How much can we influence the rate of innovation?

T. Fink, M. Reeves

Science Advances 5, 1 (2019)

#innovation#technology#statisticalphysics

LQ placeholderComparison of the innovation rates for different distributions of product complexity.

Comparison of the innovation rates for different distributions of product complexity.

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.

Download the PDF

LQ placeholder

How much can we influence the rate of innovation?

T. Fink, M. Reeves

Science Advances

LQ placeholder

How well do experience curves predict technological progress? A method for making distributional forecasts

F. Lafond, A. Bailey, J. Bakker, D. Rebois, R. Zadourian, P. McSharry, D. Farmer

Technological Forecasting and Social Change

LQ placeholder

Searching for great strategies

T. Fink, P. Ghemawat, M. Reeves

Strategy Science

LQ placeholder

Serendipity and strategy in rapid innovation

T. Fink, M. Reeves, R. Palma, R. Farr

Nature Communications

LQ placeholder

Harnessing the secret structure of innovation

M. Reeves, T. Fink, R. Palma, J. Harnoss

MIT Sloan Management Review

LQ placeholder

How predictable is technological progress?

D. Farmer, F. Lafond

Research Policy

LQ placeholder

Self-organization of knowledge economies

F. Lafond

Journal of Economic Dynamics and Control

LQ placeholder

The size of patent categories: USPTO 1976-2006

F. Lafond

NU-MERIT Working Paper Series

LQ placeholder

A new metric for countries’ fitness and products’ complexity

A. Tacchella, M. Cristelli, G. Caldarelli, A. Gabrielli, L. Pietronero

Scientific Reports

9 / 122 papers