Guilty Gear Strive Producer Ken Miyauchi Looks at the Fighting Game’s Future appeared on Den of Geek.

  • Asynchronous Design Critique: Giving Feedback

    Asynchronous Design Critique: Giving Feedback

    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 opinions 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 suggestions: 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 concepts with comments, but it also has some differences.

    The information

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

    This formula is typically used to provide feedback to people, but it also fits really well in a style criticism because it finally addresses one of the main inquiries that we work on: 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 post 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. May you alter them?

    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? From the perspective of the project manager? A first-time user’s perspective?

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

    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 feedback in general, in my experience, going back to the question approach typically leads to the best solutions because designers are generally more at ease in being given an open space to explore.

    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 spent a while working on improving my feedback, conducting anonymous feedback reviews and sharing feedback with others. 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. Quite unexpected, my next round of criticism from one particular 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 member of this other team who 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. No, but also yes. 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 implement the change. In later iterations, the interface might change or they might introduce new features—and maybe that change might not make sense anymore. Without explaining the why, the designer might assume that the change is one of consistency, 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.

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

    The atmosphere

    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 lasting change in people, and tone alone can determine 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 the one for content: the 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 time when feedback occurs is known as timing. To-the-point feedback doesn’t have much hope of being well received if it’s given at the wrong time. When a new feature’s entire high-level information architecture is about to go live, it might still be relevant if the questioning raises a significant blocker that no one saw, but those concerns are much more likely to have to wait for a later revision. So in general, attune your feedback to the stage of the project. Early iteration? Iteration that was later? Polishing work in progress? Each of these needs a different one. 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. Hopefully that’s not the case, but it can happen, which is fine. 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 be more helpful?

    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 the way I typed “oh” into my list of replaced words (your choice between aText, TextExpander, or others ), so that it was instantly deleted when I typed “oh.”

    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 you give it constructive and respectful feedback, whether it be difficult or positive. 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: we can devote more time to making sure that the suggestions ‘ clarity of communication and actionability fulfill two main objectives.

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

    In terms of clarity, start by grounding the critique that you’re about to give by providing context. This includes specifically describing where you’re coming from: do you have a thorough understanding of the project, or is this your first time seeing it? 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 project information, 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 all the things that could be improved. 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 to 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. This is powerful because there is a big difference between a critique of a design that is already in good shape and one that is critiqued for a design 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 also think about breaking up the feedback into sections or even across multiple comments if it is longer. 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 change how I communicate that.

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

    • 🔶 Navigation—I anticipate that one of these two buttons will go forward and the other will go back when I see them. But this is the only screen where this happens, as before we just used a single button and an “×” to close. This seems to be breaking the consistency in the flow. Let’s make sure that all screens have the same two forward and back buttons so that users don’t get confused.
    • � � Overall— I 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, which conveys 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. Sometimes we might feel good or bad about something, so we don’t say it. Or sometimes we might have a doubt that we don’t express because the question might sound stupid. Say it, that’s fine. 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.

    Another benefit of asynchronous feedback is that written feedback automatically monitors decisions. Especially in large projects,” Why did we do this”? There’s nothing better than open, transparent discussions that can be reviewed at any time, which 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, focusing on improving eight of the subjects ‘ focus points, including observation, impact, question, timing, attitude, form, clarity, and actionability, is a lot of work to complete 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.

  • Asynchronous Design Critique: Getting Feedback

    Asynchronous Design Critique: Getting Feedback

    “Any comment?” is probably one of the worst ways to ask for feedback. It’s vague and open ended, and it doesn’t provide any indication of what we’re looking for. Getting good feedback starts earlier than we might expect: it starts with the request. 

    It might seem counterintuitive to start the process of receiving feedback with a question, but that makes sense if we realize that getting feedback can be thought of as a form of design research. In the same way that we wouldn’t do any research without the right questions to get the insights that we need, the best way to ask for feedback is also to craft sharp questions.

    Design critique is not a one-shot process. Sure, any good feedback workflow continues until the project is finished, but this is particularly true for design because design work continues iteration after iteration, from a high level to the finest details. Each level needs its own set of questions.

    And finally, as with any good research, we need to review what we got back, get to the core of its insights, and take action. Question, iteration, and review. Let’s look at each of those.

    The question

    Being open to feedback is essential, but we need to be precise about what we’re looking for. Just saying “Any comment?”, “What do you think?”, or “I’d love to get your opinion” at the end of a presentation—whether it’s in person, over video, or through a written post—is likely to get a number of varied opinions or, even worse, get everyone to follow the direction of the first person who speaks up. And then… we get frustrated because vague questions like those can turn a high-level flows review into people instead commenting on the borders of buttons. Which might be a hearty topic, so it might be hard at that point to redirect the team to the subject that you had wanted to focus on.

    But how do we get into this situation? It’s a mix of factors. One is that we don’t usually consider asking as a part of the feedback process. Another is how natural it is to just leave the question implied, expecting the others to be on the same page. Another is that in nonprofessional discussions, there’s often no need to be that precise. In short, we tend to underestimate the importance of the questions, so we don’t work on improving them.

    The act of asking good questions guides and focuses the critique. It’s also a form of consent: it makes it clear that you’re open to comments and what kind of comments you’d like to get. It puts people in the right mental state, especially in situations when they weren’t expecting to give feedback.

    There isn’t a single best way to ask for feedback. It just needs to be specific, and specificity can take many shapes. A model for design critique that I’ve found particularly useful in my coaching is the one of stage versus depth.

    Stage” refers to each of the steps of the process—in our case, the design process. In progressing from user research to the final design, the kind of feedback evolves. But within a single step, one might still review whether some assumptions are correct and whether there’s been a proper translation of the amassed feedback into updated designs as the project has evolved. A starting point for potential questions could derive from the layers of user experience. What do you want to know: Project objectives? User needs? Functionality? Content? Interaction design? Information architecture? UI design? Navigation design? Visual design? Branding?

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

    • Functionality: Is automating account creation desirable?
    • 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: We have two competing bits of information on this page. Is the structure effective in communicating them both?
    • UI design: What are your thoughts on the error counter at the top of the page that makes sure that you see the next error, even if the error is out of 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. Are there any suggestions to address this?
    • Visual design: Are the sticky notifications in the bottom-right corner visible enough?

    The other axis of specificity is about how deep you’d like to go on what’s 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 useful from one iteration to the next where it’s important to highlight the parts that have changed.

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

    A simple trick is to remove generic qualifiers from your questions like “good,” “well,” “nice,” “bad,” “okay,” and “cool.” For example, asking, “When the block opens and the buttons appear, is this interaction good?” might look specific, but you can spot the “good” qualifier, and convert it to an even better question: “When the block opens and the buttons appear, is it clear what the next action is?”

    Sometimes we actually do want broad feedback. That’s rare, but it can happen. 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 maybe 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 expansive, and some areas may have already been explored in detail. In these situations, it might be useful to explicitly say that some parts are already locked in and aren’t open to feedback. It’s not something that I’d recommend in general, but I’ve found it useful to avoid falling again into rabbit holes of the sort that might lead to further refinement but aren’t what’s most important right now.

    Asking specific questions can completely change the quality of the feedback that you receive. People with less refined critique skills will now be able to offer more actionable feedback, and even expert designers will welcome the clarity and efficiency that comes from focusing only 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. Yet a lot of design tools with inline commenting tend to show changes as a single fluid stream in the same file, and those types of design tools make conversations disappear once they’re resolved, update shared UI components automatically, and compel designs to always show the latest version—unless these would-be helpful features were to be 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’s probably not the best way to approach design critiques, but even if I don’t want to be too prescriptive here: that could work for some teams.

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

    Using iteration posts has many advantages:

    • It creates a rhythm in the design work so that the designer can review feedback from each iteration and prepare for the next.
    • It makes decisions visible for future review, and conversations are likewise always available.
    • It creates a record of how the design changed over time.
    • Depending on the tool, it might also make it easier to collect feedback and act on it.

    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. And other feedback approaches (such as live critique, pair designing, or inline comments) can build from there.

    I don’t think there’s a standard format for iteration posts. But there are a few high-level elements that make sense to include as a baseline:

    1. The goal
    2. The design
    3. The list of changes
    4. The questions

    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. So this is something that I’d repeat in every iteration post—literally copy and pasting it. 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. If I want to know about the latest design, the latest iteration post will have all that I need.

    This copy-and-paste part introduces another relevant concept: alignment comes from repetition. So having posts that repeat information is actually very effective toward making sure 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 short, it’s any design artifact. 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 can also be useful to label the artifacts with clear titles because that can make it easier to refer to them. Write the post in a way that helps people understand the work. It’s not too different from organizing a good 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.

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

    Not all iterations are 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 start settling on a solution and refining it until the design process reaches its end and the feature ships.

    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 a draft—just a concept to get a conversation going—or it could be a cumulative list of each feature that was added over the course of each iteration until the full picture is done.

    Over time, I also started using specific labels for incremental iterations: i1, i2, i3, and so on. This might look like a minor labelling tip, but it can help in multiple ways:

    • Unique—It’s a clear unique marker. Within each project, one can easily say, “This was discussed in i4,” and everyone knows where they can go to review things.
    • 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. Iterations must be able to be exploratory, incomplete, partial.
    • Future proof—It resolves the “final” naming problem that you can run into with versions. No more files named “final final complete no-really-its-done.” Within each project, the largest number always represents the latest iteration.

    To mark when a design is complete enough to be worked on, even if there might be some bits still in need of attention and in turn more iterations needed, the wording release candidate (RC) could be used to describe it: “with i8, we reached RC” or “i12 is an RC.”

    The review

    What usually happens during a design critique is an open discussion, with a back and forth between people that can be very productive. This approach is particularly effective during live, synchronous feedback. But when we work asynchronously, it’s more effective to use a different approach: we can shift to 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.

    This shift has some major benefits that make asynchronous feedback particularly effective, especially around these friction points:

    1. It removes the pressure to reply to everyone.
    2. It reduces the frustration from swoop-by comments.
    3. It lessens our personal stake.

    The first friction point is feeling a pressure to reply to every single comment. Sometimes we write the iteration post, and we get replies from our team. It’s just a few of them, it’s easy, and it doesn’t feel like a problem. 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 person who’s replying is a stakeholder or someone directly involved in the project who we feel that we need to listen to. We need to accept that this pressure is absolutely normal, and it’s human nature to try to accommodate people who we care about. Sometimes replying to all comments can be effective, but if we treat a design critique more like user research, we realize that we don’t have to reply to every comment, and in asynchronous spaces, there are alternatives:

    • One is to let the next iteration speak for itself. When the design evolves and we post a follow-up iteration, that’s the reply. You might tag all the people who were involved in the previous discussion, but even that’s a choice, not a requirement. 
    • Another is to briefly reply to acknowledge each comment, such as “Understood. Thank you,” “Good points—I’ll review,” or “Thanks. I’ll include these in the next 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 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 second friction point is the swoop-by comment, which is the kind of feedback that comes from someone outside the project or team who might not be aware of the context, restrictions, decisions, or requirements—or of the previous iterations’ discussions. 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 often trigger the simple thought “We’ve already discussed this…”, and it can be frustrating to have to repeat the same reply over and over.

    Let’s begin by acknowledging again that there’s no need to reply to every comment. If, however, replying to a previously litigated point might be useful, a short reply with a link to the previous discussion for extra details is usually enough. Remember, alignment comes from repetition, so it’s okay to repeat things sometimes!

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

    The third friction point is the personal stake we could have with the design, which could make us feel defensive if the review were to feel more like a discussion. Treating feedback as user research helps us create a healthy distance between the people giving us feedback and our ego (because yes, even if we don’t want to admit it, it’s there). And ultimately, treating everything in aggregated form allows us to better prioritize our work.

    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 have to analyze it and make a decision that you can justify, but sometimes “no” is the right answer. 

    As the designer leading the project, you’re in charge of that decision. Ultimately, everyone has their specialty, and as the designer, you’re the one who has the most knowledge and the most context to make the right decision. 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 Brie Anne Demkiw and Mike Shelton for reviewing the first draft of this article.

  • Designing for the Unexpected

    Designing for the Unexpected

    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 items that function 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 later add willing to. The growth phase was about attaining pixel-perfect reliability using set widths, fixed levels, and absolute placement.

    All of this was altered by Ethan Marcotte’s speak at An Event Apart and the subsequent article in A Checklist Off in 2010. 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. I quickly realized that you didn’t just put responsiveness at the end of a job. To make smooth design, you need to prepare throughout the style stage.

    A new way to style

    Making information accessible to all devices a priority when designing responsive or liquid websites has always been the goal. 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 html:

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

    Media answers

    The next ingredient for reactive 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 answers 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 little- to medium-sized companies, to larger in-house teams where I worked across a collection of related sites. In those positions, I began to work more frequently with washable parts.

    Our rely on multimedia queries resulted in parts that were tied to frequent window 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 answers 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 layouts are to be replaced by responsive components.

    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;}

    You don’t need to wrap elements in container rows, which is the biggest benefit of all of this. 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 is that I now work for a sizable company, which is quite different from the design agency position I held 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 right now I feel 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 demonstrate how the site would look at all three stages at some point in our careers.

    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, like in our earlier Subgrid card illustration, which allowed the cards to modify both their own content and that of their sibling components.

    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 the dated markup tricks below,

    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 set 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 % ( the preferred value ) of its container, 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 anticipating unforeseen language or direction changes, we can begin creating future-proofing 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 lot different to design for someone using a mobile phone and walking through a crowded street in glaring sunshine than it is for someone using a desktop computer. Situations and environments are hard to plan for or predict because they change as people react to their own unique challenges and tasks.

    Choice is so crucial because of this. 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”.

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

    Chris Ashton

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

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

    Image alt text

    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 media queries are now being returned.

    Media answers 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, there is a light-level feature that enables you to alter a user’s style when they are in the sun or the darkness. 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 answers like this go beyond choices made by a browser to grant more control to the user.

    Expect the unexpected

    In the end, the one thing we should always anticipate is 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 are still many more things we can do to adopt a more intrinsic approach, from responsive to fluid and fixed. Even better, we can test these techniques during the design phase by designing in-browser and watching how our designs adapt in real-time.

    When it comes to unexpected circumstances, we need to make sure our goods are usable when people need them, whenever and wherever that may be. 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.

  • Voice Content and Usability

    Voice Content and Usability

    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 complexity of human statement, including the disfluencies and pauses, the gestures and body speech, and the variations in expression choice and spoken dialect, which may impede even the most skillfully crafted human-computer interaction. In the human-to-human situation, spoken language also has the opportunity of face-to-face call, where we can easily interpret visual interpersonal cues.

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

    Spoken language is not a luxury in this regard. Besides the nonverbal cues that decorate conversations with emphasis and emotional context, there are also verbal cues and vocal behaviors that modulate conversation in nuanced ways: how something is said, not what. Our spoken language conveys much more than the written word could ever contain, whether it be rapid-fire, low-pitched, or high-decibel, sarcastic, stilted, or sighing. So when it comes to voice interfaces—the machines we conduct spoken conversations with—we face exciting challenges as designers and content strategists.

    Voice-to-text interactions

    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 conversation as a result:

    • we need something done ( such as a transaction ),
    • we want to know something, some kind of information, or
    • we are social beings and want someone to talk to ( conversation for conversation’s sake ).

    A single conversation from beginning to end that achieves some outcome for the user, starting with the voice interface’s first greeting and ending with the user exiting the interface, also fits into these three categories, which I refer to as transactional, informational, 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 may not always be 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. Users are also debating whether or not they prefer the kind of organic human conversation that starts with a prosocial voiceover and progresses seamlessly into other types. 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 ).

    How are things going, Alison?

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

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

    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. Conversations that are transactional have certain characteristics: they are direct, concise, and cost-effective. They quickly dispense with pleasantries.

    Informational voice interactions

    Meanwhile, some conversations are primarily about obtaining information. Alison might only want to place an order at Crust Deluxe, but she might not want to leave without a pizza at all. She might be just as interested in whether they serve halal or kosher dishes, gluten-free options, or something else. We’re after much more than just a prosocial mini-conversation at the beginning, even though we do it once more to establish politeness.

    How are things going, Alison?

    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 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. Are you considering any additional dietary restrictions?

    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. Responses are typically longer, more in-depth, and carefully communicated to ensure that the customer understands the main ideas.

    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 are completely dependent on spoken conversation and lack any visual component, making them much more nuanced and challenging to deal with because multimodal voice interfaces 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 with the help of interactive voice response ( IVR ) systems, which were developed as an alternative to overburdened customer service representatives.

    IVR systems allowed organizations to reduce their reliance on call centers but soon became notorious for their clunkiness. When you call an airline or hotel company, which is a common practice in the corporate world, these systems were primarily intended as metaphorical switchboards to direct customers to a real phone agent (” Say Reservations to book a flight or check an itinerary” ), which are more likely to happen when you call 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 conversations that typically don’t veer from a single format.

    Screen readers

    The screen reader, a program that converts visual information into synthesized speech, was a development that accompanied the development of IVR systems. 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, allowing them to do so in an aural and temporal space. In other words, screen readers for the web “provide mechanisms that translate visual design constructs—proximity, proportion, etc. —into useful information,” according to Aaron Gustafson in A List Apart. ” At least they do when documents are authored thoughtfully” ( ).

    There’s a big deal with screen readers: they’re difficult to use and relentlessly verbose, despite being incredibly instructive for voice interface designers. 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 is a cognitive burden 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 worrying about it. Blind users, meanwhile, are obligated to listen to every utterance synthesized into speech and therefore prize brevity and efficiency. Users with disabilities who have long had no choice but to use clumsy screen readers might benefit from more streamlined user interfaces, especially more advanced voice assistants.

    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” ( hinter 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, so even now it isn’t possible to program Siri to perform arbitrary functions.

    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 constrained by the limitations of Siri and Cortana are increasingly using programmable voice assistants that are extensibable and customizable. 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 dominate their markets, they are also selling and open-sourcing an unmatched range of tools and frameworks for designers and developers, aiming to make creating voice interfaces as simple as possible, even without the use of any 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, like Google’s Dialogflow, now support omnichannel features, allowing 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—everything written content isn’t enough to preserve what makes human conversation so compelling in the first place.

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

    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 being viewed in microfilm format in 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 goes beyond 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.

  • Sustainable Web Design, An Excerpt

    Sustainable Web Design, An Excerpt

    Some members of the elite running group were beginning to think it was impossible to run a hour 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.

    However, on May 6, 1956, Roger Bannister caught anyone by surprise. 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 today 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, in the same race, three athletes all managed to cross the four-minute challenge. Since therefore, over 1, 400 walkers have actually run a mile in under four days, the current document is 3: 43.13, held by Moroccan performer Hicham El Guerrouj.

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

    Establishing requirements for a lasting web

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

    The main objective in green web layout is to reduce carbon emissions. However, it’s nearly impossible to accurately assess the amount of CO2 that a website 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. What then do we do?

    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 coal pollution gauges:

    1. Transfer of data
    2. Electricity’s coal 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 coal 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 underlying technology of the web like data centers and transmission networks, become more and more energy efficient, websites themselves become less effective as time goes on.

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

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

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

    If we want to take it to the next level, we could start looking at how much more popular our web pages are when people visit them frequently. 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, repeat users who load the same page frequently will likely have a high percentage of the files cached in their browser, which means they won’t need to move all of the files back 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. We can learn even more about how to optimize efficiency for users who regularly visit our pages by measuring transfer size at this next level of detail, which will also enable us to establish page weight budgets for situations that extend beyond the initial visit.

    Page weight budgets are easy to track throughout a design and development process. Although they don’t directly disclose their data on energy consumption and carbon emissions, 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 coal 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 ). This varies widely, with renewable energy sources and nuclear having an extremely low carbon intensity of less than 10 gCO2/k Wh ( even when factoring in their construction ), whereas fossil fuels have very high carbon intensity of approximately 200–400 gCO2/k Wh.

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

    Although we 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 have significantly lower carbon emissions than choosing a data center in the Netherlands ( Fig. 2.3 ).

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

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

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

    Reverting it to carbon emissions

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

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

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

    Browser Energy

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

    One part of the system we can look at in more detail is the energy used by end users ‘ devices. The computational burden is increasingly shifting from the data center to the users ‘ devices, whether they are phones, tablets, laptops, desktops, or even smart TVs, as front-end web technologies advance. Modern web browsers allow us to implement more complex styling and animation on the fly using CSS and JavaScript. Additionally, JavaScript libraries like Angular and React make it possible to create applications where the” thinking” process is performed 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. This not only harms the environment, but it places a disproportionate financial burden on the poorest members of society.

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

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

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

  • Design for Safety, An Excerpt

    Design for Safety, An Excerpt

    According to anti-racist scholar Kim Crayton, “intention without plan is chaos.” We’ve discussed how our prejudices, beliefs, and carelessness toward marginalized and resilient parties lead to dangerous and irresponsible tech—but what, precisely, do we need to do to fix it? We need a strategy, not just the desire to make our software safer.

    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 cannot solve unethical, unsafe technology. )

    The method for equitable safety

    Your objectives when designing for protection are to:

    • discover ways your solution can be used for abuse,
    • style ways to prevent the maltreatment, and
    • provide assistance for customers who are prone 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 public areas of action:

    • conducting studies
    • Creating themes
    • 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 purpose of this design is to prioritize safety when creating a more general product with a broad user base ( which, as we already know from statistics, will include some groups who need to 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 you’re creating an AI product, 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. Google Scholar is a useful resource for locating these studies.

    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 have a better understanding of the subject and be better positioned to prevent retraumatize survivors, you should interview advocates working in the area of your research first. If you’ve uncovered possible domestic violence issues, for example, the experts you’ll want to speak with are survivors themselves, as well as workers at domestic violence hotlines, shelters, other related nonprofits, and lawyers.

    It is crucial to pay people for their knowledge and lived experiences, especially when interviewing survivors of any kind of trauma. Don’t ask survivors to share their trauma for free, as this is exploitative. While some survivors may not want to be paid, you should always make the offer in the initial ask. Alternative to paying is to donate to a cause fighting the kind of violence the interviewee experienced. We’ll talk more about how to appropriately interview survivors in Chapter 6.

    Specific research: Abusers

    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. Describe the ways that abusers or bad actors use technology to harm others, how they use it to silence others, and how they justify or explain the abuse.

    Step 2: Create archetypes

    Use your research’s findings to create abuser and survivor archetypes once you’ve finished conducting your research. Archetypes are not personas, as they’re not based on real people that you interviewed and surveyed. 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 existing research and what this group requires. Personas typically represent real users and include many details, while archetypes are broader and can be more generalized.

    The abuser archetype is defined as 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.

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

    You may want to make multiple survivor archetypes to capture a range of different experiences. They may be aware of the abuse is occurring but not be able to stop it, such as when a stalker keeps figuring out where they are from ( Fig. 5.4), or they may be aware that it is happening but are unable to stop it ( such as when an abuser locks them out of IoT devices ). Include as many of these scenarios as you need to in your survivor archetype. You’ll use these later when you create solutions to help your survivor archetypes achieve 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 prevent 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: Remind yourself of your 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 end up having a good deal of fun when I’ve led Black Mirror brainstorms ( which I think 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.

    You may still not feel confident that you have found every possible source of harm after identifying as many opportunities for abuse as possible. 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, but instead of aiming for 100 %, acknowledge that you’ve done it and will continue to prioritize safety in the future. Once your product is released, your users may identify new issues that you missed, aim to receive that feedback graciously and course-correct quickly.

    Step 4: Design solutions

    You should now be aware of the ways your product can be used for harm 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 explain to the victim what they must 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 that 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 aspects of the design 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 probably too closely acquainted with the product and its design at this point, just like other usability testing techniques, and you know the product too well. Instead of doing it yourself, set up testing as you would with other usability testing: find someone who is not familiar with the product and its design, set the scene, give them a task, encourage them to think out loud, and observe how they attempt to complete it.

    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. You’d make every effort to track down another user’s location who has their privacy settings turned on with this in mind. 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, for instance, would be to discover what causes the temperature change when they aren’t altering it themselves. 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 locate? For your test, this would involve trying to figure out how to do this. This might again reveal that more work is needed to make it clear to the user how they can regain control of the device or account.

    Stress testing

    To make your product more inclusive and compassionate, consider adding stress testing. 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.

  • A Content Model Is Not a Design System

    A Content Model Is Not a Design System

    Do you recall the days gone by when having a successful site was sufficient? Nowadays, people are getting answers from Siri, Google search fragments, and mobile applications, not only our websites. Organizations with forward-thinking goals have adopted an holistic content strategy that aims to reach people across a range of digital programs and platforms.

    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 content versions that are lexical and even join related content, 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.

    For our information to be understood by many systems, the unit needed conceptual types, which are names given based on their meaning rather than their presentation. This is crucial for an multichannel content strategy. Our aim was to allow writers to write articles 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 design systems, which we were more familiar with. An omnichannel content strategy can’t rely on WYSIWYG tools for design and layout, unlike web-focused content strategies. Our tendency to approach the content model with our familiar design-system thinking constantly led us to veer away from one of the primary purposes of a content model: delivering content to audiences on multiple marketing channels.

    Two fundamental tenets govern 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 learned 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, semantics must be used by content models.
    2. And content models should connect content that belongs together.

    Semantic content models

    A semantic content model uses type and attribute names that reflect the content’s intended purpose and not how it will be displayed. For example, in a nonsemantic model, teams might create types like teasers, media blocks, and cards. These types may make it simple to present content, but they do not 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 uses type names like “product,”” service,” and “testimonial” to allow for each delivery channel to interpret and use the content as it sees fit.

    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 community-driven resource for type definitions that are understandable on platforms like Google search.

    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 an advantage in the market. 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 as be used by a bot to answer 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 piece of an article’s meaning and usefulness depend on how well it is organized. 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 take a look at how connecting related content works in a real-world setting to illustrate. The client’s design team created a challenging layout for a software product page that included numerous tabs and sections. Our instincts were to follow 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 content type called “tab section” because our design-system instincts were so well-known, so that multiple tab sections could be added to a page. Each tab section would display various types of content. One tab might contain the software’s information or specifications. A list of resources might be found under 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 these terms? 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 for each tab, their customer had a specific purpose in mind: it would reveal specific information like the software product’s overview, specifications, related resources, and pricing. 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 the content model didn’t like the idea of tabs. What was important was the meaning of the content they were planning to display in the tabs.

    In fact, the customer could have decided to display this content in a different way—without tabs—somewhere else. In response to this realization, we decided to create content types for the software product based on the meaningful qualities the client wanted to display on the web. 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. You should maintain the semantic value and contextual structure of the content strategy throughout the entire implementation process because team members might be drawn to conflate them and force your content model to resemble your design system. Without the use of a magic decoder ring, every delivery channel will be able to consume the content.
    • If your team is struggling to make this transition, you can still reap some of the benefits by using Schema. Your website uses structured data from org. The benefit of search engine optimization is a compelling reason on its own, even if additional delivery channels aren’t on the horizon in the near future.
    • 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 will be prepared for the upcoming big thing, and they will be able to create new designs without compromising the compatibility between the content and the design.

    You’ll help your team understand these principles by firmly defending them in their efforts to give content the attention it deserves as both your most valuable resource and your most effective way to engage with your audience.

  • How to Sell UX Research with Two Simple Questions

    How to Sell UX Research with Two Simple Questions

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

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

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

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

    A gauntlet between research and screen design

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

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

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

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

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

    Getting in the same curiosity-boat

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

    Mark Twain

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

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

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

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

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

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

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

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

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

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

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

    “So are caregivers in scope for this redesign?”

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

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

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

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

    The two questions

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

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

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

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

    Prep work: Noun foraging

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

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

    Here are just a few great noun foraging sources:

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

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

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

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

    1. Structure
    2. Instances
    3. Purpose

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

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

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

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

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

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

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

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

    Drumroll, please…

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

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

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

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

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

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

    Facilitate an Object Definition Workshop

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

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

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

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

    1. What is this thing?

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

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

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

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

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

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

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

    OK, moving on. 

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

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

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

    Stakeholder 1: Yes! Definitely.

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

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

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

    4. What’s the relationship between these objects?

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

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

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

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

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

    5. Is this object in scope?

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

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

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

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

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

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

    6. Create a visual representation of the objects’ relationships

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

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

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

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

    Light the fuse

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

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

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

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

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

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

    Final words: Hold the screen design!

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

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

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

    All the best of luck! Now go sell research!