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Roula Khalaf, Editor of the FT, selects her favourite stories in this weekly newsletter.
The UK government wants to sell anonymised public data. That makes sense. There’s lots of it and more is accumulating every minute. Totting up industry revenue, the European Commission projects that UK data companies will garner revenue of €30bn this year; add in the EU and it’s €145bn.
As for governments, how might they put a price on information? Data may be this century’s oil, but it doesn’t come in barrels at a daily-benchmarked price. Oil costs the same whether the buyer is an airline or toy manufacturer; data’s value is often dictated by how it will be used. It doesn’t deplete and is “non rivalrous”, meaning a given data set can be used simultaneously by multiple parties.
There’s a time value of data too. One example: data that can be acted on in capital markets has maximum utility — and profit — to those who can act on it first.
Either way, it’s profitable stuff. Gartner, a US consultancy which lives off its data and research capabilities, creams off a gross margin of 74 per cent in the segment. That’s the sort of profitability associated with low-cost businesses such as enterprise software, where users typically pay recurring fees and the cost of adding a new customer is negligible.
Fittingly, purveyors tout Data as a Service (DaaS). This works best on a subscription model, the preferred route for industry-specific data providers, such as Bloomberg for finance or the likes of Nielsen for advertising. All but a few percentage points of Gartner’s research revenue comes from this source too.
Some government data may be suitable for selling on that basis as well. Other, less high-frequency data may not — such as those planned 137mn dinosaur and other specimens being digitised at the Natural History Museum. Even seemingly basic data sets incur chunky costs: digitising analogue records, data centre upkeep and using sensors or other tools to capture information.
A key challenge will be to create a data exchange that allows data providers and users to find some kind of clearing price. That would ideally factor in variables such as the cost of production, maintenance and the value to end users, allowing for data to be benchmarked.
Efforts to develop such exchanges have yet to gain traction. There are plenty in China, where data is viewed as a factor of production alongside land and labour, but volumes are nugatory. The pioneering Guiyang Global Big Data Exchange — one of about 50 in the Chinese province — has racked up much the same turnover in its decade-long history as the Shanghai Stock Exchange trades in a week or so.
Naturally, none are as adept at juicing data as Big Tech. Meta Platforms, for example, is moving on from serving up user data to advertisers to doing the entire shebang itself — deploying artificial intelligence to write and illustrate ads tailored to users based on their data. That option is not open to governments. Still, if you can’t beat them, providing them with the digital picks and shovels is a pretty good second best.