I just finished reading Steven Johnson’s “Where Good Ideas Come From” and it’s an absolute must read for anyone interested in the sweet science of innovation; he’s actually got a TED talk that addresses some of these issues but it isn’t nearly as compelling as the book).
I was so impressed with the book that I simply had to abandon my traditional Monday Book Review format and bring you a little something deeper. At its core the book is about the origins of good ideas, while explaining these origins Johnson goes through seven integral (and interrelated) concepts of innovation:
- the adjacent possible
- liquid networks
- slow hunch
What follows is a blend of the most pertinent excerpts form the book and my own thoughts on how those excerpts relate to the public sector writ large (warning: it’s a long post, I’ve been chewing on these ideas for weeks).
The Adjacent Possible
The adjacent possible is a a kind of shadow future, hovering on the edge of present state of things, a map of all the ways in which the present can reinvent it self. Yet it is not an infinite space, or a totally open playing field… What the adjacent possible tells us is that at any moment the world is capable of extraordinary change, but only certain changes can happen. The strange and beautiful truth is that is that its boundaries grow as you explore those boundaries. Each new combination ushers in new combinations into the adjacent possible. (p.31)
Think of the adjacent possible as the doors leading out of the room you are in. The more you explore what’s behind those doors, the more doors you find to explore. The key lesson here – one that I have argued repeatedly – is that exploring the edges of the organization is what creates the room for growth. In short, organizations need people who are willing to be nomads; they need tricksters who walk the line; they need people to open doors to new ways of thinking.
My own experience is that I find it is rather easy to stand out as someone who engages in these types of activities because (in my view) its the path least travelled by fellow bureaucrats. No one ever speaks out against the notion that the public sector needs to be more innovative (its an untenable position) but my sense is that few of us actually invest time in truly understanding (and pursuing) what is required to achieve it. This is, at least in part, attributable to a culture that rewards keeping conversations within established (and hierarchical) channels. Anyone who has ever been “corrected” by a manager for corresponding with a colleague above their current pay grade knows this truth intimately.
It’s fair to say that the general criticism levied by many against governments in general is that they aren’t exactly environments that breed innovation; which I suppose leads us to the question, what kind of environment creates good ideas? According to Johnson:
The simplest way to answer it is this: innovative environments are better at helping their inhabitants explore the adjacent possible, because they expose a wide and diverse sample of spare parts – mechanical or conceptual – and they encourage novel ways of recombining those parts. Environments that block or limit those new combinations – by punishing experimentation, by securing certain branches of possibility, by making the current state so satisfying that no one bothers to explore the edges – will, on average, generate and circulate fewer innovations than environments that encourage exploration. (p. 41)
One of the key points that Johnson makes later in the chapter is on the idea of sustainability and that while there may be incredibly innovative individuals who leap ahead of what is currently possible, the innovation they bring to the market isn’t sustainable because the prerequisite doors within the adjacent possible haven’t been unlocked yet. If organizations are looking to embrace a sustainable approach to innovation they need to do a better job of weaving exploration and solidification into their business fabric. The (slightly frustrating) implication for would fast moving innovators and earlier adopters is likely that they need to slow down and work on building a foundation that will support their downsteam efforts rather then simply jumping ahead to those efforts right now.
According to Johnson ideas don’t happen in a vacuum. While we tend to characterize the greatest ideas of our times as sudden strokes of genius and “aha moments”, this characterization is incredibly flawed and often misleading:
A good idea is a network. A specific constellation of neurons–thousands of them–fire in sync with each other for the first time in your brain, and an idea pops into your consciousness. A new idea is a network of cells exploring the adjacent possible of connections that they can make in your mind. This is true whether the idea in question is a new way to solve a complex physics problem, or a closing line for a novel, or a feature for a software application. If we’re going to try to explain the mystery of where good ideas come from, we’ll have to start by shaking ourselves free of this common misconception: an idea is not a single thing. It is more like a swarm…
When you think about ideas in there native state of neural networks, two key preconditions become clear. First, the sheer size of the network: you can’t have an epiphany with only three neurons firing…The second precondition is that the network be plastic, capable of adopting new configurations. A dense network incapable of forming new patterns is, by definition, incapable of change, incapable of probing at the edges of the adjacent possible. (pp. 44-46)
Density matters; it affects the size of the adjacent possible. Maintaining a dense and diverse network is important for anyone looking to be more innovative. The more ideas you come up against the more raw materials you have for connections to be made betwixt them. Malleability also matters; yet public sector working environments are anything but plastic. I hope that public sector work environments loosen up a bit as people are increasingly realizing that less rigid environments are more conducive to innovating than rigid ones. If you are asking yourself how to push your brain towards more creative networks, Johnson agues that:
The answer, as it happens, is delightfully fractal: to make your mind more innovative, you have to place it inside environments that share that same network signature: networks of ideas or people that mimic the neural networks of a mind exploring the boundaries of the adjacent possible. (p. 47)
… the snap judgements of intuition – as powerful as they can be – are rarities in the history of world-changing ideas. Most hunches that turn into important innovations unfold over much longer time frames. They start with a vague, hard-to-describe sense that there’s an interesting solution to a problem that hasn’t yet been proposed, and they linger in the shadows of the mind, sometimes for decades, assembling new connections and gaining strength. And then one day they are transformed into something more substantial: sometimes jolted out by some newly discovered trove of information, or by another hunch lingering in another mind, or by an internal association that finally completes the though. (p. 77)
I suppose there is some sort of ironic corollory that can be drawn between slow moving bureaucracies and the slow hunch, I’d rather side step it and instead focus on the heart of the matter, namely that:
Because these slow hunches need so much time to develop, they are fragile creatures, easily lost to the more pressing needs of day-to-day issues. (p. 77)
One of the biggest challenges facing governments is that they tend to focus on the immediacy of pressing needs to the detriment of the longer game. Its the cultural underpinnings that give us table dropped documents, last minute changes, and rush translations.
The premise that innovation propsers when ideas can serendipitously connect and recombine with other ideas, when other hunches can stumble across other hunches that successfully fill in their blanks, may seem like an obvious truth, but the strange fact is that a great deal of the past two centuries of legal and folk wisdom about innovation has pursued the exact opposite argument, building walls between ideas … Ironically those walls have been erected with the explicit aim of encouraging innovation. They go by many names: patents, digital rights management, intellectual property, trade secrets, proprietary technology. But they share a founding assumption: that in the long run innovation will increase if you put restrictions on the spread of new ideas … The problem with these closed environments is that they inhibit serendipity and reduce the overall network of minds that can potentially engage with a problem. (pp. 123-124)
I’m not sure this needs elaboration; it may be sufficient to poke you in the direction of thinking about how open to serendipity your organization is, whether or not you are encouraged to meet and engage in dialogue with people outside it, and how important it is that you be physically present in the office even when its inconsequential to your ability to deliver on your responsibilities.
“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 radical breakthroughs in science and technology, that sheer quantity ultimately leads to quality. [There is a] more subtle case for the role of error in innovation, because error is not simply a phase you have to suffer through on the way to genius. Error often creates a path that leads you out of your comfortable assumptions … Being right keeps you in place. Being wrong forces you to explore. (p. 117)
Again, think about how accepting of failure your organization is; are the majority of new projects are born out of comfortable assumptions – the way we’ve always done things – or are they prompted by an admission that something is a miss and needs to be fixed from the ground up?
Taking ideas from other sectors and applying them to the public sector is what Johnson calls exaptation:
If mutation and error and serendipity unlock new doors in the biosphere’s adjacent possible, exaptations help us explore the new possibilities behind those doors. A match you light to illuminate a darkened room turns out to have a completely different use when you open a doorway and discover a room with a pile of logs and a fireplace in it. A tool that helps you see in one context ends up helping you keep warm in another. (p. 156)
I’ve said repeatedly to people that if they want to be recognized as an innovator, all they have to do is look in the direction others aren`t. If the entire organization is looking left, look right. The marginal value of another set of eyes looking left is negligible. The value of the first set of eyes to look right is enormous.
What would you rather be known for?
Platform building is, by definition, a kinds of exercise in emergent behaviour … platform builders [don’t] just open a door to the adjacent possible. They build an entire new floor. (p. 183)
The above statement isn’t surprising if you are already familiar with the idea of government as platform; however what is surprising is what Johnson has to say about the potential of bureaucracies to be a platform:
Government bureaucracies have a long and richly deserved reputation for squelching innovation, but they possess four key elements that may allow them to benefit from the innovation engine of an emergent platform. First, they are repositories of a vast amount of information and services that could be of potential value to ordinary people, if only we could organize it better. Second, ordinary people have a passionate interest in the kind of information governments deal with, whether it’s data about industrial zoning, health-care services or crime rates. Third, a long tradition exists of citizens committing time and intellectual energy to tackling problems where there is a perceived civic good at stake, And, finally, the fact that governments are not in the private sector means that they do not feel any competitive pressure to keep their data proprietary. (p. 196)
The first three points are bang on – and make a great case in support of open data – however Johnson’s final point, that governments don’t feel competitive pressure to keep their data proprietary, is (in my experience) wrong. There is tremendous pressure to keep things out of the public sphere, to minimize data sharing, and horde information; furthermore these pressures are felt at both the organizational and individual levels.
A visual conclusion selon moi
Based on my interpretation of Johnson’s book; I’ve cobbled together the following chart that shows where I think ideas go to live and where they go to die (click to enlarge):
I have read the book, liked it, and really enjoyed your digest. Many thanks!