Quality: Standards for Official Statistics with related practices
5. Chief Statisticians/Heads of Profession for Statistics must encourage a quality culture that promotes good practice and ensure their statistics will not materially mislead users
so that the public can have confidence that published statistics are fit to be used for the intended purpose
- Be open about your quality management approach and how you ensure appropriate quality standards. Be proactive in considering the dynamic nature of statistical quality
- Use independent evaluation to periodically review the effectiveness of processes
- Provide a safe environment and support staff in raising quality concerns
- Conduct timely reviews of quality issues and determine whether published statistics should be withdrawn and if unpublished statistics are suitable to be released
- Inform the Director General for Regulation of any concerns about potentially misleading statistics
- Commission reviews of statistical areas with serious quality concerns and be open about the resulting actions taken to improve the statistics
6. Producers must use suitable data sources and sound methods, and assure the quality of the statistics across the production and release processes, being open to innovate to keep statistics relevant and useful
so that the public can have confidence that the statistics are produced in robust ways
- Produce statistics to a level of quality that meets their intended uses
- Use the best available data for what needs to be measured. Monitor for changes in the sources, and explain any issues and their implications for use in producing statistics
- Check the suitability and availability of existing data from governmental and non-governmental sources before collecting new data
- Maintain constructive relationships with those involved in the statistics supply and preparation process. Be clear about your data requirements. Ensure the burden on providers is proportionate to the anticipated benefits
- Base methods on national or international good practice, scientific principles or professional consensus. Identify and address limitations. Use recognised standards, classifications and definitions
- Use data that are coherent when aggregated, consistent over time and comparable across geography. Seek to improve consistency and coherence
- Collaborate with experts, other analysts and statistics producers in the UK and internationally and share best practice
- Use a proportionate quality assurance approach across production and release processes. Be open about why you are satisfied that the statistics are of suitable quality. Monitor quality dimensions for both input data and the statistics
- Keep up to date with possible ways to improve the statistics. Assess the added value of method developments and consider the impact on the statistics
- Regularly review strengths and limitations in the data and statistics, involving users. Be open about your decisions and reasons
7. Producers must prominently explain the quality of the statistics, including any strengths and limitations, and communicate the uncertainty in the estimates
so that the public can have confidence in using the statistics to make decisions and take actions
- Prominently communicate the quality of the statistics and the strengths and limitations that impact their use. Describe any uncertainty in the estimates, for example, using qualifying words, numbers and graphics
- Explain the nature of data sources and why they were selected. Prominently communicate limitations in the underlying data and explain their impact
- Be clear about the methods used. Explain quality issues related to the methods, systems and processes. Identify potential bias and describe any steps taken to address it
- Give advance notice of method changes. Explain the nature and extent of the change, and provide a consistent back series where possible
- Clearly flag where statistics are being developed and tested. Be transparent about developments, outlining the plans and expected outcomes