Tag: Innovation

John Holland: The Building Blocks of Innovation

“Most innovation comes from combining well-known, well-established, building blocks in new ways.”

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John Holland, a professor of two vastly different fields—psychology and engineering—at the University of Michigan, frequently lectures on innovative thinking.

According to Holland, there are two steps to innovation. The first step is to try and find the right building blocks—the basic knowledge. Second, is the use of metaphors to relate understanding.

The first step is to try and find the right building blocks—the basic knowledge. Second, is the use of metaphors to relate understanding.

Holland is focused on innovation, but many readers of Farnam Street will recognize the first step—acquiring the building blocks—as the process for acquiring worldly wisdom.

Like us, Holland wants to connect well-known and well-established ideas from multiple disciplines in new ways to solve problems.

In our case, the basic building blocks are the big ideas in each major discipline. While this seems daunting, luckily, according to Charlie Munger, “80 or 90 important models will carry about 90% of the freight in making you a worldly-wise person.”

Domain Dependence and Linking

It’s important that you can link these models together and recognize them outside of the domain they are presented. Many people, for instance, don’t link the supply and demand from economics and equilibrium from physics. Yet in many ways, they are the same thing. If you can’t recognize the forces at play outside of the system in which you learned about them, you are domain-dependent.

In Antifragile, Nassim Taleb writes:

We are all, in a way, similarly handicapped, unable to recognize the same idea when it is presented in a different context. It is as if we are doomed to be deceived by the most superficial part of things, the packaging, the gift wrapping.

If you don’t have a basic understanding of each of the major models, you won’t be able to link them together. And if you can’t link them together, you’re going to go through life like a one-legged man in an ass-kicking contest.

Construction of a Model

According to Holland, “the construction of a mental model … closely resembles the construction of a metaphor:”

  1. There is a source system with an established aura of facts, interpretation and practice.
  2. There is a target system with a collection of observed phenomena that are difficult to interpret or explain.
  3. There is a translation from source to target that suggests a means of transferring inferences for the source into inferences for the target.

Seeing new connections requires models and metaphors. Holland continues:

For most who are heavily engaged in creative activities, be it in literature or the sciences, metaphor and model lie at the center of their activities. In the sciences, both the source and the target are best characterized as systems rather than isolated objects. … In the sciences, decisions about which properties of the source system are central for understanding the target, and which are incidental, are resolved by careful testing against the world. As a result of testing and deduction, a well-established model in the sciences accumulates a complicated aura of technique, interpretation, and consequences, much of it unwritten. One physicist will say to another “this is a conservation of mass problem” and immediately both will have in mind a whole array of knowledge associated with problems modeled in this way.

“The essence of metaphor,” writes Mark Johnson and George Lakoff in their book Metaphors We Live By, “is understanding and experiencing one kind of thing in terms of another.”

Holland posits that metaphors help us translate ideas into models, which form the building blocks of innovative thinking.

“In the same way that a metaphor helps communicate one concept by comparing it to another concept that is widely understood,” Robert Hagstrom writes in Investing: The Last Liberal Art, “using a simple model to describe one idea can help us grasp the complexities of a similar idea. In both cases, we are using one concept (the source) to better understand another (the target). Used this way, metaphors not only express existing ideas, they stimulate new ones.”

Metaphor and Innovation

From the Credit Suisse Thought Leader Forum:

To understand the problems in any discipline, it is necessary to have deep knowledge in that discipline. To resolve those problems, it is often necessary to look at the problem through the filters of a different and often distant discipline. The simplest analogy to the phenomenon is simply perspective. It is very difficult to understand, say, the traffic patterns of a city if you are stuck in your car at rush hour. With the distance provided by a traffic helicopter, however, it is much easier to see the major thoroughfares, the bottlenecks and the overall dynamics of the traffic system. The shift in vantage point offers better understanding and new insights for your strategy. For more abstract challenges, the use of metaphor serves the same purpose as distance in the traffic example. If we are stuck on the challenge of distribution in a global manufacturing company, for example, it may be useful to apply models from other disciplines as metaphors. The model that we have developed and used for our distribution system has been quite effective over the years, but we just cannot seem to resolve some particular challenge. Perhaps we can learn something from other kinds of distribution systems. How does an ant colony collect and distribute its resources? How does the human body manage its circulation and processing of nutrients and wastes?

Three Keys to effectively applying metaphors

There are three keys to effectively applying metaphors to achieve insight and innovation. First, you must develop a deep understanding of the metaphorical system. You will gain no new insights if you look at the human circulatory system and say, “Aha! The brain tells the rest of the body where to send things!” If you draw conclusions too quickly, then more than likely you have only recreated your existing model of distribution systems – you are seeing the human body’s circulation system as if it were the distribution system of a global manufacturing firm. If you invest the time and effort to understand this complex new system on its own merits, then you might discover something interesting about your own discipline. For instance, the human circulatory system is one of several overlapping hierarchical systems that allow the human body to grow, heal, change and yet maintain homeostatic balance. How do those systems overlap? How are the priorities of those different systems balanced? What overlapping systems exist in our global manufacturing firm, and how do they interact? An in-depth study of a new complex system should force you to ask new questions about your own, seemingly familiar system.

The second key to applying metaphors is to recognize the value of the cognitive leap. As you map the models from one system onto another, the fit will never be perfect. Our global manufacturing firm is not a human body. Therefore the solution to our challenge will not lie in our suddenly believing this to be true. Instead, the solution will lie one or two steps away. As we look at the human circulatory system, we will encounter questions and tangential thoughts. “What performs the function of ‘hormones’ in our organization?” We will not, of course, implement a system of complex chemical exchanges in our organization, but this might lead us to think about our communication systems or decision-making metrics in a new way.

The final key is often the most frustrating for managers — only a very few of the ideas that this process produces will be highly valuable. Some of the ideas will be useless. Many of the ideas will be interesting but impractical or irrelevant. Other ideas will serve as useful, incremental improvements to your system. But only a rare few of these ideas will be truly revolutionary. The secret is the same in any game of statistics – you have to try large numbers of these metaphors for the big ideas to hit. These ideas are the outliers, not the norm, and while metaphor can push your thinking towards the innovative, no process can guarantee that your new ideas will be both different and effective. Many managers are willing to try this approach once or twice, and give up when it does not immediately return impressive results. … In order to discover great innovations, you must engage regularly in the search and recognize that most of your discoveries will have either marginal or moderate value. Creative combination is a process that increases your odds of discovering breakthrough innovations, but it cannot guarantee success. This is a tool, not a silver bullet.

Are Cities More Innovative?

Jane Jacobs in The Death and Life of Great American Cities: “The larger a city, the greater the variety of its manufacturing, and also the greater both the number and the proportion of its small manufacturers.”

The benefits that cities offer to smallness are just as marked in retail trade, cultural facilities and entertainment. This is because city populations are large enough to support wide ranges of variety and choices in these things. And again we find that bigness has all the advantage in smaller settlements. Towns and suburbs for instance are natural homes for huge supermarkets, and for little else in the way of groceries, for standard movie houses or drive ins for little else in the way of theatre.

There are simply not enough people to support further variety, although there may be people(too few of them) who would draw upon it were it there. Cities, however, are the natural homes of supermarkets, and standard movie houses, plus delicatessens, Viennese bakeries, foreign groceries, art movies, and so on, all of which can be found co-existing, the standard with the strange, the large with the small. Wherever lively and popular parts of the cities are found, the small much outnumber the large.

“Cities, then,” writes Steven Johnson in Where Good Ideas Come From: The Natural History of Innovation, “Cities, then, are environments that are ripe for exaptation, because they cultivate specialized skills and interests, and they create a liquid network where information can leak out of those subcultures, and influence their neighbors in surprising ways. This is one explanation for superlinear scaling in urban creativity. The cultural diversity those subcultures create is valuable not just because it makes urban life less boring. The value also lies in the unlikely migrations that happen between the different clusters.”

And Samuel Arbesman, in The Half-life of Facts, adds: “Larger groups of interacting people can maintain skills and innovations, and in turn develop new ones. A small group doesn’t have the benefit of specialization and idea exchange necessary for any of this to happen.”

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Still curious? If you want a deeper understanding, read Growth in Cities.

The role of error in innovation

The British economist William Stanley Jevons in 1874:

It would be an error to suppose that the great discoverer seizes at once upon the truth, or has any unerring method of divining it. In all probability the errors of the great mind exceed in number those of the less vigorous one. Fertility of imagination and abundance of guesses at truth are among the first requisites of discovery; but the erroneous guesses must be many times as numerous as those that prove well founded. The weakest analogies, the most whimsical notions, the most apparently absurd theories, may pass through the teeming brain, and no record remain of more than the hundredth part.

From Steven Johnson’s Where Good Ideas Come From: The Natural History of Innovation:

“The errors of the great mind exceed in number those of the less vigorous one.” This is not merely statistics. It is not that the pioneering thinkers are simply more productive than less “vigorous” ones, generating more ideas overall, both good and bad. Some historical studies of patent records have in fact shown that overall productivity correlates with radial breakthroughs in science and technology, that sheer quantity ultimately leads to quality. But Jevons is making a more subtle case for the role of error in innovation, because error is not simply a phrase you have to suffer through on the way to genius. Error often creates a path that leads you out of your comfortable assumptions.

Thomas Khun makes a similar argument for the role of error in Scientific advancement.

And, of course, without error evolution would stagnate. We’d be nothing more than a perfect copy, incapable of adaptation. Luckily, however, DNA—whether in the code itself or in copying mistakes—is susceptible to error so we are always testing new combinations out. “Most of the time,” Johnson writes, “these errors lead to disastrous outcomes, or have no effect whatsoever. But every now and then, a mutation opens up a new wing of the adjacent possible. From an evolutionary perspective, it’s not enough to say “to err is human.” Error is what made humans possible in the first place.”

Still curious? Susan Rosenbery found that “stress” dramatically increases the mutation rates of bacteria.

The Bias Against Creativity: Why People Desire But Reject Creative Ideas

You’d be hard-pressed to find a person or organization who says they’re opposed to creativity. It’s seen as an unequivocally good thing. Everyone wants to have creative ideas.

But we don’t always behave in a way that indicates we value creativity. We resist new ideas. For instance, schools are meant to foster creativity. Yet research indicates that teachers dislike students who exhibit curiosity and creative thinking.

Why are our attitudes to creativity so contradictory?

Three researchers at Cornell University took a stab at the answer:

We offer a new perspective to explain this puzzle. Just as people have deeply-rooted biases against people of a certain age, race or gender that are not necessarily overt (Greenwald & Banaji, 1995), so too can people hold deeply-rooted negative views of creativity that are not openly acknowledged. Revealing the existence and nature of a bias against creativity can help explain why people might reject creative ideas and stifle scientific advancement, even in the face of strong intentions to the contrary.

Creative ideas are novel and useful. Yet idea-evaluators (decision-makers) have a hard time “viewing novelty and practicality as attributes that go hand in hand,” and, in fact, often view them as inversely related.

When endorsing a novel idea, people can experience failure, perceptions of risk, social rejection when expressing the idea to others, and uncertainty about when their idea will reach completion.

And we generally like to avoid uncertainty:

Although the positive associations with creativity are typically the focus of attention both among scholars and practitioners, the negative associations may also be activated when people evaluate a creative idea. For example, research on associative thinking suggests that strong uncertainty feelings may make the negative attributes of creativity, particularly those related to uncertainty, more salient

The authors conclude:

Our results show that regardless of how open minded people are, when they feel motivated to reduce uncertainty either because they have an immediate goal of reducing uncertainty, or feel uncertain generally, this may bring negative associations with creativity to mind which result in lower evaluations of a creative idea.

Source: The Bias Against Creativity: Why People Desire: But Reject Creative Ideas