Concerns about the declining pace and quality of innovation are legitimate but misplaced. Innovation is not slowing. The size of the space of the possible has increased, but we are exploring only a portion of it. VR technology has existed in some capacity for years, and driverless cars already exist. However, in both of these cases, realistic integration of these technologies into our daily lives lags behind. The origination of ideas and the commercial integration of those ideas represents two distinct processes: invention and innovation. In recent years, the gap between these two stages has been decreasing in some areas (internet technologies, nanotech, and biotech to name a few), but has been increasing in others. To understand why, it is helpful to think about technological progress as an evolutionary process.
There are many parallels between technological and biological evolution. One parallel is the importance of selection. In biological systems, survival of the fittest and other rules ensure that the only species who survive are those that are fit for their environments. In technological systems, survival depends on finding product-market fit. The parallel continues. A species’ fitness in its environment depends on the relative fitnesses of surrounding species and how they interact. Similarly, a technology’s product market fit depends on the actions of the other technologies in the market.
Here, the analogy breaks down. Successful technologies go on to interact with, and define a surrounding civil society. This civil society is composed of the societal infrastructural, cultural, political, and economic systems. These interactions refine the selection criteria, as only inventions that fit both the technological and civil markets survive.
Innovators search over a common pool of inventive possibility for ideas with civil and market viability. How innovators explore and define this pool constitutes the rules of the innovation commons. The nature of the innovation commons and its rules simultaneously enables and constrains technological change. Inventions that lie “close” to existing innovations share clearly defined civil and technological problems and will find it easier to become innovations. Inventions that do not share common components are further from the existing collective of innovations. Inventions in this latter category are naturally riskier, oftentimes requiring both technological and socio-political shifts and reallocations of resources. These “fringe” inventions remain underdeveloped, making the innovation system as a whole seem stagnant.
Innovation and Collective Action
Inventions are combinatorial. When a new idea is developed, it spawns a certain number of problems that may be technological or civil in nature. If these problems are not addressed the new invention may never become an innovation. A single innovator (either an individual or an organization) may be able to solve some of these problems independently, but many of the problems will depend on exogenous factors beyond the innovator’s direct control. The invention’s chance of succeeding depends on the actions of other innovators in the environment and the set of technological and civil problems that they are solving.
Google Glass would have had a better chance of success if a robust app ecosystem had sprung into existence early on. Nest’s value proposition increases exponentially when it is part of a connected network of devices that work together. Tesla and other companies that can marshal enormous resources and talent can attempt to bypass this collective action problem. But even these companies encounter limitations at some point. As Tesla rolls out the Model 3 and sets its sights on mass-market adoption, it is limited by the distribution of supercharging stations.
When considering civil problems, collective action becomes even more important. In addition to addressing any technological barriers, innovators must consider how an invention fits within the broader cultural and political environment. Tesla still can’t be sold in Texas or Michigan because of protectionist laws requiring cars to be sold through franchised dealerships. Uber’s struggles with regulation are well documented. To address these political roadblocks to innovation an innovator would have to organize and coordinate groups with diverse interests. Technologies that fit well within existing civil structures will have an easier time attracting attention and becoming innovations.
The Innovator’s Problem
An innovator searches over an inventive landscape of possibility, discovering and creating solutions that change the landscape. Some of these inventions find commercial success and achieve market engagement. A smaller subset disperses widely into society. The recursive cycle of creation, selection, and survival constantly changes the landscape, creating uncertainty.
Working together reduces uncertainty. You and your fellow innovators are explorers in the unknown, working on different problems. The more overlap there is between the problems that groups of innovators are solving, the faster those problems get solved. The distance between two inventions is given by the number of sub-components and sub-problems that they share. To succeed, a critical number of problems must be solved. The limits of what a lone entrepreneur can accomplish means that each new idea needs to attract a critical mass of entrepreneurs, innovators, and investment before it can succeed. The existing collective of entrepreneurs working on solving problems defines a discovered portion of the space of possibility. A new idea’s chances of succeeding depend on the density of sub-problems it generates and the distance between that idea and the existing collective. The “difficulty” of solving the new set of problems will depend on their distance to the existing sets problems. For example, the set of problems that Amazon solved directly facilitated the rise of the self-publishing industry. Difficulty and distance interact and shape one another as part of a miniature complex system nested within the larger invention/innovation system.
The “rules” of innovation define the manner in which innovators search through the realm of possibility, testing and refining inventions while responding to the way that dispersed innovations change the landscape.1 More importantly, these rules define the maximum allowable distance and density of problems associated with a new idea. Beyond a certain point, too many problems will go unaddressed. The critical threshold of solved problems will never be reached.
Inventions that lie beyond that maximum distance won’t reach maturity and become innovations. Occasionally, highly skilled lone inventors with massive resources and large tolerances for risk manage to carve out sustaining niches for radically novel ideas. But most ideas outside of this bubble will fail. Failure is important in selecting for success, and failed inventions still add to the technology stock in the world, creating more components that can be drawn from while contributing to advancing other technology trajectories. However, we must distinguish between when an invention fails because there is a better idea and when it fails because the necessary supporting structures have yet to be developed.
For inventions to become innovations, they must surpass both technological and civil barriers. The technological structures determine what technologies are feasible, but the civil systems determine their market viability and the rate of dispersion. These two systems must be considered together. Inventions that survive integrate into and define civil environments. However, civil structures determine what is viable and constrain how innovators develop technologies.
The complex interactions between these two systems simultaneously facilitates and hinders innovation. The struggle between diversity and specialization is central to the innovator’s problem. An individual asks: should I explore a new area? Or should I continue to specialize in this area that I understand. Exploration of diverse new areas ensures that innovation and invention address a myriad of problems. Conversely, thorough specialization improves the quality of the answers and increases the complexity of problems that can be addressed.
Because of the collective action nature of innovation, innovation systems tend to trend towards specialization, oftentimes unintentionally. The closer innovators work, the more they reduce uncertainty. Each successful innovation generates its own subset of problems that attract innovators.2 These new branches of possibility are by definition close to the existing pool of innovations. Shared complementarities, overlapping problems, cheap labor and defined civil systems all work to reduce uncertainty. In this manner, technological trajectories cluster in noticeable ways. VR technology is suddenly relevant because declining costs are emerging in a civil environment primed for VR technology. The network of digital and civil communications built over the last thirty plus years and the integration of social media into daily life built the infrastructure for a society with a distinct digital reality. Four main environments are primed for virtual reality technologies: technological, social, cultural, and political.
How VR will manifest, and which manifestations will integrate and disperse remains to be seen. But the manner in which technological trajectories clustered built the necessary foundations for VR technologies. The creation of this digital infrastructure has come at the expense of developing infrastructure for other branches of innovation simply because we live in a resource constrained world. The nature of constraints on resources helps tip the scale towards specialization over diversity. When inventions fail because they lack supporting systems, or can’t quite cross that critical threshold, entire branches of technological and civil possibilities go underdeveloped.
Lags Between Invention and Innovation
Close attention must be paid to the health of the innovation commons and the implicit incentive based rules that percolate around. Monitoring technological clusters makes predicting the future easier by clarifying how things fit. A skilled monitor would spot the major inventions that lag developmentally. These represent opportunities to monitor and facilitate, and ways to generate more possibilities. When inventions fail because they lack supporting systems, or can’t quite cross that critical threshold, entire branches of technological and civil possibilities go underdeveloped.
Imagine a diver searching the ocean for treasure. At first, she starts on the surface, sending out probes to identify potential hotspots. In the beginning, she can see for miles around her, but identifying opportunity is difficult and costly. When she finds an area that seems promising, she begins to dive. If she finds the treasure she is looking for, she dives deeper, eager to discover more. At some point, she may have to build supporting structures to help mine and gather the treasure: apparatuses to help her dive deeper, machines to retrieve treasure found at the murky depths, and on. But the deeper she dives, the narrower her field of vision gets. The more supporting infrastructure she needs, the costlier switching to explore a new area will be. In this manner, it is easy to understand how the diver would could get stuck in a location that seems to be optimal at the moment while missing out on other potentially richer areas of possibility.
If the pace of innovation is slowing, is the nature of innovation and invention changing because of a lack of ideas? Or does the pace of innovation seem to be slowing because we are moving towards the end of certain branches of technological development? My belief is in line with the latter of these two diagnoses. In recent years, outside of the realm of internet technologies, lags between invention and innovation seem to be increasing. The existence of appropriate technological and civil systems to support internet technologies facilitated the dispersal and integration of these technologies. However, the absence of these supporting systems seems to be hindering the development and deployment of other technologies, such as self-driving cars. Lacking the necessary supporting technological and civil organizational structures, inventions that lie at the edges of the existing pool innovations will continue to lag behind and remain underdeveloped. In this manner, the developmental history of technological and civil innovations can act as a constraint on what is possible in the future.
Innovation is inherently random. While we can understand the past, we cannot predict the future. However, in the present, the shape of the future remains ours to define. As innovations continue to cluster, some critics will naturally worry. The tighter these clusters, the more incremental innovation will appear: Uber and AirBnB pulled antiquated industries into the modern age. Now the Uber or AirBnB of x, y, and z are attempting to follow along defined paths, seeking to replicate the success of those companies. Incremental progress rarely yields truly revolutionary inventions that cause paradigm shifts. These ideas often originate far from the existing collective of innovations and are important because they open and enable entire new branches of technological and civil possibility. When building innovation systems, or designing innovation policy, the biasing influence of developmental history must be factored in. By understanding the structural reasons behind innovative failures, we can move towards developing ways to re-balance diversity and specialization.
How quickly do we want to move forward? How fast can we change? Who benefits from innovation? Who gets to innovate? Who does innovation hurt? The answers to these questions are governed by the the web of relationships and interconnected processes that compose the innovation commons. By attempting to untangle this complex web, we gain degrees of control over the answers to these questions.
The following essays will explore examples of the innovation commons and her rules.
- Disruption and Overgrazing
- Moonshots and Market Engagement
- Working Backwards and The Slow Pace of Fast Change
- Startups (!)
- Connectivity and Distance: Theranos and the Business Backer
- Patents and the Innovation Fed
- A New Age of Autonomous Transportation
References
- The idea of rules builds on work done by Tim Kastelle, Jason Potts, and Mark Dodgson in “The Evolution of Innovation Systems” at the Copenhagen Business School’s 2009 Summer Conference.
- Arthur W,B. 2009. The Nature of Technology: What it is and How it Evolves, Free Press, New York, 2009.