Flexibility vs. Ease-of-use

Chris Welch, reporting in The Verge about a new Android tablet feature:

The simply named “Entertainment Space” will be a new section to the left of the home screen on tablets… It’s an all-encompassing hub that brings together video (TV shows, movies, and YouTube), games, and books.

In other words, the feature aggregates the user’s media, making it easier to access. Instead of having to open individual apps to find movies, TV shows, YouTube clips, etc., users can now access a single screen that puts content upfront.

Computers are universal devices — tools for making tools. Depending on what app you’re using, your computer can be a spreadsheet, a music player, a book, a video editor, etc. This flexibility is a big part of what makes computers powerful.

The tradeoff is complexity. Learning to use a single-purpose tool entails forming an accurate mental model of how it works. This can be hard enough. (I’ve been using Excel for decades and still learning new things it can do.)

But when you’re using a platform, you must not only form a model of each tool but also of the means through which you manage tools — where to find them, how to install, launch, and configure them, where to save work-in-progress, etc.

There’s an inherent tension between flexibility and ease of use. System designers oscillate between both extremes. A new device may launch as a single-purpose appliance and evolve towards platformhood.

An example of this is Apple TV. Originally designed as a simple living room media player, today’s models offer a broad range of functions, including the ability to install apps like games and third-party media “stores.”

This flexibility makes the system more powerful but also more complex. In the earlier, simpler version, users could easily choose what content to experience. Now, they must keep track not just of what to experience, but where to do it.

Users of a single-purpose system must only understand a small set of taxonomies. For example, if they’re going to watch movies, they’ll expect to deal with genres, movie studios, directors, etc.

In contrast, a more complex system asks that users understand taxonomies of taxonomies: “this is the type of app where I can expect to see movie genres, whereas this other app over here has levels and health points.”

Features like Entertainment Space aim to square this circle by layering a simplified, content-first experience atop the platform. I expect their effectiveness depends on their discovery algorithms. It’s a tricky design challenge.

Google’s Entertainment Space makes Android tablets look like Google TV – The Verge

Building Bridges to Understanding

Some tasks are easy, like choosing a flavor of ice cream; other tasks are hard, like choosing a medical treatment. Consider, for example, an ice cream shop where the varieties differ only in flavor, not calories or other nutritional content. Selecting which ice cream to eat is merely a matter of choosing the one that tastes best. If the flavors are all familiar, such as vanilla, chocolate, and strawberry, most people will be able to predict with considerable accuracy the relation between their choice and their ultimate consumption experience. Call this relation between choice and welfare a mapping. Even if there are some exotic flavors, the ice cream store can solve the mapping problem by offering a free taste.

Richard H. Thaler, Cass R. Sunstein, Nudge

Thaler and Sunstein are describing part of what I understand as a mental model. New users aren’t blank slates. They approach interactions with a system using preconceptions shaped by prior experiences with analogous systems.

For example, imagine you encounter chocolate as a possible ice cream choice for the first time. (I know, it’s inconceivable. Everyone loves chocolate ice cream. Right? I know I do. Please bear with me.) If you’ve had chocolate candy and any other kind of ice cream before, you may have a rough idea of what to expect. Chocolate has a particular flavor, and ice cream is sweet, cold, and creamy.

Now consider an exotic ice cream flavor such as green tea. You may have had ice cream and green tea before, so you have reference points for both. However, your prior experiences confound your expectations of how green tea ice cream will taste and feel. Ice cream is sweet and cold; green tea is bitter and hot.

So, when choosing between chocolate or green tea ice cream, you’ll have a better model of the former. That is, your expectations of the taste of chocolate ice cream map more closely to your experience of eating it. If you’re feeling adventurous, you may pick green tea anyway. But it’s a gamble. Hence, those (obnoxiously small) free sample spoons in ice cream shops.

The primary function of information architecture is establishing meaningful distinctions. These distinctions appear as choices to users. Users understand those choices in relation to other choices (i.e., as sets of concepts) and in relation to prior interactions with similar choices (i.e., as individual concepts.)

Some of these concepts will be more obvious than others, much like chocolate is a more obvious choice of ice cream flavor than green tea. Users need help when choosing between unfamiliar or ambiguous concepts.

In other words, users need semantic analogs to those free ice cream samples. For example, each choice could include a clear label, plus an icon or a short phrase that clarifies its meaning in this particular context. Ideally, such aids give users a high-level preview of what they can expect to find when they choose that option. (I.e., they “give them a taste of what’s to come.”)

Much of the craft of IA consists of orchestrating the expectations of users as they’re inducted into new systems. This requires building nuanced bridges between users’ (imperfect) mental models and systems’ (complex, unfamiliar) conceptual models. When done successfully, a user‘s confidence in making choices will increase as he or she interacts with the system.

Cover photo: Ruth Hartnupt (CC BY 2.0)


Subscribe to my newsletter

If you find this post useful, you may also like my newsletter. Every other Sunday, I share ideas and resources about strategic design, systems thinking, and information architecture. Join us!

Processing…
Success! You're on the list.

Overcoming Objections to Modeling

Recently, I asked on Twitter,

What’s the best objection you’ve heard to making conceptual models as part of the design process?

A lively discussion ensued. Some respondents were unclear on what I meant by “conceptual models,” which speaks to the lack of mainstream awareness of this crucial design artifact. (Here’s my latest stab at clarifying.) Others, clear on what conceptual models are, pointed out that the process matters more than ‘deliverables.’ Great point.

But I’m especially interested in the objections. Here are some that represent what I see as the main gist. Chris Avore pointed out that conceptual models are seen as “too hand-wavey or theater-like,” and that they “lead to a few head nods but the world/plan/goal doesn’t change at the end.” To put it bluntly, as Hà Phan did, some people see conceptual models as “bullshit.” (My take: true insofar as they know about modeling at all; I suspect most people don’t.)

Continue reading

Models Before Screens

Tanner Christensen asked a good question on Twitter:

Peter tagged me on his reply, leading me to respond with a few thoughts. I’m restating (and expanding) them here to keep them from disappearing in Twitter’s fast-moving stream.

Whenever I work on a new navigation system, I start by establishing its ideal user conceptual model. This model must be informed by research. (So, research is the place to start. But that should be self-evident.)

Continue reading

Citibank’s $500m ‘UI’ Problem

Timothy B. Lee reporting for Ars Technica:

A federal judge has ruled that Citibank isn’t entitled to the return of $500 million it sent to various creditors last August. Kludgey software and a poorly designed user interface contributed to the massive screwup.

Citibank was acting as an agent for Revlon, which owed hundreds of millions of dollars to various creditors. On August 11, Citibank was supposed to send out interest payments totaling $7.8 million to these creditors.

However, Revlon was in the process of refinancing its debt—paying off a few creditors while rolling the rest of its debt into a new loan. And this, combined with the confusing interface of financial software called Flexcube, led the bank to accidentally pay back the principal on the entire loan—most of which wasn’t due until 2023.

My initial reaction on reading this was: wow, $500m is a lot of money — I wonder how bad the UI is? The article provides a screenshot, which it credits to Judge Jesse Furman:

Continue reading

Three Models

The men who are cursed with the gift of the literal mind are the unfortunate ones who are always busy with their nets and neglect the fishing.

– Rabindranath Tagore, Sadhana

Modeling is the most critical underused design skill. The ability to examine a domain abstractly — to consider its components, how they relate to each other, and how they allow people to achieve their goals — is essential to designing complex systems that balance the needs of users with the organization’s strategic goals and, more broadly, social well-being.

Continue reading

The ‘Culture’ Layer

As someone who cares about the longevity of systems, I love Stewart Brand’s Pace Layer model. In case you’re unfamiliar with the idea, the Pace Layer model explains how complex systems change over time. Such systems don’t change uniformly; instead, they’re composed of elements that vary in scale and rates of change.

The model has roots in architecture, and that’s how I usually introduce it. Mr. Brand’s book How Building’s Learn presents the following version, which is based on the work of architect Frank Duffy:

Continue reading

Screens and Models

Designers — at least the good ones — have a rare superpower: they can leap several levels of abstraction in a single bound. Among other things, this allows them to look at the form of a thing (a building, a kettle, a website) and get a sense of its constituent parts, the relationships between those parts, how those relationships help serve particular functions, and what those parts, relationships, and functions say about the goals of the entity that commissioned the thing — all without getting hung up on its “look and feel.” In other words, good designers can look beyond the tangible forms of things to the conceptual models they manifest. Some designers can even map out these models in ways that make sense to the rest of us.

Working with models is a key skill — perhaps the key skill — in 21st Century design. Today’s most important design challenges deal with complex, evolving systems. The parts of these systems we see and interact with (such as user interfaces) are only surface manifestations of deeper structures. It’s essential to understand the connection between these structures, the forces that call them forth, and the user interfaces that manifest them. You can’t skillfully intervene by acting solely on the surface.

However, many designers (and most stakeholders) want to work with screens, not models. Screens are things they can test and critique. Models? Not so much. It takes practice to see the tangible forms latent in an abstract diagram. Most of us lack the patience to acquire the practice. We’re drawn to screens because we can draw screens; they’re familiar, things we deal with every day. Models, on the other hand, are abstractions. They can be ambiguous and subjective and unfamiliar. This makes them hard to communicate. How do we begin to draw such a thing?

And yet, draw them we must. Only by understanding models can we effectively deal with fitness-to-purpose and second- and third-order effects, and thereby ensure design directions are strategically and ethically sound. Of course, this doesn’t mean we won’t work on screens at all. As I said, we can’t test models without manifesting them as tangible artifacts. But these artifacts must be rooted in a clear understanding of the underlying models, not the other way around. The ability to jump back-and-forth between models and their expression as UI requires training and practice. It’s an essential skill for today’s designers, and one I’m increasingly focused on learning and teaching.

TAOI: Gmail’s New Conceptual Model

The architecture of information:

Yesterday, Google announced an upcoming Gmail redesign. Here’s an overview:

As you can see, these aren’t cosmetic tweaks, but significant changes to Gmail’s structure. Where previously the app aspired to be a great email client, now its stated goal is to be “your new home for work.” This goal reflects three fundamental premises:

  • Much of what many of us do for “work” consists of coordinating with and informing each other
  • Most of these communications happen over digital channels (especially now that many of us are working “remotely”)
  • Email is no longer the only (or even primary) channel for these communications
Continue reading