Beware big data doomsayers

It’s become almost cliché to complain that Facebook, Amazon and Google have become unassailable monopolies. Critics, from the left and right, argue that big data and network effects combine to create massive barriers to entry.

The idea behind network effects is straightforward. Facebook isn’t very useful to me if none of my friends are on it. Google’s ability to put the right adverts in front of your eyeballs depends on their ability to analyse large pools of data. The more data-points they get, the better they can target consumers. Intuitively, it implies that there are massive first-mover advantages in the platform economy and that once a firm gains critical mass then insurgent startups don’t have a chance. Calls for trustbusting, and even public utility regulation inevitably follow.

The problem is, as an excellent article in this month’s edition of Regulation points out, that the evidence doesn’t fit the theory. Authors Evans and Schmalensee bash the armchair theorists who presume that whenever there are network effects then insurmountable monopolies inevitably follow.

One key mistake is to ignore that network effects can work in reverse too. Take instant messaging services. They’re only useful if your friends use them too. If there is anywhere where network effects should be able to create insurmountable monopolies then it is instant messaging. But, we’ve seen AOL Instant Messenger and MSN Messenger lose their market-share to WhatsApp, Snapchat and Slack.

The same is true of social media. The Guardian may now publish op-eds arguing that “We need to nationalise Google, Facebook and Amazon”, but just a decade ago they were asking “Will MySpace ever lose its monopoly?”

Why are the doomsayers wrong? Evans and Schmalensee explain:

“The flaw in that reasoning is that people can use multiple online communications platforms, what economists call ‘multihoming.’ A few people in a social network try a new platform. If enough do so and like it, then eventually all network members could use it and even drop their initial platform.”

Examples of ‘winner take all’ markets are often the result of economists and journalists misidentifying what the market is. Google may be the dominant search engine, but in the highly profitable product search market it has stiff competition from Amazon.

It’s become trendy to say ‘data is the new oil’ but slogans shouldn’t be a substitute for evidence. It is often asserted that ‘big data is bad for competition’, yet the last twenty years have seen incumbents with reams of data being displaced by nimble better services. Evans and Schmalensee give half-a-dozen examples:

“AOL, Friendster, MySpace, Orkut, Yahoo, and many other attention platforms had data on their many users. So did Blackberry and Microsoft in mobile. As did numerous search engines, including AltaVista, Infoseek, and Lycos. Microsoft did in browsers. Yet in these and other categories, data didn’t give the incumbents the power to prevent competition. Nor is there any evidence that their data increased the network effects for these firms in any way that gave them a substantial advantage over challengers.”

This isn’t to say it is impossible for Google, Amazon and Facebook to abuse their market position, but just as competition theorists rejected simplistic ‘big is bad’ assumptions in the 80s, it’s time for critics of so-called ‘tech titans’ to move beyond ‘big data is bad’.