Fink T M A, Reeves M
London Institute for Mathematical Sciences, 35a South Street, Mayfair, London W1K 2XF, UK.
BCG Henderson Institute, The Boston Consulting Group, New York, NY, USA.
Sci Adv. 2019 Jan 9;5(1):eaat6107. doi: 10.1126/sciadv.aat6107. eCollection 2019 Jan.
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.
创新是组织推动技术变革的方式，但创新速度在不同技术领域可能有很大差异。为了理解为什么有些领域比其他领域发展得更快，我们研究了一种创新模型，在该模型中产品由组件构建而成。随着获取更多组件，我们推导出了产品空间平均大小的守恒定律，并使用来自语言、美食、混合饮料和技术的历史数据检验了我们的见解。我们发现创新速度部分是可影响的，部分是预先确定的，这类似于特质部分由后天培养决定，部分由先天决定的方式。预先确定的方面仅由每个领域中产品复杂性的分布所固定。不同的分布会产生明显不同的创新速度。这有助于解释为什么尽管在加速创新方面付出了类似努力，但有些领域的创新速度比其他领域更快。我们的见解还为精益方法、节俭创新以及鼓励尝试的机制提供了定量视角。
