Yesterday, the Chancellor gave a ringing endorsement to Charlie Bean’s recently published review of UK economic statistics. Bean’s excellent report sets out a series of radical recommendations that, if implemented, will herald a new era for measuring and understanding the economy. The wide-ranging recommendations span data sources and methodology, capabilities of the Office for National Statistics (ONS) and governance of statistics.
At Nesta we’re particularly pleased to see so much emphasis on the provision of statistics that properly reflect the changing structure of the economy, and making the most of novel data sources and technologies for enabling this. As Professor Bean’s report recognises, these themes have featured strongly in our research, whether it is in the use of data scraped from online game review sites and predictive models in our map of the UK video games industry, the use of meetup activity and social network analysis to analyse the digital tech ecosystem in Tech Nation, or the use of detailed job task data and machine learning to quantify the labour market impact of future automation.
As many as seven of Bean's 24 recommendations relate directly to this area:
Recommendation 3: Institute an ambitious work programme to evaluate the quantitative implications for the measurement of economic activity associated with the digital economy.
Recommendation 4: In conjunction with suitable partners in academia and the user community, ONS should establish a new centre of excellence for the analysis of emerging and future issues in measuring the modern economy.
Recommendation 11: Exploit new methods for collecting data and explore the scope for using information gathered by private sector entities in the production of economic statistics, nowcasting and one-off studies of emerging measurement issues.
Recommendation 12: Ensure ONS’s technology and data systems are capable of supporting the flexible exploitation of very large data sets.
Recommendation 13: Build ONS’s capacity to clean, match and analyse very large datasets, including through the recruitment of a cadre of data scientists.
Recommendation 14: Establish a new centre for the development and application of data-science techniques to the production of economic statistics.
Recommendation 16: Introduce recruitment and training schemes to raise analytical skills across ONS, including offering opportunities for specialists to progress in their careers by contributing to research and development of value to the organisation.
Happily, in the Budget the Chancellor announced that the government would respond to Professor Bean’s report by spending over £10 million on a new hub for data science and a centre of excellence for economic measurement.
We have a practical suggestion for how the ONS can use some of this investment to address all seven challenges listed above, namely by creating a series of ONS collaborative ‘Data Challenges’, whereby external data scientists and developers are incentivised to collaborate with ONS personnel in projects involving selected ONS data sets.
The Data Challenges might be structured in three stages: 1. Data Production and Collection; 2. Data Preparation and Analysis; and 3. Data Dissemination. Challenge sites like Kaggle and Nesta’s own Challenge Prize Centre provide great online forums for engaging the global community of data scientists. This approach would enable the ONS to benefit from the diversity of talent that experience suggests is important for tackling such challenges, while at the same boosting the data science capabilities and data science networks of its staff.