How to go beyond a narrow understanding that sees innovation only in the start-up world, or only in new technology? How to inspire an in-depth appreciation of innovation in all its facets, cutting across technology, business, and society? What is the foundation of innovation literacy, and what could a curriculum for “studies in innovation” look like?
Commonly asked questions focus on “How to do innovation?” – and many answers then either address concrete business problems (for example in Masters of Business Administration) or seek to enhance creative processes (for example through Design Thinking). I will try to develop a broader perspective by tackling the much wider question “How to think about innovation?” The story line will build on three guiding questions: What is the world around us made up of? How does that world behave? And how do we act in and on this world? While I’ll keep my focus on the needs of innovators and policy makers, I believe the essence of this little programme should be of interest to a general audience. Therefore, the following ideas are very much built around some of the writing that has crucially influenced my thinking. [Links to the sources cited below – and many more – are available on the inspirations page.]
Complex adaptive systems
We are all surrounded by systems, each composed of numerous bits and pieces that interact in various ways to get a certain job done. As a fairly simple example, take your dish washer: it consists of metal, plastic, wire, a few sensors and a bit of programming to, well, clean your plates and cutlery. Press the button and it does the job.
But there’s an entirely different class of systems that “do things you don’t expect”, that demonstrate emergent behaviours: ant colonies, groups of people, or computer code are well-known examples. Even if you were to know all the component parts of such a system, and their individual characteristics, you still could not predict the system’s responses to its environment; you could only explain the system’s actions and reactions in hindsight. Such systems cannot be predetermined, they are in fact un-pre-determinable: these are complex adaptive systems.
A broad range of human-made systems fall into this category. These include technologies (as laid out by Brian Arthur in “The Nature of Technology”), economies (see Jane Jacobs’ characterisation of “The Nature of Economies”), companies and cities (read Geoffrey West’s account of growth patterns in natural and human-made systems in “Scale”), and even science itself (expanding on Thomas Kuhn‘s seminal “The Structure of Scientific Revolution“).
Given that many natural systems show emergent behaviours as well, we should necessarily include ecosystems in these considerations. Lance Gunderson and C.S. Holling‘s work on “Panarchy” and their concept of Adaptive Cycles provides a wonderful, generally applicable framework to describe a system’s state and trajectory along three axis: wealth (the resources accumulated within a system), connectedness (the interdependency and coupling between a system’s component parts), and resilience (a system’s ability to maintain core functionalities even after catastrophic shock). This framework is particularly useful to understand a system’s development and continuous change over time, as nothing ever stays the same.
The world around us is made up of complex adaptive systems. That’s what innovators and policy makers have to deal with. Both as concrete targets and as abstract context.
Patterns of the past
At first glance, this second big topic must seem counter-intuitive: Why should a forward-oriented topic like innovation at all benefit from historic perspectives? But keep in mind the key characteristics of complex adaptive systems: their behaviour cannot be predicted, yet they can be explained and understood in hindsight. Hence historic analysis can provide astonishing insights in complex adaptive systems, their patterns of development and potential future trajectories. That’s history for a purpose.
Economic history serves as a good starting point, for example Joel Mokyr‘s analysis of the evolution of technology since the Industrial Revolution (in “The Lever of Riches“) or the development of science and the general appreciation of and quest for knowledge (in “A Culture of Growth“). Along similar timelines, economist Daron Acemoglu and political scientist James Robinson investigated the successes and failures of political and economic institutions (“Why Nations Fail“). In a long-data analysis that is equally original and daring, historian and archaeologist Ian Morris undertook an assessment of social development over roughly 12,000 years, since the last ice age (“Why the West Rules“). Acknowledging the bleak reality that developments do not automatically deliver progress and improvements, anthropologist Joseph Tainter focused his work on the collapse of social and political systems (“The Collapse of Complex Societies“). Political scientist Thomas Homer-Dixon took a similar perspective in “The Upsides of Down“.
Economist and innovation scholar Carlota Perez took an integrating approach when she proposed that recurrent phases of change shape great surges of development. In “Technological Revolutions and Financial Capital“, she portraits the interactions between technological, economic, and political changes to present one coherent narrative of large-scale, far-reaching, long-term developments, which lead to considerable ups and downs, including periods of turmoil as well as golden ages.
Historic analysis helps innovators and policy makers to understand patterns of interactions and interdependencies, to anticipate potential responses and behaviours of the world around us, and to develop a viable way forward to implement their ideas.
Innovation is an intentional human activity. While a thorough understanding of our environment, its development and trajectories is vitally important, it is the human touch that remains decisive. Hence we need to take an honest look in the mirror to “think about our ways of thinking“.
Given that innovation is associated with plans and ideas for the future that have no guaranteed outcomes, it’ll be useful to start with our thinking about uncertainty and time: Bill Sharpe‘s “Three Horizons” provides valuable insights in our short-, medium-, and longer-term perspectives and how they interact. Secondly, we’ll benefit from some support in making sense of our environments, separating simple from complicated settings, identifying whether we are in complex or chaotic situations, and adjusting our actions accordingly: that’s the purpose behind Dave Snowden‘s “Cynefin framework“.
On that basis, we can then tackle three core questions about what it means to be human. The first is: How do we make choices and decisions? With “Thinking, Fast and Slow“, Daniel Kahneman gave us the guidebook to understanding our inner wiring, the powers and flaws of our thinking. Building on that work, Hans Rosling delivered a succinct summary of human biases, how they show and how we can try to avoid them (“Factfulness“).
The second core question is about the origin of novel thoughts. I’d suggest we tackle it from two angles. In “Seeing What Others Don’t“, Gary Klein analysed our ways of having insights (i.e., developing our narrative of how the world around us works). In parallel, building on Stephen Johnson‘s “Where Good Ideas Come From“, we should consider how we have ideas (whether they are abstract or concrete, theoretical and practical, for something intangible like a narrative or something tangible like a tool).
Finally, the third core question is about value and values. Here, Mariana Mazzucato (in “The Value of Everything“) eloquently makes the case that monetary values (a.k.a. prices) are not to be mistaken for societal benefit or social values. Her work serves as strong reminder that innovation should be purpose-driven, striving to develop and implement novel problem-solutions, benefiting the many rather than only enriching the few.
The understanding of human agency gives innovators and policy makers the necessary in-depth appreciation of the multitude of intended and unintended consequences their actions and decisions will have.
Sketching out a curriculum for “studies in innovation” is in itself an innovative endeavour. However, such a curriculum does not, and to my mind should not intend to, deliver simple answers to complex questions: No ready-made advice on “how to innovate“. No step-by-step recipe for “how to create a world-class innovation ecosystem” either.
A meaningful curriculum will necessarily be of a multi- / inter- / cross-disciplinary nature, cut across engineering, economics, psychology, sociology, history, and numerous other domains. In the end, it’s all about how we act in this world, and interact with it. For that we need to understand the world, and understand ourselves. First and foremost, we have to remain humble about our skills and acknowledge the limitations inherent to our thinking.
With this approach, I’d hope to position innovators and policy makers to ask the right questions, giving them the tools to comprehend innovation in all its intertwined aspects, all its potential implications. This curriculum should make students of innovation feel comfortable in a volatile, uncertain, complex, and ambiguous world, and equip them to chart their own way forward.