Transparency data

Quality management approach for statistical publications

Published 27 August 2026

This document outlines the Home Office’s approach to ensuring its statistical publications are robust and fit for purpose, with respect to its role as a producer of statistics under the UK Statistics Authority Code of Practice for Statistics.

Quality assurance: Home Office’s approach

In producing statistics, the Home Office works with the following frameworks in mind:

• The Code of Practice for Statistics, outlining the standards to be followed in the production of official statistics, including its 3 principles of trustworthiness, quality and value
• The AQuA book, outlining principles for good practice in the quality assurance of data analytics
• The Government Functional Standard for Analysis, outlining expectations for planning and undertaking the analysis of data
• The Reproducible Analytical Pipelines (RAP) strategy, outlining techniques that can be used to carry out reproducible, transparent, efficient, auditable and high-quality data analysis
• The Quality Assurance of Administrative Data (QAAD) framework, outlining standards against which organisations can assess the quality of administrative source data

The various principles and practices outlined in these frameworks allow the Home Office to carry out robust and high-quality analysis, ensuring that methods, processes and practices are based on established cross-government good practice. We continue to challenge ourselves in the extent to which we are meeting these principles and will continue to develop our staff and our analytical pipelines where opportunities to do so are identified.

To support our quality assurance activities, we encourage and maintain an open dialogue with our data suppliers, to gain an understanding of any limitations of our source data so that we can take appropriate action, including communicating remaining caveats to users in our statistical releases. We have regular meetings with data supplier forums, such as the Police Data Requirement Group (PDRG), as well as on an ad-hoc basis as issues arise. We work closely with operational colleagues, in the police and border force, to understand the practicalities and feasibility of collecting data, plus to explain changes in trends when they occur. More information on the data we use for statistical publications can be found in our use of administrative sources for statistical purposes.

To ensure that our statistical releases continue to offer good value to users, we encourage feedback via email or surveys in every release, acting upon feedback gained as and when appropriate to do so. More information can be found in our user engagement strategy for statistics users.

To ensure our statistics remain high-quality and relevant to users, we identify development projects each year. These include focusing on improving data quality, implementing automation through RAPs and developing the explanation of limitations and uncertainty in the outputs. More information can be found in our statistical work programme.

More information can be found in individual topic methodology and quality notes, available through Statistics at Home Office.

Dimensions of quality

The European Statistical System Committee (ESSC) outlined the following 5 dimensions of quality in their European Statistics Code of Practice.

Relevance

Statistics should offer, and continue to offer, value which is relevant to users’ needs.

Home Office continually assesses the relevance of its statistics via insights gathered through the methods outlined in our user engagement strategy for statistics users. Where practical and appropriate to do so, we will make changes with those user needs in mind.

Accuracy and reliability

Source data should be error-free and consistent over time.

Home Office carries out routine data validation and maintains an open dialogue with its data suppliers to gain an awareness of the potential limitations associated with data and works with those suppliers to improve data at source, as described in our statement on administrative data sources.

We carry out robust quality assurance on our analysis, in line with the principles outlined in The AQuA Book. Working under the Reproducible Analytical Pipelines (RAP) framework allows us to set up our analytical pipelines in a way that facilitates more effective quality assurance.

Timelines and punctuality

Statistics should be published in a timely manner, as soon as practical after the data becoming available, and in line with users’ needs.

Home Office publishes its official statistics as soon as practical after the data becoming available, with any delays usually being due to the need for thorough quality assurance.

RAP enables us to produce statistics in a more efficient manner, reducing the time it takes to prepare releases for publication.

We are fully transparent on where and when we will publish releases; for more information, see our statement on release practices.

Comparability and coherence

Statistics should be coherent and consistent both within the same release, over time, and when compared with other similar releases.

We routinely carry out checks as part of quality assurance steps to ensure that all the sections within an individual report are coherent wherever possible, and that the release is also coherent over time.

On occasion, figures may be legitimately different within a release or may have changed since the previous release. Where identified, these will be explained.

Accessibility and clarity

Statistics should be clear and accessible to all users. Statistics producers should be transparent about the quality of the release.

Home Office publishes its statistics openly on GOV.UK (Statistics at Home Office), using accessible file formats wherever possible. We focus on our presentation of charts and tables to ensure they are formatted in a manner that is as clear and accessible as possible, to the greatest range of potential users.

We include statements on the quality of the release in our publications and are transparent on known data limitations and sources of uncertainty.

For more information, see our statement on release practices and our statement on accessibility