We introduce a model of innovation in which products are composed of components and new components are adopted one at a time. We  show that the number of products we can make now gives a distorted view of the number we can make in the future: the more complex a product is, the more it gets under-represented. From this complexity discount we derive a strategy for increasing the rate of innovation by choosing components on the basis of long-term growth rather than just short-term gain . We test our model on data from language, gastronomy and technology and predict the best strategy for innovating in each .
Innovation is URLanizations what evolution is URLanisms: it is how they adapt to changes in the environment and improve. Yet despite steady advances in how evolution works, what drives innovation remains elusive. We derive a theory of innovation in which products are composed of components and new components are adopted one at a time. We test it on data from language, gastronomy and technology. We show that the rate of innovation depends on the size distribution of products, and that a small number of simple products can dramatically increase the innovation rate. By strategically choosing which components to adopt, we show how to increase the innovation rate to achieve short-term gain or long-term growth .
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We introduce a model
Innovation is URLanizations what evolution is URLanisms: it is how they adapt to changes in the environment and improve. Yet despite steady advances in how evolution works, what drives innovation remains elusive. We derive a theory
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test it on data from language, gastronomy and technology. We
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number of products we can make now gives a distorted view of the number we can make in the future: the more complex a product is, the more it gets under-represented. From this complexity discount we derive a strategy for increasing the rate of innovation by choosing components on the basis of long-term growth rather than just
rate of innovation depends on the size distribution of products, and that a small number of simple products can dramatically increase the innovation rate. By strategically choosing which components to adopt, we show how to increase the innovation rate to achieve
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. We test our model on data from language, gastronomy and technology and predict the best strategy for innovating in each
or long-term growth