Measuring and communicating the quality of government statistics is crucial if they are to be trusted by the public. There is support available for everyone in the Government Statistical Service (GSS) to improve quality.
What support is available?
Guidance on the GSS website:
- Quality statistics in government (a useful introduction to quality)
- Quality Assurance of Administrative Data (QAAD)
- Communicating quality, uncertainty and change
- Tips for urgent quality assurance of ad-hoc statistical analysis
- Tips for urgent quality assurance of data
- GSS Quality strategy case studies
Guidance from other sources:
- The Aqua Book
- Thinking about quality when producing statistics
- The Generic Statistical Business Process Model (GSBPM)
If a department needs help with anything related to measuring or reporting the quality of their statistics, the Government Data Quality Hub (previously known as the Quality Centre) based in the Best Practice and Impact division of the Office for National Statistics are here to help the whole Government Statistical Service. Email firstname.lastname@example.org to find out more.
The Data Quality Hub (DQHub) have completed several consultancy projects for departments including the Ministry of Housing, Communities and Local Government (MHCLG), Department for International Development (DfID), NHS Digital and Department for Digital, Culture, Media and Sport (DCMS). Two of these consultancy projects can be seen in more detail.
Case study: Ministry of Housing, Communities and Local Government
Following the identification of an error in the Ministry of Housing, Communities & Local Government (MHCLG) Rough sleeping in England: autumn 2018 statistics, the DQHub were commissioned to undertake a review of the Quality Assurance (QA) processes in place for the statistics. The DQHub developed a report which identified several recommendations to improve the QA processes and prevent a similar error from occurring in the future.
Sandra Tudor, the Head of Professions for Statistics at MHCLG, said of the consultancy project:
“We’re really grateful for the way in which the Best Practice and Impact Team were able to lead a review of quality assurance for us. They worked well with our teams to understand the practices at MHCLG and made practical recommendations which will help improve our statistics going forwards.”
Case study: Department for International Development
The DQHub developed recommendations to help the Department for International Development (DfID) raise awareness of the importance of data quality in the organisation, improve collaboration between DfID central and country offices and make links with similar organisations and work with them to overcome data quality issues. A member of the team also went on secondment to help implement these recommendations and assist in updating their internal guidance.
Neil Jackson, the Chief Statistician for DfID, said of the consultancy project:
“The review was really helpful. We knew our approach needed refinement and having an external perspective was really useful. We have some good suggestions to take on board and look forward to continue working with the Best Practice and Impact Division through the secondment to drive the improvement of our results data.”
We have developed a two year GSS Quality Strategy.
This strategy sets direction on the quality of statistics across the GSS. It was developed through consultation with key stakeholders across the GSS and sets out realistic actions to improve quality and address key quality challenges. The strategy will provide guidance for all those involved in delivering statistics across the GSS.
Data and Analysis Method Reviews (DAMR) cover topics of interest and innovation in data. These review state-of-the-art methods in these topics and make recommendations for government work. These were previously known as National Statistician Quality Reviews (NSQRs).
DAMRs complement existing quality assurance practices, further ensuring methods are, and remain to be, fit for purpose.
These reviews are endorsed by the Government Analysis Function.
Quality champions aim to raise the quality of official statistics produced by government departments.
For general questions about measuring and reporting the quality of statistics, please email email@example.com
If you want to find out more about measuring and reporting quality in your department speak to your quality champion.