Why and how government can make more of ‘Big Data’ in the global post-Brexit world

Why and how government can make more of ‘Big Data’ in the global post-Brexit world

Edward Farmer is co-author of a paper on Big Data for the Brexit Alliance with Violi Sahaj and Gavriel Merkado

Brexit is an excellent opportunity for the UK to redefine its place in the world, but how can government inform itself sufficiently to implement the best policies without relevant, up-to-date and comprehensive data? Given the two year window following the triggering of Article 50 and the general workload of Brexit, now more than ever, government needs immediate access to such data, to be able to manage it effectively and to present it in a user-friendly fashion.

There is what we might describe as a ‘movement online’ for many of our everyday activities. This has resulted in an exponential increase in the data that is added, stored and available for use online. Correspondingly, there have been major advances in the methods of gathering, analysing and utilising this data, known as ‘big data analytics’.

A number of well-known tech and media companies, like Google, Facebook and Twitter use big data analytics extensively, but a growing number of alternative companies are also using it, such as Bloomberg in the City and so-called ‘fintech’ and ‘proptech’ companies. The latter, for example, have technologies that map and show trends in different data sets. They build a picture from the data itself rather than from brokers or consultants, effectively bypassing opinion.

The applications of big data analytics as a result of recent technological advances are seemingly endless. government, in our view, can make use of these advances, which are far more efficient methods of informing policy than the once every ten years national census. The next national census is not due until 2021.

On immigration policy, for example, the Prime Minister has discounted the use of a points-based system proposed by the Vote Leave campaign during the referendum. We believe that government could seek to determine the real need in the economy and thus assess the merits of a needs-based immigration policy. Big data analytics can help formulate such a needs-based policy on a sector-by-sector basis, which will be better informed, independent, objective and flexible over time as the need changes. In fact, big data analytics enables policy-making in general to become easier, clearer, faster and more objective.

The sorts of questions a big data analytics approach would allow us to answer include:

  • Do we need more or fewer engineers nationally, or in South Wales versus the Midlands, or in London versus Birmingham?
  • Do we need fewer doctors and nurses from overseas if we can train our own by promoting already existing places or funding new ones?
  • Are temporary or long-term work visas preferable to citizenship?
  • Do migrants need to earn a minimum amount that then allows them to contribute on a net basis to the UK via tax?

It is also possible to map several data sets to spot a progression – for example, which GCSEs lead to A-levels, degrees, skill sets, jobs and so on?

It is possible to gather data on the labour market from online job sites and other sources to determine the different number of jobs, sectors, salaries and so on listed around the country – and even compare one region with another so as to identify shortages. These various data sets can be quizzed in multiple ways to help draw conclusions and, in turn, to inform and formulate policy. It even allows policymakers to not only react—often late—to emerging trends, but anticipate and get ahead of them as well.

Another key feature of big data analytics is that it allows multiple users to look at the same data and draw their own conclusions. This will be particularly useful for better “joined-up” government, where multiple departments need to have policies that work as a whole without severe conflicts between them. So, for example, the Education department can cooperate effectively with Treasury and the Home Office as each benefits from the sector-by-sector, national and regional analysis of the current state of the job market, qualifications and so on provided by the intelligent use of big data.

The last time the UK had such a dramatic rebalancing of the economy was during the privatisations of the early 80s. It is to be hoped that as Brexit is implemented, government can use the latest technological advances to do it quicker in the current context, but also better this time around. The UK has great capability with respect to such technologies and so we are well-placed to make merit of that capability in the context of achieving Global Britain.