Intertwingled: Information Changes Everything

October 6, 2014

This is a sample chapter from Peter Morville’s new book, Intertwingled: Information Changes Everything. 2014 Semantic Studios.

Chapter 3: Connections

Intertwingled CoverTwo roads diverged in a wood, and I—
I took the one less traveled by,
And that has made all the difference.
—Robert Frost

We’re singing with Vienna Teng in her front yard, and we are joyful. It’s the first Sunday in May, and I’m with our teenage daughters, Claire and Claudia, at the Water Hill Music Festival, a free, annual, all-afternoon, front porch concert put on by residents for their neighbors and the rest of the world. It’s a blue sky sunshine dancing barefoot in the grass sorta day, and each of us has traveled our own path on the map of music, time, and porches, but now we sing as one people in the ancient pattern of call and response.

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There’ll be an evolution of the human soul (soon love soon)

We will know that to be a part is to be truly whole (soon love soon)

We will know the pattern of centuries’ rise and fall (soon love soon)

We will know that the fate of one is the fate of all.

In a bittersweet moment of connection we’re entangled by haunting lyrics, ethereal piano, and the tie-dye caramel swirl of our own voices, and then it’s all fading too quickly, a memory we share and hold dearly, like rose-lipt maidens, light foot lads, and the dawning of the age of the Internet.

Music triggers associations—intellectual, emotional, social—that tickle our brains with dopamine, transposing joy with inspiration and a sense of community, and that’s what I remember about the birth of the Internet. We were in love with our newborn ability to share ideas and experiences with people all around the world. We helped one another with Telnet, FTP, and Gopher. We discovered recipes for Russian pelmeni. We built digital libraries for philosophy, beer, nanotechnology, and social justice. We were exhilarated by co-learning and co-creation, and deeply inspired by the potential of this global network to lift us up and bring us together.

Today, it’s easy to get lost in the streams of Facebook and Netflix, but back then it was all about the bridges. In 1934, Paul Otlet envisioned a scholar’s workstation that turned millions of 3 x 5 index cards into a web of knowledge by using a new kind of relationship known as the “Link.”

In 1945, Vannevar Bush imagined the memex, a machine that enabled its users to share an associative “web of trails.” In the early 60s, Ted Nelson coined “hypertext” and set out to build Xanadu, a non-sequential writing system with visible, clickable, unbreakable, bi-directional hyperlinks.

Figure 3-1— Ted Nelson’s Xanalogical Structure
Ted Nelson’s Xanalogical Structure

In 1968, Doug Englebart “real-ized” these dreams by showing hypertext (and most elements of modern computing) in “the mother of all demos.” Through the 70s and 80s, dozens of protocols and networks were made and merged, and in 1991, Tim Berners-Lee launched the World Wide Web as a public service on the Internet. The rest, as everyone knows, is history.

It’s hard to argue with the success of the Internet since, and yet it’s worth reflecting upon what was lost in the translation from idea to implementation. Ted Nelson did just that in 2013 in a tearful eulogy for his old friend, Doug Englebart. It opens with a pledge, “I for one carry on his work by keeping the links outside the file, as he did.” The inclusion of this technical reference in a eulogy shows the depth of commitment of both men to an unrealized ideal. In all the dreams of hypertext, from Otlet and Bush to Nelson and Englebart, users were able to build and explore shared trails, but that’s not the realized model. In HTML, authors create one-way links inside the file. This simple, modular approach helped the Web to spread like wildfire, yet it also ruled out core features of earlier visions.

Ted Nelson imagined a vertically integrated system that managed everything from code and interface to copyright and micropayment. Xanadu’s transpointing windows would support bi-directional links, transclusion, and side-by-side comparison. It would elevate the work of scholars and advance Doug Englebart’s dream to augment human intellect, so we might understand and resolve the world’s seemingly insoluble problems. In the eulogy, Ted Nelson makes clear the heights of their ambition and their depth of disappointment.

I used to have a high view of human potential. But no one ever had such a soaring view of human potential as Douglas Carl Engelbart—and he gave us wings to soar with him, though his mind flew on ahead, where few could see… And here we twiddle in a world of computer glitz, as the winds rise, and the seas rise, and the debts rise, and the terrorists rise, and the nukes tick.

Now I appreciate Ted’s perspective, and I find his honesty refreshing, but I choose the confusion of hope over the clarity of despair. I don’t see the success of Steve Krug’s Don’t Make Me Think as a condemnation of human nature. The simple solution won because most people are too busy thinking to think about interface design and information structure. We’re not too lazy to play Englebart’s violin but are simply preoccupied with our own ways of making music. And while civilization may be headed for collapse, it’s not too late for course correction. That’s why I care about the Web. It’s not only a mirror but a lever as well. And while today’s Web is more terrible than ever imagined, it’s also more amazing.

Ted Nelson invokes our past sense of possibility and asks us to imagine the Web that might have been if only we’d traveled a different road. It’s not a bad way to spend time, but only if we dedicate ourselves to the divergent, forking paths ahead, because it’s what we do next that makes all the difference.


The core feature of the Web is the link. Likes and keywords are important too, but social and search at scale would fail without links. It’s the links that make a web, yet we spend our time on interfaces, designing the surface without analyzing the structure. This is a shame. The richness and diversity of link types is rising, but to benefit we must pay attention.

Initially, we fixed on navigation, and our maps and paths remain vital for mobile and cross-channel design. We use links to forge paths for users. They serve as transparent tools for people who are too busy doing something to pay attention to what they’re doing. The link is like a pencil or a hammer. In the words of Martin Heidegger, each tool is invisible, implicit, and ready-to-hand. But users do get stuck, so we use links to make maps as well. Our menus and taxonomies are visible, explicit, and present-at-hand. They demand our attention in return for understanding. This is almost always not a bad deal.

Figure 3-2— We use links to make maps and paths.
We use links to make maps and paths.

Since recognition is easier than recall, search is no substitute for words on the screen. As Marcia Bates illustrated long ago, the process of seeking is iterative and interactive, more berrypicking than math. What we find and learn changes how and where we look and who and what we seek. To information foragers who satisfice in patchy environments, words are the signs and scent. Words as links invite choice and inspire confidence, letting us know we’re on the right path. As we may think, the map is the territory, and the paths and places we build with links are physically real.

Search increases precision at the expense of serendipity. It also reminds us that navigation isn’t the sole lens for links. In the eyes of Google, links are votes. In the aggregate, they reveal structures invisible except at scale. Of course, links take us outside the frame of findability. Is the link useful, usable, accessible, credible, and desirable? Must it be blue or might it be better as a button? How about an icon with hover text, or a full-blown mega-menu? And what about mobile? Code, content, design, and brand offer diverse ways to understand that a link affords more than a click.

While one-way is the norm, our systems host many link types. Links open tabs, windows, media players; make phone calls, run queries, launch apps. While trackbacks aren’t mainstream, we use analytics and referrer logs to monitor backlinks. We want to know who links to us. On Kindle, popular highlights become shared links, revealing the passages we respond to the most. In tweets, #hashtags aren’t only links but categories and comments as well. User names are bi-directional. Maybe that’s why @TheTedNelson is on Twitter.

Figure 3-3— N-directional links on Twitter
N-directional links on Twitter.

If you look deeper, you’ll see triples—subject, predicate, object—defining semantic relations as precisely as possible. In ontological experiments, domain-specific models of entities, relationships, and attributes push the limits of information visualization and knowledge discovery. We’re on the verge of teaching systems to make links that uncover new questions.

Figure 3-4— The Semantic Web is built on triples.
The Semantic Web is built on triples.

Of course, links aren’t limited to digital networks. A book affords random access with its index and citations. A park links places with signs, paths, and bridges. And, off course, we may need a table of contents or a map or a metaphor, so we might know where we can go from where we are. As Richard Saul Wurman says “we only understand something relative to something we already understand,” and this only grows more important as we orchestrate cross-channel services. In shops, barcodes and URLs serve as links to product details and the endless aisle. In airports, mobile phones let us check in, swap seats, find gates, and make connections we’d never have made before. The rollout of cross-channel services is fast and near invisible, so we need paths and maps to help us see what’s possible. As Andy Polaine suggests in Service Design, the space-time “in between” deserves more of our attention.

It is much easier to focus design effort on the boxes because they represent tangible touchpoints—the website, the ticket machine, and so on—but most people forget to think about designing the experience of the arrows, which are the transitions from one touchpoint to the next.

Links afford movement in space and time and help us make what we can barely imagine. In augmented reality with a heads-up display, places are links to people, content, and services. We must be careful where we step. And in the Internet of Things, objects are links to their own stories, spime that may change culture by absorbing externality. The service evidence of folded toilet paper is but a sign of things to come.

As discrete products shift into service ecosystems, our information shadows grow, and so do complexity and confusion. We will need the limits of paths, the myths of maps, and the serendipity of ourselves to make sense. We will also need a remembrance of things past, from transclusion to transpointing windows, since meaning is lost in translation, and memory isn’t nearly as reliable as seeing connections side by side. In the futures of user experience and service design, the architecture of cross-channel links is critical. The boxes still matter, but it’s the arrows that amplify their consequence.


The business theorist Karl Weick tells managers to shift from nouns to verbs, from organization to organizing. We’d do well to heed his words. As information architects, we must marry our passion for structure and semantics with an appreciation for the causal arrows of time. We might begin by dusting off old diagrams, asking what each map is made to show and hide. For instance, a process flow makes it look simple, defining major actions and decisions as steps, but the linearity may be deceptive, its purpose to hide politics and mess.

Figure 3-5— A flow diagram shows tasks and decisions as steps.
A flow diagram shows tasks and decisions as steps.

A Gantt chart gets us on schedule, making deadlines and dependencies our aim. It shows concurrency nicely, but quality may go down the drain.

Figure 3-6— A Gantt chart shows deadlines and dependencies.
A Gantt chart shows deadlines and dependencies.

When we’re ready to dig deeper, the “fishbone diagram” can facilitate root cause analysis. To begin, we define the problem and its major causal categories, then brainstorm the branching sub-causes by asking five why’s. Fishboning helps us to improve quality and understand cause-and-effect, but it rarely tells us precisely where to fish or swim next.

Figure 3-7— A fishbone diagram shows cause and effect.
A fishbone diagram shows cause and effect.

The stock-and-flow gets us thinking about the inputs, outputs, loops, limits, and delays behind oscillation, equilibrium, and resilience. It’s useful for prediction and analysis, to see where systems may go wrong, but it’s too complex for most folks and vulnerable to the black swan.

Figure 3-8— A stock-and-flow shows controls and context.
A stock-and-flow shows controls and context.

Each diagram is useful, but all maps are traps; that’s why we need more than one. By mixing models we paint a picture that helps us see the truth. We’ve done this with spatial maps, but it’s time to tackle time. Business is stuck at the surface. Managers pretend measurement is simple and clear: set goals, track progress, reward success. But that’s not how it works. The loops that bind goals, process, and metrics are very tricky.

The story of how we work and what we count is told by the faults in our products and the seams in our services. Today’s shallow, siloed analytics will not stand. Of course we should measure clicks and conversions, but fixation on feedback loops that are easy to see is reminiscent of the drunk seeking his car keys under the streetlight. What’s lost in the chatter about KPIs (key performance indicators) and OKRs (objectives and key results) is the value of insight and synthesis. Should we survey customer satisfaction and loyalty? Absolutely! Can the practice of making public commitments to ambitious, measurable goals boost motivation and performance? Yes!

But we must be wary of reductionism and recidivism. Our numbers tell us what but not why; they calculate the future as the sum of its past; and shape how we think and what we do more than we know. Once a metric is defined, it’s hard to ignore. If we use conversions as a metric, satisfaction and loyalty may suffer. When we commit in public to a goal, we’re less likely to pivot. It’s our conversations about the numbers that count. Right action follows the whole of what and why.

Peter Drucker, the legendary management consultant, is credited with the maxim “if you can’t measure it, you can’t manage it,” but he was far too wise to say that. The truth is self-evident in his advice to an executive.

Your first role…is the personal one. It is the relationship with people, the development of mutual confidence, the identification of people, the creation of a community. This is something only you can do. It cannot be measured or easily defined. But it is not only a key function. It is one only you can perform.

These are the questions we must ask. What’s important but can’t be measured? Is it being ignored? What’s the something only you can do that’s not being done right now? Is it time for you to act? I’m hopeful we will make connections that make a difference by shining our light into the darkness beyond the streetlamp. To sketch links and loops out of thin air is to make the invisible visible. It’s a power we must use responsibly, since the lines we draw are harder to erase than we may think.

Our interventions in complex systems beg for humor and humility. We are all butterflies, flapping our wings, no idea of the chaos we cause. In physics and ecology, complexity limits prediction, and that’s without the multiplier of mankind. Our plans are not only subject to butterflies but to the cobra effect as well. In colonial India, the British government tried to reduce the number of venomous snakes in Delhi by paying cash for dead cobras. It worked for a while until people began breeding cobras, then the government killed the bounty, and breeders set their snakes free. Our actions may achieve the opposite of our goals especially when humans are involved. Pads and helmets made football a more dangerous sport. Censorship generates enormous publicity. Iatrogenics, adverse effects from medical treatment and advice, is the third leading cause of death in the United States; a visit to your doctor may kill you. Of course, perverse incentives are partly to blame, but it’s messier than that. People are hard to predict. We make mistakes. We’re bad with numbers. We’re surprisingly irrational. And we imitate each other, so ideas and behaviors, good and bad, spread like wildfire. In short, people make complex systems even more weird and unpredictable.

Years ago, I redesigned the information architecture for a philanthropy. Stakeholder interviews confirmed the main goal of the website was to help aspiring grantees apply for funding. User research suggested that grant seekers were frustrated that critical data about opportunities and deadlines was scattered around the site. I had an idea to create one new page with a simple table to show “what’s open when” across all the program areas of the foundation. This Apply for a Grant page was a big hit with users, becoming the second most visited node after the home page. However, not long after launch, the Board of Trustees noticed the table, and they were shocked by the number of programs that were not accepting applications.

This made waves in the organization. There was talk of removing the page. Then a few programs changed status from closed to open, suggesting that the tail might wag the dog. Then I heard that wasn’t true. Those programs weren’t truly open. Fortunately this didn’t last long, and transparency won the day. The philanthropy clarified itself, explaining that its strategic approach to funding obviates the need for unsolicited applications in several areas. Managers already know who’s who in their community. They invite applications, advance collaborations, and make investments accordingly.

Figure 3-9— Information changes organizations.
Information changes organizations.

The ripples made by this pebble were fascinating. A modest change to the information architecture brought strategy and culture into question. I’m pleased by the introspection it led to, but I can’t take credit as it wasn’t my goal. Surprises in life are more common than most of us care to admit.

One reason we make mistakes is known as the problem of induction. We spend our lives trying to see the future using our knowledge of the past. We draw general conclusions by observing specific events. Induction is the root of how we know what we know, and it works surprisingly well, until as Nassim Taleb explains, we find we’re the turkey, not the swan.

Consider a turkey that is fed every day. Every single feeding will firm up the bird’s belief that it is the general rule of life to be fed every day by friendly members of the human race “looking out for its best interests,” as a politician would say. On the afternoon of the Wednesday before Thanksgiving, something unexpected will happen to the turkey. It will incur a revision of belief.

This reminds me of the J. C. Penney link spamming scandal. The retailer hired a search marketing firm to improve its ranking in Google; and they got great results. Month after month JCP was the top search result for such queries as “samsonite carry on luggage” and “little black dress.” Executives were happy and well fed until the New York Times exposed the black hat campaign behind their results, Google banished them, and they discovered they were the turkeys.

Years later, JCP still fails to make Google’s first page except by paying for ads. Relying on results from a black box is foolish. Don’t trust that it works. Ask why. When we understand, we increase our ability to manage events. We can change tactics or plan a response. But we can never fully escape the limits of induction. That’s the moral of the story of the lucky farmer.

One day the farmer’s horse ran away. His neighbors cried “such bad luck” to which he replied “maybe.” His horse returned the next day with three wild horses. His neighbors shouted “that’s wonderful” and the old farmer replied “maybe.” The next day his son rode one of the wild horses, fell off, and broke his leg. The neighbors called it a “terrible misfortune.” The old man replied “maybe.” The day after, the army came to the village to draft young men, but the son was spared thanks to his broken leg. The neighbors said the farmer was lucky how things turned out, and the old man answered “maybe.”

It’s impossible to predict the future, yet we do it all the time. We nod at the wisdom of the Zen farmer, then proceed with business as usual. We make plans, take steps, and get angry when things go awry. Awareness isn’t ambivalence. We care about outcomes, and to some degree we are in control. Prediction helps us to see the future in more ways than one.

Prediction is so pervasive that what we “perceive”—that is, how the world appears to us—does not come solely from our senses. What we perceive is a combination of what we sense and our brains’ memory-derived predictions.

As Jeff Hawkins explains, the simple act of opening a door is built on prediction. Memory enables us to open our front door without thinking. We predict what will occur when we turn the knob and push. If the door is stuck and our prediction proves wrong, then our attention turns on, and we start asking questions. Much of what we “see” is based on what we expect. As the neuroscientist V.S. Ramachandran explains:

There are at least as many fibers (actually many more!) coming back from each stage of processing to an earlier stage as there are fibers going forward…The classical notion of vision as a stage-by-stage sequential analysis of the image, with increasing sophistication as you go along, is demolished by the existence of so much feedback.

This explains our susceptibility to optical illusions and the fallibility of eyewitness testimony. The truth lies in between “seeing is believing” and “believing is seeing” and this prediction isn’t only about eyesight.

Figure 3-10— In vision, there’s more feedback than input.
In vision, there’s more feedback than input.

Music, management, and imagination are all about prediction. A song tickles us by surprise, managers count on cause and effect, and we dream in folded feedback, exploring the consequences of our own predictions. Anticipation is behind all we think and do. In the words of Jeff Hawkins, “Prediction is not just one of the things your brain does. It is the primary function of the neocortex and the foundation of intelligence.”

It’s impossible not to predict the future, yet we get it wrong all the time. We use our “theory of mind” to anticipate the actions and reactions of colleagues and customers, but people are full of surprises. Experiments help, but induction has its limits. Even minimum viable products can’t predict the long now at scale. Inevitably we must move forward, often at a fast clip, but it pays to be aware of error even as we race along. Often our mistakes are small, obvious, and easy to fix. It’s the big ones we must look out for. They’re not only hard to correct but amazingly hard to see. Chris Argyris, a pioneer in organizational learning, had it right when he advocated double-loop learning, a concept he introduces by analogy.

A thermostat that automatically turns on the heat whenever the temperature in a room drops below 68 degrees is a good example of single-loop learning. A thermostat that could ask, “Why am I set at 68 degrees?” and then explore whether or not some other temperature might more economically achieve the goal of heating the room would be engaging in double-loop learning.

Of course, double-loop learning in organizations is rare. Defensiveness in cognition and culture makes it hard to question basic beliefs. Successful people and organizations are the worst, as they’ve never learned to learn from failure. Experts and executives alike deny the problem, shift blame, and shut down; and the organization runs efficiently off a cliff. We can get better, but it takes commitment. We must confront the assumptions behind our ideas. We must surface conflicting opinions and recast them as hypotheses to be tested in public. And we must be willing to critique and change our goals, values, frameworks, policies, and strategies.

Figure 3-11— The two loops of double-loop learning
The two loops of double-loop learning

In short, we must go deep, breaking the icy surface in search of the truth. This reminds me of Robert Frost’s The Road Not Taken, a poem I’ve loved since high school, and a source of inspiration in my decision two decades past to take the road less traveled by becoming an information architect. Of course, the joke’s on me. A few years ago, while helping our daughter with homework, I searched for “road not taken meaning” and found “in leaves no step had trodden black,” I’d been wrong all that time. No road is less trodden, and that truth is revealed with a sigh. Frost dropped hints and warned us explicitly.

You have to be careful of that one; it’s a tricky poem—very tricky.

But, inspired by his words, we missed his meaning. We chose our roads less traveled, knowing that made all the difference. One can only imagine the unintended consequences of this mass misinterpretation. As for me, I love it all the more as the poem about forks that took me for two loops.


In 1941, Jorge Luis Borges, a blind Argentine librarian, wrote an amazing story, The Garden of Forking Paths, about a book and a labyrinth containing “an infinite series of times, a growing, dizzying web of divergent, convergent, and parallel times…all possibilities.” This use of analogy to connect the forks of space and time is poetic, irresistible, and recursive.

In 1991, Herbert Simon, the polymath pioneer of artificial intelligence and decision theory, wrote “I have encountered many branches in the maze of my life’s path, where I have followed now the left fork, now the right. The metaphor of the maze is irresistible to someone who has devoted his scientific career to understanding human choice.”

It’s a powerful metaphor, but all maps are traps. While divergent paths may seem obvious in hindsight, they aren’t easy to see in advance. All of our decisions are made without a complete understanding of the options and consequences; not that we don’t try. Our brains routinely imagine choices and outcomes, and when the possibilities are too fuzzy, we stall.

We muddle around in a state of productive procrastination, and while muddling can be hard to defend, it’s precisely the right thing to do. We must buy time to find our way, because the relationships between choice, action, and cognition are far messier than we like to admit; and once we step from the handle to the tine, there’s no going back. Perhaps the utensil that affords the wisest decisions isn’t a fork but a spork.

Figure 3-12— Choose your fork carefully.
Choose your fork carefully.

Nobody understands the trickiness of decisions better than Karl Weick, but in explaining his perspective, it’s hard to know where to begin. Like E.M. Forster, Weick invites us to consider the effect of action on cognition by asking “how can I know what I think till I see what I say?” He argues that retrospective sensemaking is more common than we know. We act first, then rationalize our aim, but prediction is part of it too. In organizations, the basic unit of sensemaking is the double interact. An interact exists when an act by Person A evokes a response by Person B. A double loop is created by A’s reaction to B’s response. This is how meaning is made.

Figure 3-13— A double interact loop
A double interact loop

The first act is shaped by models we’ve built to make sense of the past. In Weick’s words, our thoughts are “real-ized” as self-fulfilling prophecies.

I mean literally that people make real, or turn into a reality, those ideas that they have in their heads. It is that sense in which the phrase “believing is seeing” is more than a play on words.

But, after that initial action, our sensemaking is complicated by commitment.

When people take actions that are visible (the act clearly occurred), irrevocable (the act cannot be undone), and volitional (the act is the responsibility of the person who did it), they often feel pressure to justify those actions, especially if their self-esteem is shaky…thus, commitment, like metaphor, can be an enemy of wisdom. Both of them minimize doubt and doubting.

I’m reminded of a comment by Scott McNealy, the outspoken co-founder of Sun Microsystems and its CEO for 22 years. After a lecture at Stanford, when asked how he made decisions, he responded by saying in effect “It’s important to make good decisions. But I spend much less time and energy worrying about making the right decision and more time and energy ensuring that any decision I make turns out right.”

There’s insight in those words but danger too. Wisdom requires a balance between confidence and caution. Sun failed to see the shift from hardware to software and was acquired by Oracle. For double loop learning, we must first admit error, something Bill Gates does well. After the Gates Foundation spent $2 billion to replace large schools with small ones and realized only modest gains, Gates publicly concluded they’d made an expensive mistake, and decided to switch direction.

In Mistakes Were Made (But Not By Me), we’re reminded such honest admissions are refreshing because they’re so rare. The main problem isn’t that we aim to deceive others; it’s that we fool ourselves. The engine of self-justification is cognitive dissonance, the state of tension that occurs when we hold ideas or beliefs that are psychologically inconsistent. If a “good person” does a “bad thing” self-deception kicks in. And, if on opposite sides of a decision, time will tear us apart.

Imagine two students with similar attitudes and abilities who struggle with the temptation to cheat on a test. One yields and the other resists. How do they feel about cheating a week later? The first tells herself it’s no big deal, whereas the second decides it’s totally immoral. In time the two slide further apart, until the cheater and do-gooder can’t stand each other. They began together but were polarized by the pyramid of choice.

Figure 3-14— Separated by self-justification
Separated by self-justification

Retrospective sensemaking is an invisible yet powerful force in our lives. As Karl Weick suggests, when what precedes why, it’s

People need to be less casual about action since whatever they do has the potential to bind them and focus their sensemaking.

That’s why we must make time and space to explore before we act. As Dave Gray explains, in knowledge work our goals are fuzzy, creativity is vital, and the path to success is not a straight line. In Gamestorming, he presents the shape of innovation in three acts. Act one is divergent. We open minds and expand options with optimism and freedom. Act two is emergent. We explore by seeking patterns, testing prototypes, and trusting serendipity. Act three is convergent. We employ synthesis and evaluation to come together and make a decision. Dave sketches this process—open, explore, close—as a stubby pencil sharpened at both ends, but in my mind it’s a spork with space-time between the handle and tine.

Figure 3-15— The spork of innovation
The spork of innovation

Either way, there are three acts before the act that commits. It’s okay if the iffiness is visible. Agile and Beta made it safe to experiment in public. The thing to be aware of is irrevocable, a word that means you can’t go back. In Antifragile, Nassim Taleb promotes “optionality” as a way to benefit from the positive side of uncertainty. It’s best to keep our options open, since information and intelligence are often no match for wait and see. Anyone who’s watched House has seen applied optionality in the sequence of symptom-treatment-diagnosis; it’s a strategy Karl Weick prescribes.

When physicians make a formal diagnosis under time pressure, their rush to label the disease, begin treatment, and achieve closure leads them to overlook and then forget symptoms that don’t fit the diagnosis. This encourages more confidence than may be warranted…A hunch held lightly (that is, without commitment) is a direction to be followed, not a decision to be defended.

The act of labeling merits attention in all the work we do. Like maps, words are traps. We must speak carefully since we think what we say. The order of operations makes a difference; that’s why process is key. Recently, I worked on a prototyping project in which we purposefully created wireframes and design comps in parallel. In weekly reviews, we’d flip back and forth, at times asking questions we’d already asked.

Interestingly, the answers sometimes changed. When I first suggested we merge Save Search and Save/Share Results, our client defended their existence as separate features. But a week later, we revisited the same interface, and once again I made the case for convergence. A single Save/Share menu button makes it impossible to choose the wrong option and helps users to learn about related features. And this time our client agreed. I’d had time to clarify my argument. Our client had time to get used to the idea. Also, it was a less hectic meeting, and the group was receptive to change. This collaboration took time and was messy. We’d pick a road in the fork only to loop back around. But this process improved quality enormously. By creating a safe space-time in which actions and decisions aren’t binding, we defused self-justification for a while.

Of course, we often lack the luxury of space-time. This limits collaboration and the scientific method. When thorny questions arise, folks love to suggest A/B testing. Sometimes that’s a great idea, but often the complexity and connectedness of the system make it unfeasible. It’s difficult to isolate variables, and we can’t always judge long term efficacy based upon the initial response. Users adapt to change over time. Also, creating dual designs that integrate into the whole takes a lot of effort. Eric Raymond argues that forking is a taboo of open source culture and almost never happens.

There is strong social pressure against forking projects. It does not happen except under plea of dire necessity, with much public self-justification, and with a renaming.

The right to fork is an important freedom of open source, but it’s also a last resort. Both child projects have fewer designers and developers; and once done, it’s impossible to undo. While it’s pretty to think so, we truly can’t explore parallel universes. It’s simply not possible to put all your energy and resources into both sides of an A/B test. In reality, we often must satisfice with imperfect information. This is where strategy can help.

To outsiders, a company’s actions and acquisitions can appear chaotic, but behind the scenes it may all make sense. For instance, Walt Disney built a sprawling empire, but each asset fit strategically in his map. He knew how the parts made a whole and never made decisions in the dark.

Figure 3-16— Walt Disney’s Theory of the Firm
Walt Disney’s Theory of the Firm

There’s a similar story behind Southwest Airlines. It began as a triangle on the back of a napkin with direct routes between Dallas, San Antonio, and Houston. But the simple plan to ditch hub-and-spoke soon evolved into a textbook case of what Michael Porter calls strategic fit.

Figure 3-17— The “Fit” for Southwest Airlines
The “Fit” for Southwest Airlines

First, there’s simple consistency between each activity and the overall strategy. Second, the activities are reinforcing. Third, the system allows for an optimization of effort that makes the whole greater than the sum of its parts. Fit’s hard to decipher without a key, so competitors can’t copy, and we’re more likely to enjoy sustainable competitive advantage. Plus, once we’ve done the synthesis needed to make the map, decisions are easier. We know why and where each part belongs, and we’re able to balance local maxima with optimization of the whole. Dig deep into any successful organization, and you’ll find the fingerprints of a leader who understands the art of connection; it’s built into every link, loop and fork.


The oldest known musical instruments, flutes made of bird bone and mammoth ivory, are roughly 40,000 years old, but our tribal ancestors were singing, whistling, and tapping their hairy toes long before that. Music isn’t apart from us but a part of us. Its cross-modal power to trigger social, emotional, and intellectual associations isn’t incidental. From beat to lyrics, music, poetry, and metaphor have played instrumental roles in the co-evolution of our mind-body-environment. In The Tell-Tale Brain, V. S. Ramachandran connects the dots between creativity, synesthesia, and the architecture of the brain.

In biological systems, there is a deep unity between structure, function, and origin. You cannot make very much progress understanding any one of these unless you are also paying close attention to the other two.

I recall learning my mum sees letters, numbers, and words in color. B is dark blue. 7 is pale green. Monday is cream yellow. We all had a laugh at her craziness. Years later, we discovered she had a rare neurological disorder known as synesthesia. To some synesthetes, the touch of denim is sadness; for others, C-sharp on a piano is blue. She was still crazy, but she wasn’t alone. Then synesthesia became popular. Studies revealed cross-sensory perception to be surprisingly common among artists, poets, and musicians. Suddenly, everyone and their mother was a synesthete. And, according to Ramachandran, that’s not far from the truth. We are all on the synesthesia spectrum. The neural linking of color and emotion is an evolutionary adaptation for finding ripe berries, and our proclivity for synesthesia is an exaptation layered on top of that. “The angular gyrus may have originally evolved for mediating cross-sensory associations and abstractions but then, in humans, was co-opted for making all kinds of associations, including metaphorical ones.”

The ability to use analogy is the root of creativity, and like the future, it’s unevenly distributed. We all see the road not taken isn’t really about a road, but its meaning is missed by many, and its artistry is the domain of the few. We will invent the Web ahead by making cross-modal connections in our mind-body-environment. That’s what we all missed in our original vision in a dream of Xanadu. To augment human intellect isn’t enough. Action, emotion, and perception are part of it too.

Hypertext is a place to start, but one-dimensional links are a trap. To escape flatland, we must expand awareness. As information architects, we must identify and use invisible connections in space and time. To build places made of information is exciting, but it’s not the point. We must also rise to the challenge as architects of individual, organizational, and environmental synesthesia. We must make links, loops, and forks into levers for positive change. Cross-channel isn’t enough. The systems of the future are cross-sensory. It’s time to design and experience new forms of connectedness.

There’s a reason systems thinking isn’t popular. It’s too hard. In place of understanding, most folks rely on culture, which not only tells us which road to take, but also that it made all the difference. Culture is a powerful, hidden force, highly resistant to change. That’s why, to make systems better, we must start by mapping culture. It’s hard to see, but it’s not invisible. If we look beneath the surface, we see that like art, music and all the webs we weave, culture is a reflection of ourselves and our unquenchable thirst for connection. 

President, Semantic Studios

Ann Arbor, Michigan, USA

Peter MorvillePeter is a pioneer in the fields of information architecture and user experience. He is best known for being an author of the polar bear book on information architecture—Information Architecture for the World Wide Web. Other books by Peter include Ambient Findability, Search Patterns, and Intertwingled. His latest book, Planning for Everything, is about the design of paths and goals. Peter has been helping people to plan since 1994. His clients include AT&T, eBay, Harvard, IBM, the Library of Congress, Microsoft, the National Cancer Institute, and Vodafone.  Read More

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