How much can we influence the rate of innovation?
The distribution of product complexity helps explain why some technology sectors tend to exhibit faster innovation rates than others.
Innovation is how organizations drive technological change, but the rate of innovation can vary considerably from one technological domain to another. To understand why some domains flourish more rapidly than others, we studied a model of innovation in which products are built out of components. We derived a conservation law for the average size of the product space as more components are acquired and tested our insights using historical data from language, gastronomy, mixed drinks, and technology. We find that the innovation rate is partly influenceable and partly predetermined, similar to how traits are partly set by nurture and partly set by nature. The predetermined aspect is fixed solely by the distribution of the complexity of products in each domain. Different distributions can produce markedly different innovation rates. This helps explain why some domains show faster innovation than others, despite similar efforts to accelerate them. Our insights also give a quantitative perspective on lean methodology, frugal innovation, and mechanisms to encourage tinkering.
More in The structure of innovation
Insights from biology, physics and business shed light on the nature and costs of complexity and how to manage it in business organizations.
A theoretical model of recursive innovation suggests that new technologies are recursively built up from new combinations of existing ones.
The usefulness of components and the complexity of products inform the best strategy for innovation at different stages of the process.
Firms can harness the shifting importance of component building blocks to build better products and services and hence increase their chances of sustained success.
In systems of innovation, the relative usefulness of different components changes as the number of components we possess increases.