Data Quality Management Policy

This Data Quality Management policy covers all data held by the Office for National Statistics (ONS), including management information such as HR and finance data, as well as administrative and survey data. All ONS employees, in any role, should be aware of and adhere to this policy, as it covers the whole data lifecycle, from data inputs to outputs. This policy provides high-level data quality management requirements covering both data and statistical quality and is part of the UK Government’s Data Quality Framework.

This policy applies to all UK Statistics Authority staff, including ONS employees, staff on fixed-term, temporary or permanent contracts, staff on secondment, students, and contingent workers.

This policy covers all the data that the Office for National Statistics (ONS) holds, either as a data controller or a data processor, including those obtained through surveys and from administrative sources in the private or public sectors. The policy is valid from data acquisition and collection by the ONS and extends through the lifecycle up to and including data archiving and data disposal. This does not just include data sources we acquire or collect and the outputs we produce, but also any intermediate data product within the data lifecycle. This may include data that are not collected or used for statistics and statistical research, such as HR and finance data.

This policy helps to ensure that all UK Statistics Authority staff members consider and manage data quality throughout the data lifecycle. Any user of ONS data (internal or external) is encouraged to raise any issues related to data quality.

This policy supports the Code of Practice for Statistics, specifically its Quality pillar, which provides guidance to ensure that data and methods that produce assured statistics are adhered to.

Establishing and maintaining a consistent approach to assuring that data quality covers the Data Quality Dimensions is important to the ONS. This is to support our overall strategic direction and achieve our corporate objectives by using policies and data standards to uncover and address issues and risks associated with the quality of ONS data.

Finally, this policy covers the full data lifecycle and should be used in conjunction with the UK Government's Data quality dimensions.

Public trust in our statistics relies on high‑quality data. To rebuild and strengthen that trust, we must better understand, manage, and communicate the quality of all data we collect and use.

Data quality should shape every stage of the data lifecycle, from planning and design to analysis and publication.

Good quality data are fit for purpose, supported by strong governance, clear communication, and continuous attention, and go beyond just data cleaning.

As set out in the UK Statistics Authority’s strategy for the UK's official statistical system, Statistics for the public good, its mission is to produce high-quality data and analysis to inform the UK, improve lives, and build the future. The Authority’s Strategic priorities for the UK statistical system highlight the main priorities for the ONS, including increased focus on improving quality and restoring trust. In our The plan for ONS economic statistics page, we explain that this 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.”

1. We will consider and embed data quality at every step, from planning and collecting data to storing, using, and sharing it, meaning we make sure the data are fit for purpose, monitored, and that any problem that arises from it is fixed early:

• while this may involve multiple stakeholders, primary ownership of these tasks rests within the roles identified in this policy’s Section 6: Roles and responsibilities

• processes shall be in place to systematically review and assess the quality of data

• the impacts that quality has on data use and decision making shall be considered; if the quality is low, it is essential to make sure that everyone is aware of the risks

• data quality shall be built in from the start and considered throughout the data lifecycle (for example, considering the quality of the data shall be included in data sharing agreements)

• any remediation activities shall be documented to include the impacts to the rest of the data lifecycle

• data quality issues shall be identified, documented, escalated, and communicated as appropriate in each area

• a formal data handover procedure must be agreed and implemented between teams involved in the data lifecycle; this shall include accompanying agreements on communication, documentation, and quality metrics

• inappropriate use of data shall be challenged as per the Code of Practice for Statistics’ statement that statistics should be based on data sources that are appropriate for the intended uses; if there are any concerns around the appropriate use of statistics, then the concerned party is instructed to email the head of profession for advice

• where data is combined or linked, consideration shall be given to potential data quality challenges that this may introduce

• processes shall be in place for reviewing the quality of data

• any substantial changes to this Data Quality Management policy that establish a new mandatory process shall be approved by the Data Governance Council (once established)

2. Data quality shall be communicated to all users and data quality issues shall be documented (for example, through data quality action plans) at all stages of the data lifecycle, ensuring risks are known and understood:

• data quality action plans, as described in the UK Government’s Data quality action plan: implementation guide, must be in place for at least each Essential Shared Data Asset (ESDA), critical data asset, or critical data element, as described in the UK Government’s guidance on ESDAs

• any changes to or improvements on data quality within the data life cycle shall be appropriately communicated to all users

• all supporting data quality information shall be communicated, retained, kept up to date, and its impact must be clearly explained to users

• supporting data quality information shall inform users through tailored communications, so they may form their own opinion of the quality of the data, based on their specific needs

• quality information and metadata shall be made available at the same time as the data, regularly updated when necessary, and clearly communicated to users

• all contracts and agreements for the supply or use of data shall consider how to maintain, assess, and communicate data quality, and escalate any issues

• the ONS must have in place robust and transparent procedures, across all business areas, to capture feedback on data quality and resolve quality challenges by taking appropriate and proportionate actions, across the whole data lifecycle

• a process that details the path to engagement and resolution shall be in place for each critical data set

3. All teams in the ONS shall establish a culture of good data quality, meaning that data quality shall be at the core of every activity across the full statistical production lifecycle:

• all ONS staff are to be aware and acknowledge that support is available through Quality Central, or by request to our Quality and Improvement Division, if quality capability is not held within the team

• all ONS staff shall be empowered to challenge data providers, internally and externally, where data isn’t fit for purpose; there shall be access to the required data quality information so that users can make informed decisions

• data quality culture shall work such a way that information can be shared throughout the data life cycle; questions and challenges shall be encouraged, including reflective practices and sharing lessons learned, to develop confidence among colleagues; senior leaders shall implement these behaviours and share their own experiences, as to promote this culture

This section describes our data governance roles, which have been defined based on the UK Government’s guidance on Data Ownership in Government.

ONS staff working with data

Staff working with data must:

• demonstrate compliance with this Data Quality Management policy

• demonstrate awareness of their individual responsibilities contained within this policy relating to data quality and quality assurance of data and their effect on the quality of data, statistics, and analysis · demonstrate awareness of their obligations under the Quality Standard for Analysis

• demonstrate awareness of the Quality Assurance of Administrative Data (QAAD) standard supporting the Code of Practice for Statistics principle on Q1: Suitable data sources

• raise concerns regarding data quality through line management and Quality Champions, and through the Statistical Quality Maturity Model Exercise

• ensure that risks and issues associated with data quality, together with associated actions, are appropriately recorded in their Divisional Quality Improvement Plan

• ensure that the commentary accompanying statistics and supporting Quality and methodology information appropriately reflect the quality of the data

Quality and Improvement division

Our Quality and Improvement division are responsible for:

• providing expert advice and guidance on best practice related to data quality

• acting as an ONS-wide sponsor for data quality, clearly communicating data quality requirements

• supporting data quality remediation and escalation to the ONS Strategic Design committee as and when required

ONS Strategic Design Committee

Our Strategic Design Committee is accountable to the ONS Permanent Secretary and the UK Statistics Authority Board, and is responsible for:

• overseeing data and technology architecture, and methods, governance, and data protection obligations

• leading strategic investment and reducing redundancy by streamlining platforms and guiding the sequencing of work

UK Statistics Authority

The UK Statistics Authority is accountable to the ONS Permanent Secretary and responsible for:

• providing independent scrutiny and assurance against the policy on behalf of our Permanent Secretary

• supporting data policy development to ensure that it represents data quality well

• providing independent scrutiny of data quality audits as and when required

• ensuring that data quality activities remain transparent and align with this policy