Good IA is Good Business

An emerging pattern: recognizing the findability of information as a central business concern. In some cases, it’s trumpeted as a competitive advantage. In others, its absence is recognized as a significant liability. For example, a couple of weeks ago, I wrote about how classical music streaming service IDAGIO is touting its search features as a competitive differentiator. And just last week, an article in The Verge highlighted the costs of poor metadata.

Following this trend, earlier this week, Apple’s WWDC keynote showcased structural changes to a few of its key apps. The company’s Podcasts app — one of the most popular in the world — is gaining a new feature that allows users to search for keywords in audio content. This represents a major improvement in findability, and the fact it got stage time during a very packed keynote is significant. (I’ve been told Google’ podcasts app has a similar feature.)

Another big change announced during Apple’s keynote was the structural redesign of iTunes on the Mac, which is being broken up into separate apps (as it is on Apple’s other operating systems.) In describing the rationale behind the changes, Apple exec Craig Federighi walked the audience through a history of iTunes, how it accreted features over the years, and how a different approach was now needed. It was a very compelling pitch for rethinking a complex system’s information architecture.

Although none of these examples talk explicitly about IA, they’re all showcasing the importance of digital systems’ structural layers to the businesses that operate them. As such systems become more complex and central to their organizations’ bottom lines, savvy business leaders will inevitably look to improve their information architectures. To paraphrase Thomas Watson, good IA is good business.

The Dollar Value of Metadata

As software eats more of the world, it becomes increasingly evident to people just how important it is to structure information correctly. It’s not just about finding and understanding stuff; in some cases lacking the right structure can be costly. One such case is that of music artists, which — according to an article on The Verge — are leaving billions of dollars on the table due to bad metadata:

Metadata sounds like one of the smallest, most boring things in music. But as it turns out, it’s one of the most important, complex, and broken, leaving many musicians unable to get paid for their work. “Every second that goes by and it’s not fixed, I’m dripping pennies,” said the musician, who asked to remain anonymous because of “the repercussions of even mentioning that this type of thing happens.”

Entering the correct information about a song sounds like it should be easy enough, but metadata problems have plagued the music industry for decades. Not only are there no standards for how music metadata is collected or displayed, there’s no need to verify the accuracy of a song’s metadata before it gets released, and there’s no one place where music metadata is stored. Instead, fractions of that data is kept in hundreds of different places across the world.

Although its description of what metadata is could be clearer (which I empathize with; this isn’t easy to describe to a general audience), the article does a pretty good job of highlighting some common issues that arise when organizations don’t deal with this stuff properly: a lack of standard frameworks, bad information, no clear mechanisms for collaboration, lack of agreement between the various parties involved, etc. It’s worth your attention:

Metadata is the Biggest Little Problem Plaguing the Music Industry

A Key to the Design Problem

One of my favorite presentations about design is an interview with Charles Eames, which inspired the exhibition “Qu’est ce que le design?” at the Musée des Arts Décoratifs in Paris:

Speaking for himself and his partner Ray, Eames answers questions from curator Mme. L’Amic on the nature of design. They cover lots of ground in the span of a few minutes. Eventually, they come around to the role of constraints in the design process:

L’Amic: Does the creation of design admit constraint?

Eames: Design depends largely on constraints.

L’Amic: What constraints?

Eames: The sum of all constraints. Here’s one of the few effective keys to the design problem: the ability of the designer to recognize as many of the constraints as possible; his willingness and enthusiasm for working within these constraints — constraints of price, of size, of strength, of balance, of surface, of time, and so forth. Each problem has its own peculiar list.

L’Amic: Does design obey laws?

Eames: Aren’t constraints enough?

Mme. L’Amic eventually asks Eames if he’s ever been forced to accept compromises. His reply is gold: “I don’t remember ever being forced to accept compromises, but I’ve willingly accepted constraints.”

The interview ends on an ellipsis. But before that, Eames delivers a great line:

L’Amic: What do you feel is the primary condition for the practice of design and its propagation?

Eames: The recognition of need.

The whole thing is worth your attention:

Design Q & A: Charles and Ray Eames

The Bridge Model

In a 2008 paper in ACM’s Interactions, Hugh Dubberly, Shelley Evenson, and Rick Robinson presented the Analysis-Synthesis Bridge Model. This bridge model describes how designers move from the understanding of a problem domain to a proposed solution. It’s laid out along two dimensions:

Bridge model matrix

On the left half, you have the current state you’re addressing, while the right half represents the future (changed) state. (The authors refer to “the solution, preferred future, concept, proposed response, form.”) The bottom row corresponds to tangible conditions in the world that we can observe and interact with, while the top row refers to abstract models of those things. The design process goes from the lower left quadrant — a solid understanding of conditions in the “real” world through abstraction towards a tangible construct that represents a possible future:

Bridge model

While it seems to imply a clear linear progression (something I’ve seldom experienced in real projects), this model corresponds closely to how I design — especially when dealing with complex domains. I can’t sketch tangible structures (e.g., wireframes, sitemaps, etc.) without having 1) a solid understanding of the domain and 2) models that describe it. This requires spending time dealing with abstract models — and abstraction makes people uncomfortable. Clients want to get as quickly as possible to the lower right quadrant, where they can see and interact with things that look like the thing they’ve hired me to produce. (E.g., prototypes.)

But it’s important to acknowledge that when dealing with complex systems, you’re doing clients a disservice by jumping straight to screens. You really must figure out the structures that underlie the domain first, and that requires devising models — both of the current and future states. The bridge model is a useful tool to help explain how the process works and why abstraction is important to a successful outcome.

The Analysis-Synthesis Bridge Model

TAOI: YouTube Subscriber Counts

The architecture of information:

A headline on The Verge: YouTube is changing how subscriber counts are displayed, possibly shifting its culture.

One of the most famous aphorisms in management is Peter Drucker’s observation that “if you can’t measure it, you can’t improve it.” This phrase succinctly captures an important idea: when deciding the way forward, data is your friend. Rather than discussing directions in the abstract, this concept encourages us to break down problems into impartial facets we can trace over time.

However, as useful as it is, there’s a flip side to this concept: with a compelling enough measure, we can lose sight of the ultimate “it” we’re trying to improve. The point of losing weight isn’t to read a lower number on a scale; it’s to get healthier. The number is a proxy for health — and an imperfect one at that. “Health” is a complex subject with lots of nuances. Articulating it as a single number can make it easier to understand, but oversimplifies a complex whole.

We compound the problem when we base incentives on these numbers. Let’s say you’re promised a $500 bonus if you lose a certain amount of weight by a particular date. At that point “health” is twice abstracted: your goal is now neither health nor weight but the money. The numbers start to become more important than the ultimate thing we want to achieve. The map is not the territory, but we’re being incentivized to navigate the map.

We hope to get to the goal on the real ground the map represents. But sometimes we don’t. Sometimes the map is so compelling that it becomes the territory. This has happened with measures in social media such as follower counts on Twitter.

Back to The Verge article. High-level summary: After a recent kerfuffle between two “creators,” YouTube is changing how its system displays subscriber counts. Creators compete for subscribers, and their fortunes wax and wane accordingly. In this system, follower counts are a proxy for popularity. It’s an imperfect measure, but it’s clear and compelling, and so emerges as the locus of attention for an economy of influence. I didn’t realize it until reading about this issue, but there’s a secondary market on these stats: websites like Social Blade exist solely to track how these people are doing relative to each other. It’s a big deal.

But what’s the ultimate goal here? What social function is this system enabling? (What’s the equivalent of “health”?) Is it entertainment? Commerce? Both?

The Informed Life With Peter Morville

Episode 10 of The Informed Life podcast features an interview with my friend, information architecture and user experience pioneer Peter Morville. Peter is one of the most thoughtful people I know about the subject of information management, and in this interview we discussed how we can be more mindful when living an informed life:

If we think about the questions around how we manage information, what tools do we use to manage information for our personal and professional interests, and then we try to apply metrics or evaluation, am I using these tools efficiently and effectively? Are these the right tools? It begs the question, the right tools to achieve what?… Are these tools and the way I’m managing information leading me in a positive direction where I’m learning and changing? I don’t think we asked these questions very often, but I think that if we want to sort of talk about the tools that we use to manage information, we have to be mindful of what is the purpose behind that.

Peter introduced me to Henry David Thoreau’s concept of the root-striker (“If you really want to solve the problem, you have to strike at the root”), an apt image for a discussion that centered on thinking deeply about the source of the challenges we face when living in an information-saturated culture. Overcoming these challenges requires that we acknowledge that the system isn’t set up to look after our interests:

The first step in protecting yourself from the information deluge is to understand and accept that nobody’s looking out for you, that you have to protect yourself, that it’s not all good. You’re not going to take any steps to protect yourself unless you feel that you have some something you want to protect yourself from.

He goes on to describe some of the practices that have allowed him to protect himself from some of the more noxious aspects of our “seductive information” culture, including meditation and taking sabbaticals from social media.

This interview made me reconsider the foundations of own personal information environment. I hope you get as much value from this conversation as I have.

The Informed Life Episode 10: Peter Morville

Karl Popper on Definitions

Although it’s less common today, in the past, my peer community has engaged in what we call DTDT — “Defining the Damned Thing.” The term describes a discussion that devolves into the ​definition of terms. For example, a discussion about user experience design may lead someone to ask, “What do you mean by ‘experience’?” whereafter the conversation can go down a semantic rabbit hole.

Some folks have a strong aversion to DTDT. However, it’s crucial to ensure that we’re aligned on meaning — especially when we’re using relatively new terms. Despite its popularity among designers and techie folks, “user experience” is still a new term; I’d bet that most people don’t have a clear grasp of what it means. So there’s value to ensuring that everybody’s on the same footing with the language we’re using.

As my friend Andrew Hinton has eloquently written, definitions play an important role in a maturing discipline — and that necessitates these conversations. That said, there’s a flipside to DTDT: it can give the illusion that intelligent discussion is happening when, in fact, no progress is being made. I suspect this is what upsets most people who protest against DTDT.

I was reminded of this issue when I saw this clip from an interview with the philosopher Karl Popper:

In my opinion, it’s a task in life to train oneself to speak as clearly as possible. This isn’t achieved by paying special attention to words, but by clearly formulating theses, so formulated as to be criticizable. People who speak too much about words or concepts or definitions don’t actually bring anything forward that makes a claim to truth. So you can’t do anything against it. A definition is a pure conventional matter.

He goes on to expand on why he thinks definitions aren’t helpful to philosophy:

They only lead to a pretentious, false precision, to the impression that one is particularly precise. But it’s a sham precision, it isn’t genuine clarity. For that reason, I’m against the discussion of terms and definitions. I’m rather for plain, clear speaking.

That’s the goal: alignment through plain, clear speaking.

Karl Popper on Definitions (1974)

Book Notes: “Design Unbound”

Design Unbound: Designing for Emergence in a White Water World
By Ann M. Pendleton-Jullian and John Seely Brown
The MIT Press, 2018

Most people think design is about making better things: a more engaging website, a more usable gadget, a more satisfying experience, a bigger logo, etc. More enlightened folks will quote Steve Jobs, saying that design isn’t how something looks but how it works. While that sentiment is indeed a deeper take on design, it still misses an important point: design is not just about making things, it’s also a way of knowing and intervening in the world. And it’s a special way, since it allows us to tackle what Horst Rittel and Melvin Webber dubbed wicked problems.

Most designers (or the general public, for that matter) don’t see design in this light. This book aims to change that. The preface to the first volume spells out the works’ goal:

Design Unbound set out to define a new tool set for the world we find ourselves in — a world that is rapidly changing, increasingly interconnected, and where, because of this increasing interconnectivity, everything is more contingent on everything else happening around it — much more so than ever before.

The authors use the analogy of white water kayaking to describe complex decision-making under such dynamic conditions. Navigating a turbulent river calls for a completely different approach than doing so in a calm lake. “The interesting thing about white water rivers is that they are navigable,” they state, “but under new terms.”

What new terms? Design Unbound offers a set of design practices and mental models – “an offspring of complexity science, married to architectural design” — to help us navigate complex challenges. These “tools” include a reframing of design briefs, critique, ambiguity, skills, emergence, world-building, networks, and “intervals of possibility.” The book also features several meta-tools, which reframe design practice itself for work at a higher level of abstraction.

These concepts are presented in five books over two volumes. The authors suggest that the work doesn’t need to be read linearly, and offer a useful (and beautiful) guide to its content:

A map to the content in Design Unbound

This is a map for pragmatic design-doing — not for making widgets better (or even better widgets), but operating at a much higher, systemic level: that of social, economic, ecologic transformation. Design enables us to engage these domains through abductive reasoning, a different way of knowing (and acting in) the world than the better-known modalities of deductive and inductive reasoning. I first encountered this powerful idea in Nigel Cross’s Designerly Ways of Knowing, where it’s presented in the abstract. Design Unbound offers concrete practices that allow us to put it in action.

The two volumes of this work comprise a rich and valuable framework for tackling some of our most pressing and complex challenges. I’ll be returning to its pages often, both in my practice and teaching.

Buy it on Amazon:

Design Unbound, Vol. 1

Design Unbound, Vol. 2

TAOI: IDAGIO

The architecture of information:

IDAGIO is a music streaming service. It competes with the likes of Spotify and Apple Music — big players with deep pockets! But IDAGIO is different: it only streams classical music.

If you’re into classical music, you know the other music streaming services aren’t good at classical. Not because of the quality of the recordings, but because they’re set up for pop music, which is usually consumed in single tracks. Classical music, on the other hand, is usually presented in “works,” compositions that consist of several tracks. Structuring information in this way is the first feature IDAGIO highlights on its homepage:

The best search
Unlike other streaming services, we organise music by work not track. Compare all recordings of your favourite work, browse different interpretations, and find the latest albums.

Information architecture as strategic differentiator.