ASRB Quality Management Approach

Last updated: 23 September 2026

Introduction

Analysis, Statistics and Research Branch (ASRB) within the Department for Infrastructure (DfI) is responsible for producing and disseminating a range of Official Statistics and Accredited Official Statistics relating to the Department’s travel, transport and planning functions. Statistics and research published by ASRB are available on the DfI website.

Background

ASRB staff are statisticians within NISRA and work in compliance with the Code of Practice for Statistics. The Code sets out the standards that producers of official statistics are expected to meet to ensure their work serves the public good, as required under Section 10 of the Statistics and Registration Service Act 2007. The Code is based on the three core principles of:

  • Trustworthiness;
  • Quality; and
  • Value.

This document focuses on the core principle of Quality and outlines the quality management approach taken by ASRB and how this aligns with our commitment to data quality.

Quality

Standard five of the Code of Practice (Edition 3) states:

Producers must support a quality culture that promotes good practice and encourages learning and improvement, under the direction of the Chief Statistician/Head of Profession for Statistics – so that the public can have confidence that published statistics are produced by organisations that continuously improve quality standards.


Within this standard, it states under 5.8:

Publish your quality management approach and explain how it aligns with your organisation’s commitment to data quality.


ASRB is committed to working to ensure that statistics are produced to a level of quality that meets users’ needs. We will proritise quality and will aim to do this by:

  • Engaging with users;
  • Collaborating with data suppliers;
  • Internal data validation; and
  • Continuous improvement.

Engaging with users

By engaging with our users, ASRB will be able to understand the level of quality that users need to ensure our published statistics are fit for purpose and can be trusted by the public. Our User Engagement Strategy outlines how we engage with our users. We will commit to having information on data quality published as part of or alongside our statistical reports. All statistics will be published with either a Background Quality Report or links to the relevant data providers’ quality documentation. Furthermore, all statistics published from administrative data sources will, where appropriate, be supported by a Quality of Administrative Data document, and all statistics published from survey data will include information on the survey methodology and sampling errors/confidence intervals, either within the report or in an accompanying technical report. We will clearly communicate any information users need to know prominently in a ‘User Information’ or an equivalent introductory section within our reports and we will highlight any limitations or caveats where relevant. We will use our customer email distribution lists and DfI/NISRA websites and social media channels where appropriate. We will seek feedback from users on our key statistical publications and use platforms available to us, such as Rate-it and Citizen Space, to make it easy for users to provide their input. As NISRA statisticians, we will contribute to the implementation of NISRA’s new Dissemination Strategy as outlined in the NISRA Corporate Plan.

Collaborating with data suppliers

All data received from outside DfI will be managed and transferred in accordance with Data Sharing Agreements, Information Sharing Agreements and/or Memoranda of Understanding agreed by the relevant parties. Data suppliers will be required to highlight any potential data quality issues which can then be investigated further. We will collaborate with our data suppliers to ensure the timely receipt of quality data but when issues arise we will keep our users informed. We will engage with data suppliers pre data collection and/or transfer to develop a common understanding of quality matters and strengthen working relationships. Our Quality of Administrative Data reports will all include a section on data supply and communication to support openness and transparency.

Internal data validation

Internal data validation will be led by appropriately skilled staff in a supportive working environment, with access to expertise from colleagues within the branch and across the wider NISRA network. NISRA provides centralised training on data quality, which all new ASRB staff will undertake. This training helps promote good practice in data validation and supports the consistent completion of quality assurance documentation. ASRB will validate statistics through comparison with other relevant statistics and data sources, where possible, and seek feedback from topic experts through our working groups and partnership meetings when appropriate. ASRB will continue to roll out its Reproducible Analytical Pipleline (RAP) implementation plan in line with NISRA’s vision to widen the use of RAP to produce outputs efficiently and to a consistently high standard; this will bring greater confidence that published statistics are accurate, transparent, reproducible and defensible. ASRB will continue to develop its expertise in tools such as Python and further enhance its R coding capabilities to support more efficient validation and quality assurance of official statistics. We will consider new and innovative approaches to quality assurance where appropriate, including the use of tools such as Microsoft 365 Copilot to support and enhance our processes. ASRB will actively encourage and respond to user feedback on the quality of our statistics, including through our ongoing online survey, using this insight to inform continuous improvement. We will also draw on the skills, knowledge and expertise of colleagues and stakeholders to strengthen our quality assurance processes, including through output and code peer reviews.

Continuous improvement

NISRA is committed to continuous improvement in its statistical processes, adapting to new digital tools and methods to enhance data quality. The NISRA Corporate Plan sets out the Agency’s aspirations and ambitions for 2025-2029. ASRB will contribute to the delivery of these objectives and may benefit from NISRA’s ongoing focus on developing advanced analytical and statistical skills across the organisation. Our statistical practice is regulated by the Office for Statistics Regulation (OSR) and recommendations from OSR assessments are shared between sections e.g. at DfI statistical team briefs. In addition, OSR compliance reviews of existing accredited official statistics will check our compliance with the code and highlight any opportunities for improvements. Again these improvements will be highlighted across the branch, encouraging best practice and learning from others. We will explore self-evaluation to support high-quality statistical practice and drive continuous improvement. Where feasible, the OSR Self-Evaluation Tool will be used as a living document to assess current performance, identify opportunities for enhancement and monitor progress against improvement actions. We will aim to embed ongoing self-evaluation as part of our continuous improvement.

Conclusion

ASRB is committed to prioritising Quality as a core principle of the Code of Practice for Statistics. This document sets out our approach to quality management and reflects our commitment to using appropriate data sources and robust methods to produce statistics that are reliable, fit for purpose and worthy of public confidence. We recognise the importance of being transparent about the quality of our statistics, enabling users to understand both the strengths and limitations of the data and the extent to which it meets their needs. We also acknowledge that quality is not static; it can change over time as data sources, methodologies and user requirements evolve. It is therefore essential that we regularly review our data, processes and outputs, and embed a culture of continuous improvement to ensure our statistics remain relevant, accurate and of high quality.


Contact Details

For further information contact Regina McGeown or Martin Devlin
Principal Statisticians ASRB