Guidance

Defra group Statistics Quality Statement

Published 6 August 2020

Defra group Statistics Quality Statement

1. Why is quality important

Quality is important to:

• Establish Trust and Confidence - in the knowledge that statistics are produced to a high standard

• Provide Robust Evidence - underpins and enhances decision making.

2. Definition

The routes of the definition of quality are:

• The definition of quality for Official Statistics agreed by the Government Statistical Service (GSS) is “fitness for purpose”

• Statistical quality is defined as meeting users’ needs with particular reference to the Relevance, Accuracy, Timeliness, Accessibility, Comparability and Coherence of the statistics collected, analysed and reported.

3. Scope

Covers all statistics produced across the Defra group. Defra group is the combination of a number of statistics producing organisations:

• Core Department

• Forestry Commission (non-Ministerial Department)

• Executive agencies - Animal and Plant Health Agency (APHA), Centre for Fisheries and Aquaculture Science (CEFAS), Rural Payments Agency (RPA), Veterinary medicines Directorate (VMD)

• Executive non-departmental public bodies - Environment Agency (EA), Joint Nature Conservation Committee (JNCC), Marine Management Organisation (MMO), Natural England (NE).

4. Who has responsibility?

Responsibilities for quality are held by:

• We all have responsibility for the quality of our statistics, their quality assurance and continuous improvement

• Lead statisticians have responsibility for Quality Management, Peer Review and reporting to the Defra group Head of Profession for Statistics on Quality issues

• Quality and Publication Champions and GSS Good Practice Team for the provision of expert advice.

5. How do we achieve this?

Our primary aim is to improve and sustain a mutually beneficial partnership between the users and producers of our statistics, which is based on open and continuous dialogue / consultation User Engagement Policy Statement.

Key principles underpin the delivery of statistical quality:

• Users are identified and dealt with in a spirit of consultation and responsiveness and their needs prioritised and met within the available resources

• Methodologies, processes and practices are documented to the correct level of detail for their purpose, kept up to date and made publicly available where appropriate

• Statistical processes and outputs are monitored and measured against quality standards with a view to their maintenance and improvement

• High standards applied to dissemination / clarity covering the quality of the output and also the means by which the statistics reach the audience

• Suppliers, including third party suppliers of information are respected and dealt with ethically, legally and effectively.

6. Process Quality applied to the raw statistical data

Information obtained at each process stage can be analysed and problems addressed, leading to a process of ongoing improvement.

Process quality used	What’s this about
Efficient	Producing the desired outcome in a cost-effective way, considering performance cost and where relevant respondent burden
Effective	A process that is successful in delivering the desired outcome to meet user / business needs
Transparent	A process that is open, visible and clearly understood and must include procedures to ensure confidentiality and security
Flexible	A process that can readily adapt to changing priorities and demands
Integration	Is about processes that complement each other

7. Output Quality

Relates to the quality of the final output and it’s “fitness for purpose” and covers five key areas.

Output quality used	What’s this about
Relevance	The degree to which the statistical outputs meet user needs for both coverage and content
Accuracy and Reliability	The closeness between an estimated result and the (unknown) true value. For all data sources-how well the information is recorded and transmitted
Timeliness and Punctuality	Timeliness refers to the lapse of time between the publication and the period to which the data refers. Punctuality refers to the time between the actual and planned dates of publication
Accessibility and Clarity	Accessibility is the ease with which users are able to access the data. Clarity refers to the quality and sufficiency of the metadata
Coherence and Comparability	Coherence is the degree to which data derived from different sources refer to the same phenomenon. Comparability is the degree to which data can be compared over time and domain

8. How are we doing?

What we are doing to achieve our aims on quality:

• Feedback - we actively encourage and respond constructively to all feedback received from our users e.g. complaints via the Office for Statistics Regulation (OSR) and conduct periodic internal reviews

• Quality Assurance Tools - used to ensure the methodology is robust, the text is clearly presented, and the outputs disseminated to a high standard

• Continuous Internal Quality/ Peer Reviews - ongoing commitment to enhance the quality of our outputs and to ensure they keep pace with priorities and changing needs.

Defra group Head of Profession Statistics

21 February 2017