How to Work with Tension in Design

The ultimate purpose of a design project is to change something. It might be kickstarting sales, making stuff more findable, or addressing a competitive challenge. Whatever it is, the project exists because someone wants something to be different.

Changes reveal tensions. Often, teams are invested in the status quo. For example, sales may want product to introduce new features, while product wants a simpler experience. More capabilities increase complexity, so the two are in tension.

Projects are rife with such tensions — and they often go unacknowledged. Not surprising, since dealing with tensions can be uncomfortable. If you’ve ever been in a meeting with a surly stakeholder, you know how awkward these situations can be.

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Clarity vs. Confidence: Starting Conceptual Models Right

Few things are as powerful as a good model of a complex domain. A clear representation of the domain’s key elements and their relationships creates alignment. The model becomes a shared point of reference and shorthand for decision-making.

Good models eschew some complexity. But complex domains aren’t simple. A model that aims to encompass a domain’s full complexity will likely fail at building shared understanding. But a model that over-simplifies won’t be useful.

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The Key to Understanding Why Things Happen

When a systems thinker encounters a problem, the first thing he or she does is look for data, time graphs, the history of the system. That’s because long term behavior provides clues to the underlying system structure. And structure is the key to understanding not just what is happening, but why.

— Donella H. Meadows, Thinking in Systems

Every year, I introduce systems students to the iceberg model. The model is a helpful way of understanding situations by looking ‘beneath the surface’ of the things we experience, to the structures and mental models they manifest.

In case you’re unfamiliar with the iceberg model, it’s a framework that encourages you to think about situations at four levels:

  1. Events, or the tangible manifestations of the situation; the things we can see, hear, and record — “just the facts.”
  2. Patterns we perceive in events; outcomes that happen not just once but manifest time and again.
  3. Structures that may be causing the patterns we perceive; these could include rules, regulations, incentives, etc.
  4. Mental models that bring these structures into being.

Notice the fourth level is more abstract than the first: we can ascertain events, but we must hypothesize mental models. There’s also a causal relationship between levels: mental models elicit structures that elicit patterns of events.

As a result, events are easier to grok than mental models. But as with pace layers, the deep levels are where the true power lies. A change at the level you can see has less impact than tweaking the mental models that bring it forth. The ability to change minds is an incredibly powerful lever.

The iceberg model is helpful when doing research. Research produces lots of data points: Google Analytics and search logs tell you about usage, landscape analyses tell you about competitors and analogs, user interviews tell you about intent, etc.

But research doesn’t stop with data. Insights only emerge once you spot patterns in data. If lots of people enter the same term into the search box and do not get good results, that tells you something important about your system.

But you can go deeper still. Patterns only tell you what is happening, not why. You should at least have a hypothesis about why things are happening. This calls for understanding the underlying structures and the mental models that enable them.

Collaborating on these levels can be uncomfortable since the work is speculative. Acknowledge the awkwardness upfront. Allow the team to speculate. You’re not making anything normative yet, just understanding why things might be happening.

Knowing causes helps produce better outcomes. You might not know causes precisely, but you can test hypotheses. Ultimately, a better understanding of the system’s structures and underlying mental models will lead to more skillful interventions.

Cover image: NOAA’s National Ocean Survey (CC BY 2.0)


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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)


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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.)

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Internal Design Teams and Thought Leadership

There’s a sense of disillusionment among some designers about UX’s ‘lost potential’ — that it’s been co-opted for purely commercial (and in some cases, unscrupulous) ends. It’s articulated in this post by Mark Hurst, and I’m reading it into this tweet by Jesse James Garrett:

I haven’t experienced this malaise myself. (But I’ve seen lots of it on Twitter, a platform that rewards kvetching.) Most designers I know are engaged with their work, and my students seem excited for the future. So, I suspect Jesse’s ‘more than a decade’ qualifier matters.

That said, I believe he’s onto something. Designers should be ecstatic about our field’s increased visibility and impact, but we don’t seem to be. What’s going on? I responded to Jesse’s tweet with one possibility:

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Design with Strategic Intent

Many designers can’t effectively speak to the value they create. Instead, they mostly focus on the beautiful, elegant, user-centered, screen-level artifacts they make.

As a result, many stakeholders don’t see designers as strategic partners but as implementors whose role is designing products right (more engaging, usable, attractive, etc.) rather than designing the right products. Ironically, it’s in the latter where design can make a real difference.

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How to Keep a Long-term Focus

Point of view is worth eighty IQ points.

— Alan Kay

Sometimes we face situations that demand an immediate response. A few weeks ago, millions of Americans dealt with unexpected weather conditions that disrupted their ability to keep themselves and their families fed and warm. On February 20, the crew of United flight 328 had to deal with an engine that exploded in mid-air. (Fortunately — and through excellent piloting and engineering — the plane landed safely.) Such life-threatening situations call for skillful action now.

Most situations aren’t as urgent as landing a crippled plane or finding shelter in freezing temperatures. And yet, we often feel the stress of urgency in our day-to-day lives. Perhaps we’re on the hook for meeting this quarter’s KPIs, or we’re running late to take our child to her 10 am martial arts class, or we have a big presentation on Tuesday. Whatever the case, we’re under pressure to deliver now.

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Meta-IA

My friends Jesse James Garrett and Peter Merholz recently wrapped up the first season (my phrase) of their podcast Finding Our Way. The show is about “navigating the opportunities and challenges of design leadership,” and it takes form as an ongoing conversation between the co-hosts. (And occasional guests, including yours truly.)

Peter and Jesse are rendering a tremendous service to the design community by having these conversations in public. They’re experienced practitioners reflecting on what they’ve learned both in their own journeys to design leadership and through advising other design leaders. If you haven’t heard Finding Our Way, I encourage you to listen.

Episode 25 (“The Reckoning”) is especially worth your attention. In it, Peter and Jesse reflect on emerging themes in their conversation. An exchange early in that episode resonated strongly with me. Peter observed that “the crafts of (design) leadership are communication and information architecture.” He elaborated:

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