GSS subnational data strategy

Policy details

Metadata item Details
Author:Subnational Statistics and Analysis Division
Approver:National Statistician
Who this is for:Producers and users of subnational data and statistics
Type:Strategy
Contact:Subnational@ons.gov.uk
Review frequency:Every three years

Foreword

Sam Beckett looking directly into camera
Sam Beckett – Second Permanent Secretary, Office for National Statistics and Joint Head of the Government Economics Service

Granular, harmonised and timely subnational statistics are crucial to ensuring citizens, businesses and policymakers can take informed decisions on the economy, environment and society. This is true at all levels of targeted decision making: from informing the UK Government’s policies on levelling up and net zero, to providing an evidence base to manage the devolved adult education budget in the Combined Authorities.

As we launch the Government Statistical Service (GSS) subnational data strategy, I invite you all to think subnational by default. This mindset is not new for analysts across the GSS, but there is more to be done to fill the long-standing gaps in the subnational evidence base and to meet our users’ evolving needs.

With this in mind, the strategy sets out an ambitious vision that enhances the production and dissemination of subnational data and statistics.

Led by the Office for National Statistics in partnership with the wider GSS, under the leadership of the National Statistician, Professor Sir Ian Diamond, the strategy is centred on collaboration within the GSS, with academia and with the private sector. Now is the time to come together, from across the GSS and beyond, to deliver an ambitious future for subnational statistics for the public good.

Sam Beckett – Second Permanent Secretary, Office for National Statistics and Joint Head of the Government Economics Service

Andy Haldane – Head of the Levelling Up Taskforce
Andy Haldane – Head of the Levelling Up Taskforce, Cabinet Office (Copyright Bank of England)

What is not measured tends not to be managed. This is the story of the UK’s geographic disparities.

These spatial differences are among the highest among advanced economies and have been widening for several decades. They are often hyper-local, with within-region differences larger than between-region differences. Pockets of affluence and deprivation often sit cheek-by-jowl in a single area.

At the same time, UK data at the subnational level is currently far from perfect. It often lacks timeliness. It is of mixed quality. And it also often fails to have sufficient spatial granularity to understand hyper-local problems.

These data gaps have been an obstacle to our understanding of the UK’s rich economic geography. Their removal will empower the users of these data – central and local government, local businesses, the general public – taking decisions crucial to the success of these places.

The Government’s levelling up agenda has put issues of place at the very top of the policy agenda. A White Paper is soon to be published. That makes the publication of this subnational data strategy by the independent Government Statistical Service both timely and important. Alongside the White Paper, it will make a key contribution to levelling up the UK.

Andy Haldane – Head of the Levelling Up Taskforce, Cabinet Office

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Executive summary

The GSS subnational data strategy brings the GSS closer to unlocking the full power of subnational data by providing a framework to guide the GSS in producing and disseminating subnational statistics in a more timely, granular and harmonised way. Led by the Office for National Statistics (ONS), this strategy is the result of a collaborative effort across the GSS.

Aligned to the ambitions of the national data strategy, the GSS subnational data strategy is published at a pivotal moment for the UK statistical infrastructure, when ONS is leading the way on critical programmes and services which will radically change the way data are collected and shared, and statistics are produced and disseminated. The strategy follows the standards set out by the Code of Practice for Statistics and the principles outlined in the UK Statistics Authority’s strategy: Statistics for the public good.

The recent launch of the private BETA for the Integrated Data Service, a crucial enabler of the national data strategy, is the first step towards the secure multi-cloud infrastructure that will support the UK government in unlocking the power of cross-departmental collaboration. A roadmap is in place to deliver a public BETA for accredited researchers outside of government in 2022.

The first results of Census 2021 will be available in late spring 2022 and will provide up to date and granular data on the population of England and Wales, informing our statistical and analytical insights. The process has generated a wealth of new insight on engaging at local level, methodologies and the role of innovative dissemination tools.

The GSS subnational data strategy is centred around the inclusivity of data, statistics and analysis, echoing the sentiment of the Inclusive Data Taskforce recommendations, as well as the ‘leave no one behind’ principle of the Sustainable Development Goals. It promotes the production of statistics that represent the full diversity of both people and places that are needed to inform effective decisions.

Subnational data and statistics across the GSS

Statistics at granular levels of geography are essential to understand the issues affecting local areas. As emphasised in the 2016 final report of the Independent Review of UK Economic Statistics, a strong evidence base is vital to inform public understanding and policy discussion (decision making and the monitoring of policy impacts). The impact of devolution and the increasing focus on subnational outcomes has led to increased demand for regional and local statistics to monitor our economy, environment and society at a subnational level.

Production of subnational statistics spans the GSS, but often data collection is planned, and official statistics published, at UK, GB, country or regional level only. This often happens for good reasons, such as ensuring international comparability, mitigating the risk of low quality due to the low coverage, high levels of uncertainty, issues around confidentiality, or the devolved nature of the topic covered. However, this leaves gaps in the evidence base that need to be addressed to provide meaningful data for the public good.

For the purposes of this strategy, ‘subnational’ refers to all data and statistics that are provided for the 12 International Territorial Level 1 (ITL1) areas in the UK, which include Northern Ireland, Scotland, Wales, and the nine English regions, and for lower-level geographies.

Our vision

The strategy sets out three ambitions by building on existing good practice, showcased through case studies and guidance, while also highlighting areas for improvement to enable this transformation. Guidance in the strategy should inform both new production and dissemination methods, but also when updating or enhancing existing methods.

Our first ambition is to produce more timely, granular and harmonised subnational statistics, aiming for subnational by default. This will provide our users with the flexibility required to select geographical options according to their needs, ensuring the availability of local data to derive important insights on local areas.

1.1 Think subnational by default and break down subnational statistics to an agreed set of standardised geographies where this is appropriate and data allow.

1.2 Investigate alternative data sources and innovatively bring data sources together ensuring quality, accuracy and confidentiality.

1.3 Explore statistical methodologies and data science techniques to enable improvements to the timely production of more granular subnational statistics.

1.4 Work towards the harmonisation of subnational statistics and data, to make them more comparable, consistent and coherent across the GSS.

1.5 Adopt the Inclusive Data Taskforce recommendations to enable robust and reliable disaggregation and intersectional analysis at differing levels of geography.

Our second ambition is to build capability and capacity for subnational statistics and analysis by improving the way we share data, methods and expertise. This will lead to increased quality of data and value for money while ensuring data reach the users who need them to produce crucial statistics.

2.1 Build the capability and capacity needed to use geographic reference data and exploit geospatial data and methods.

2.2 Improve the way in which subnational data and metadata are shared across the GSS and with the wider research and analytical community, where appropriate.

2.3 Improve the way in which methodologies used to produce subnational statistics are discussed, agreed and shared across the GSS and where appropriate, the wider research and analytical community.

Our third ambition is to improve the dissemination of subnational statistics so that our users can draw insights from our outputs more efficiently. This will ensure decision makers will be able to access data-led evidence to guide the planning and policy decisions needed in their area, and residents will be able to access better data to understand the opportunities and challenges that their area face.

3.1 Ensure our stakeholders are informed about new and updated subnational outputs published across the GSS, making them easy to locate.

3.2 Make subnational statistics accessible to a wide range of users.

3.3 Provide users with the necessary guidance on how to use subnational statistics and how to communicate their quality.

Explore Subnational Statistics service

Together, the ambitions in this strategy set out a vision for the creation of an Explore Subnational Statistics, service a single service for the dissemination of subnational data and statistics organised by standardised geographies and able to accommodate flexible user-defined areas.

The strategy seeks to pursue this objective through strong collaboration, user engagement and appropriate investment, where possible, that ensures value for money. Grounded firmly in user needs, the Explore Subnational Statistics service, and subnational data strategy will respond flexibly to shifting priorities for both policy and public understanding.

The relevance of this strategy extends to analysts in the devolved administrations, ministerial departments, non-ministerial departments, agencies and other public bodies across the Government Analysis Function. As such, we encourage and welcome collaboration across all the analytical government professions to promote fruitful discussion, exchange of expertise and cross-fertilisation.

Following the strategy, ONS will publish a workplan setting out delivery specifics and plans to monitor progress through existing governance channels and under the leadership of the National Statistician. This will be informed by the needs of the wide range of users of subnational statistics across the UK, spanning from government officials to combined and local authorities, and from academics, businesses and the public at large.

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Ambition 1: Produce more timely, granular and harmonised subnational statistics

The demand for subnational statistics is increasing. Statistics at granular levels of geography are essential to understand the issues affecting local areas, ensuring the best evidence base to enable good decision making and monitoring of the impact of policies.

Feedback from local stakeholders indicates a need for more data at lower-level and user-defined flexible areas, to meet planning and policy needs. This includes more timely and accurate estimates of the size of the population broken down by demographics for small, local areas, and small area statistics that can help them to understand relationships between the outcomes people experience, such as their health, education or job, and their characteristics, for example their ethnicity or disability.

The case study on the Office for National Statistics (ONS) Health Index describes how a new experimental statistic has been created to provide a single value to measure health for each local authority in England that can be tracked over time and compared between different areas.

Policymakers need high-quality data and insight at their fingertips to make timely decisions to improve public health. This is the case whether they are responding to crises, such as the coronavirus (COVID-19) pandemic, or making longer-term decisions about addressing health inequalities.
The Health Index provides a single value for health for each local authority in England. It can be broken down into further domains allowing users to better understand any changes over time or differences between areas, or to focus on a particular aspect of the index. Currently, the domains split the index into three broad areas:

  • Healthy People – focusing on health outcomes such as life expectancy, health conditions and personal well-being
  • Healthy Lives – health-related behaviours and personal circumstances such as smoking, alcohol misuse, unemployment and working conditions
  • Healthy Places – wider determinants of health, including environmental factors including access to green space, air pollution and access to amenities (such as housing, GP surgeries)

ONS has developed a BETA web tool for exploring the Health Index further, which illustrates the type of presentation possible for the Health Index and its findings.

However, producing more timely and granular statistics can be very complex, costly, and burdensome. There is often a trade-off between timeliness and granularity as larger surveys, for example, may take longer to collect and process with lengthy and complex methods to disaggregate. Where statistics are produced for small area geographies, caveats on quality and statistical disclosure controls can result in data being unsuitable for some purposes such as monitoring and evaluation. Data availability at small area geographies was an important challenge for the Chief Medical Officer’s Annual Report 2021 for England “Health in Coastal Communities”, which highlighted that health outcomes in coastal communities can be significantly masked when analysis is at a wider geographical footprint such as local authority or Clinical Commissioning Group.

Even at the country level, business structures can make the development of subnational statistics complex. For example, when producing experimental statistics on Welsh trade, crucial questions included:

  • How does one define a Welsh business? Are these businesses with headquarters in Wales, with some employees in Wales, or with a business premises located in Wales?
  • Do the businesses record the data at the required level of granularity in the first place?

Many existing statistics require further work to improve granularity, timeliness or quality. For example, air and energy accounts statistics are only available at UK level, limiting coherence across the devolved administrations who produce their own estimates. Similarly, natural capital accounts are published at UK level, but subnational stakeholders have expressed great interest in more granular breakdowns.

Productivity statistics differ in coverage. Statistics on multi-factor productivity are currently published at UK level. Industry subnational labour productivity and business enterprise research and development are available at country and at regional level. Labour productivity estimates are available for International Territorial Level 2 (ITL2), International Territorial Level 3 (ITL3), combined authorities and local authorities at ‘total industry’ only.

Vacancies by industry and by size of business are published at UK level only as three-month average estimates. Single month vacancies estimates and regional online job advert estimates are published but not designated as National Statistics.

Similarly, stakeholders have expressed an interest for increased timeliness in statistics on country and regional public sector finances; the current release is published with a long time lag due to the availability of supporting subnational data.

As well as needing more timely and granular subnational statistics, decision makers, particularly in central government, require coherent UK-wide subnational statistics to monitor the progress of policies across the whole of the UK. However, due to different policy or legislative frameworks, or different approaches to data collection and methodology, government analysts often cannot provide policy makers with a coherent set of subnational statistics covering the four countries of the UK. This is the case, for example, for statistics on loneliness, homelessness, ethnicity and the Indices of Multiple Deprivation, which are not comparable across the UK. While different legislative frameworks can act as a barrier to achieving increased harmonisation and coherence at a UK level, devolution provides opportunities to develop innovative and creative approaches to social policy, and to share learning about how different approaches work.

By following the principles set out in this strategy, the Government Statistical Service (GSS) will have the framework in place to produce more timely, granular and harmonised subnational statistics. This will enable improved production of subnational statistics, particularly those that are currently limited by issues around quality, uncertainty, confidentiality, respondent burden, and expensive data collection. It will be easier to access and use statistical releases produced across the GSS, while acknowledging the devolved nature of statistics.

Ultimately, by producing more timely, granular and harmonised subnational statistics across the GSS, particularly for small area geographies, we will provide our users with the flexibility required to select geographical options (including user-defined areas) according to their needs, ensuring the availability of local data to derive important insights on local areas, building the evidence base for policy making, monitoring and evaluation.

Leading by example, ONS is transforming the national accounts by increasing the granularity of subnational statistics, including gross domestic product (GDP), for areas as small as 400 to 1,200 households. They will also be exploring the feasibility of breaking down a range of other estimates of expenditure to subnational levels never produced before, to enhance the understanding of inputs and outputs flows around the UK.

Through the use of new and innovative data sources, ONS is also developing a proposed programme of work to improve spatial granularity and timeliness of subnational indicators necessary to ensure policy priorities, such as the UK government’s climate change, net zero and levelling up policies, can be made available transparently and monitored.

1.1 Think subnational by default and break down subnational statistics to an agreed set of standardised geographies, where this is appropriate and data allow

We the GSS propose the following standard geographies should be considered for inclusion in every publication: ITL 1, 2 and 3 (for international comparability), counties and unitary authorities (also known as Upper Tier Local Authorities) and local authority districts (also known as Lower Tier Local Authorities). This set of standardised geographies will be subject to further user research and discussion across the GSS.

Where quality and sample size allow, we encourage the production of statistics at smaller geographies. These smaller geographies include Middle layer Super Output Areas (MSOAs), Lower layer Super Output Areas (LSOAs) and Output Areas (OAs) for England and Wales; Intermediate Zones, Data Zones and Output Areas for Scotland; and Super Output Areas and Small Areas for Northern Ireland.

Where relevant to users, the GSS will also publish statistics for corresponding local economic policy geographies such as Travel to Work Areas, combined authorities, local enterprise partnerships, as well as for towns and cities. We recognise that certain policy priorities require speciality geographies, as is the case for parliamentary constituencies, fire and rescue authorities, health authorities and police authorities.

The GSS Regional and Geography Committee will act to ensure these geographies are available for use across government, alongside spatial classifications such as the Rural-Urban Classification and Output Area Classification. The committee will provide guidance on the use of other geographies, such as on areas with distinct policy needs including Coastal areas. The committee will also provide a platform to review the relevance of the geographies currently in use and to discuss whether new ones are required.

For example, the towns and high streets case study highlights two new geographical products that have been recently created to respond to the increasing need for evidence at a granular geographical level.

Since 2018, the increased focus of the UK government on local areas of the UK, including on towns and high streets, highlighted some large gaps in the statistical provision of data across government. Therefore, the ONS Centre for Subnational Analysis set up the towns and high Streets projects to respond to the increased need for insight, evidence and good quality data at the town and high street level that will help inform, appraise, monitor and evaluate local policy making.

The projects link data to actual town and high street geographies. Using these geographies for data, analysis and insight, together with other existing geographies such as Travel to Work Areas, gives a much more informative view of the UK rather than simply providing data aggregated only at the local authority level.

The towns outputs have provided data for 1,082 towns and urban settlements in England and 104 in Wales with populations ranging from 5,000 to 225,000. Having this data available allows analysis that can help inform users on the differences and similarities between different types of towns and also between towns and cities.

In the case of high streets, the project uses innovative work undertaken by Ordnance Survey, in collaboration with ONS, to digitally identify the high streets of Great Britain, for the first time. The experimental high street dataset considers a high street as an extent along a named street predominately consisting of retailing, defined by a cluster of 15 or more retail addresses within 150 metres. The dataset included over 7,000 high streets and is currently being extended to cover other retail functions such as retail parks, shopping centres and out of town shopping.

The project has generated multiple analytical insights with ONS working closely with the Department for Levelling Up, Housing and Communities (DLUHC) on the needs and priorities to be addressed. The high streets project has been highlighted by the Geospatial Commission’s UK geospatial strategy, “Unlocking the power of location”, and the project continues to be developed to illustrate the benefits of using geospatial data and to further increase the amount of data and insight available on these topics.

The towns project includes a workstream focused on coastal towns. This analysis, produced on the deprivation and challenges of coastal towns, was then integrated into the wider research on the topic included in the Chief Medical Officer’s Annual Report 2021.

1.2 Investigate alternative data sources and innovatively bring data sources together ensuring quality, accuracy and confidentiality

Developing robust and high-quality subnational statistics may require data from different sources be brought together in an optimal way. To do so effectively, the starting point will always be to work in conjunction with stakeholders; to assess the feasibility of collecting data or repurposing existing data at the required level of granularity, and to identify appropriate modelling or apportionment methods to provide small area statistics.

Surveys have the strength of asking questions directly relevant to the concepts of interest. However, increasing the granularity of subnational statistics, for instance to enable the use of flexible user-defined areas, requires increasing the sample size, which in turn requires more resources and increases the burden on respondents. Where the production of more granular and timely subnational statistics is hindered by limited survey sample sizes, there is huge potential for administrative or commercial data to help fill the gaps. Alternative data sources, particularly administrative data, can be a useful resource to increase the granularity and timeliness of subnational statistics, but also pose methodological challenges around comparability, coverage and quality.

The case study on the experimental subnational consumer prices pilot for Northern Ireland is an example of a project aimed at improving the granularity of statistics which will take a hybrid approach by boosting the sample size of an existing survey, while investigating the possibility of incorporating alternative data sources in the long term.

Extensive stakeholder engagement conducted by the Office for National Statistics (ONS) across government, including with Her Majesty’s Treasury (HMT), Department for Environment, Food and Rural Affairs (Defra) and devolved administrations officials has shown that national and regional consumer price indices could improve the understanding of the state of the economy in each region and how it compares to the UK level, providing clearer evidence for decision making on locally directed investments and policies.

However, it is not currently possible with existing data sources to produce national or regional indices that are consistent with the Consumer Prices Index (CPI) or the Consumer Prices Index including owner occupiers’ housing costs (CPIH). A series of research pieces has been commissioned by ONS to explore the feasibility of regional price statistics and what the most appropriate methodologies might be. Overall, the research finds that regional indices do follow the UK CPIH trend but are more volatile. The quality of indices is limited by the current size of the locally collected sample (Dawber and Smith, 2019), which is suitable at UK level, but would be too unreliable to support decision making at a more granular geographic breakdown.

To produce national and regional consumer price indices there would be, therefore, a clear need for an increased sample size in the local price collection. ONS is launching an early regional pilot of boosted local collection in collaboration with the Northern Ireland Executive in 2022 (dependent on Spending Review funding). After engagement with Northern Ireland’s Department for the Economy, Northern Ireland Statistics and Research Agency (NISRA) and the Consumer Council, ONS has agreed to initiate an early pilot of boosting local price collection in Northern Ireland from January 2022, part-funded by the Consumer Council. The pilot will allow ONS to work with the collectors to understand any potential practical challenges of boosting local collection, as well as produce experimental consumer price indices for Northern Ireland and assess their robustness through 2022 and 2023. Subnational consumer prices for further nations and regions will be considered in the longer term dependent on the outcomes of the pilot and future funding.

Simultaneously, ONS is undertaking a project to incorporate alternative data sources, such as retailer-provided scanner (point-of-sale) data into CPI and CPIH. These data will contain a rich depth of information including geography. ONS has commissioned academic research to address the question of how best alternative data sources can supplement national and regional price statistics. To quickly address user need, ONS is also exploring possible analysis on scanner and other available data sources to provide timely evidence on possible regional price disparities.

We will learn from the Census and Data Collection Transformation Programme which is transforming the way ONS produces population, migration and social statistics to provide more frequent, responsive and timely estimates at both the national and subnational level. We will capitalise on the transformative work that is already happening across the GSS to use administrative data to produce, for example, modelled estimates of international migration, looking for principles and methodologies transferrable to economic statistics and subnational statistics more widely.

As part of the Census and Data Collection Transformation Programme (CDCTP), the Office for National Statistics (ONS) is transforming the way it produces statistics about the population. The goal is to better meet the needs of users by providing more frequent, responsive and timely estimates at both the national and subnational level.

ONS’s two key aims are to produce:

  • more frequent local-level population estimates which provide a key denominator for calculating rates informing important decisions at the national and subnational level – for example, COVID-19 positivity rates, or the proportion of those who have received their first and second doses of a COVID-19 vaccine;
  • more regular small area multivariate estimates, especially during the intercensal period. As part of this the ONS will be producing statistics at the small area level on distributions of income for the first time.

Over time, this will enable users to better understand their populations at all levels of geography, including the drivers and impacts of inequality, and how this varies across different population groups and geographies.

To achieve these aims ONS is building an integrated system with administrative data at its heart, supplemented by other sources of data, including social surveys. This will make use of the best sources of information at any given point and create a social statistics system that is responsive to change, whether in data and technology, policy developments, or ongoing changes in society.

In 2023, the National Statistician will report to government on the progress of this transformation, and set out what is needed in future to continue achieving ONS’s ambitions, iteratively building on what has been achieved so far.

Through this transformation ONS will improve the frequency, timeliness, and inclusivity of subnational population, migration and social statistics, in turn supporting the delivery of other aspects of the GSS subnational data strategy that depend on these statistics.

The national data strategy recognises that “much of the transformative potential of data lies in the potential for linkage and re-use of datasets across organisations, domains and sectors.” Therefore, we will also explore relationships with data providers across the private sector to increase data linkage opportunities, where this is ethical and for the public good. In doing so, we will establish transparent data management arrangements which meet the relevant data ethics standards.

The pandemic brought a common goal for the public and private sectors, and commercial organisations partnered with public bodies to ensure that government had access to the information needed to make crucial policy decisions. This was the case for ONS which, during the pandemic, received new data from a number of private and public sector organisations to help improve current statistics or produce new metrics. Now the UK government, business, and other sectors are converging on the need to collaborate on complex and cross-cutting policy priority areas such as climate change and net zero, particularly following COP26, levelling up, jobs and skills and renewal of public services.

The case study on Using Facebook data to understand changing mobility patterns explains how the ONS Data Science Campus used data from a private company to provide timely insights about the impact of lockdown restrictions on how people moved around the country.

The Data Science Campus was established within the Office for National Statistics in 2017 with the goal of investigating the use of new data sources, including administrative data and big data for public good exploiting data science tools and techniques; and to help build data science capability for the benefit of the UK.

Throughout the coronavirus (COVID-19) pandemic the Data Science Campus has been exploring new data sources that can provide insights into mobility.

Facebook Data for Good is one of the sources of mobility data that the Data Science Campus has been investigating, resulting in the ONS publication “Comparing behaviours and economic activity during lockdown periods” published on 19 March 2021.

All data provided to the ONS Data Science Campus are strictly de-identified and in an aggregated and re-scaled form so that no individual can be identified in any of the ONS work, and only relative changes are analysed. The Data Science Campus also carried out an ethical review to ensure that the use of these data was appropriate.

Going forward, the Data Science Campus will be also exploring alternative innovative data sources to answer questions relevant to the UK government’s levelling up agenda, such as:

  • news text sentiment analysis to identify what sentiment is associated to a specific area
  • analysis of images of places to assess the presence of amenities people care about, such as parking spaces, green spaces, or rundown buildings
  • analysis of online job adverts to assess mismatch between supply and demand of jobs at a local level
  • analysis of travel times and costs to measure inequality of access to critical services, such as GPs.

1.3 Explore statistical methodologies and data science techniques to enable improvements to the timely production of more granular subnational statistics

We recognise that small area estimation methodologies that incorporate survey, administrative and, where possible, census data may offer a solution to produce robust estimates where the quality of survey and administrative data is not sufficiently good.

This principle includes learning from existing model-based methodologies used to produce, among others, unemployment estimates for local authorities in Great Britain, household income and poverty estimates for England and Wales at Middle layer Super Output Areas (MSOAs). Where necessary, we will also consult the GSS Administrative Data Methods Research Programme, which aims to develop methods to use administrative data for statistical purposes.

We will collaborate with the ONS Data Science Campus to explore the implementation of innovative methods and data science techniques to improve the timeliness and granularity of existing subnational statistics, and to start creating exploratory indices.

For example, the case study on access to services in the Welsh Index of Multiple Deprivation describes how the Welsh Government and the Data Science Campus worked together to develop a tool that uses open private and public transport data to build a transport network and perform travel estimates.

The Welsh Index of Multiple Deprivation (WIMD) is the official measure of relative deprivation for small areas in Wales. WIMD is currently made up of eight separate domains (or types) of deprivation: income, employment, health, education, access to services, community safety, physical environment, housing. Each domain is compiled from a range of different indicators.

The purpose of access to services domain is to capture deprivation as a result of a household’s inability to access a range of services considered necessary for day-to-day living, both physically and online.

In 2018, the Welsh Government and the Data Science Campus worked together to develop a tool that uses open private and public transport data and the OpenTripPlanner (OTP) open-source route planner to build a transport network and perform travel estimates. The tool was used to improve the granularity and ease of performing public transport travel time analysis across Wales.

With further development, the tool has many potential wider applications, including informing location of employment/strategic hubs, transport planning, or even listing tourist accommodations accessible by public transport from key tourist sites such as Cadw properties.

The WIMD is also a success story when it comes to collaboration across the four nations. In 2020, the Office for Statistics Regulation (OSR) reviewed WIMD 2019 statistics against the Code of Practice for Statistics, as part of a wider review of the indices of deprivation statistics in Great Britain, alongside compliance checks of the statistics produced by the Scottish Government and the Ministry of Housing, Communities and Local Government (now the Department for Levelling Up, Housing and Communities). The OSR particularly praised the role of the ‘four nations group’ which meets regularly and works collaboratively to make guidance and presentation across the deprivation statistics more consistent. The review encouraged the ‘four nations group’ to ensure that appropriate resource is devoted to developing update UK-wide guidance and insight on how to combine and compare indices of deprivation across the devolved nations, as this area continues to be of interest to users and can further enhance the public value of the statistics.

Finally, the WIMD provides an example of how to disseminate subnational statistics effectively and meeting different stakeholders’ needs. The WIMD area of gov.wales includes previous releases of data as well as latest news and updates. WIMD rank and indicator data are available to download from StatsWales, while geospatial information on WIMD 2019 is available on Data Map Wales. The WIMD 2019 interactive tool allows users to explore WIMD data by entering a postcode or location, as well as to learn more about how each domain contribute to the overall index.

1.4 Work towards the harmonisation and coherence of subnational statistics and data, to make them more comparable, consistent and coherent across the GSS

Harmonisation is about making statistics and data more comparable, consistent and coherent. Statistical coherence is about drawing together outputs on the same topic to better explain the part of the world they describe.

The Concordat on Statistics identifies coherence as one of the main areas of joint working for the UK government and devolved administrations. It specifies that “While recognising that the policy context within administrations might not always be identical and that official statistics should reflect local as well as UK user needs, producers of official statistics across the administrations will look to develop new or existing statistics in such a way that, while meeting the needs of primary users, aids coherence and comparability in the UK as well as internationally”.

This strategy and the associated workplan which will follow will support the GSS Coherence Programme, as subnational statistics cut across all its thematic workstreams. These include adult social care, climate change, COVID-19, crime, equalities, health, housing, income and earnings, migration and trade and investment.

Improving harmonisation requires collaboration as highlighted by the case study on the development of coherent estimates of International Trade and Foreign Direct Investment at subnational level across the UK.

Until 2016, international trade was only calculated at the national level as part of the National Accounts. However, engagement with authorities including London, Manchester, and the West Midlands, as well as with departments including Her Majesty’s Treasury and the Department for International Trade (DIT), highlighted there was a clear demand to understand the international activities of businesses at their specific locations across the country.

To meet this need, a collaborative cross-department project including the Office for National Statistics (ONS), DIT, Her Majesty’s Revenue and Customs (HMRC), the Department for Business, Energy, and Industrial Strategy (BEIS), and the devolved administrations of Wales, Scotland and Northern Ireland started to find ways to break national-level results down to smaller geographies. Making use of a collection of administrative and survey sources including business structure databases, employment surveys, banking returns, and tourist spending, ONS created a methodology to apportion national-level estimates and trade survey results for individual businesses to more detailed geographic regions.

This has since been expanded to create estimates of imports and exports of goods and services, providing a new resource of information about the trading patterns, partner countries, industrial breakdowns and characteristics of businesses in sub-regional geographies. Building upon this, similar approaches with other statistics including Foreign Direct Investment are under way, leading toward a better understanding of supply chains and economic resilience of local areas.

1.5 Adopt the Inclusive Data Taskforce recommendations to enable robust and reliable disaggregation and intersectional analysis at differing levels of geography

In line with the Inclusive Data Taskforce recommendations, data and evidence should comprehensively and reliably reflect our society, now and as it evolves.

We will consider using targeted oversampling of under-represented groups as an approach to address specific gaps in subnational statistics that result from small sample sizes.

We will link administrative datasets to fill the gaps for relevant characteristics, and their intersections across and within the different countries of the UK.

Analysing the population by multiple characteristics and by granular geographies can often have implications on the accuracy and risk of disclosure of the resulting estimates. This can also create a risk of fatigue amongst under-represented groups. For these reasons, we will explore methods that could provide valuable additional insight, such as qualitative methods.

We will seek advice from the ONS Centre for Equalities and Inclusion, that leads the Equality Data Programme together with the Government Equalities Office.

The Equality Data Programme, a large-scale project aimed at gathering data to better understand the barriers that people from every background face across the UK, was launched in 2020.

Led by the Government Equalities Office with the support of the Centre for Equalities and Inclusion within the Office for National Statistics, this analytical programme will improve the quality of equality data and equality analysis and will produce outputs to inform government policy around equality. The initial phase of the work will look at how outcomes vary across different groups for a broad range of outcomes including health, justice and living standards. The second phase of the work will develop an Equality Data Asset in collaboration with the Integrated Data Service. This will link together data from multiple different sources to build a picture of how people’s lifepaths are shaped in the UK.

The Centre for Equalities and Inclusion also launched a GSS Equalities Data Navigator Tool, a searchable, interactive online tool to enable researchers to find the equalities data they need.

Scoping subnational data collection and producing subnational statistics with inclusivity in mind will support the Inclusive Data Taskforce and the Inclusive Data Charter in their promise to leave no one behind.

  1. Create an environment of trust and trustworthiness which allows and encourages everyone to count and be counted in UK data and evidence.
  2. Take a whole system approach, working in partnership with others to improve the inclusiveness of UK data and evidence.
  3. Ensure that all groups are robustly captured across key areas of life in UK data and review practices regularly.
  4. Improve the UK data infrastructure to enable robust and reliable disaggregation and intersectional analysis across the full range of relevant groups and populations, and at differing levels of geography.
  5. Ensure appropriateness and clarity over the concepts being measured across all data collected.
  6. Broaden the range of methods that are routinely used and create new approaches to understanding experiences across the population of the UK.
  7. Harmonised standards for relevant groups and populations should be reviewed at least every five years and updated and expanded where necessary, in line with changing social norms and respondent and user needs.
  8. Ensure UK data and evidence are equally accessible to all, while protecting the identity and confidentiality of those sharing their data.

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Ambition 2: Build capability and capacity for subnational statistics and analysis

The second ambition set out by this strategy is deeply interconnected with the first ambition: stronger collaboration and capacity building across the GSS are a prerequisite to the production of more timely, granular and harmonised subnational statistics.

As outlined in the Code of Practice for Statistics within the value pillar, this includes being responsible and efficient in the collection, sharing and use of statistical information.

Feedback from producers of statistics suggests a need for additional guidance and training on using and analysing geospatial data, and a central source of all geographic references and boundaries, with guidance on using them, choosing geographies, and dealing with changes over time.

Secondly, feedback suggests a need for more investment in data collection and for the development of standardised processes to share data and metadata, in order to enable government analysts to access subnational data in one place and where possible, at the same time.

Thirdly, feedback acknowledged an opportunity to improve ways to discuss, agree and share methods across the GSS, particularly around data linkage, small area estimation and disclosure control.

Therefore, this strategy sets out a series of principles aimed at building capability and capacity, acknowledging that many aspects of these challenges also affect analysts in local government and the wider research and analytical community.

By improving collaboration on subnational statistics and analysis, and sharing data, methods and expertise across government, the devolved administrations, academia, and the private sector, the GSS will support and steward the UK’s statistical infrastructure as a whole. By building geospatial capability and ensuring that geographic reference data are easy to find, understand and use, we will be one step closer to unlocking the unexploited spatial potential of GSS’s data holdings. Developing and adopting consistent standards in data acquisition and sharing across the GSS will lead to increased quality of data and value for money by reducing data management costs as well as acquiring datasets only once but using multiple times. By granting proportionate access to the same wealth of subnational data and methods across the GSS, accredited researchers in local government and the wider research community, we will ensure value for money while delivering the critical statistics and insights that users of subnational data need.

2.1 Build the capability and capacity needed to use geographic reference data and exploit geospatial data and methods

Effective use of geospatial data has been a recent priority for the UK government, as evidenced by the establishment of the Geospatial Commission in 2018 and the publication of the UK’s geospatial strategy for 2020 – 2025.

We the GSS will improve the way GSS geography policy, geographic reference data and guidance documents are made accessible to analysts within and outside government. This includes up to date geographic boundary sets and geographies lookups.

We will do this by strengthening the role of existing tools, such as DataMapWales, Geography Linked Data, the Open Geography Portal and SpatialData.gov.scot, taking proactive steps to publicise their content and functionalities, and to remove barriers to accessibility and wider use.

While most of their content is already freely available under the Open Government Licence, we will further unlock the potential of location data available to the public sector through the Public Sector Geospatial Agreement (PSGA) and the existing relationship with Ordnance Survey within Great Britain, and the Northern Ireland Mapping Agreement (NIMA).

Working closely with GSS Geography champions, we will share new and existing guidance and training materials on using and choosing geographies and classifications, for example those available through the Geography and Statistics training webpage.

2.2 Improve the way in which subnational data and metadata are shared across the GSS and with the wider research and analytical community, where appropriate

This strategy echoes the national data strategy’s data foundations pillar which details the need to “future-proof systems” and to hold data “in a condition that means it is findable, accessible, interoperable and reusable”.

We will work closely with data providers, data acquisition and data architecture teams across the GSS to develop clear, secure and standardised processes to acquire and share data and metadata. This will include the development and sharing of information on the suitability of data sources for the purpose of producing high quality subnational statistics.

We will agree standards for data and metadata and test their quality. This includes promoting consistent naming, coding, linking and organisation of information, particularly with reference to standard geographies. We will agree protocols to share metadata and will consider how to effectively retain and transfer the skills and knowledge needed to use the data and improve the subnational data estate in a sustainable way.

In doing so, we will follow the Data Standards Authority (DSA) guidance on how to improve metadata sharing across government, how to observe data ethics principles to use data appropriately and responsibly and how to choose data tools and infrastructure that are flexible, scalable, sustainable and secure.

The Integrated Data Service (IDS) and the ONS Reference Data Management Framework will be critical in enabling these improvements in data acquisition and sharing, as well as in building a solid architecture for the subnational data estate. They will ensure better linked and anonymised microdata are made available securely across government and the devolved administrations, allowing us to solve increasingly complex challenges by harnessing the power of cross-departmental collaboration.

In October 2021, the Office for National Statistics (ONS) launched the first stage of the Integrated Data Service (IDS).

IDS is a key enabler of the national data strategy and the government’s reform agenda, and will provide improved forms of data, alongside analytical and visualisation tools, in a secure multi-cloud infrastructure. Its focus is on linking data to provide otherwise untapped insight and to allow real-time analysis on a growing range of integrated data assets. It builds on the success of ONS’s Trusted Research Environment, the Secure Research Service (SRS), which has been securely providing a variety of de-identified data to accredited researchers for over 15 years, and like the SRS, it will not provide any personal information that could be used to identify individuals.

The private BETA version will allow a selection of government analysts to compare and combine data held by ONS and other departments, helping to unlock the full potential of data, inform policy decisions and encourage collaboration across government. Launching next spring, a public BETA will open the door for accredited researchers outside of government to use the new service.

The launch of the BETA will take data linkage and collaboration to the next stage with three new and ambitious government priority projects:

  • an ONS and Her Majesty’s Treasury collaboration to investigate in detail how wages change across the country to provide evidence to inform levelling up policies
  • working with the Valuation Office Agency (VOA) to provide better information on the energy efficiency of homes around the country as part of wider work to help measure the UK’s progress towards reaching net zero by 2050
  • a collaboration with Department for Business, Energy, and Industrial Strategy to analyse how text from local BBC news sources across the UK can be used to understand concerns of communities around the country

Under robust security and ethical protocols, the service will enable analysts to access, link, analyse and disseminate a range of data, encouraging a new culture of research collaboration that will enable rapid policy decisions and interventions.

Collaboration is crucial to enable new insights. The case study on the Energy Efficiency of Housing publication highlights how inter-departmental data sharing enabled the creation of linked datasets and enhanced the production of subnational statistics.

Improvements to the energy efficiency of the UK’s building stock will play a crucial role in achieving net zero to address climate change. When schemes aimed at improving energy efficiency and meeting climate targets are developed, it is increasingly important to have statistics that inform the public, and future policies, on the energy efficiency of homes and their decarbonisation. Having that information at a local level can add additional value by helping to target specific policies when needed.

This research project was developed by the Office for National Statistics (ONS) to complement headline figures published by the Department for Levelling Up, Housing and Communities (DLUHC).

The project provides more detailed insight into the energy efficiency of housing in England and Wales at subnational geographies and with analysis into patterns of energy efficiency by housing variables such as property age, tenure, and property type. The quality assurance processes implemented in the project meant that analysis of main indicators such as ‘Median Energy Efficiency Score’ could take place at local level (Middle layer Super Output Area, MSOA) with sufficient confidence.

Cross-government cooperation formed an important part of this research and will do even more so in the future. The project involved the linkage of two datasets from different departments in a secure environment to produce the data upon which the analysis was conducted. Dwelling level data provided by the Valuation Office Agency (VOA) and Energy Performance Certificates (EPC) published by DLUHC Open Communities were used to produce a dataset of complete, quality assured records for around half of domestic dwellings in England and Wales. Communication with partners in VOA and DLUHC meant that the efforts to join these datasets were successful as ONS was provided with the necessary expertise and supporting documentation (metadata) to enable a successful link. Communication has already begun between ONS and other departments such as the Department for Business, Energy, and Industrial Strategy as well as the devolved administrations to further develop the scope of this project in the near future.

2.3 Improve the way in which methodologies used to produce subnational statistics are discussed, agreed and shared across the GSS and where appropriate, wider research and analytical community

This principle requires collaboration with academic and research partners. For example, the Economic Statistics Centre of Excellence (ESCoE), Administrative Data Research UK (ADR UK), and existing GSS expert groups whose aim is to maintain and share best practice and build expertise and capability in their specific areas. For example, the Small area estimation and modelling expert group, the Sample design and estimation group and the Statistical disclosure control expert group.

Building on the GSS data linking guidance and cross-government review, we will share best practice for data linkage through the GSS data linkage champions.

We will also follow the guidance on standard statistical methods and developing Reproducible Analytic Pipelines (RAP), sharing code and methods for analysis as well-documented, public assets for other research groups nationally to re-use and extend. By facilitating a wider knowledge sharing, we will improve the efficient use of resources and we will ensure that the value from GSS expertise is built on across the research and analytic community.

Successful collaboration in the modern statistical world must be international, reflecting the nature of issues the statistics provide insights on. We will support the  GSS international strategy, tapping into the network of International Liaison Officers and taking an active part in global forums, providing statistical leadership on subnational statistics.

We will continue to work with, and learn from, our international partners to ensure subnational statistics and data are at the heart of the UK’s development policies and agenda, as ONS did to develop the Open Sustainable Development Goals Platform which is now used by several countries, regions, and cities worldwide.

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Ambition 3: Improve the dissemination of subnational statistics

Producing more timely, granular and harmonised subnational statistics which meet user needs through strong collaboration and capability is not enough. To ensure they are truly provided for the public good, they must be easily accessible, usable and understandable to our users.

Feedback suggests that our users want increasingly rapid access to subnational data and statistics covering a breadth of cross-cutting topics, presented and delivered in digital formats which meet diverse needs. Difficulties in locating and accessing subnational statistics is one of the main barriers.

Therefore, this strategy sets out a series of principles to ensure the production of subnational statistics goes hand in hand with their dissemination, particularly through digital services.

By improving the discoverability of subnational statistics and by considering the needs and accessibility requirements of our users when determining ways to present subnational data and statistics, we the GSS, will enable our users to draw insights from our outputs more efficiently. By equipping our users with necessary guidance, they can be confident in the insight they extract from our subnational statistics and in the decisions they make based on it. Local decision makers will be able to access data-led evidence to guide the planning and policy decisions needed in their area, and residents will be able to access better data to understand the opportunities and challenges that their area face.

3.1 Ensure our stakeholders are informed about new and updated subnational outputs published across the GSS, making them easy to locate

Our vision is to develop a new service, the Explore Subnational Statistics service, to find, analyse, visualise and compare subnational data and statistics by standardised geographies and by flexible user-defined areas.

The development of this service will be approached as an iterative and evolving process, starting from focussing on ONS statistics with a vision to expand it through cross-government collaboration.

A range of past and present dissemination services will be explored to understand the functionality and user experience. This includes the Neighbourhood Statistics Service (NeSS) active between 2001 and 2017, Nomis first launched in 1981 and still widely used by subnational statistics users, Explore education statistics, Northern Ireland Neighbourhood Information Service (NINIS), the Office of Rail and Road data portal, Public Health Profiles, Scotland’s Census website, statistics.gov.scot, StatsWales, and the recently launched  cross-government UK Climate Change Statistics portal among others.

While we work towards our vision for the Explore Subnational Statistics service, we will seek to improve user journeys through other relevant services via cross-referencing, including clear hyperlinks and explanations.

The case studies on Northern Ireland Neighbourhood Information Service (NINIS), Scotland’s Census results portal and Nomis describe dissemination services currently available to users

NINIS is a service provided by the Northern Ireland Statistics and Research Agency (NISRA). It provides access to statistical and locational information relating to small areas across Northern Ireland as well as Northern Ireland as a whole. Information is available across 11 statistical themes as well as Census 2001 and 2011, Deprivation, Making Life Better and Neighbourhood Renewal.

The NINIS website contains datasets for statistical and administrative geographies; area profiles providing statistical snapshots of your area; and mapping facilities that enable statistics to be interpreted readily in a spatial context as well as other data visualisation tools. A comprehensive suite of interactive content is available on the NINIS website and includes population pyramids and interactive maps. These offer powerful data visualisation tools to aid research and flexibility in data dissemination. Free Information workshops on NINIS are provided for anyone with an interest in Neighbourhood Statistics. The primary aim of the workshop is to provide information on the background to and purpose of Neighbourhood Statistics and to give a demonstration of the NINIS website.

Scotland’s Census website is managed by the National Records of Scotland (NRS). It provides access to results for the 2001 and 2011 Scottish Censuses, and will also be the platform for publishing 2022 Census data. The data are available at national level down to small areas for Scotland.  Results are provided in a range of formats to meet user’s needs, including commentary, visualisations and the ability to view and download the Census tables. The Area Overview section of the website enables users to view and compare Census results across Scotland, providing summary statistics for the area they are interested in and the ability to compare against other areas in Scotland or against previous censuses.

For the 2022 Census results NRS are planning to make use of a Flexible Table Builder, this will allow users to create their own Census tables. This will also offer users the ability to create their own bespoke geographies which can be saved for reuse.

Nomis is a web-based dissemination tool for subnational statistics run by the University of Durham on behalf of the Office for National Statistics. First launched in 1981, Nomis houses an extensive range of government statistical datasets covering aspects of the UK labour market, life events and other topics from the Office for National Statistics.

Nomis offers three main ways to access data:

  • area profiles provide key summary data from a range of sources for a single area
  • data downloads provide access to the full range of data, allowing users to formulate their own queries to explore the data sources in greater depth
  • Nomis API provides capability for programmers to perform a variety of structural discovery and data download requests

Nomis provides a user interface to allow people to easily access data and a free helpdesk to assist users with any problems they may have using the site.

The statistics disseminated through Nomis include:

  • labour market statistics for local areas from a variety of sources including the Annual Population Survey (APS), out-of-work benefits, Business Register and Employment Survey (BRES), Annual Survey of Hours and Earnings (ASHE) and UK Business Counts
  • Censuses of Population from 1981 to 2011
  • life events data covering topics such as marriages, divorces and deaths
  • data from official government sources (Office for National Statistics and Department for Work and Pensions)

3.2 Make subnational statistics accessible to a wide range of users

We will continue to consider accessibility requirements while planning the dissemination of our subnational statistics. This includes the language, literacy, format and comprehension when publishing subnational evidence and presenting analysis, in line with the 2018 Accessibility Regulations. We will consider accessibility requirements while planning the dissemination of our subnational statistics and we will aim to minimise the learning curve for users moving between different statistics dissemination services.

In doing so, we will follow the principles provided by the Government Digital Service in the Government Design Principles, and collaborate and share learning with colleagues working on the Integrated Data Service (IDS) and Census 2021 outputs dissemination.

3.3 Provide users with the necessary guidance on how to use subnational statistics and how to communicate their quality

We will work with our quality champions to pursue the second goal of the GSS quality strategy: ensuring our data are of sufficient quality and communicating the quality implications to users.

We will follow GSS guidance on communicating quality, uncertainty and change and we will disseminate quality indicators with our subnational statistics in plain language.

We will continue to provide our users with indications on expected publication dates for new statistical releases, contact details for the team responsible for producing the statistics and prominent transparent information on revisions and methodological changes with upfront guidance on how to manage these changes across timeseries and geographies.

The case study on Local Knowledge and Intelligence Service presents how the service supports users in the use and interpretation of subnational statistics on public health.

The Local Knowledge and Intelligence Service (LKIS) sits within the Office for Health Improvement and Disparities within the Department of Health and Social Care. A nationally distributed service with teams based within each region of England, it works across three main topic areas: analysis, training and knowledge mobilisation.

Each regional team has specialists in knowledge mobilisation whose aim is to promote the use of intelligence products in public health decisions, ensuring the products get to the right people at the right time, are understood, and can be used for maximum impact. In other words, using data in a way which has the greatest impact on the health of local people. The regional teams do not work in isolation; within the national Knowledge Mobilisation network they work together on ‘do once and share’ projects. This allows them to maximise the resources, share learning and offer training.

For example, during summer 2020, LKIS was asked to facilitate a knowledge-to-action process for a selection of daily and weekly Coronavirus (COVID-19) reports. Produced in collaboration between LKIS and the UK Health Security Agency (UKHSA)’s Field Services, these reports were initially produced in a variety of formats, such as pdf, Excel, Word and HTML, with a programme of transition to a PowerBI portal. Products included COVID-19 surveillance, contact tracing, excess mortality and early warning reports. Key messages needed to be timely, accessible and understood by those taking public health action in response to the pandemic.

To address the key questions, the team set out to gather user insight by formal and informal feedback. The feedback was collated from meetings with directors of public health and local authority health intelligence teams, as well using the ad hoc enquiries that the UKHSA teams received. This was topped up by a rapid feedback exercise with local authority intelligence leads. The team worked closely with the producers of the various reports, who very quickly adapted changes in line with the feedback, where possible. Other support for the key messages included the development of webinars, guidance documents and a mechanism for systematically gathering and responding to user needs.

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Explore Subnational Statistics service

This strategy presents three ambitions underpinned by principles which together constitute the vision for the creation of the Explore Subnational Statistics service a single service for the dissemination of subnational data and statistics organised by standardised geographies and able to accommodate flexible user-defined areas.

Based on the Code of Practice for Statistics’ three pillars – Trustworthiness, Quality and Value – the Explore Subnational Statistics service aims are to:

  • be a one-stop shop, allowing users to find, analyse, visualise and compare subnational data and statistics produced across the GSS in a single place
  • allow users to interrogate, download and explore high-quality GSS subnational statistics
  • provide public value by making subnational statistics available at a sufficient level of granularity, allowing users the flexibility to select geographical breakdowns according to their analytical needs
  • provide public value by allowing users to make meaningful comparisons across different measures to better understand local areas
  • draw upon a structured data repository based on small area geography building blocks
  • promote trustworthiness by embedding dynamic disclosure control to safeguard confidentiality of data and comply with data protection regulation, and signposting GSS guidance on statistical disclosure control
  • ensure a sustainable future of the service through automated dissemination of data for easier use by analysts

The project described in the case study is the first step on our journey towards the Explore Subnational Statistics service. It provides gross value added (GVA) for lower levels of geographies, on which users are able to build larger user-defined analysis areas. This is in line with the GSS Geography Policy, which states that source data relating to individuals, households or businesses should be collected and recorded at the lowest possible geographical level using a standard identifier, and official statistics for any geographies should be built from whole statistical building blocks.

The Office for National Statistics (ONS) is working on providing more granular economic data to users. This project develops and applies a method that disaggregates GVA to lower levels of geography, with flexibility for users to define their own geographies for analysis. The project will, for the first time, publish GVA for lower levels of geography (below local authorities)​.

The project apportions local authority level GVA to lower-layer super output areas (LSOAs), with the apportionment process constrained to the local authority totals. The LSOA data are thus the building blocks that can be used to build higher levels of geography. The project uses VAT Admin turnover data, the Inter-Departmental Business Register (IDBR) employment, dwelling stock and/or population data as bases for the apportionment process. Total LSOA GVA without industry disaggregation are produced because the latter is disclosive at that level of geography. The total LSOA GVA data are also disclosive in a few cases, and will not be published. Instead, the data will be accessible through the Secure Research Service.

Total GVA for middle-layer super output areas (MSOAs) or equivalent are published as the lowest level of geography. Data for higher level geographies are also published, built using the building blocks (e.g. parliamentary constituencies and health board areas). The accompanying article explains the method and processes and also illustrates the flexibility of using the building blocks in four test cases: Clyde River Region, the Clyde Gateway Region, the West Midlands Metro Region, and Old Oak and Park Royal Development Corporation (OPDC). For all the areas, the article presents maps using the best-fit approach. It also presents a map of the OPDC area based on the intersection approach.

Our vision for the Explore Subnational Statistics service is ambitious and we know it will require strong collaboration and appropriate resources across the GSS.

For this reason the first step of this journey will be learning from the successes and lessons of services such as Nomis and Neighbourhood Statistics (NeSS), and from the user research informing the Integrated Data Service (IDS) and Census 2021 outputs dissemination.

The second step will be engaging with a range of subnational data and statistics users to identify their needs from and expectations for the service, and define appropriate user journeys to model the service on. Aligned to the principles of the GSS user engagement strategy for statistics, engagement with users will happen on an ongoing basis across a range of initiatives, including identifying needs and expectations for the service, acknowledging that there is no one-size-fits-all approach to subnational statistics’ production and dissemination.

Expanding on the existing networks of users across the GSS will be crucial to and use services such as the Secure Research Service and the UK Data Service. For example, the network of local public health decision makers developed by the Local Knowledge and Intelligence Service in the Department of Health and Social Care (DHSC), the network of local enterprise partnerships, and the established channels of communication between combined authorities in England and ONS Cities and Analysis team. This will include continuing to engage with academics and researchers who have an interest in subnational statistics and use services such as the Secure Research Service and the UK Data Service.

In summary, this strategy has set out an ambitious intention of the GSS to produce and disseminate subnational statistics in a more consistent, granular and timely way for the public good. Grounded firmly in user needs, the Explore Subnational Statistics service, and subnational data strategy will help to ensure that the GSS is able to respond flexibly to shifting priorities for both policy and public understanding.

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Glossary

Code of Practice for Statistics – the Code of Practice for Statistics sets the standards that producers of official statistics should commit to. Compliance with the Code gives you confidence that published government statistics have public value, are high quality, and are produced by people and organisations that are trustworthy.

Government Analysis Function – a cross-government network of around 17,000 civil servants involved in the generation and dissemination of analysis. The government profession groups within the Analysis Function include:

Government Statistical Service (GSS) – the cross-government community of all civil servants working in the collection, production and communication of official statistics.

International Territorial Levels (ITL) – as of 1 January 2021, the internationally comparable regional geography for the UK is the International Territorial Levels (ITLs) geography. This has replaced the Nomenclature of territorial units for statistics (NUTS) geographies for the UK that were operational when the UK was a member of the European Union. The International Territorial Levels and associated lookups are available to download from the Open Geography portal.

Office for Statistics Regulation (OSR) – OSR is the regulatory arm of the UK Statistics Authority, a body established by the Statistics and Registration Service Act (2007). It is independent from government ministers and separate from producers of statistics. Their role is to set the statutory Code of Practice for Statistics, assess compliance with the Code of Practice and award National Statistics designation.

Official statistics – statistics produced by crown bodies, those acting on behalf of crown bodies, or those specified in statutory orders, as defined in section 6 of the Statistics and Registration Service Act 2007. The term official statistics includes National Statistics, experimental statistics and statistics that have not been assessed as fully compliant with the Code of Practice for Statistics.

Output Area (OA) – OA were created for Census data, specifically for the output of census estimates. The OA is the lowest geographical level at which census estimates are provided. OAs were introduced in Scotland at the 1981 Census and in all the countries of the UK at the 2001 Census.

Public good – our statistics should serve a very wide range of users and answer people’s questions. Our references to serving the public good in the strategy are based on the Statistics and Registration Service Act 2007 definition and include:

  1. informing the public about social and economic matters
  2. assisting in the development and evaluation of public policy

Super Output Area (SOA) – SOAs are a geography hierarchy designed to improve the reporting of small-area statistics. In England and Wales Lower Layer SOAs (LSOA) with a minimum population of 1,000 and Middle Layer SOAs (MSOA) with a minimum population of 5,000 were introduced in 2004. Unlike electoral wards, LSOAs and MSOAs are of consistent size across the country and won’t be subject to regular boundary change. In Northern Ireland there is a single layer of SOAs, with a minimum population of 1,300. The Scottish equivalents of SOAs are Data Zones (DZ) with a minimum population of 500 and Intermediate Zones (IZ) with a minimum population of 2,500.

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