What's On Your Mind, Mr. Buffett ? 2017

Machine learning and a learning machine

In a digital era, Google, Apple and Amazon are examples of companies with the right trappings that will reinforce their moats

Illustration: Kishore Das

“It was a very good sign that Warren bought Apple. Either he’s gone crazy or is learning. I prefer to think he’s learning.”

— Charlie Munger, Berkshire Hathaway Annual Meeting 2017

A recent issue of The Economist (May 6, 2017) had a cover story titled, “The world’s most valuable resource...”– data – which the magazine called “the oil of the digital era”. It went on to state: “Machine learning will extract more value from data...This abundance of data changes the nature of competition. Technology giants have always benefited from network effects...With data there are extra network effects. By collecting more data, a firm has more scope to improve its products, which attracts more users, generating even more data, and so on...Vast pools of data can thus act as protective moats.”

Mr Buffett noted at the recent Berkshire Hathaway Annual Meeting: “The five largest US market cap companies are $2.5 trillion, close to 10% of the US market. One could run them with no equity capital at all. It’s a very different world than Carnegie’s steel mills and Rockefeller’s tank cars.”

So, how different are the moats and the economics in this world – the world of the Apples, Amazons and Googles – from those of the past century on which much of our understanding of competitive advantage and strategy is based?

Go back to an article in the April 2016 issue of the Harvard Business Review titled, “Pipelines, Platforms and the New Rules of Strategy”. The authors distinguish between conventional “pipeline” businesses that have been dominant for a long time and whose value creation can be understood by examining the value chain, versus technology-based “platform” businesses which facilitate interactions between participants and increase their value as the network grows. Modern “platform” businesses rely extensively on information technology that reduces the need to own physical infrastructure, makes scaling up relatively simpler and cheaper and enhances the ability to capture, analyse and exchange large amounts of data that increases the platform’s value.

Some businesses, as will be seen later when analysing Apple, have both “pipelin


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