Ways Of Thinking About Google

| About: Alphabet Inc. (GOOG)

There's a fairly obvious and straightforward way to think about Google (NASDAQ:GOOG) - it's an ad company and a search company, and it cares about reach. The purpose of all its web projects is reach, and the purpose of Android and any other mobile projects is the same - more reach, more search, more advertising.

This is certainly true up to a point, but it doesn't seem to capture all of the things that Google does and all the plans it might have. Now, for example, is not really search or advertising (arguably it might become both, but it doesn't really need to). It seems to me that a better model is to see Google as a vast machine learning project, that's been fed with information for a decade or so. The text box that you enter a search into, that we're all familiar with, is really just an output (and of course input) for this underlying project, as is advertising. Now, Maps and Books are others, Glass and many future projects are others. It's all about ingesting the world's information and learning from it.

Hence, one could suggest that plain old web search is just the first expression of the Google vision in the same way that books were just the first expression of Jeff Bezos' vision for Amazon (which at one point he planned to call 'Relentless.com').

This may also be a good lens for looking at the countless abandoned Google projects. Some types of sharks apparently bite things to see if they're edible - they bite surfers to see if they're actually seals. If not, you get spat out (this may not be much comfort for the surfer). In the same way, Google tests segments to see if they fit the automation + machine learning implementation model. The dMarc acquisition is a good case study - once Google worked out that, making local radio advertising work would require lots of local sales forces, and would change the character and operating model of Google, it got out of the space.

Nest, though, is a puzzle. One could see it (and indeed self-driving cars) as a data collection story - reach, in other words. But there isn't really a very strong information story here. There's nothing here that you could eventually search for, or to help understand what a search might mean.

Hence, an interesting parallel pointed out by Michael Mace here after the Nest deal and John Gapper at the FT (account required) here last summer is with GE. As John put it:

"The best comparison for Google seems to me not Microsoft in the 1980s but General Electric in the late 19th century - the age of electrification. Like GE, Google is a multifaceted industrial enterprise riding a wave of technology with an uncanny ability not only to invent far-reaching products but also to produce them commercially.

Hence, one could argue that Nest or self-driving cars (and the next big hardware move that Google does) are not really about understanding 'information' in any sense, and certainly not about advertising, but about finding ways to deploy being very good at machine learning and, say, connected systems, just as GE's business is to be very good at making big complicated precision-engineered pieces of capital equipment.

In that sense, Tony Fadell's vision is very apt - to 'take unloved things' and connect them to the software revolution that my new boss Marc Andreessen talks about. If software is eating the world, then much of what is eaten is probably running software that's at least partly in the cloud (especially if it doesn't really have a screen), and that can benefit from machine intelligence and big data, and isn't that what Google does?

Disclosure: No positions.

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