The plan for ONS economic statistics

Core economic and population statistics produced by the Office for National Statistics (ONS) are vital to how the UK understands and manages its economy and society. They shape decisions made by national and local governments, the Bank of England, businesses, and households every day. We have heard the clear messages from our users that some of these statistics are not meeting expectations on quality and trustworthiness. We take that extremely seriously.

First, ONS acknowledges and regrets these quality issues. We agree with the Office for Statistics Regulation (OSR) that such acknowledgement is the foundation for any credible plans for improvement.

Second, ONS recognises the urgency with which these issues need to be addressed. This document sets out new plans for the investment of a further £10m (including around 150 skilled people) into core economic and population statistics. This investment will build over this financial year and into early 2026 to 2027 by re-prioritising our original business plan, including rapidly deploying skilled people to the work from other areas of the office. On top of this, we will make additional investment in later years to support the effective implementation of the System of National Accounts (SNA25) changes and updates to associated International Frameworks.

This plan is our response to restore quality and confidence in our economic statistics. It sets out how we currently assess the quality of our core statistics, what we are doing to address issues and risks, and how we are putting the right foundations in place for the future. It reflects a clear commitment to openness, about where things stand today, where we need to do better, and how we will be held to account for progress. Together, these changes will help us deliver lasting improvements and build a more resilient statistical system that underpins confident decision making on the UK economy and ensures a clear understanding of society.

Improving these statistics will take collective effort. The expertise, judgement and leadership of colleagues across the ONS will be central to success. That means building a culture that values quality at every stage, from the data we collect to how we quality assure, process, analyse and publish it, and supporting people with the time, tools and confidence to challenge and improve what we produce.

In some cases, this may mean revising published figures or historical series. That is not a sign of failure, but of a statistical system willing to evolve, led by evidence, and open about how it improves. We will work closely with users to ensure revisions and breaks in series are well managed, with support provided to users.

The implementation of this plan will complement our ongoing commitment to produce the vital statistics that our users expect – and need – from their National Statistical Institute. We are setting a clear direction which we will pursue relentlessly: a transparent, inclusive and high-quality approach focusing on the statistics that matter most. We are moving at pace. I am grateful for the strong support and challenge of key stakeholders including HM Treasury, the Bank of England, the Office for Budget Responsibility, the Devolved Administrations and the Office for Statistics Regulation. This momentum will continue. I am proud to support this work and proud of colleagues across the ONS who are driving it forward.

Emma Rourke

Acting National Statistician

Responding to issues with quality

The Office for National Statistics (ONS) is the UK’s national statistical institute. It is responsible for delivering economic statistics, alongside social, population and environmental data. Core economic statistics include those measuring inflation, Labour Market, Gross Domestic Product (GDP) and the public finances. These statistics, and those on population, inform public-policy and business decisions alike, supporting the entire breadth of the economy.

This document has been prepared in the light of high-profile problems relating to several of these key statistics, and the consequence those failures have had on users and the ONS’s reputation. These problems include the impact of low response rates on Labour Force Survey statistics, and errors in trade, consumer prices, and producer prices statistics.

As the Office for Statistics Regulation (OSR) notes in their recent Systemic Review of economic statistics, ONS has found it difficult

• to maintain real-terms funding for core economic statistics and to adequately support data collection, particularly social and business surveys. This partly reflects the diversion of statistical and survey staff to the Coronavirus pandemic response, and the impact of major new programmes such as the Integrated Data Service and Future of Population and Migration Statistics;
• to move promptly away from reliance on legacy IT systems, and to make progress with administrative data;
• to ensure adequate expertise in statistical production teams, with unfilled vacancies and loss of experienced staff and,
• to act upon early warnings of emerging quality concerns and delivery risks.

This document directly addresses these problems, and the impact they have caused. It covers both what needs to be done, and how ONS plans to do so. Annexes A to C cover in detail plans for individual statistics: while there are some common themes, it is important in rebuilding confidence to be explicit about what needs to be done on each one in turn. In addition, we have published the Survey Improvement and Enhancement Plan to restore confidence, ensure strategic transparency and enhance focus on quality of data inputs. All of which will be reflected and published in a revised strategic business plan.

These details also illustrate why ONS has confidence that quality can be improved, and in many cases, in relatively short order. The plans reflect approaches to change which have been shown to work in the past but now need to be used at scale and with consistency. We also will always remain open to feedback from our users, including on this plan. As a result, some of the details and timings are subject to change.

What needs to be done

The production of our statistics is underpinned by the Generic Statistical Business Process Model (GSBPM). The model encompasses all aspects of statistics production, from data collection through statistical processing to publication, all of which in turn rely on skilled expertise and technology.

A stylised presentation of the building blocks needed to implement the GSBPM for the ONS’s core economic and population statistics is shown in Figure 1. Using this model helps us ensure our resources and improvement activity are focused on priority areas.

Figure 1: The ONS building block model

Notes:

1. Methods, data and systems underpin all our statistics. Separate international manuals for the Government Finance Statistics (GFS), System of Environment Economic Accounts (SEEA) and the Manual for Government Deficit and Debt are also relevant.

Download this image Figure 1: The ONS building block model

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The foundational blocks are the ONS’s common capabilities: the indexes, classification systems and registers which drive our survey designs and enable us to link data; our surveys; and our collection systems for non-survey data. Consistency and coherence across these foundations is crucial to produce quality statistics.

There is considerable detail in our plans to improve each of these foundational building blocks, as described in Annex A: ONS common capability.

This plan focuses on the ONS’s core economic statistics, which we have grouped into five statistical themes: labour market, prices, public sector and balance of payments and trade; and their aggregation with other data to create the National Accounts and calculate Gross Domestic Product (GDP) and other headline indicators.

Since different statistics face different challenges, our plan provides detailed plans for each core economic statistic. These plans (excluding GDP) are set out in Annex B: Statistical themes.

For labour market statistics, a particular challenge has been the sharp decline in response rates since the pandemic, exacerbated by capacity constraints on our interviewer community. The subsequent reduction in quality and reliability of the aggregate estimates saw the ONS suspend publication of the Labour Force Survey (LFS) in October 2023. While publication has resumed and quality has been improving (as set out in our recent assessment) following the implementation of our LFS improvement plan, we recognise the critical use made of these statistics and the significant challenges the quality issues have resulted in, for users of them. We are committed to learning lessons as we continue towards our transition to the Transformed Labour Force Survey (TLFS) with our plan for the way forward, endorsed by key stakeholders, set out in the recent Labour Market Transformation: update on progress and plans publication and summarised in Annex B.

Plans for improving GDP are set out in Annex C: National Accounts and GDP. This reflects both the greater complexity of GDP itself, and the context of changing international macro-economic statistical standards (IMSS), such as the new System of National Accounts (SNA25), the new Balance of Payments Manual (BPM7), and the new Standard Industrial Classification (SIC2026). These changes aim to ensure that economic statistics reflect the modern economy, driven by digitalisation, global value chains and a proliferation of hybrid and intangible-intensive business models.

Adopting these new international standards within the UK National Accounts requires changes across most of the common capabilities and statistical themes described above: from the new Statistical Business Register, new survey and administrative data collection and new time series methods; through to analysis, production and publication. As a result, both Annexes B and C contain detailed plans of relevance to delivering new international standards for GDP and the Balance of Payments and further information can be found in the supplementary section that summarises the suite of workstreams that make up our approach to adhering to the IMSS.

A sixth statistical theme is core population statistics, given its importance to economic statistics. Population estimates and projections are used in economic statistics as denominators and informing survey weights. They underpin productivity and GDP per capita estimates. They also influence surveys including the Labour Force Survey, enabling measures such as rates of employment. Users of ONS economic statistics also value population outputs in other ways, such as to inform fiscal forecasts and improve understanding of the impacts of migration or an aging population on the labour market. Detailed plans for this area are set out in Annex D: Core population statistics.

Population estimates are underpinned by a decennial census. To support the future system of population and migration estimates, the UK Statistics Authority Board has recommended to the UK Government that a whole population census of England and Wales is undertaken in 2031. This would combine the strengths of a whole-population data collection with the additional value that administrative data can provide. The decision to undertake a census rests with the Government. If it is confirmed by the Government, planning and testing for a 2031 Census in England and Wales will be carried out by the ONS in parallel to this plan.

How the ONS will deliver the necessary changes

The ONS is consciously addressing quality improvement in a new way.

Learning the lessons of recent years, much more emphasis will be placed on continuous improvement, enabling production teams to have the resource, bandwidth and necessary skills to identify and deliver changes necessary in their area and engage in continuous development. This contrasts with past practice in which the great majority of funding for improvements were ring-fenced within specific programmes, under separate management from production areas. Such programmes are necessary for particularly complex change and will continue to be used where appropriate.

Continuous improvement requires clear metrics. The ONS plans to roll out to each production area the framework for Quality Excellence already successfully trialled in two areas. The framework enables production teams themselves to monitor and improve the quality of processes from data collection through to statistical output. The two pilots were undertaken in one of our annual structural business surveys (UK Manufacturers' Sales by Product) and in our Mid-Year Population Estimates.

The pilots identified how targeted measurement of the processes could identify areas of low performance and risk (including legacy technology and pipelines), providing an opportunity for early intervention, course correction and identification of future improvements.

Continuous improvement also relies on having the right skills in production areas. Each of the examples below resulted from a multi-disciplinary team working collaboratively, bringing together subject matter expertise and statistical and digital skills. The ONS has taken steps already to strengthen its capacity for continuous improvement and plans to increase this capacity further. Every core statistical production area will have a continuous improvement team embedded of 4-6 people, which will be retained in later years. This will be supplemented by additional resources for specific additional tasks.

Parallel working across different areas also requires the appropriate level of common standards, whether in software development, delivery or methodology. The ONS has already established both its Data Preparation Platform, and its Data Access Platform, providing enterprise level capabilities which can now be exploited by individual teams, working in parallel. The ONS is taking steps to ensure that all development follows the appropriate coding standards, standard deployment processes, standard tooling and that these are universally used and monitored. We will also have more automated metrics on code quality and risks to systems. A Statistical Method Library (SML) is being further developed to ensure access to common methods that are configurable and coded to best practice coding standards. The ONS already has strong standards and will ensure controls are in place to assure their use.

When each of these elements are brought together, individual production teams can make material improvements to the quality of their statistics. A key focus will be making our statistical production workflows reproducible, mainly through automation, by building Reproducible Analytical Pipelines (RAPs) where they do not yet exist. RAPs create a transparent, auditable and verifiable process, embedding Quality Assurance using logging and automated testing. They reduce the risk of errors occurring in the production process and can improve timeliness and free up staff time for curiosity and analysis.

The examples below illustrate how this continuous improvement approach has been used in ONS:

• House Price Index (HPI) – A recent project to modernise the HPI reduced reliance on legacy software, reduced manual steps and cut the system’s monthly run time by several hours, significantly reducing the risk of error. The improvements were delivered by a small development team working together with the production area, adopting modern software engineering practices, including regular system updates and the responsible use of AI-assisted coding. Targeted training was also provided to the production team, enabling them to maintain and enhance the system independently without the need for future development projects.
• Business Enterprise Research & Development (BERD) – A project to transform the R&D statistics successfully redesigned and re-platformed the end-to-end statistical production, including significant improvements to sample, methods, systems, and the use of administrative data. The project was phased to enable early value, rather than waiting for a full transformation. The project delivered improvements because of collaborative, iterative work between expert methodologists to ensure robust design, a team of coders and developers that knew how to build systems to agreed standards, and a small, dedicated team that understood the requirements for statistical production. This ensured there was capacity to support the development but protected the production team in their busy production rounds.
• Annual Survey of Hours and Earnings (ASHE) – A project to deliver an AI-powered text classification tool into live production. The tool improved data quality by more accurately assigning employees to occupations, and halved the time required to code survey responses, allowing staff to focus on other critical aspects of the data collection process. The project progressed rapidly from prototype to production and was the first use of Large Language Models in ongoing statistics production at the ONS. Developed in close partnership between digital specialists and the ASHE team, the work spanned cloud infrastructure, user interface, and AI model evaluation.
• Core population statistics inputs – An embedded team of coders and statistical production experts were tasked with building RAPs. The first pipeline brought in coding experts from other areas of the office who upskilled the team in how to build and maintain pipelines. The initial RAP was built for Weekly Deaths statistics and created efficiencies, significantly reducing run-times. Since the initial pipeline build, the embedded team has now rebuilt over 20 Reproducible Analytical Pipelines, including for Births and Deaths statistics that input into core population statistics.

Not all changes required can happen with a small continuous improvement team. Therefore, the ONS will continue to use a more expansive approach for changes that are larger or more complex, building on its transformation experience, for example in introducing much richer datasets into consumer prices.

All these improvements are illustrations of the ONS’s ability to deliver change successfully.

The ONS’s new approach will be underpinned by clear and effective assurance and governance that will enable monitoring and evaluation of progress and impact. An essential factor in ensuring greater curiosity, challenge and effective quality assurance is ensuring that data collection and statistical production teams are sustainably staffed, focus on building and retaining domain expertise, are able to draw on broader economic expertise and engender a culture of curiosity and analysis. Moving from legacy systems to reproducible workflows will also assist, with automation reducing the likelihood of errors and more staff time available for detection. This includes greater scrutiny of data supplied by other government departments and businesses – a key factor in some recent errors.

Alongside this, we remain deeply committed to both engaging users and drawing on external expertise to ensure our work remains relevant, high-quality, and responsive to the evolving economic landscape.

We will continue to actively seek external insights, collaboration and challenge through our various channels, including involving external expertise to bring academic rigour and independent analysis to our statistics. In particular, our Stakeholder Advisory Panels on Labour Market, Prices, Migration, and (in the future) National Accounts; our Technical Group on Classifications, and the National Statistician's Committee for Advice on Standards for Economic Statistics serve as vital forums for dialogue with a broad range of users, including academics, policymakers, and industry representatives. These, alongside our range of other regular engagement with users, will help ensure our outputs meet user needs, reflect the latest thinking, and support robust, evidence-based decision-making across the UK economy.

Conclusion

This plan sets out our new approach to stabilise and improve the quality of our core economic and population statistics. It reflects new decisions about priorities, resulting in new investment in these core statistics, and a change in the way ONS makes decisions. ONS is committed to rebuilding its reputation, with strong leadership and the right skills and culture to succeed. We welcome any feedback from users of these statistics as we progress.

We will review and update the plan annually at around the start of each financial year, to report on progress and reflect lessons learnt from implementation, as well as to respond effectively to emerging opportunities and challenges.

A1: Indexes, Classifications and Registers

Indexes, classifications and registers are fundamental in the production of statistics.

• Indexes are the backbone for creating registers.
• Registers act as sampling frames for surveys, describing the population of interest that allows for representative samples to be drawn that provide the foundation to quality statistics.
• Indexes and registers provide the opportunity for the population of interest to be categorised in different ways, for example, size of business, geography and type of activity.
• Classifications are an important way of being able to categorise and classify industries, products or occupations.

These elements are described in sections A1.1 to A1.3.

A1.1 Indexes

The various statistical registers, sampling frames and reference products are created from administrative data that is combined into indexes of people, organisations and places. These provide the raw material for the registers and are also used to enable data linkage at scale and with improved consistency, via the Reference Data Management Framework (RDMF). This technology for improved data linkage also allows us to provision de-identified datasets without losing analytic effectiveness – improving data security and confidentiality by ensuring that no personal data is used in the preparation of analysis.

Briefly, the core indexes are:

• The Demographic Index, which is a comprehensive view of everyone who has interacted with the administrative state since 2016. It allows a view of the resident population in each year since to be derived using a set of rules. It also enables the processing and linkage of any dataset that includes individuals and allows their details to be removed and replaced with a unique identifier which allows analytic use and data linkage.
• The Business Index, which covers all organisations legally operating in the country, from multi-nationals through charities to sole traders and contractors. It concentrates on legal entities and enables the Statistical Business Register to produce much more granular reporting and local unit data for samples.
• The Location Index, which combines the Address Index, which improves on commercially available address services by improving granular detail of multiple occupancy addresses, and the Geography Index, a collection of statistical geographies, which are crucial for sub-national statistics.
• The Classifications Index, which is a means of mapping Standard Industry Classification (SIC) and Standard Occupational Classification (SOC) codes at a row level, using machine learning methods to enable more accurate classification of responses and administrative data.

A1.2 Classifications

Updates to nearly all the core classifications that underpin the structure of economic statistics have been agreed internationally.

These include:

• Standard Industry Classification (SIC)
• Central Product Classification (CPC) and Classification of Products by Activity (CPA)
• Classification of Individual Consumption According to Purpose (COICOP)
• Standard Occupational Classification (SOC)

These generational updates reflect the modern-day economy; driven by digitalisation, global value chains and proliferation of hybrid and intangible-intensive business models. Therefore, to maintain integrity of our statistics in the UK’s evolving economy it is imperative we adopt these foundational changes as soon as we can. These types of changes necessitate the need to closely review and update both the data collection, and statistical methods and systems which are used to compile the economic outputs.

Due to the exit of the UK from the EU, and the cross-governmental impact of the changes to the Standard Industrial Classification (SIC), a consultation process was carried out between October 2023 and January 2024. This agreed that the UK would follow the internationally recognised NACE framework (Nomenclature statistique des activités économiques dans la Communauté européenne), but with flexibility to make changes at four- and five-digit levels to reflect the structure of the UK economy.

By March 2026

• The ONS plans to complete a cross-government co-ordination and revisions process on lower levels, resulting in an agreed UK Standard Industrial classification (SIC2026) that will be adopted by the ONS and across the GSS.

Alongside this consultation work we will look at the impact of adopting SIC2026 on the core National Accounts, including methods, data and system reviews; and conduct an evaluation of the detail needed as part of supply use balancing. This is crucial to ensure analysis over time. This work will also plan out and appraise the impact of the updates to the product classification (CPA), with the expectation that changes in CPA will mirror those in SIC.

In conjunction, we will continue to move our Household and Consumer Price Indices to use COICOP2018 (see section B4: Prices); and continue work within Social Surveys and Labour Market statistics to adopt an updated SOC (see sections A3: Social Survey Data and B2: Labour Market respectively for further detail).

The implementation of SIC2026 will depend on having a fully functional Statistical Business Register with the ability to dual code businesses to the old and new classification (this is covered in the next section) and updating the systems used to produce economic statistics.

A1.3 Registers

The ONS holds three registers:

• Address Register – The address register is built from AddressBase, refined with further information about properties, and is used as a sampling frame for households.
• Statistical Population Dataset (SPD) – Built from the Demographic Index along with various other administrative data sources, the SPD is used in population estimation.
• Statistical Business Register – Brings together data from administrative and survey sources to provide a list of businesses in the UK and their structure. The register is used as a sampling frame.

The Business Register is critical to production of core economic statistics and so plans for this are set out here.

A1.3.1 Statistical Business Register

The current sampling frame for business surveys is the Inter-Departmental Business Register (IDBR) which brings together data from administrative and survey sources to provide a list of business within the UK.

The IDBR meets the current System of National Accounts and Balance of Payments requirements and businesses are classified to the current Standard Industrial Classification (SIC2007). However, the IDBR will not support new international standards and future user requirements because:

• it has incomplete coverage of small and micro businesses: only businesses that have a VAT, PAYE and Companies House registration are included;
• samples can only be stratified by employment, turnover or a combination of the two and these variables can be poorly correlated with the objective of our surveys, for example our financial surveys;
• it is not possible to incorporate additional administrative data to ensure more relevant sample designs.

In 2022, a programme of work was commissioned to replace the IDBR with the Statistical Business Register (SBR). The SBR will provide an extended population data set through ensuring all businesses registered with Companies House are included. By also incorporating additional administrative data (for example Corporation Tax), the SBR will provide greater flexibility in the way business survey samples are created. The addition of Self-Assessment data when available for use will further enhance the detail the register holds on the self-employed.

To adopt the new Standard Industrial Classification (SIC2026), the SBR needs to be dual coded with the existing SIC and the new. Changes needed to meet new SNA standards can also be incorporated.

The sampling and methods changes within the SBR along with the changes needed to business surveys to make use of these will be implemented in an integrated way across our core economic statistics.

The ONS plans to deliver and fully implement the SBR as follows:

By March 2026

• The extended data set available along with the ability to produce all samples.
• An implementation plan for adoption of the SBR across the ONS’s core economic statistics in place.

By March 2027

• The SBR to incorporate SIC2026, allowing surveys to transition to the SBR; along with the ability to process the Business Register and Employment Survey, resulting in another survey being removed from legacy technology.
• Annual critical path surveys and supporting systems implemented including reduction of legacy technology.

By March 2028

• A review of methods and sample design, including parameters, undertaken, based on changes to the SBR universe.
• Aim that all surveys transitioned to use the SBR for their sampling frames.

A2: Business Surveys

A2.1 Introduction and current challenges

The ONS is responsible for the collection and transformation of a suite of 74 surveys, that are used as input sources for economic statistics such as monthly Gross Domestic Product, Business Prices and Average Weekly Earnings.

Chief among these surveys are:

• Annual Survey of Hours and Earnings, Business Register and Employment Survey and Monthly Wages and Salaries Survey for Labour Market;
• Short terms surveys such as the Monthly Business Survey, Construction and Allied Trades, Retail Sales, and Business Impacts and Conditions Survey;
• Quarterly structural surveys such as Quarterly Capital Assets and Quarterly Stocks surveys;
• Annual structural surveys, for example the Annual Business and Annual Purchases Surveys, Products of the European Community (PRODCOM) and Annual Survey of Goods and Services Surveys;
• Producer Price Indices, Services Producer Prices and Import and Export Price surveys for Prices;
• Quarterly and annual Foreign Direct Investment surveys and quarterly and annual International Trade in Services surveys for Trade;
• Specialist financial sector surveys, Financial Services Survey.

All business surveys, except the Business Impacts and Conditions Survey and UK Innovation Survey (run on behalf of the Department for Business and Trade) are mandatory for businesses to complete. Most of the surveys are digital, using an electronic questionnaire or Secure Electronic File Transfer.

Despite mandating, considerable ONS effort is expended both on obtaining responses and validating returned data. A large team manages the invitations to participate (typically by letter) and engages with business respondents to secure response and to clarify any concerns over data.

At present, this collection team has a number of vacancies, affecting the team’s ability to meet the quality targets set by output teams for some business surveys, to address this our plans include increasing the collection teams to full capacity. Team members also typically work on one survey at a time in a siloed approach, which results in inefficiencies in following up with businesses and validating their responses.

The data requested can often also be complex, based on both business accountancy and National Accounts concepts. While some more experienced members of the collection team are confident engaging businesses on such data, there is a need to increase the capacity of this expertise.

The technology underpinning the collection and validation of business surveys typically includes an element of legacy system, which limits functionality and constrains the ability to make changes at pace.

A2.2 Recent progress

To improve quality, especially on responses from larger businesses, the ONS has progressively introduced teams which focus on individual businesses. These teams collect and validate all surveys for those businesses, ensuring a coherent data picture across each business. There are two teams:

• the Large Case Unit (LCU), who focus on 125 reporting units equating to approximately 5% coverage of the total economy.
• an Account Management Unit (AMU), which – following a successful proof of concept – now covers 25 reporting units.

The LCU and AMU can identify, and address, data discrepancies at the start of the statistical value chain, before it enters the production cycle. Both units can evidence an increase in quality because of their work, for example of the 25 reporting units covered by the AMU, we have seen an increase of:

• 10% in response to surveys;
• 17% increase in the forms returned on time;
• Useable data items increased by 5%; and
• 6% reduction in recontact burden across all businesses, in some cases this was over 60% reduction for individual businesses.

To increase response from late and non-respondents, the ONS has redesigned questionnaires and improved our invitation letters. These new style communications have increased overall response rates. For some surveys, there was also an increased first-time clearance, when the data returned passes validation gates without requiring follow-up.

To reduce the number of business surveys, and to improve data quality, the Future Business Surveys and Statistics (FBSS) programme is now well underway with plans to deliver a suite of surveys (around 40) with an updated modular design, see further information in section SI1: The Future of Business Surveys and Statistics. We have already created a consolidated business survey portfolio, with one survey removed so far.

Collection and validation for two of the 74 business surveys have also been moved from legacy systems onto the strategic Data Preparation Platform.

The Survey Improvement and Enhancement Plan details work across four themes to build on progress and deliver against our priorities:

• Sustainable operation
• Enhanced business engagement
• Improved survey and statistical design
• Technology and automation

The Survey Improvement and Enhancement Plan details in each area the full range of short and longer-term research and survey improvements being implemented, explored and trialled. The mature activities at present are described for each area in the following sections.

A2.3 Sustainable operation

We are planning to extend the coverage of our Large Case Unit and our Account Management Units, and so extend their proven impact on data quality and simplify engagement with more businesses. We plan to expand their combined coverage from 150 today to:

• around 850 business units this year (2025 to 2026)
• increasing to in the region of 1,800 business units in 2026 to 2027
• rising to a combined total of around 4,000 business units by the end of 2027 to 2028.

Throughout 2025 to 2026 and beyond we plan to invest in the capability of our workforce, to improve their knowledge of core economic themes, and the part that business surveys play in the creation of statistics on prices, trade, GDP etc. Our plans include increased investment in analytical and accountancy knowledge, to support the more complex surveys. We expect this investment progressively to improve the quality of the data collected.

A2.4 Enhanced business engagement

Our plans for 2025 to 2026 are to move to a respondent centric service, using improved communications and engagement, coupled with expansion of the Large Case Units and Account Management Units.

To support this, our plans are to create and implement a non-response strategy which will include tailored collection services to respondents and ensure a business-centred approach to the design of our questionnaires and all communications. This work will also include a refreshed approach to enforcement activities while maintaining the obligations we have under the Statistics of Trade Act. This will result in a more tailored accessible service, flexibility, richer feedback on our questionnaires and increased quality, improving the ONS’ reputation, providing greater transparencies and efficiencies within the collection operation, while reducing the burden on businesses.

In addition, we are actively increasing our engagement with businesses, ensuring they understand the importance of our surveys and how they can use the data we publish, as a means of encouraging response.

This work will continue beyond 2025 to 2026, and in future years we aim to reduce the burden placed on the respondent.

A2.5 Improved survey and statistical design

Across the next year we aim to complete the survey and statistical design of the Integrated Annual Business Survey integrating all annual surveys over a phased implementation across the next three to four years, before moving to other survey themes or periodicities. Starting with the Annual Surveys facilitates the adoption of the new System of National Accounts (SNA) and new Standard Industrial Classification (SIC). To adopt the new SNA and SIC at pace, we plan to introduce a second theme to our work on survey design, where surveys will be modularised and integrated.

A2.6 Technology and automation

The ONS plans to achieve the following improvements in this area:

• Producer Price Surveys moved online by September 2025, further reducing our legacy estate through decommissioning the Telephone Data Entry system currently used by these surveys;
• In April 2026, the full Annual Survey of Hours and Earnings (ASHE) sample to be digital by default – making it easier and more convenient for respondents to submit data through digital channels whilst ensuring those who cannot access digital services are not excluded.

The remaining paper-based surveys, all largely complex in their nature, are planned to move to digital data collection, either through the creation of the SBR, the FBSS programme or legacy reduction over the coming years.

The collection of a further three business surveys will be moved onto the strategic Data Preparation Platform in December 2025. This will increase efficiency of our teams and provides the opportunity also to increase the quality of business survey data. We intend then to prioritise the replacement of end-to-end legacy technology for the ASHE and other Employment surveys.

To increase pace, survey technical teams will now work alongside digital colleagues to build the smaller and less complex Data Preparation Platform pipelines. This will also progressively reduce the business survey area’s dependence on legacy technology.

ClassifAI will replace the existing Standard Industrial Coding tool for the Business Register and Employment Survey. This is already showing strong potential for greater efficiencies, so we are investigating its use to code products on other surveys.

A3: Social Survey Data

A3.1 Background and post-pandemic challenges

The production of the ONS’ core economic statistics relies on four social surveys. Three are large household surveys: the Labour Force Survey (LFS); the Wealth and Assets Survey (WAS); and the Living Costs and Food (LCF) Survey. The fourth is the International Passenger Survey (IPS), which interviews travellers at ports and airports across the country. The quality and impact of our economic statistics is dependent on capturing sufficient volumes of representative and timely data from households and individuals.

Like other data collection agencies nationally and internationally, the ONS has faced unprecedented recent challenges in household data collection as long-term trends in declining response rates were accelerated as a result of the pandemic. While response rates across the whole sector have settled at between 10 and 20 percentage points lower than pre-pandemic because of societal changes and respondent security and confidentiality concerns, the quality of the ONS’s social surveys has been disproportionality impacted due to their voluntary nature, significant length and continued reliance on in-home face-to-face interviewing. These challenges highlight the importance of our ongoing Transformed Labour Force Survey (TLFS) strategic transformation programme. For the TLFS, we are implementing a shorter ‘online-first’ survey design to minimise respondent burden, and increase data quality, value-for-money and sustainability of household data collection.

The post-pandemic data collection challenges on our core surveys, and the additional demand of testing the TLFS alongside the LFS, has increased the workload on our interviewing community. This has coincided with financial austerity measures, recruitment restrictions and high levels of interviewer attrition that have reduced our interviewer capacity and capability. This mismatch in interviewer supply and demand has further contributed to post-pandemic social survey data quality reductions and ensured that a central focus of the ONS’s social survey quality improvement work since October 2023 has been to rebuild our interviewer community.

A3.2 Recent progress

Recognising the post-pandemic quality issues that the ONS has faced on social surveys, an initial recovery plan was launched in October 2023 and expanded to a full portfolio of work following HM Treasury investment in April 2024. This investment has already made a difference:

• The field community has increased from a low of 517 in March 2024 to 785 in May 2025. Attrition is still higher than pre-pandemic, at 25% in May 2025, but has reduced from 32% in August 2023;
• Recruitment to our field community has diversified and strengthened, through both the introduction of agency interviewers specifically to support the TLFS (which requires a reduced level of interviewer training) and the outsourcing of recruitment to an external resourcing partner. These changes underpin our growth to 785 field interviewers;
• To build the capability of our new interviewers, and improve retention of experienced colleagues, we have implemented a new progression and promotion pathway, creating 42 new Coaching and Learning Partners roles;
• We have increased the value of respondent incentives for taking part in our surveys across our survey portfolio. For example, on the Labour Force Survey we have moved from a £10 incentive to a £50 incentive per household (£25 unconditional and £25 conditional) for wave 1 of the survey;
• Major improvements to the IPS survey design, methods, processing and operation were successfully implemented in July 2024 to increase achieved sample sizes and improve survey cost-effectiveness;
• The ONS’s strategic transformation of the LFS has continued, as outlined in our April 2025 update, including progress on our research, test results and forward plans.

Taken together, by the end of May 2025, all these developments have started to increase achieved interview levels compared with the post-pandemic period, although the benefits to the multi-year datasets on some surveys will take time to feed through. Our recent LFS quality update details how Wave 1 response levels are now very close to pre-pandemic levels with accompanying improvements in representativeness.

A3.3 Immediate improvement plans

To deliver further improvements in the quality of economics statistics, the priority for Social Surveys is to implement the improved TLFS design, while increasing the number of achieved interviewers and further reducing biases on waves 2 to 5 of the LFS. We also plan to expand our quality improvement work across the LCF Survey and WAS to streamline data collection and increase the number of responses. With the number of achieved interviewers a key driver for data quality, the plan is to reach monthly target achieved interview levels for each survey within the following timescales:

• LFS (all waves) – November 2025
• LCF – January 2026
• TLFS (new short core design, in-home supported completion, data rotation and increased sample sizes) – January 2026
• WAS – March 2026

The Survey Improvement and Enhancement Plan details work across four themes to build on progress and deliver against these priorities and targets:

1. Sustainable Field Operations – focused on improving capacity and capability across our interviewer community;

2. Refreshed Citizen Relationship – to improve trust, brand recognition and understanding of the importance of our surveys;

3. Improved Survey and Statistical Design – redesigning our surveys to be more streamlined, reduce respondent burden, and improve accessibility for the population; and

4. Technology Improvement – focused on improving our systems and processes, taking opportunities to improve efficiency and agility of our technology.

The Survey Improvement and Enhancement Plan provides detail of the full range of short and longer-term research and survey improvements being implemented, explored and trialled. The mature activities at present are described for each area in subsections A.3.3.1 to A.3.3.4.

Following the recent suspension of the accreditation of wealth statistics, based on WAS, we will also develop a plan for the work required to bring Household Finance statistics back to the standard needed for our key users, which we intend to publish in the Autumn. This will build on the activities set out in the forthcoming Surveys Improvement and Enhancement Plan.

A3.3.1 Sustainable field operations

Over the coming year we plan to increase our field community to 1,023 field interviewers, our telephone community to 206 interviewers and the International Passenger Survey interviewer community at ports and airports to 110 interviewers. This will ensure our surveys portfolio is fully resourced and provides the opportunity to maximise response rates and boost samples to further increase quality. To support our increased field numbers, we plan to increase the number of interviewer coaching and learning partner roles to 65 by November 2025 and are continuing to focus on building the capability, confidence and experience of our interviewer communities.

To further improve recruitment and retention across our interviewer community, we plan to trial a new recognition scheme that enhances the benefits offered to interviewers. The new scheme will better recognise and reward the valuable work interviewers do and aims to increase the number of achieved interviews for our critical surveys. It will also support the development of skills and capability across the entire interviewer community.

A3.3.2 Refreshed citizen relationship

There is a need to address respondent reluctance to participate in the ONS’s household surveys. While reduced respondent burden from shorter surveys and online modes is key, the ONS has researched and tested the barriers associated with trust, survey legitimacy, data security, and brand recognition over the last 18 months. In September 2025 we plan to share this research and the findings from a targeted communications campaign to encourage survey responses in Birmingham that we completed earlier this year. This research will define the work to refresh our citizen relationship over the next three years.

A3.3.3 Improved survey and statistical design

Since successfully testing an experimental, shortened TLFS, work is now in the final build and test stages to implement a short ‘core’ online-first labour market-focused survey from July 2025. We plan to then introduce further improvements to the TLFS design over the following six months as per our recent publication.

On the WAS, we plan to increase the number of interviewers by March 2026 to effectively support an annual sample size of 33,000 households. This will ensure monthly minimum achieved sample requirements are met, with the full benefits and impact on yearly achieved sample sizes flowing through in future years.

We plan to introduce significant updates to the LCF survey from April 2026 which will encompass:

• An updated questionnaire with the aim of introducing COICOP2018 (see Section A1.2), incorporating critical questions from the recently stopped Survey of Living Conditions (SLC) and reducing overall respondent burden.
• A further sample boost to 30,000 households.
• Updated processing infrastructure and pipelines, including automated receipt coding (see Section A3.3.4).

A3.3.4 Technology improvement

On the LCF survey, alongside exploration of a digital online diary for respondents to use, we are developing a tool that can read receipts automatically, reducing the need for manual receipt coding. We plan to implement this tool in April 2026 to improve the quality and efficiency of data entry on the LCF.

The ONS plans to continue to uplift legacy survey processing systems, moving to the use of open-source software, common capabilities, standards and methodologies to improve speed, efficiency and strengthen quality assurance. The next major milestone on this work is an upgrade to the TLFS processing pipeline to support data rotation between longitudinal waves, which we plan to complete by January 2026.

A3.4 Social Survey forward look

With the research and development outlined within the Surveys Improvement and Enhancement Plan progressing, further details on medium- and longer-term Social Survey improvements will be included in future versions of this plan as they mature. At a high-level, across the timeframe of the Spending Review 2025, the key priorities will be to complete the TLFS development and decommission the LFS, while stabilising our interviewer field community at its increased capacity and continuing to build its capability and improve retention.

More broadly, we recognise that a new Household Financial Survey (HFS) design is required to ensure the ONS can sustain financial survey collection into the future. This should be complemented by the ONS exploring the opportunities of both administrative data to replace questions and online-first data collection. The full development of HFS is currently unfunded, but we aim to exploit opportunities during this forthcoming SR period to conduct initial research, design and options analysis, with the aim of delivering a clear way forward ready for future SRs.

To reduce the use of legacy technology across Social Surveys, the ONS plan to upgrade all Social Surveys onto the latest version of our Blaise data collection software, in-line with a new technology roadmap. We also plan to progress a new Strategy, Research and Innovation Hub to enable a step change in the use of alternative data sources and artificial intelligence integration. Our plan is for the Hub to drive forward and improve national and international collaboration, drawing on the latest internal and external research and best practice.

Although currently unfunded, based on research findings and decisions made this financial year, we may look to implement targeted communication campaigns to build trust and address security and confidentiality concerns amongst citizens.

A4: Administrative and alternative data

The ONS now holds a huge amount of administrative and alternative data. These datasets are used extensively in the production of our core statistics such as GDP, Prices, Labour Market and Population. They include regular and mature feeds from a range of departments, including HMRC on corporations and income; on population and migration; from banks on financial transactions; and supermarkets on retail sales, among others.

Administrative and alternative data are important to the production of quality statistics, and we will continue to explore how these data can be further deployed to improve statistical production as part of our focus on stabilising these core statistics. Throughout the ‘Statistical Themes’ in the following section we reference where work with administrative data will be prioritised to further stabilise and improve the quality of our core statistics.

The ONS has also committed to publishing a new Data Sourcing Strategy before the end of the year, as recommended at the 2025 UK Statistics Assembly. It will consider the strategic principles and drivers underpinning the ONS’s approach to sourcing data for core statistics; the “data that matters.” This strategic approach will be used to ensure we are focusing resources and investment on the most critical data, to drive improved quality, reliability and confidence of our core outputs. It will also consider an increased role for data exploitation and data integration, to ensure we are making the most of the data we already have access to, alongside bringing greater transparency to the way in which we are using our data. It will highlight areas of good practice where we are already integrating high volumes of diverse data sources to improve the quality of our outputs.

We are conscious of the need to maintain public trust in our use of data, and we continue to find ways to minimise the use of personal data in our processes, including via the use of data indexed and de-identified via the RDMF. Throughout the statistical production process, we maintain the security and confidentiality of administration and alternative data – ensuring it's appropriately accessed, information systems are secured by design, and our protective and responsive security measures implemented are informed by threat, vulnerability and risk analysis.

B1: Introduction to themes

The previous annex explained challenges and plans across the key enablers of all our statistics. This annex looks at each of our six core economic and population themes in more detail, since the challenges and plans are different within each theme.

At the level of an individual statistic, the plans explain how the ONS will act, in some cases necessarily over several years, so that the statistic:

• meets key user needs
• utilises the right data, at the right time, to the right quality
• uses production methods that are fit for purpose
• is produced with acceptable technology risks
• enables flexibility and agility to support change at pace
• is transparent, documented and maintainable by teams in place
• methods are implemented correctly
• has a level of automation which removes material manual handling
• has an adequate depth of expertise to provide resilience, removing single points of failure

The ONS also needs to ensure consistency and coherence:

• across the individual statistics within each theme - for example, how do the various statistics about the labour market combine to give a rounded, coherent picture of the labour market as a whole
• across the various themes, and particularly the components of GDP, to give a rounded, coherent picture of the economy as a whole

Whilst such change will form an important part of the evolution of our statistics, in the immediate term focus remains on improving individual statistics, to ensure a strong foundation is in place.

B2: Labour Market

B2.1 Introduction and current challenges

The ONS produces a wide range of labour market statistics covering topics on labour supply (including employment, unemployment, inactivity and hours worked), labour demand (including workforce jobs and vacancies) and earnings. These are derived from a range of data sources including surveys of households (the Labour Force Survey), surveys of businesses and administrative data, most notably payroll data from HM Revenue & Customs (HMRC). Labour market statistics are a significant source of evidence for decision-making that underpins financial and economic stability and, more broadly, are an important source of information and insight for a wide range of users including businesses, policy makers and parliamentarians, and researchers and academics.

While administrative data contribute to the evidence base for the labour market, they largely complement – rather than replace – survey data. This is because currently surveys alone can provide users with some of the timeliness, granularity and concepts they require, such as the split between unemployment and inactivity. For this reason, it is vital for data quality to invest in survey inputs, methods, processes and systems (as in Annex A) to reduce risk, increase efficiency and enable continuous improvement.

Currently there are several challenges with and risks to labour market statistics relating to legacy systems, methods and processes including:

• the well documented challenges to the Labour Force Survey (LFS), where the new design for the Transformed Labour Force Survey (TLFS) will go live shortly, supported by additional funding for a period of dual running.
• more widely, reliance on outdated systems and processes have led to issues such as published errors in the Annual Survey of Hours and Earnings (ASHE) and release dates being delayed for the Business Register and Employment Survey (BRES). This has also led to a lack of flexibility to enable the introduction of new or improved methods across releases.

Our immediate focus is on measures that will enable labour market statistics to be at expected levels of quality, with suitable data inputs and methods and with sustainable platforms and processes with scope for continuous improvement, supported by adequate resource in terms of headcount and skills.

To achieve this, we will be focusing on those outputs that have been assessed as most at risk: LFS, Earnings (ASHE and AWE), Jobs (Workforce Jobs and BRES). Vacancies and the current PAYE Real-Time Information (RTI) outputs are more robust and are not covered explicitly but will be subject to continuous improvement over this period.

As part of the work to improve quality, we will be drawing on insights from administrative data, particularly PAYE RTI. We already use PAYE RTI and the Claimant Count to inform the narrative of the labour market and improve the coherence of estimates published as part of the regular labour market statistics, as well as producing experimental productivity statistics using both survey and administrative data . As part of the work leading to the transition to TLFS we are linking LFS and TLFS data to PAYE RTI to assess the coherence and accuracy of the survey data. Alongside the work to move our current outputs to a more sustainable position we will consider:

• how we can integrate administrative data with our survey data to improve reporting on the labour market
• the work needed to produce labour market accounts that provide a comprehensive understanding of the UK's labour market, by using the optimum balance of survey and administrative data, including the viability of undertaking this through integrated labour accounts

Further work will then be reflected in future iterations of this plan.

B2.2 Employment, Unemployment and Inactivity (LFS/ and TLFS)

The headline measures of employment, unemployment and hours worked currently come from the Labour Force Survey (LFS). LFS response rates have been falling for a number of years and, in 2023, the quality of results from the survey led to a suspension of outputs for nearly five months. In response, a number of measures to improve the quality of LFS responses were implemented, with their resultant impact described in more detail in an article published in May 2025.

Over recent years, the ONS has been developing an online first alternative to the LFS, the Transformed Labour Force Survey (TLFS). The ONS is currently working towards a transition from LFS to TLFS which will provide a more sustainable basis for our headline statistics; not just from the survey side but also in how the survey is processed and the platforms used. The latest position on TLFS is in the most recent update published in April 2025.

The ONS plans to achieve the following improvements in this area:

By March 2026

• Improvements to initial LFS sample size implemented in January 2024 fully fed through into published estimates of levels and quarterly changes (A recent article in May 2025 gave an assessment of quality, where challenges remain and how LFS data should be interpreted).
• Increased LFS field interviewer capacity for waves 2 to 5 from April 2025 in place.
• Full reweighting for LFS and related datasets in progress, starting in 2025 following publication of subnational population projections.
• First quarterly dataset available for processing from TLFS with planned improvements (shorter survey, data rotation, split between core and plus surveys).

By March 2027

• Full reweighting for LFS complete.
• We will have carried out a readiness assessment in collaboration with main users in July 2026, aiming for transition of our published headline labour market statistics in November 2026, though transition timing will be data-led and could be in 2027 if our assessment or user needs require more data to be collected and assessed.

B2.3 Annual earnings (ASHE)

• The Annual Survey of Hours and Earnings (ASHE) is the main source of structural earnings data for the UK. Data are collected from one per cent of employees on the PAYE tax system enabling information on earnings and hours to be provided at a detailed occupation and geographical level. ASHE results also provide the headline gender pay gap figure and feed directly into the calculation of the National Living Wage and National Minimum Wage. Reliance on legacy systems and methods have led to a number of challenges including challenges with data processing and the need to correct a notable error in the 2022 publication. ASHE has been identified as a priority for further improvement in 2025 and 2026 following on from methodological improvements to the validation process in the release for 2024 which brought more high-paid individuals into the final results, and implementation of a new coding tool for the 2025 results round that led to improved quality and reduced time taken to apply coding.

ONS plans to achieve the following improvements to ASHE:

By March 2026

• Extended use of electronic data collection in place for businesses with more than five responses, so more than half of the sample is covered (already implemented for 2025 results round). This improves respondent experience and efficiency in ingesting survey responses more quickly.
• Table production system moved onto a new platform.
• Work continuing to review methods (imputation, validation, sampling, weighting) which will improve quality of future publications.

By March 2027

• All data collected online, improving respondent experience and the efficiency of ingesting survey data.
• Production system no longer dependent on legacy software (for publication in October 2026).

By March 2028

• Improved methods implemented from review in 2026.

B2.4 Jobs (Workforce Jobs, Business Register and Employment Survey)

Jobs data are collected from businesses and provide a vital source of information for use in productivity and local area statistics. Work is underway to move the quarterly employee jobs series (part of workforce jobs) onto a new software platform. The annual Business Register and Employment Survey (BRES) is an important source of information for the business register and local area data. BRES is currently on legacy platforms with the system hard to run and difficult to maintain. There have also been delays in BRES publication due to issues with the system and processes.

The ONS plans to achieve the following improvements in this area:

By March 2026

• Short-term employment surveys no longer run on legacy technology.

By March 2027

• BRES take-on and validation moved from legacy software.

By March 2028

• BRES production moved from legacy software.

B2.5 Monthly Earnings (AWE)

The Average Weekly Earnings (AWE) series is the headline measure for earnings growth. It is used extensively by the Bank of England, HMT and others as a key economic indicator. While the output has generally been robust, there are a number of methods that have not been reviewed for a number of years - for example, sample allocation and adjustment for small businesses. In addition, the recent implementation of a revision outside our normal revisions process highlighted the inflexibility of the current system.

The ONS plans to achieve the following improvements in this area:

By March 2026

• Methods review completed, including sample optimisation, seasonal adjustment, selective editing, outliers, imputation and small companies’ adjustment.

By March 2027

• Methods review implemented, and AWE system moved off legacy software.

B2.6 Labour Productivity (including Multi-factor Productivity, Regional and International Comparisons of Productivity)

Productivity statistics are crucial for understanding the whole economy, drawing on a range of National Accounts and Labour Market data sources. Statistical outputs are produced quarterly and annually and provide granular industry and regional breakdowns. These productivity statistics are used extensively across government, the Bank of England and academia. Most of the production systems are still produced using legacy systems, although work is ongoing to move to Python and RAP.

The ONS plans to achieve the following improvements in this area:

By March 2026

• Migration of quarterly release from legacy systems complete, improving quality and reducing the risk of processing errors.
• Improved methods implemented for quarterly labour productivity whilst moving to new systems to improve quality.

By March 2027

• Labour productivity systems implemented to allow processing of TLFS and RTI PAYE data to allow for increased analysis.
• Sustainable systems implemented for Regional Productivity and Labour Costs and Labour Income to improve quality. Team members able to step away from system issues and concentrate on the economic stories.
• Sustainable systems implemented for International Comparisons of Productivity.

B3: Trade and Balance of Payments

B3.1 Introduction and challenges

Trade statistics are a key component of the UK’s National Accounts, forming part of the expenditure approach to GDP. They are compiled using a range of data sources, including household and business surveys, commercial data, and administrative data including from customs declarations. Most trade statistics are processed on legacy systems. A recent review by OSR highlighted areas for improvement.

Trade statistics often show “asymmetries” - the differences between the published trade statistics of a given country and its partner countries' equivalent “mirror flows”. They are especially common in trade in services data and result from conceptual and measurement differences between countries. The presence of trade asymmetries does not indicate that either country is inaccurate in their estimation but are an inevitable consequence affecting all data compilers, given confidence intervals around central estimates. We have already made significant progress to understand, quantify, and reduce these asymmetries where possible, with efforts ongoing.

The Balance of Payments (BoP) are a measure of the UK’s economic transactions with the rest of the world and include the current account (of which trade statistics are a component), the capital account and the financial account. BoP reporting includes the International Investment Position, a key data source for which is the Foreign Direct Investment survey. BoP is compiled using legacy technology. Statistics in this domain are complex and require high levels of subject matter expertise, which takes significant time to build.

The compilation of these statistics is underpinned by a range of international standards: the Balance of Payments Manual (BPM7), the related Manual on Statistics of International Trade in Services (MSITs), and the OECD Benchmark Definition of Foreign Direct Investment. The Standard Industry Classification framework also underpins the sampling of business surveys which are key data sources.

Capability has already been established to implement methods and systems improvements to the Trade and BoP statistics. There is an established and experienced continuous improvement team who are undertaking system re-platforming and automation to long timescales. There is also an embedded Trade methods development team who are continuously working on the methodologies that underpin the production process to make identified improvements where possible.

There is a backlog of known methods improvements, some of which are already in progress given their high priority.

This chapter captures improvement activities and resource planned to stabilise the production of Trade and Balance of Payment statistics, improve the quality and ensure fit for the future.

B3.2 Trade in Goods

Trade in goods data forms an essential part of both the expenditure measure of GDP and current account in BoP. It is also used by key stakeholders to inform trade policy decisions and trade agreements.

Processing for Trade in Goods relies on a legacy system which constrains our ability to introduce methods improvements. Our plans include a review and modernisation of the system and bringing forward methods improvements. This will enhance data quality and ensure long-term sustainability.

The ONS plans to achieve the following improvements in this area:

By March 2026

• Methodology review and accompanying system design complete.

By March 2027

• Requirements of reconfigured system specified and ready for implementation.

By March 2028

• Reconfigured system implemented and ready for use in live production.

B3.3 Trade in Services

Trade in services data forms an essential part of both the expenditure measure of GDP and current account in BoP. It is also used by key stakeholders to inform trade policy decisions and trade agreements.

While trade in goods data is largely available from administrative data from HMRC, this is not true of services trade which requires a more complex measurement. A key data source for Trade in Services is the International Trade in Services (ITIS) survey. The Trade in Services data is predominantly produced through legacy technology and manual processing. Incorrect implementation of methods in the ITIS legacy system recently contributed to a data error, alongside production area capacity and capability issues. A return to a sustainable position would be supported by a range of systems and methods improvements.

The ONS plans to achieve the following improvements in this area:

By March 2026

• Improved response rate and clearance rate (which is the proportion of survey forms returned by businesses which have been validated as accurate) of ITIS survey and therefore improved data quality, as a result of increased capacity in the data collection and validation team (see Section A2.3: Sustainable operation).
• A new mechanism (modelling and forecasting) to overcome a temporary gap in trade services data because of a change in the collection method for the International Passenger Survey (IPS). This will ensure users continue to have good quality data on trade in travel services, which represents around 8% of total trade.
• Investigation and analysis of potential bias adjustments underway to minimise revisions between early and final estimates, to improve usefulness of early data for users.
• Publication of a user guide on trade asymmetries, synthesising previous work alongside updated asymmetries analysis, to support users’ understanding and use of the data.

By March 2027

• Full sample design and estimation, imputation and questionnaire reviews completed for ITIS and accompanying system changes specified for implementation.
• ITIS results system re-platformed and in use for production ready for January 2027. Re-platforming will deliver a flexible system, fit to take on the new international standards (BPM7, MSITs), and improve efficiency by allowing more time for data curiosity and quality assurance.
• Bias adjustments finalised, ready for later implementation in next Annual National Accounts (see the following bullet point).

By March 2028

• New IPS data implemented, ensuring accurate travel services data is available to users and removing temporary fix described in the previous bullet point.
• Agreed bias adjustments implemented in Annual National Accounts in October 2027.
• Deflators for Trade in Services reviewed, and improvements identified for iterative implementation, to ensure trade estimates are accurately adjusted for inflation.

By March 2029

• Improved and rationalised collection mechanism for all Trade data despatched by March 2029, reducing respondent burden and improving experience for businesses. Based on sampling from the new Statistical Business Register and using the new industrial classification. This includes collection of Globalisation data to accurately capture the trading activity of multinational enterprises in a strategic way.

These changes pave the way for incorporation of new data into the Trade and BoP statistics, possibly by 2031, dependent on feasibility analysis. Incorporation of the Globalisation data into Trade, Balance of Payments and the National Accounts will likely require four years from questionnaire despatch to undertake the required analysis and quality assurance (2033). These timelines are based on switching focus to the trade data collection after the transition of the Annual Business Survey (ABS). While it might be possible to develop the trade data collection in parallel with the ABS, and so bring forward timelines, this would require significant additional funding not currently in our planned budget.

B3.4 Foreign Direct Investment

Foreign Direct Investment (FDI) statistics are a core component of the Balance of Payments, showing inward and outward investment. The FDI processing systems have already undergone significant investment, following a pause to production to provide capacity to undertake transformation, with higher quality data already starting to feed through into the Balance of Payments. There remain further legacy processing systems and methods improvements that need to be made to further enhance quality and bring us to a sustainable position.

The ONS plans to achieve the following improvements in this area:

By March 2026

• The full suite of improved FDI data feeds through to the Balance of Payments in Pink Book 2025, meaning the most up to date high quality data is available to users.
• Improved response and clearance rates, and therefore improved data quality, following boosted capacity of data collection and validation team.

By March 2027

• FDI will draw a sample of majority relationship businesses from the new Statistical Business Register, improving efficiency.
• Remaining legacy technology used to process Mergers & Acquisitions (M&A) data, geography data, and benchmark quarterly and annual data will be re-platformed, improving efficiency and freeing up time for additional quality assurance and improved collaboration with data customers.
• Career pathway implemented to upskill and improve subject matter expertise within the data collection and validation team due to the complexity of FDI. This will improve data quality at the point of validation and minimise burden on businesses.

By March 2028

• Full sample design and estimation, imputation, and questionnaire reviews completed for FDI, and accompanying system changes implemented.

By March 2029

• FDI will draw full sample of both majority and minority relationship businesses from the new Statistical Business Register (SBR), and using new industrial classification, further improving efficiency and coverage.

B3.5 Balance of Payments

Balance of Payments statistics show the UK’s economic transactions with the rest of the world, broken down into the current account (of which trade statistics are a component), the capital account and the financial account. They are fundamental to policy making and bring together a wide range of data sources internal and external to the ONS. The statistics are extremely complex and are produced using legacy technology, requiring high levels of domain expertise which takes significant time to build.

The ONS plans to achieve the following improvements in this area:

By March 2026

• Improved Foreign Direct Investment data is on track for integration into the Balance of Payments in Pink Book 2025.
• Re-platforming complete of the legacy BoP system used for processing geography data, supporting the sustainable production of BoP statistics due to improved efficiency and reliability, and fit for the future through increased flexibility to make changes.
• Domain and technical expertise increased to enable ongoing improvement and effective support, in preparation for BPM7 implementation, including ability to provide increased data curiosity and quality assurance. Retention plan in place to maintain expertise and ensure a resilient production team.

By March 2027

• Review completed of data sources used in compilation of Balance of Payments, and associated methods, to ensure fit for purpose against international standards. Further investigation may be required dependent on review findings.

By March 2028

• The re-platforming of the legacy system underpinning the Financial Accounts, Dividend and Investment Matrix, and Balance of Payments (FA DIM BoP) on track, enabling the re-platformed system to be used for the Pink Book 2028. The re-platforming will improve efficiency and consistency of methods between Balance of Payments and Sector Financial Accounts, ensuring current methods are implemented correctly, which will improve quality and coherence. This re-platforming will ensure the system is fit for the future with increased flexibility to implement the new international standards.

Beyond March 2029

• BPM7 implementation: Research to determine what is required to implement BPM7 is already underway in 2025 to 2026 - for example, changes to methods, systems, data sources, questionnaires and published breakdowns, and will continue over the next three years. We plan to have made good progress by 2028 to 2029 in defining requirements, however, some changes within BPM7 are conceptually challenging to measure - for example, capturing crypto. We will need to work alongside international bodies to identify potential sources of data, and timeframes will need to be confirmed.
• There will be more to do beyond 2028 to 2029, to fully implement required BPM7 changes in systems, once all requirements are known. There are also dependencies on other workstreams such as SBR and FBSS.

B4: Prices

B4.1 Introduction and challenges

Prices are some of the highest profile UK statistics. They include all consumer price statistics, statistics on business prices and the housing market, and the development and assurance of deflators used in the national accounts.

A wide range of development activity is underway, including using new platforms, data sources, and methods to improve the quality and granularity of these important economic statistics. Recent achievements include transitioning substantial parts of our estate from legacy infrastructure, incorporating large administrative data into our consumer price statistics, transforming our rents statistics and delivering an extensive package of deflator improvements for Blue Book 2025.

However, several risks remain across price statistics relating to legacy systems, methods and processes and the resources needed to mitigate these risks and work sustainably. This chapter looks at different price statistics in turn.

B4.2 Consumer prices (CPI, CPIH, RPI)

While significant improvements have been made in recent years, Consumer Prices remain reliant on legacy technology for key parts of our production process. This limits our ability to flexibly update our systems. In particular, some central data collection is currently done using legacy technology. We also use other legacy systems for processing some data manually collected at the ONS.

Alongside these technology challenges, pressures on production teams have meant that sample review work has been squeezed in recent years. Since consumer prices data rely on the LCF for weights, the quality of prices data also relies on the delivery of improvements to social surveys (Section A3: Immediate improvement plans).

There is also a substantial change required to our classification structure to adhere to international standards with the introduction of COICOP18. This will require investment in both methods and systems both in Prices Division but also in other partner directorates across ONS.

The ONS plans to achieve the following improvements in this area:

By March 2026

• The central data collection will begin transitioning from legacy technology to a cloud-based strategic platform.
• Point-of-sale scanner data will be introduced into monthly production for grocery retailers covering around 50% of the UK market, to improve the quality of inflation estimates.
• The first tranche of improvements to samples and methods in specific parts of the inflation basket will be implemented.
• Feasibility work will begin into the implementation of COICOP-18, remaining legacy improvements and updates to the Living Costs and Food Survey (LCF).

By March 2027

• Continued implementation will begin for the remaining legacy (processing of some data manually collected at ONS).

By March 2028

• CPI, CPIH, RPI will no longer use legacy data collection platform.
• COICOP18 will be implemented.

B4.3. Business prices

Business Prices are used by a wide range of internal and external customers. In particular, under double deflation, PPIs and SPPIs are used throughout the national accounts such as GDP and trade statistics. It is therefore essential to improve and ensure their quality and sustainability.

These statistics are carrying substantial risk following an error being identified in PPI weights in 2022. Reviews carried out by the ONS’s Quality and Improvement Division and by the Office for Statistics Regulation (OSR) led to the publication of a structured improvement plan in October 2023. The ONS has completed the majority of the work recommended in this plan. However, the monthly publication is currently paused following separate issues discovered in the chain-linking methods and weights.

To restart the publication, we need to resolve the issues by rebuilding the pipeline, testing and parallel running, and this work is underway.

In addition to restarting the publication, there are additional quality and legacy challenges:

• pressures on production teams have meant that sample design and respondent recruitment has been delayed. This work is essential to improve the quality of the source data
• we are planning to migrate source data collection for PPI over to an electronic collection system during 2025. This will save time for survey teams by reducing manual processing, allowing the teams time for more structured and focused quality assurance
• to further reduce our risk, we need to extend this work to complete a major legacy uplift programme. The end-to end transformation of business price statistics includes redeveloping the existing production system in line with best practice and moving the remaining legacy elements onto strategic platforms. We will also work with the Advisory Panels for Consumer Prices to define any quality improvements. This would all put business prices production on a more sustainable and resilient platform and allow new methods and data sources to be implemented in line with stakeholder priorities. It will also allow aggregation and publication to be updated to reflect revised international classifications of industry and occupation

There is existing capacity to deliver essential improvements in the short term, with more detailed planning required for 2027 and 2028 to fully scope and set more confident timelines for the additional work to address the legacy uplift. This will be set out in the next annual update of the Economic Statistics Plan.

The ONS plans to achieve the following improvements:

By Summer 2025:

• Restart monthly producer prices bulletin and tables

By March 2026

• Source data collection for business price statistics migrated to an electronic collection system.
• Planning complete for end-to end transformation of business price statistics.

By March 2027

• Improvements complete on sample design and respondent recruitment for business price statistics.

By March 2028

• Production system migrated onto strategic platform, and off legacy technologies.

B4.4 House prices (HPI)

ONS works closely with HM Land Registry, Land and Property Services Northern Ireland, and Registers of Scotland to produce the UK HPI, and regularly discusses the development of methods and systems with them. House price production at ONS is partly reliant on legacy technology for key parts of our production process, although recent improvements have been made with the monthly production round now having been successfully re-platformed onto a strategic platform. We expect to complete the remainder of the work (for the annual production round) by the autumn.

The legacy uplift work has revealed the need to carry out further improvements in the underlying methods, reflecting the fact that those are more than ten years old. This will help to reduce revisions to early estimates, an issue our key stakeholders have highlighted. Work is underway in collaboration with our advisory panels to define what imputation improvement would have the best effect as an interim solution, followed by a full methods review.

As with the approach for business prices, we plan to deliver the following improvements:

By March 2026

• Full HPI production round moved onto strategic platform.
• Interim methods improvements implemented to improve revisions.

By March 2027

• Full methods review complete, and implementation plan agreed.

By March 2028

• Iterative implementation of full methods review will start.

B4.5 Private rents

Price Index of Private Rents (PIPR) has recently been through a successful transformation project, under the ARIES programme. Transformed rents statistics for Great Britain was delivered in March 2024 and Northern Ireland in March 2025; these new statistics provide a greater level of granularity in rental price statistics, including local authority estimates, and estimates by property type and number of bedrooms. The transformation project also included re-platforming the end-to-end production process onto a strategic platform.

Our rents development plan shows how we are responding to recent user feedback by publishing further information on our rents statistics for example, on collection volumes and distributions, to improve transparency and allow stakeholders to assess their quality. The main goal is to meet requirements set out in the OSR review with the aim of achieving accredited status in 2025 and 2026 for PIPR. This can be delivered using existing capacity.

The actions being taken here also respond to the OSR recommendations in Spotlight on Quality Assessment: Price Index of Private Rents (PIPR) – Office for Statistics Regulation.

B5. Public Sector

B5.1 Introduction and challenges

The ONS produces both the monthly Public Sector Finances (jointly with HM Treasury) and the Public Sector’s contribution to GDP (currently equivalent to approximately 20% of GDP). This includes the Economic Statistics classification process which determines which organisations sit within the Public Sector boundary, which in turn impacts headline estimates, including the UK Government’s target measure Public Sector Net Financial Liabilities.

Improving Public Sector Finances estimates requires:

• improving the systems and methods for each sub-sector (for example Local and Central Government) in addition to redeveloping the overall public sector finances processing systems
• increasing our subject matter expertise: to keep pace with real-world policy changes, to accelerate process modernisation, and to remove single points of failure

B5.2 Progress to date

An automated data ingestion and data cleaning process has been developed and will progressively be incorporated into use during 2025 and 2026 for local government statistics. This provides a blueprint for future Public Sector legacy system transformation, and the systems development team has built considerable subject matter knowledge, leaving them well placed to continue our development programme. Work is already underway to expand the solution for central government statistics.

Accompanying the fiscal rules announced at Autumn Budget 2024, the Treasury, OBR and ONS established a net financial debt working group with an agreed joint work programme, taking forward statistical and forecast development relevant for public sector net financial liabilities. This group aims to drive data quality improvements for both the forecast and outturn statistics, such as improving the timeliness of updates to funded pensions data in the public finances, and as part of ONS’s continuous statistical development programme.

We have begun to increase headcount, and to invest more systematically in specialist training related to the Public Sector.

B5.3 Plans for 2025 to 2026 and Spending Review 2025 years

To keep users informed of our statistical development plans, we publish an article called Looking ahead: developments in public sector finances statistics. Last published in December 2023, our latest edition is planned for 27 June 2025. Our plans include developments in key fiscal statistics, such as those referenced in fiscal rules, and public sector funded pensions data, in addition to plans for implementing classification decisions. Alongside these developments, our systems redevelopment work will be a continuing high priority.

The ONS plans to achieve the following improvements in this area:

By March 2026

• To realise the benefits of the Local Government Non-Financial Account system.
• For Central Government to complete the build of pipeline moving towards removing the Central Shared Database legacy.
• For Public Sector Finances system; initial discovery work, selected processing systems will be developed, and a roadmap for the approach to subsequent development will be completed.
• Recruit for our pensions development work, start to build knowledge of methods and concepts related to public sector funded pensions and (jointly with HMT and OBR) engage with research work by Government Actuary’s Department (GAD).
• Meet our first set of requirements from the OSR review of classifications, which includes adding additional resilience to the classifications team and committee.

By March 2027

• Realise the benefits of the new non-legacy Central Government system module as part of Annual National Accounts in summer 2026 and Public Sector Finance release.
• Develop various new system modules: for Local Government system (the Financial Account and Balance Sheet modules); for Central Government system (remaining modules); and for Public Sector Finances system (first module).
• Meet all our requirements from the OSR review of classifications.
• Update Public Sector funded pensions estimates in Public Sector Finances, incorporating outcomes of 2025/26 research work to the extent possible.

By March 2028

• Realise benefits for Local Government system (the Financial Account and Balance Sheet modules); for Central Government system (all remaining modules); and for Public Sector Finances system (first new modules) as part of Annual National Accounts in summer 2027 and Public Sector Finance release.
• Incorporate further modules into the Public Sector Finances system.
• Deliver continuous improvement of methods within the new pipelines over subsequent years such as new Classification of Functions of Government (COFOG) and SNA impacts.
• Responsive service for classifications advice and robust decisions which reflect economic reality and have proportional external assurance.
• Prepare for transition to updated statistical guidance (prompted by System of National Accounts 2025).
• Improve Public Sector funded pensions estimates in Public Sector Finances, including incorporating remaining outcomes of 2025/26 research work by GAD (with HMT and OBR).

By March 2029

• Deliver a Public Sector Finances aggregation system.
• Deliver continuous improvement of methods within the new pipelines over subsequent years such as new Classification of Functions of Government (COFOG) and SNA impacts.
•  Ongoing continuous improvement for Public Sector funded pensions estimates.
• Classifications work meets requirements and is an example of good practice.

We will also be focusing on the method and system development for non-market output for GDP.

By March 2027

• Develop output methods recommended by the Public Service Productivity Review and build expertise for development of improved Government system.

By March 2028

• Begin discovery and produce a road map for Government GDP system, preparing for implementation of methods improvements into National Accounts.

By March 2029:

• Develop and implement first processing systems with method improvements into ANA28, continuation of system development and preparation for the quality adjustment of non-market output in National Accounts, including ensuring systems are built to manage this change.

C1. Introduction and current challenges

The compilation of the UK’s National Accounts, including GDP and other related statistics, is incredibly complex and brings together a large number of different data sources covering ONS data, external suppliers, and of different frequencies; outputs from many different ONS processing (compiler) systems; and involves the necessary data confrontation of different measures of the economy.

The National Accounts framework and approach to compilation allows expert judgements to be made to deliver the highest quality of data based on the available information at the time of publication.

These range of issues naturally can lead to revisions of published estimates. ONS have worked closely with OSR to identify challenges related to revisions and uncertainty.

At a conceptual level, the latest System of National Accounts (SNA 2025) and the Balance of Payments (BPM7) are internationally endorsed frameworks which provide the foundation for the measurement of the economy. There are also the System of Environment Accounts (SEEA) Central Framework and Ecosystem Accounting, and Government Finance Statistics (GFS) manuals. Underpinning the compilation of the National Accounts are the classification frameworks, which cover industry (Standard Industry Classification, SIC); Classification of Individual Consumption by Purpose, COICOP); Standard Occupational Classification, SOC). Quality economic data can only be derived from the use of a high quality and modern business register as this is crucial for population coverage of businesses, and survey sampling needs. Further information is available in the Supplementary section.

C2. Different approaches to measuring GDP and balancing

While users typically only see the resultant high-level published outputs for monthly, quarterly or annual GDP, the approach to compilation is multifaceted.

From a compilation perspective, it is helpful to focus on the three different approaches to measuring GDP. These are Income, Production and Expenditure. This focus allows us to identify targeted improvements to be made to each different approach.

This is important as the approaches use different data sources to capture the information needed. For example, the output (production) approach is typically the timeliest, as it is often easier for businesses to know their turnover data in a very responsive way. This is why the ONS leads on the output approach to measuring GDP for the monthly GDP as it has the highest data content at an earlier stage. So, any improvement in the production approach will naturally translate to improvement in the quality of the monthly GDP estimates.

Fundamentally, the three approaches to measuring GDP should be equal. If the three approaches diverge, this can indicate areas of data weakness and allow constructive challenge on the underlying data sources and components. This balancing step, which assures all three approaches are equal, is a central feature in the National Accounts framework. As an end-to-end compilation process, data sources for each approach are actively managed in a way to balance timeliness, and the assessment of the different component approaches occur through the different and separate compilation systems.

The ONS operates on the basis of continuous improvement, however there are identified areas in each of the three approaches to measuring GDP which are listed in the following section.

C2.1 Income approach to measuring GDP

A step change in the measurement of income could be achieved using the real-time pay as you earn (RTI PAYE) information. Gross Operating Surplus is conceptually challenging to measure, with most countries making this a residual component. An improvement in external data feeds would be strongly desirable to reduce time lags for use of these data.

Summary of planned work:

By March 2027

• Compensation of Employees: To improve quality, investigate the use of the monthly RTI PAYE data for quarterly and annual Compensation of Employee estimates. The monthly RTI PAYE dataset is complex and requires detailed reproducible analytical pipelines for our processing. This will be a staggered delivery approach, with replicating the RTI data feed into the annual process being completed by March 2026 as a first step; and this will inform the approach for the quarterly process.
• Private non-financial corporations gross operating surplus (PNFC GOS): Investigate a source for PNFC GOS data both for the short-term and the annual data, including if existing data sharing arrangements can be enhanced.

C2.2 Expenditure approach to measuring GDP

Within Household final consumption expenditure, increasing survey response in the Living Costs and Food survey will help with quality in the short term, though this source is already triangulated with other data, while the longer-term aim of alternative data sources such as credit card data and scanner data are researched and introduced into the accounts. The components of gross capital formation (investment and inventories) are harder to find alternative data sources for, so boosts to the sample sizes here would help to reduce volatility and revision to the data. Trade data are discussed in Section B.3: Trade and Balance of Payments, but are another very important component of the expenditure approach.

Summary of planned work:

By March 2027

• Household Final Consumption expenditure (HHFCE): The HHFCE quarterly data feed is partly sourced by the Living Costs and Food (LCF). While in the short-term we will look to increase the LCF survey response we will separately investigate alternative data sources such as credit card data, energy use data, and prices scanner data. We aim that this proof of concept will enable us to embed this approach for full use by March 2028. This will also link closely to COICOP classification updates (see Section C3.1: COICOP and Household expenditure).

C2.3 Production approach to measuring GDP

The production (or output) approach to measuring GDP is critical in the current model as it is the basis for which the other measures come into alignment in the short-term. Quality improvements can be made in focused areas with administrative and alternative data sources.

Summary of planned work:

By March 2027

• Use of VAT data in monthly GDP: Currently, VAT data is only used in a sub-set of industries, and then only six months after the reference period which can cause some revision to GDP estimates. Investigations are needed into the earlier use of VAT data, the revisions profile of VAT data and possible expansion to cover more industries.
• Intermediate consumption: Introduce information on intermediate consumption changes sooner, ideally using the VAT dataset. This would allow adjustments to be made in real time, reducing revisions to GDP estimates when we supply-use balance.

By March 2028

• Deflators: Improvements to quality and coverage of our suite of National Accounts are ongoing in a rolling program, including ensuring coherence of use.
• Annual Structural Statistics: Current statistical design and systems are not fully meeting user needs. Enhanced systems mean we will be able to rapidly update survey questions to better reflect the modern economy, integrate administrative data sources to processing, and improve subnational estimates.

C2.4 Balancing as part of Supply-Use and Input-Output

The confrontation of the three different approaches to measuring GDP and the detailed data available from the annual supply-use and input-output datasets, are a crucial step in understanding the economy in its totality. This is known as balancing and is one of the fundamental processing steps that sets the levels of the economy using detailed product and industry information. Having congruence between the short-term data (monthly and quarterly) and annual data sources (for example, the Annual Business Survey) ensures revisions can be minimised at the Supply-Use and Input-output stages.

Summary of planned work:

By March 2026

• Balancing: this is a fundamental step in National Accounts which is monitored closely. Research in partnership with the Economic Statistics Centre of Excellence has commenced which will also inform ONS practice.

By March 2028

• Congruence of surveys: Introduce enhanced congruency checks between the turnover collected on the MBS monthly form and the annual ABS form, both at company level and top down by industry.
• Improved timeliness of the delivery for the Annual Business Survey with additional targeted quality assurance to meet user needs.

C3. Prioritised themes

The ONS has a continuous improvement approach to ensure the ongoing relevance of the National Accounts where changes to data, methods and systems are managed in a tightly controlled way to ensure the integrity of the National Accounts. Change is often grouped and prioritised by theme, with updates managed in a way to balance the revisions of data, and the interconnectedness across the National Accounts.

In recent years, themes have included updates to price deflators, research and development, re-platforming from legacy systems (for example, on the short-term surveys), trade, and globalisation (see Section B3.3: Trade in Services).

While not exhaustive, this section highlights upcoming themes, in addition to those discussed in part in Section C2: Different approaches to measuring GDP and balancing, which will ensure the ongoing relevance of the National Accounts (classifications and financial), while also tackling areas of significant user interest (for example, regional, and environmental).

C3.1 COICOP and Household expenditure

At a foundational level, classifications underpin the economic measurement. Annex D describes the latest foundational changes.

With these latest updates to the international manuals, these include the latest Standard Industrial Classifications (SIC), Standard Occupational Codes (SOC), Classification of Individual Consumption by Purpose, COICOP). Having a dual-coded understanding of businesses on an existing and new classification basis, is essential to ensuring a robust transition between the classification updates, along with providing consistency over time for analytical and policy implications.

One of the prioritised changes needed to be introduced is the use of the new COICOP. This impacts both Price collection, and the measurement of Household expenditure.

Summary of planned work:

By March 2028

• Classification of Individual Consumption by Purpose (COICOP): National Accounts and Prices need to take on the new COICOP classification, agreed as an international standard in 2018. The new classification better reflects new products and is much better suited to classify current consumer expenditure. In 2026 we will have started data collection using the new COICOP classification as part of the Living Cost and Food survey; while in 2027 we aim to have completed the required National Accounts system redevelopment to use the new COICOP in the production of Household Final Consumption Expenditure statistics with the intention that relevant National Accounts data are published on this new basis from 2028 onwards.

C3.2 Financial and non-financial accounts

High priority developments are already underway and planned on these areas. The use of automated methods for balancing will enhance and streamline the Sector and Financial Accounts. The re-platforming work for the Financial Accounts, Dividend and Investment Matrix, and Balance of Payments is also underway. In the Non-Financial Accounts development work is progressing on improving timeliness for Capital Stock estimates in the context of Net Domestic Product, and integrated work for Volume Index of Capital Services.

Summary of planned work:

By March 2027

• Quality improvement in balancing with the use of automated methods: A new automated whom to whom balancing process which functions at the most appropriate level and is flexible to adjust to changing data quality. This will minimise the size of balancing adjustments and create a more efficient, timely process. The system will need to be integrated utilising the newly re-platformed financial account system.

By March 2028

• Transformation of FA DIM BOP systems, which includes the Sector and Financial Accounts - this project is already underway. The re-platforming of the FA DIM BoP system will facilitate the move away from the current legacy technology. This will improve efficiency and consistency of methods between Balance of Payments and Sector Financial Accounts which will improve quality and coherence. This re-platforming will ensure the system is fit for the future with increased flexibility to implement the new international standards.
• Enhancement and use of Financial Services Survey data in GDP and financial accounts.
• Legacy uplift of processing systems for the 1) Financial Services Survey, 2) non-monetary financial institutions (NMFI), and 3) related financial sector processing such as insurance regulatory data.
• Improved timeliness for Capital Stocks in context of Net Domestic Product calculations.

C3.3 Regional and sub-national estimates of GDP

Robust regional and sub-national estimates of Gross Domestic Product (GDP) are essential for understanding the distribution of economic activity across the UK. There is increasing emphasis on place-based growth, levelling up, devolved decision-making and evaluating local economic performance.

Summary of planned work:

By March 2026

• Regional estimates of GDP: Following the recent Economic Statistics Centre of Excellence (ESCOE) review of methods, the ONS will reinstate the regional estimates of GDP implementing the recommendations made by ESCOE with improved methods.

C3.4 Environmental economy

Robust, rapid and detailed measurement of the environmental economy is crucial to meet policy requirements and our own objectives of understanding the interactions between environment and economy. High quality UK natural capital accounts statistics will be central to meeting SNA25 requirements for estimates of depletion of natural resources for use in calculation of the Net Domestic Product measure.

Summary of planned work:

By March 2027

• Natural Capital Accounts quality improvement: Higher quality statistics demanded by users, initial enabling work on methods and systems improvements to build on in moving to official statistic status and potentially progress towards accredited statistics status by end 2028 to 2029, as a prerequisite for work due to be undertaken by the same deadline on SNA25 natural resource depletion.

The ONS delivers population statistics, including demographic insights on the current and future population, migration, births and deaths. The statistics are essential to inform decisions, support service delivery, and determine financial allocations.

The ONS’s population outputs form the foundation of the statistical system and are a vital contributor to economic statistics through their role as denominators and survey weights. They are essential to GDP per capita and survey-derived Labour Market statistics. Users of ONS economic statistics also value population outputs to inform fiscal forecasts and support understanding of the impact of migration or an ageing population on the labour market.

The context of changing migration patterns following the coronavirus pandemic and changes to travel following the UK’s departure from the EU has increased the complexity of measuring the population.

The ONS has been making greater use of administrative data to improve the quality, frequency and range of statistics available and reduce reliance on data collection through surveys. These developments have been positive, but require continued focus, as outlined in the following paragraphs, to ensure the statistics support key user needs. Our improvements will also include supporting users in understanding the variety of published estimates and giving greater clarity on which figures are most suitable for different purposes.

Population estimates are underpinned by a decennial census. To support the future system of population and migration estimates, the UK Statistics Authority Board has recommended to the UK Government that a whole population census of England and Wales is undertaken in 2031. This would combine the strengths of a whole-population data collection with the additional value that administrative data can provide. The decision to undertake a census rests with government. If it is confirmed, planning and testing for a 2031 Census in England and Wales will be carried out in parallel to the activity outlined in this annex. Decisions in Scotland and Northern Ireland are for governments in these nations, on advice from their statisticians.

D1.1 Population estimates

The ONS produces national and local authority mid-year population estimates by age and sex for England and Wales and publishes UK estimates drawing on data from other UK nations.

The ONS also produces smaller geographic area estimates including health geographies and output areas. We are working towards new methods for mid-year population estimates and have published our current assessment against the decision criteria for transition. We are aiming to transition in summer 2026, subject to assessment against the criteria.

To support this, by March 2026, we plan to achieve:

• Improved understanding of the quality of the Demographic Index (DI).
• Tested sensitivity of model to input data sources.
• Met ONS coding best practice standards and fully delivered on network IT.
• Demonstrated better understanding of coherence across different data and across the UK.
• Confirmed whether DWP Registration and Population Interaction Database (RAPID) data should be included in DI and population statistics estimation.

More broadly, the ONS plans to achieve the following improvements and milestones to improve mid-year population estimates:

By March 2026

• Initial scoping on method improvements for internal migration.
• In winter 2025/26, publish first official provisional mid-2025 estimates.
• Developed methods for small area population estimates, to support conclusion on best future approach.

By March 2027

• Adopted admin-based estimates as official mid-year population estimate by summer 2026, subject to assessment against the decision criteria, and requested assessment for accreditation.
• Developed proof of concept methods for internal migration.
• Published “in development” small areas population estimates based on new methods.

By March 2028

• Introduced new internal migration methods to official estimates.
• Provided clear explanation of coherence of population statistics system in terms of coherence of population and migration estimates and coherence of estimates across the UK.

D1.2 Population Projections

The ONS produces national population projections for the UK and its constituent countries. They are widely used in planning, including fiscal projections, health, education and pensions. Subnational population projections (SNPPs) for England provides data down to local authority level and are used for local housing, education and healthcare planning and funding. Both products are also used as population denominators in economic and health statistics, and as control totals for survey weighting. The ONS plans to achieve the following improvements and milestones:

By March 2026

• Identified potential to reduce lag in production of estimates, including consideration of alternative products to meet user needs for shorter term projections and provide greater clarity on the best estimates for specific purposes – this includes working with economic statistics colleagues to support rhythm of outputs and any planned revisions meet their needs, alongside other users.
• Improved modelling for mortality, fertility and migration assumptions.

By March 2027

• Completed system change for SNPPs to move off legacy systems.
• Incorporated new population estimates methods into projections processes.
• Concluded (and published if relevant) work on alternative products.

D1.3 Migration

The ONS produces estimates of UK Long Term International Migration, including information on reasons for migration and nationality. This is a high-profile output in its own right, but also a key input into population estimates and projections.

The ONS plans to achieve the following improvements in this area:

By March 2026

• Published update on new methods for EU and British Nationals (in advance of November 2025 publication).
• Outputs produced using reproducible analytical pipelines which meet ONS best practice coding standards.
• Subject to meeting quality criteria, implemented new EU and British Nationals methods in regular long term international migration statistics.

By March 2027

• Requested assessment with view to becoming accredited official statistics.

D1.4 Births and Deaths

The ONS publishes weekly deaths and quarterly births data. They are mature outputs based on high-quality admin data, produced using reproducible analytical pipelines and meet most user needs.

However, delays to death registrations impact some areas, such as estimates of excess deaths, and causes of death with typically long registration delays, such as suicides and drug and alcohol-related.

We are focused on the following planned developments:

By March 2026

• Decide on merits of moving to occurrence-based reporting, based on earlier access to coronial cases, and to police data for suspected suicide deaths. If the decision is positive, incorporate change into workflow by end 2025/26 reporting year.

By March 2028

• Transition to the latest International Classification of Diseases for cause of death (ICD-11) from the start of 2028, subject to external bodies maintaining their current timelines.

D1.5 Life expectancy

National Life tables are published annually based on internationally agreed methodology. They provide period life expectancy by age and sex for the UK. Each national life table is based on population estimates, births and deaths for a period of three consecutive years. Our focus of future work is continuous improvement.

D1.6 Housing and household projections

The ONS produces estimates of families and households for the UK annually using LFS data. Our ability to produce these estimates to appropriate quality standards is dependent on LFS and TLFS development (as set out in A3 Social Surveys and B2 Labour Market). Alongside this we are also developing estimates from administrative data in the medium term.

SI1 The Future of Business Surveys and Statistics

The Future of Business Surveys and Statistics (FBSS) is an ambitious programme of work, which sets the foundations for transforming business surveys and its associated outputs. It has been established as a cross-organisational project focused on business surveys and associated business statistics which provide many of the key inputs for our core economic statistics. It is also relevant in responding to wider user needs, including those that are interested in microdata research. It is also a key enabler for our ability to adhere to changes in international standards.

FBSS itself is likely to be a multi-year work programme, aimed at achieving the following key goals:

• Ensure statistical outputs are in line with user needs, international standards, and comply with the code of practice.

• Improve quality of data (including coherence and validity) collected / acquired from respondent and alternative sources.

• Minimise burden of collection of data from respondents and businesses and improve responder experience.

• Improve flexibility, sustainability, integration and efficiency of affordable statistical production.

• Improve output flexibility, accessibility and coherence to support trend tracking, analysis and granularity.

• Enhance and develop ONS strategic platforms and solutions aligned with relevant ONS programmes and regularity needs.

The FBSS is set up to take a holistic approach to the transformation of business surveys and statistics. All elements of the end-to-end Generic Statistical Business Process Model (GSBPM) are included in the scope of the project to ensure that the ONS produces more relevant, efficient, and coherent statistics from businesses, about businesses and the wider economy.

The FBSS vision is to deliver:

• Improved measurement of the UK economy reflecting changing user needs through more coherent and representative business statistics.

• Data collection that is driven by a business-centred approach to design and engagement, and better use of alternative data sources.

• An efficient, adaptable and sustainable system for collecting business data and producing business statistics.

The project’s scope includes reducing redundancy in business surveys to reduce respondent burden, removal of legacy technology, improving efficiency and lowering risk in operational processes, and laying a foundation path for future years, including the ability to adopt new international standards. All of which supports the UK Statistics Authority (UKSA) strategy by making statistics more efficient, coherent, and of higher quality. By consolidating surveys, eliminating duplication, and modernising the data collection and statistical production process, the ONS will deliver more reliable statistics, support informed decision-making, and respond more effectively to emerging economic trends.

Within the FBSS scope of work, one of the core delivery objectives and initial area of focus is an Integrated Annual Business Survey (IABS) which will collect data through themed modules to improve data validity and coherence across surveys and statistical outputs. A core spine will replace the current Annual Business Survey and be necessitated by changes across the statistical value chain, from results processing to integration in the National Accounts. The core spine will provide the foundation for integration of some other key annual surveys which will reduce respondent burden and ensure that survey design is both sustainable and future-proofed to adapt to emerging user needs.

Critically, the delivery of the IABS will enable the delivery of other organisational priorities, otherwise not achievable with the current design of statistical production and survey portfolio. The changes to collection will require changes to the results and processing across the statistical value chain to achieve these benefits. These include:

• Adoption of agreed international standards following the 2025 revision of the System of National Accounts (SNA) and Balance of Payments (BPM) and associated manual and classification changes, which will be crucial for ONS to maintain international comparability.

• A further reduction in the ONS legacy estate, which will build a foundation for other integrated and modularised business surveys.

• Adoption and exploitation of the new Statistical Business Register (SBR), which will provide us with improved business population coverage, quality and capability, alongside opportunities for future exploitation to enhance design and data linkage.

• Better coherence across statistical production, including ability to exploit alternative data sources.

Scope and Plan

The preliminary work required to take place during 2025 to 2026 financial year is currently funded. A transition phase 1 of the Integrated Annual Business Survey has a target date for despatch of March 2027, which also includes completing the changes required to support data collection, editing and validation and results processing. Future phases of FBSS are likely to include progress against all collection groupings which sit within the broad scope of the FBSS:

The ONS plans to achieve the following:

By March 2027

• Integrated Annual Business Survey future transitions (ABS, Purchases, plus potentially Prodcom and ASGS).

By March 2029

• Integrated International Trade survey (QITIS, AITIS plus possible Trade in Goods).
• Integrated non-financial assets and liabilities survey (QCAS, ACAS, QSS, FALS (BSS).
• Integrated Financial Business data collection grouping.

SI2 International Macro-economic Statistical Standards (IMSS)

Following the recent sign-off of the core System of National Accounts (SNA25) and Balance of Payments (BPM7) revisions, the UK has proposed to implement these changes via a multi-year process involving tightly sequenced changes to each of the economic frameworks; aiming to conclude implementation by end of 2030.

The latest International Framework changes include updates to several classifications which underpin the structure of the economy in the UK and across the world.

Of particular importance is the update to the Standard Industrial Classification (SIC) which represents a foundational enhancement to the architecture of economic statistics. As structural transformation accelerates—driven by digitalisation, global value chains, and the use of intangible-intensive business models—our legacy classifications need updating. This reclassification is a methodological upgrade that will ensure the accuracy, relevance, and analytical power of economic data, and continue to ensure statistical outputs remain relevant in a post-industrial, innovation-led economy.

This round of international SNA 2025 revisions has been aligned with changes to numerous other related manuals (e.g. Balance of Payments, Manual for Government Deficit and Debt) and classification structures (e.g. industry and occupation classifications). This has significant implications across the ONS, as this implies changes will be integrated into registers and surveys, as well as impacting the statistics and analysis generated.

The international frameworks are very important for economic statistics:

• they reassure financial markets, investors and credit rating agencies that UK economic statistics can be trusted and readily compared with other advanced economies.

• failure to adopt them can have direct consequences. For example, part of our trade asymmetry with the USA is because the USA have not moved with the UK to the latest BPM framework; and;

• compliance with them is an important indicator of the quality of our statistics.

• they sometimes have direct financial consequences, for example; the UK’s contributions to the European Union (EU) (both in the past and under the withdrawal agreement) are based on national accounts concepts in the legal document for the European System of Accounts (ESA 2010).

The ONS has developed early and work in progress implementation plans taking account of international and domestic priorities. While subject to change as we develop deliverable plans, the following sets out some examples of key areas of focus that will enable us to adhere to agreed priorities within the suite of international macro-economic statistical standards (IMSS). Some of these workstreams are change activities highlighted elsewhere in this paper and demonstrate the integrated approach towards adhering to these standards, and can be summarised as follows:

• Foundational activity that underpins how we will adopt the new International Macro-economic Statistical Standards:
  • The development and delivery of a new Statistical Business Register (SBR) to enable inclusion of the new Standard Industrial Classification.
  • The development and delivery of the annual structural surveys and statistics through the FBSS program of work - for example, development of the Integrated Annual Business Survey.
• Classifications that define data in the frameworks:
  • Standard Industrial Classification (SIC).
  • Product classifications - for example, Classification of Product by Activity (CPA), Classification of Individual Consumption According to Purpose (COICOP) and Classification of Functional of Government (COFOG).
  • Others – assets, sectors, transactions.

Part of this includes updating our statistical outputs to align to the revised standards for SDMX (Statistical Data Metaexchange – the ISO standard for statistical data). In addition, this standard will also be used as the basis for providing data outputs for the ONS website.

• Other key enabling activity that is needed to support some aspect of the International Macro-economic Statistical Standards
  • Re-platform of Sector and Financial Accounts and Balance of Payments systems (FA DIM BOP).
  • The development and delivery of the Financial Services Survey (FSS).
  • Redevelopment of Household Financial Consumption systems.
• Prioritised changes to adhere to the System of National Accounts (GDP impacting):
  • Data as an asset.
  • Enhancement of Globalisation Treatment.
  • Digitalisation - for example, cloud computing, artificial intelligence.
  • Quality adjustments of public sector output.
  • Alignment of sum of costs approach.
  • Natural resource depletion.
• Prioritised changes to adhere to the System of National Accounts (non-GDP impacting):
  • Core National Accounts.
  • Satellite and other accounts.
• Other framework specific prioritised changes beyond what is delivered via adhering to the SNA:

  • Balance of Payments Manual 7.
  • Government Finance Statistics (GFS).
  • System of Environmental Economic Accounting (SEEA).
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