Draw Near to Go Far: The Role of Convergence in Capitalizing on Exploration

Organizations are often advised to engage heavily in exploration in order to succeed – to cast a wide net for diverse solutions that are superior to what they currently exploit. However, what is the organization to do when the fruits of its exploration are inconsistent with one another? Specifically, if all solutions appear beneficial, but each recommends different decisions for the same organizational choice, how should an organization aggregate lessons across them? Unfortunately, such a mixed bag of learning opportunities is likely to arise in the presence of complementarities, where solutions succeed not because of specific individual choices, but due to valuable interdependencies between these choices. By applying the learning mechanisms in March (1991) on a rugged NK landscape, this paper is able to show that such a challenge is surprisingly surmountable. Firms can benefit by aggregating lessons across explorations, regardless of the extent of interdependence. Even if such efforts may initially stymie the organization, the mutual learning that occurs between explorations enables them to grow progressively similar, so as to converge upon a smooth locality on the problem landscape. On this smoothed locality, valuable explorations then become salient enough to learn from. The counterintuitive takeaway is thus that in order to capitalize on diverse explorations, an organization must first engage in convergence.

企业常常被建议投入大量精力进行探索以实现成功——广泛撒网以寻找优于其现有利用的多样化解决方案。然而，当企业探索的成果彼此不一致时，企业应如何应对？特别是，如果所有解决方案都看似有利，但针对同一企业选择的决策却各不相同，企业应如何综合这些经验教训？不幸的是，在互补性存在的情况下，这种混合的学习机会很可能会出现，其中解决方案的成功并非源于特定个体的选择，而是由于这些选择之间宝贵的相互依赖。通过在 March (1991) 的学习机制上应用粗糙的 NK 景观，本文能够展示这样的挑战出人意料地是可以克服的。企业可以通过综合探索中的经验教训来获益，无论相互依赖的程度如何。即使这样的努力可能最初会阻碍企业，探索之间的相互学习使得它们逐渐相似，以便在问题景观上的平滑区域内收敛。在这个平滑区域内，有价值的探索变得足够显著，从而可以从中学习。因此，这一反直觉的启示是，为了充分利用多样化的探索，企业必须首先追求收敛。