Dave Gray talks about Gamestorming at UX Week in San Francisco

Posted: November 21st, 2010 | Added by: | Filed under: The Knowledge Economy | 3 comments »

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Dave Gray’s Knowledge Games talk from the Interaction 10 conference

Posted: March 2nd, 2010 | Added by: | Filed under: The Knowledge Economy | 2 comments »

Dave Gray-Knowledge Games: A Grammar for Creativity and Innovation from Interaction Design Association on Vimeo.

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Why knowledge games work

Posted: December 7th, 2009 | Added by: | Filed under: The Knowledge Economy | 7 comments »

Information-vs.-Transformation

The way humans gain the lion’s share of what we know is through a slow process of gathering informational knowledge – accumulated layers of additive information based on years of exposure and experience. For example, my knowledge of Spanish is informational knowledge. I learned it through years of listening to Spanish speakers and eventually formalized it by taking multiple semesters at university, building up bits of knowledge to get a fairly complete understanding of the language. And along this learning path, I had an anticipated outcome – fluency. I would eventually know enough verbs, conjugations, vocabulary, etc. to present myself as a Spanish speaker. But nowhere along that learning curve did I create something rather than just accumulate it. Spanish was already there; it was just a matter of me methodically crawling through it, adding to my increasingly large pile of information.

And this is how most of us approach problem-solving – by applying informational knowledge. We think of a problem (or perhaps create one!), get a sense of its magnitude, reference relevant information we know and then apply it as a solution. And there are many situations in which this is a perfectly appropriate plan of attack: you see someone choking in a restaurant, you hurriedly scan your knowledge from the past, you perform the Heimlich. Brilliant. But the shadow side to this type of problem solving is that it confines you to the boundaries of the smaller pieces of the pie chart above – the realm of what you know and the realm of what you know that you don’t know. So if you know the Heimlich (even half-assed), you try it. And if you know that you don’t know the Heimlich, you’re likely going to seek out someone who does and ask them to solve the problem. But it’s highly unlikely that you’re going to spontaneously invent a new move and liberate a choking gentleman from his hambone. That’s just not the way informational knowledge works. And if you impress yourself by actually inventing a new anti-choking technique, well, surprise. You’ve just entered the realm of transformational knowledge.

Transformational knowledge is knowledge that can seem to appear out of the ether. It emerges almost as a flash – a eureka moment – and appears most often when we’re either under duress or in a child-like state of learning.  But since most of us eschew being “child-like” – we do take ourselves rather seriously – rarely do we get access to the biggest piece of the pie chart. We spend almost all of our time vacillating between the two dinky realms of either ‘what we know’ or ‘what we know that we don’t know.’  So it’s not shocking that when we’re tackling problems – business or personal – we find our way to the same results. How innovative can we really be when we’re treading and retreading the same ground? But don’t misunderstand; we’re not at fault – we can hardly be held responsible for what we don’t know that we don’t know. But we can be responsible for actively trying to get access to that space. To that big, mysterious piece of the pie that’s hoarding almost all of the creative solutions.

Knowledge games, as set forth in our book, are powerful because they’re designed to help us move out of the familiar and predictable and into the uncertain and unknown – where creation actually lives. We’re including games and meeting processes in which the rules aren’t rigid, you can veer away from a directed outcome and you’ll often be surprised at how it all turns out. We’re giving you tools to create, not repackage. And this is important because, as Einstein understood, “Problems cannot be solved by the same level of thinking that created them.”

Eureka.

Note: This post was inspired by Landmark Education, a forum that applies the notions of informational vs. transformational knowledge in the areas of human consciousness and performance.
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What is a knowledge game?

Posted: December 2nd, 2009 | Added by: | Filed under: The Knowledge Economy | 22 comments »

What is a knowledge game?, originally uploaded by dgray_xplane.

Games and play are not the same thing.

Imagine a boy playing with a ball. He kicks the ball against a wall, and the ball bounces back to him. He stops the ball with his foot, and kicks the ball again. By engaging in this kind of play, the boy learns to associate certain movements of his body with the movements of the ball in space. We could call this associative play.

Now imagine that the boy is waiting for a friend. The friend appears, and the two boys begin to walk down a sidewalk together, kicking the ball back and forth as they go. Now the play has gained a social dimension; one boy’s actions suggest a response, and vice versa. You could think of this form of play as a kind of improvised conversation, where the two boys engage each other using the ball as a medium. This kind of play has no clear beginning or end: rather, it flows seamlessly from one state into another. We could call this streaming play.

Now imagine that the boys come to a small park, and that they become bored simply kicking the ball back and forth. One boy says to the other, “Let’s take turns trying to hit that tree. You have to kick the ball from behind this line.” The boy draws a line by dragging his heel through the dirt. “We’ll take turns kicking the ball. Each time you hit the tree you get a point. First one to five wins.” The other boy agrees and they begin to play. Now the play has become a game; a fundamentally different kind of play.

What makes a game different? We can break down this very simple game into some basic components that separate it from other kinds of play.

Game space: To enter into a game is to enter another kind of space, where the rules of ordinary life are temporarily suspended and replaced with the rules of the game space. In effect, a game creates an alternative world, a model world. To enter a game space, the players must agree to abide by the rules of that space, and they must enter willingly. It’s not a game if people are forced to play. This agreement among the players to temporarily suspend reality creates a safe place where the players can engage in behavior that might be risky, uncomfortable or even rude in their normal lives. By agreeing to a set of rules (stay behind the line, take turns kicking the ball, and so on), the two boys enter a shared world. Without that agreement the game would not be possible.

Boundaries: A game has boundaries in time and space. There is a time when a game begins – when the players enter the game space – and a time when they leave the game space, ending the game. The game space can be paused or activated by agreement of the players. We can imagine that the players agree to pause the game for lunch, or so one of them can go to the bathroom. The game will usually have a spatial boundary, outside of which the rules do not apply. Imagine, for example, that spectators gather to observe the kicking contest. It’s easy to see that they could not insert themselves between a player and the tree, or distract the players, without spoiling, or at least, changing, the game.

Rules for interaction: Within the game space, players agree to abide by rules that define the way the game-world operates. The game rules define the constraints of the game space, just as physical laws, like gravity, constrain the real world. According to the rules of the game world, a boy could no more kick the ball from the wrong side of the line than he could make a ball fall up. Of course he could do this, but not without violating the game space – something we call “cheating.”

Artifacts: Most games employ physical artifacts; objects that hold information about the game, either intrinsically or in their position. The ball and the tree in our game are such objects. When the ball hits the tree a point is scored. That’s information. Artifacts can be used to track progress and maintain a picture of the game’s current state. We can easily imagine, for example, that as each point is scored the boys place a stone on the ground, to help them keep track of the score – another kind of information artifact. The players are also artifacts in the sense that their position can hold information about the state of a game. Compare the position of players on a sporting field to the pieces on a chess board.

Goal: Players must have a way to know when the game is over; an end state that they are all striving to attain, that is understood and agreed to by all players. Sometimes a game can be timed, as in many sports, such as football. In our case, a goal is met every time a player hits the tree with the ball, and the game ends when the first player reaches five points.

We can find these familiar elements in any game, whether it be chess, tennis, poker or ring-around-the rosie. On reflection, you will see that every game is a world which evolves in stages, as follows: Imagine the world, create the world, enter the world, explore the world, leave the world.

THE EVOLUTION OF THE GAME WORLD

1. Imagine the world. Before the game can begin you must imagine a possible world. The world is a temporary space, within which players can explore any set of ideas or possibilities.

2. Create the world. A game world is formed by giving it boundaries, rules, and artifacts. Boundaries are the spatial and temporal boundaries of the world; its beginning and end, and its edges; Rules are the laws that govern the world; and artifacts are the things that populate the world.

3. Enter the world. A game world can only be entered by agreement among the players. To agree, they must understand the game’s boundaries, rules and artifacts; what they represent, how they operate, and so on.

4. Explore the world. Goals are the animating force that drives exploration; they provide a necessary tension between the initial condition of the world and some desired state. Goals can be defined in advance or by the players within the context of the game. Once players have entered the world they can try to realize their goals within the constraints of the game-world’s system. They can interact with artifacts, test ideas, try out various strategies, and adapt to changing conditions as the game progresses, in their drive to achieve their goals.

5. Leave the world. A game is finished when the game’s goals have been met. Although achieving a goal gives the players a sense of gratification and accomplishment, the goal is not really the point of the game so much as a kind of marker to ceremonially close the game space. The point of the game is the play itself, the exploration of an imaginary space that happens during the play, and the insights that come from that exploration.

Imagine the world, create the world, enter the world, explore the world, and leave the world.

A knowledge game is a game-world created specifically to explore and examine business challenges, to improve collaboration, and generate novel insights about the way the world works and what kinds of possibilities we might find there. Game worlds are alternative realities, parallel universes that we can create and explore, limited only by our imagination. A game can be carefully designed in advance, or put together in an instant, with found materials. A game can take 15 minutes or several days to complete. The number of possible games, like the number of possible worlds, is infinite. By imagining, creating and exploring possible worlds, you open the door to breakthrough thinking and real innovation.

We are writing a book about knowledge games. What games are you practicing in your workplace? What kinds of experiences have you had? Please leave a comment and share them with us!

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Fuzzy goals

Posted: October 7th, 2009 | Added by: | Filed under: The Knowledge Economy | 14 comments »

Fuzzy goals, originally uploaded by dgray_xplane.

In industrial work, we want to manage work for consistent, repeatable, predictable results. Industrial goals are best when they are specific and quantifiable.

But in knowledge work we need to manage for creativity – in effect, we don’t want predictability so much as breakthrough ideas, which are inherently unpredictable. For knowledge work we need our goals to be fuzzy. In any creative endeavor, the goal is not to incrementally improve on the past but to generate something new.

New, by definition, means “not seen before.” So if a team wants to truly create, there is simply no way to precisely define the goal in advance, because there are too many unknowns. Embarking on this kind of project is akin to a voyage of discovery: you may begin your journey by searching for a route to India, but you might find something completely different, but even more valuable. At the beginning of such a project, the unknowns outweigh the knowns, and the biggest problem is finding the right questions to ask.

In a paper titled Radical innovation: crossing boundaries with interdisciplinary teams, Cambridge researcher Alan Blackwell and colleagues identified something they called the “pole-star vision” as an essential element of successful innovation. A pole-star vision is one in which the goal “motivates the general direction of their work, without blinding the team to opportunities along the journey.” One leader described his approach as “sideways management.” Important factors identified by the Cambridge research team include the balance between focus and serendipity and coordinating team goals and the goals of individual collaborators.

A fuzzy goal straddles the space between two contradictory criteria: At one end of the spectrum is the clear, specific, quantifiable goal, such as 1,000 units or $1,000. At the other end is the goal that is so vague as to be, in practice, impossible to achieve; for example, peace on earth or a theory of everything. While these kinds of goals may be noble, and even theoretically achievable, they lack sufficient definition to focus the creative activity. Fuzzy goals must give a team a sense of direction and purpose while leaving team members free to follow their intuition.

What is the optimal level of fuzziness? To define a fuzzy goal you need a certain amount of ESP: Fuzzy goals are Emotional, Sensory and Progressive.

Emotional: Fuzzy goals must be aligned with people’s passion and energy for the project. It’s this passion and energy that gives creative projects their momentum, therefore fuzzy goals must have a compelling emotional component.

Sensory: The more tangible you can make a goal, the easier it is to share it with others. Sketches and crude physical models help to bring form to ideas that might otherwise be too vague to grasp. You may be able to visualize the goal itself, or you may be able to visualize an effect of the goal, such as a customer experience. Either way, before a goal can be shared it needs to be made explicit in some way.

Progressive: Fuzzy goals are not static; they change over time. This is because, when you begin to move toward a fuzzy goal, you don’t know what you don’t know. The process of moving toward the goal is also a learning process, sometimes called successive approximation. As the team learns, the goals may change, so it’s important to stop every once in awhile and look around. Fuzzy goals must be adjusted, and sometimes completely changed, based on what you learn as you go.

Innovative teams need to navigate ambiguous, uncertain and often complex information spaces. What is unknown usually far outweighs what is known. In many ways it’s a journey in the fog. The case studies haven’t been written yet and there are no examples of where it’s been done successfully before. Voyages of discovery involve greater risks and more failures along the way than other endeavors. But the rewards are worth it.

I would appreciate your comments.

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The knowledge economy

Posted: September 15th, 2009 | Added by: | Filed under: The Knowledge Economy | 3 comments »

The industries are toppling like dominoes

In a 1936 “thought experiment,” Alan Turing described a hypothetical machine that could perform any calculation. Fifteen years later the first mass-produced computer was delivered to the U.S. Census Bureau. In 1969 the first link on the internet – then called ARPANET – was established, between UCLA and Stanford. In the 1970’s, the introduction of the microprocessor made possible the personal computer. Computing power has approximately doubled every two years since 1960, a trend which continues today and is not expected to change until 2015 or later. Internet traffic is growing at a similar rate, with no signs of diminishing any time soon.

In combination, personal computers and the internet that links them together have transformed society as profoundly as industrialization did.

We’re now in the process of digitizing everything; wrapping our physical world with a digital layer of information which parallels and reflects our own. We want to know everything we can think of about everything we can think of. Our world is awhirl with digital information.

In a digital world, the product or service has no physical substance. There are no distribution costs. A single prototype can generate an infinite number of copies at no cost. And since the products and services are so different, the environment around them becomes unstable; as the digital layer interacts with the physical layer, everything in the ecosystem is up for grabs. Suddenly new products become possible and established ones become obsolete overnight.

The rules of creation and distribution are changing, and it’s driving a massive shift: As the software used to create new products becomes cheaper and easier to use, and as internet distribution models emerge, the barriers that keep individuals and small teams from competing with mega-corporations are melting away.

Industries are falling like dominoes. The first to feel the blow were publishers, with the desktop-publishing revolution of the 80’s, blogging in the 90’s, and now the Kindle and Sony Reader. Second came music, when software like GarageBand gave artists a desktop recording studio and distribution channels like iTunes gave them access to global markets. Next will be film and software, followed soon by physical products. Products, you say? Yes, soon we will see the equivalent of the “Garage band” in product design. It’s already begun. 3-D modeling software is getting cheaper and easier to use all the time. Today, you can take a 3-D computer file and deliver it directly to an overseas factory for production.

As technology gets cheaper and easier to use, and as more things become digitized or have digital reflections on the internet, the power that has traditionally been the exclusive province of large corporations now devolves to the individual or small group. Increasingly, technology is becoming “indistinguishable from magic.”

The trend is toward the small team, or the company of one, where creativity and adaptiveness trump money and resources, which are increasingly becoming commodities, losing the power they once had as barriers to competition.

Hard to believe? The digital revolution is rife with examples. Most of today’s dominant information-driven companies started with little or no startup capital.

The first Apple computers were hand-built in a garage. Microsoft was started by a college dropout. Oracle was started by another college dropout, with $2,000 of his own money. Google and Yahoo were started by college students. EBay was started by a 28-year-old computer programmer on a holiday weekend. Amazon.com was started in a garage. Numerous other successful information-driven companies were started by young people on a nickel. The next wave is already underway with companies like Facebook, started by a college sophomore, now making $500 million a year and growing.

Individuals, working alone, now can design and command workflows that requires massive financial resources only a few years ago. Given enough motivation, an individual with modest resources can now make a feature-length film, publish a hardcover book, start a TV or radio station, outsource manufacturing of sophisticated products, and sell products to a global marketplace.

The bottom line is that success in a knowledge economy requires different thinking, different aptitudes, and a different approach to work. The focus of a knowledge-driven company must be on creativity and systems thinking rather than planning and efficiency.

In a world where manufacturing and distribution are commodities, the only thing that can differentiate a product or service is creativity and customer relationships. This is soft stuff – it’s not quantifiable or easily measured, and it’s not the stuff that business schools are good at teaching. But we need to get start getting good at it.

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