The Four Triggers For The 'Big Data' Bubble To Burst

Following the earlier warning of the extreme valuation levels of the FANG-type stocks...

Nomura exposes the bubble you didn’t know about could be bursting without you knowing...

One of the challenges of identifying bubbles is that too often we use the playbook of the previous bubble.

Today's asset bubble is in data and platforms. And yes, these are assets even though most economic data or even financial accounts do not classify them as such. The reason is that assets are things that can generate recurring income, and thanks to the revenues of many social media and tech companies we know that is the case. 

Data are an (intangible) asset

To understand this better, we take for an example a tech company that offers a service to micro-target consumers with customised “ads”. The way it does this is by hiring data scientists, providing a “free” service that allows it capture consumer data, and monitoring public profiles of consumers. The costs incurred in doing this would typically be classified as an operating expense, rather than a capital expenditure. The value of the data and algorithms would therefore not appear on the balance sheet as an asset, yet this “intangible asset” undoubtedly provided recurring revenues to the company. 

Markets know this and so value the company as if it did have these assets, while the “book value” (accounting value) would not reflect this – the end-result are tech companies with very high price-to-book ratios. The only time the book value would reflect the value of these intangible assets is when the company gets acquired by another company. In that case, the difference between the price paid and the book value gets booked as “goodwill”.  The other consequence of this is that all the comments about the lack of investment in developed economies may be misplaced. There may well have been lots of investment, but it has not been accounted for correctly in official statistics.

The four triggers for the data bubble to burst

But more important than the above are that four forces are coming together to potentially burst the data/platform bubble.

1. The cab-driver is talking data/platforms Returning to market valuations of these intangible assets, they have been surging in recent years. Investors are assigning more and more value to data and platforms (Figure 1). The number of books, articles and non-tech corporates talking about big data, AI and blockchain is also reflective of this. Even cab-drivers (or should I say Uber drivers) are talking about some of these trends. A classic sign of the late stages of a boom is when non-specialists start to become the most vocal advocates for the boom.

2. Politics is turning against the sector The more fundamental trigger of the bursting of this “bubble” is the shift in politics on the data/platform industry, especially in the US. President Obama could be thought of as the “Silicon Valley” President, with his tendency to embrace that sector and lean on the sector for economic and business strategy. After all, it was President Obama who was the first one to appoint a Chief Technology Officer. 

President Trump by contrast has been more sceptical and instead has focused on the manufactured sector. It is notable that whenever President Trump talks about the US trade deficit, he focuses on the goods balance, rather than trade in services or invisibles. Part of the reason for this is the fruits of the data/platform revolution has not been shared across the economy – if anything, it has seen income inequality widen as intangible asset-intensive industries tend to create winner-takes-all-dynamics. The thrust of US policy is therefore moving back towards tangible asset industries, such as manufacturing, and away from intangible asset industries, like data/platform companies.  

3. The perception of the accuracy and use of the data are being questioned Part of the explosion in the use of these platforms was the disruption of the conventional distribution and verification of information. Before social media, information was distributed and verified by particular institutions such as press/media companies, universities and government bodies. Social media allowed distribution to be wrestled away from these institutions thus allowing millions more “publishers” and importantly the verification was done by crowdsourcing the opinions of other individuals through user reviews.  

Today thanks to the increasing concerns that platforms and data-holders have been “gamed” by corporations and foreign governments to manipulate consumers and voters, there is a growing backlash from individuals and governments on how these platforms can operate. For individuals, this could be resulting in a shift from “crowd-sourced” information to “reputation-based”

Information and opinion. For governments, this could result in greater regulation on how and where the data/platform companies can operate. 

4. A move away from global towards regional standards Finally, there is a move to regionalise standards on big data/AI/platforms rather than globalise. The big three regions are the US, China and EU. China has a clear policy of a state-centric data/platform model, where Chinese data have to be held in China with oversight from the authorities. The EU is increasingly flexing its muscles on the rights of the consumer in relation to data/platform owners. That leaves the pioneering US companies with the most to lose as they have to retrench from these markets.

This year will be bumpy

The bottom line is that trade wars, populism, income inequality can be looked at in isolation, but together they all point to a reaction against the growth of fluid intangible intensive industries such as the data/platform companies. This means that these markets will come under increasing pressure on how they value data/platforms as the year unfolds. While the direct fall-out of this could be seen in equity markets, the currency markets could also be affected. The most obvious currency to benefit from these dynamics would likely be the yen, which is not at the centre of the tri-polar data/platform world and typically performs well in a volatile world. 

Source: Nomura