“Never let an MBA near a marketplace that can run itself.”

So said Ming Zeng, CSO of Alibaba, when I was interviewing him for my upcoming book. His words struck me as deeply provocative. As we dug into what he meant, we realized that we had both been thinking independently about what we came to call the “self tuning enterprise.”

What Ming meant was, in essence, don’t try to manage what is better left to market mechanisms. As a young enterprise in a fast changing environment, Alibaba had been trying not only to institutionalize change, but to bring the marketplace into the organization. Adapting to change through managed experimentation had already become a popular idea and a reality for many net-native companies. But Alibaba was taking it a step further by trying to continuously update not only its product offering, but also the elements of the business which we might ordinarily assume are fixed: the vision, business model, organization, and information systems.

Georg Wittenberg and I at BCG had, in parallel, been modeling the effectiveness of different approaches to strategy and execution in different environments. We carried out this modeling using a so-called multi-armed bandit algorithm – coincidentally, the same sort of algorithm which Alibaba and other digital market players use to recommend products to customers. These algorithms turn out to be extraordinarily good at rapidly tracking and stretching customers’ changing needs – tuning themselves into changing circumstances. They do so by operating three learning loops in a rapid, automated fashion: adapting to changing customer needs, modulating the exploration of new needs, and shaping the emergence of new needs.