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.
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