06 //

A prompt:


Your friendly neighborhood developer emails you the following: “My client has me building this kind of personnel ‘data grid’ for a client. (Example: https://www.ag-grid.com/example.php) My old employer used PeopleSoft as an employee management system, and working with it was painful. From a usability standpoint, how does one make dealing with a big giant chart of data less painful?” How do you respond?




Dear friendly neighborhood developer,

“A big giant chart of data” is never a fun thing to deal with, but often necessary. Fortunately, there are a number of UX principles that would be applicable in your situation and will hopefully ease some of the pain for both you and your client (and their client).

To more specifically answer your question, the first thing I would want to do is determine who will be using this personnel data grid and what they are wanting to accomplish by using it. An employee management system might have multiple users, each wanting to enter or find information pertaining to employee details, scheduling, attendance, leave, payroll, and so on. Throwing all of this information into a grid without considering how it will be used is likely to cause pain for every type of user.

Usability-wise, there is a long-standing “mantra” for information visualization which I believe applies to your project: "Overview first, zoom and filter, then details-on-demand.” Applying this guideline from the onset of creating your data grid will go a long way in increasing the flexibility and efficiency of the grid for your user. Big repositories of data will benefit immensely from having a well-thought out structure that users can easily navigate. This means creating pathways within the structure that a user can follow in order to find the information most relevant to their need. Content prioritization, filter tools, and sort functionality are all means to achieve this end. Ben Schneiderman, in his paper The Eyes  Have It: A Task by Data Type  Taxonomy for Information Visualizations, coined the mantra above and goes into further detail:

  1. Overview: Gain an overview of the entire collection.
  2. Zoom : Zoom in on items of interest.
  3. Filter: Filter out uninteresting items.
  4. Details-on-demand: Select an item or group and get details when needed.
  5. Relate: View relationships among items.
  6. History: Keep a history of actions to support undo, replay, and progressive refinement.
  7. Extract: Allow extraction of sub-collections and of the query parameters.

Each of the tasks above allows users to get informed and take action. Taken together, the seven tasks help create a user-friendly data grid regardless of content. An overview helps users easily find patterns and outliers, while also clueing them into where they might look to find what they need. Based on context, users should be able to hide information they don’t need, as well as dive deeper into data points they find relevant. Column sorting, filtering, grouping, and pivot tables will all aid in this process and should be made available to the user whenever possible. Reducing the data set also helps users view meaningful relationships and compare data.

With that being said, simplicity is key for users to be able to successfully use a massive data grid. All the filter and sort tools in the world won't fix an experience perceived as complicated, bloated, and messy. This is where aesthetic and minimalist design principles come in, making content easy on the eyes and allowing the tools you have built to feel accessible. By removing clutter you are also minimizing the perception of complexity. White space, visual hierarchy, and sectioning are all ways to accomplish this. Simply adding white space around data points can go a long way in helping users scan and find information without feeling lost or overwhelmed. Breaking complex data into sections helps users focus on content and control what they view. Finally, keeping the language, sizes, and colors consistent throughout headers, labels, and action buttons will help your user complete their tasks. Remember, every element in the design should help the user achieve his or her goal, which is why it is so important to define one (or several) in the first place.

I hope this helps!


05 //

UX Design Strategy


When I began designing identities for people, I was working at a studio that had no established way to collect information from the client and organize it into a proposal that could guide the project. I watched projects crash and burn; I watched them drag out for months or simply fizzle out altogether. It was excruciating, not only for the designers, but for our lost and dubious clients. I went through the process once, completely oblivious to another way, and immediately knew that this was not how design projects should be run. Design strategy seems completely obvious once you know what it is, but without it, everything seems impossibly overwhelming, messy, and without direction.

To me, design strategy is the same as any strategy—a game plan for moving forward based on sound research, a high level goal, and a boatload of preparation. UX design strategy is exactly that and much more. It includes researching and learning about the product or idea at hand, the people who will be using it, the people involved in making it, and prioritizing next steps. I really like this definition from Robert Hoekman Jr.: "What good UX strategy actually entails is researching and recognizing the constraints and concerns from all sides and painting a big red target on the wall so that everyone involved can make decisions that serve researched, vetted, and defined objectives.” Design strategy is the foundation on which a product is built, and the roadmap people can refer to when they are feeling lost along the way.

Once I became a freelancer, design strategy was an integral part of my process. I spent hours and hours crafting intake questionnaires, outlining a step by step journey for my client, designing templates and and figuring out my delivery method. All in all, it saved me tons of time, my clients were more satisfied, and I actually enjoyed designing. What I was missing however is an important part of design strategy: success metrics. I would hand off logos and style guides, content that my clients were excited about the work and would whisk the files off to do great things. The truth was, I had no idea if the designs were working, and I hadn’t planned any way to measure that. Again, Hoekman sums it up best: "Without constraints, without understanding, without research, without vision and success metrics and guiding design principles, design is not design. It’s decoration. With these things, however, we practice design at its very best. We design with purpose, intent, and measurable outcomes."

04 //

Desirability Testing


As a visual person, I often judge products based on the way they look and the way they make me feel — sometimes even at the expense of features. This is not to say I would commit to using something that is frustrating or difficult, but, all things being equal, I would certainly choose a product that feels more desirable to me. 

Desirability is highly subjective, and traditional user studies have found difficulty in collecting data that accurately accounts for this. In interviews and usability testing, users are often asked questions that are more important to the researchers than to them personally and are also hesitant to provide negative feedback. It can be difficult for users to come up with the right words to describe something, so having a set that they can pull from makes the process quicker and more efficient.

Microsoft developed a technique to measure desirability that would allow participants to select from a range of words, both positive and negative, to describe their feelings toward a product. The method allows researchers to control which things they are interested in getting feedback on, and can then ask specific questions related to these answers. It also helps to bypass the noise that can often come from asking about aesthetics or trying gain this kind of feedback in another way. The participants even seem to enjoy the process.

Though this method collects primarily qualitative data, it is also possible to obtain metrics by using a simple word cloud. Once organized, the selected words paint a quite useful picture of users’ feelings toward the product. 

One case study I found showed compiled word clouds next to the designs they were testing. They tested three versions of the same site, and it is interesting to see how varied the emotional responses were from design to design. They were also able to determine percentages of positive and negative feedback as additional data to help them move forward. I’d be curious to know what aspects of the site made people respond the way they did — was it the color schemes? The stock photography? The heading copy or layout? 

As usability increases across the board (as I hope it will continue to do) the importance of desirability will also grow. Obviously it is so important to have something that functions and does what it is supposed to do, but aesthetics and visceral reactions are definitely a huge part of the picture. Having some way to measure this to help guide design decisions is important for design teams, business owners, and users alike.

03 //

User Research: Our Hero


"Get the Most Out of User Research"


This article starts out with an interesting perspective: user research is our hero. It provides all of our answers and is essential for creating optimal solutions to human problems. The author goes on to describe the purpose of a user research goal, which is to provide direction for the research. A goal is a concept that sometimes seems slippery and amorphous. To someone just starting out, it feels like something that is easy to get wrong — it can go too far or not far enough, or in the wrong direction altogether. But then the author provides an easy description of this type of goal: "What I need to do is ask a question that can be answered through user research. Something concrete that can lead to an outcome that is actionable.” Actionable is a key word — what is the point of stockpiling research and data without being able to do anything with it? It becomes about employing the right user research (quantitative vs. qualitative), in order to find the information that will actually help achieve the defined goal. This article skips over the part about actually coming up with the right questions (he relies on a research expert, so maybe that makes sense) and delves right into the importance of observing and recording. There are details about running a session, and details about capturing information, but the critical point is to show up. Be there, write things down, and write them down immediately — you cannot count on your memory to keep track of important moments. The end of the session is not really the end of anything, it is simply the part where everyone comes together to analyze what happened and what findings exist. There are no answers, only educated assumptions that provide a foundation for the next step. This was the interesting part to me — what feels like an answer is just something else to test, to prove or disprove.  

02 //

Ethnographic Data in Design


"The 3 Tenets of Applied Ethnography"


It is interesting to read articles that confess the major subjectivity of the topic at hand. UX is notoriously subjective, something it very much has in common with psychology. "UX is essentially an extension of psychology. Indeed, UX is an application of psychological principles in a context that traditionally has little to do with psychology.” This article notes how design logic varies from designer to designer, and yet that logic is the foundation of the field — and the reason for innovation. Because of this subjectivity, ethnographic research is imperative to understanding the people we are designing for and allows us to develop ideas that perhaps begin and end outside of ourselves. Even taking a single step in another person’s shoes can have vast implications over how we think about a problem. Today, more than ever, this is the way to solve problems. The article then points out that having raw qualitative data is great, but fairly meaningless when it comes to moving forward. Analyzing information and attaching confidence to it (the confidence interval) tempers subjectivity and provides support for design decisions. “Ethnographic data helps you generate, challenge, and validate your design assumptions.” Understanding user roadblocks and what informs user choices is critical to design, and something that ethnographic research is poised to deliver. To have this technique in today’s world is invaluable to gain real insight in getting to the root of problems, where we can then begin to develop solutions. 

01 //

Mental Health and Design


"Designing A Product With Mental Health Issues In Mind"


This article grabbed my attention because I glimpsed the subheading “positive friction”. The article offers a great design example: blister packaging for pills, something which I had never even questioned. Positive friction is a design tool that allows us to insert speed bumps into an experience in order to bring about a positive effect or offer a safety net. With relevance to our studies this past week, it is an interesting example of how and when to break design principles. For products that appeal to a wide range of people, breaking these rules becomes a delicate balancing act of not turning off customers who don’t have a need for speed bumps (although there are certainly many examples in which Patricia Moore’s theory that making things better for a vulnerable group will undoubtedly make them better for all people). The article goes on to detail what Monzo is and how it works. Their goal is to hold people accountable while giving them the tools to take action when things go wrong -- as opposed to simply alerting them that something is wrong. The app is working to facilitate relationships and interactions between people, a perfect example of humans and technology working together. As a UX designer, I enjoy reading about these kinds of examples since they can help inform my research methods and decisions when it come to following best practices.