The Self-Tuning Enterprise

Wouldn’t it be great if there were an algorithm that could tell you when to develop a new business model or enter an emerging market? Unfortunately, one doesn’t exist. However, it is possible to use the principles behind algorithms to continually retune your strategy and your organization.

In online enterprises, algorithms constantly readjust the products and content shown to customers. They do this by operating three learning loops: experimentation, modulation, and shaping. Algorithms keep generating new options and testing reactions to them. But over time the algorithms modulate the rate of experimentation, scaling it back as they learn more about people’s likes and dislikes. Algorithms shape preferences too, by introducing customers to products they might not have otherwise discovered. Critically, they do this all in a self-directed manner, without any human intervention.

Now some internet companies have begun to regularly readjust their business models, allocation processes, and structures using the same self-directed learning loops. This approach works especially well in rapidly changing markets, like China. In this article, the authors look at how China’s Alibaba grew from an 18-person start-up to an $8 billion empire by regularly resetting its vision, testing out new models, shaping opportunities, and building adaptive structures.

HBR Reprint R1506E