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The ALIBABA Case

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The ALIBABA Case

The ALIBABA Case

The Alibaba Case. 
Translated by MarketingDigital.blog 
Original article: Greg JenkinsWould not it be nice if an algorithm tells you when to develop a new business model or if you should enter a new market?

We would be lying if we said that there is such an algorithm. Not so, and we do not imagine a moment in the foreseeable future when algorithms (or other forms of artificial intelligence) can angola email lists answer such difficult strategic questions. But we believe that something almost as interesting is emerging: a way in which organizations can apply algorithmic principles to make frequent and calibrated adjustments in their business models, allocation processes of resources and structures, without a direction from the top.

It is a provocative claim, but it is based on real developments that we have observed in Internet companies such as Google, Netflix, Amazon and

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Alibaba. These companies have become extraordinarily good in the automatic reorganization of their offers for millions of individual customers, taking advantage of real-time data on their behavior. These constant updates are, in fact, driven by algorithms, but the processes and technologies that underlie the algorithms are not magical: it is possible to separate them, see how they work and use that knowledge in other environments. And that is precisely what some of those same companies have begun to do.

In this article we will first see how self-tuning algorithms can learn and adjust so effectively in complex and dynamic environments. Then, we will examine how some organizations are applying self-adjustments in their companies, using as a case example the Chinese giant of e-commerce Alibaba.