Standard nine of the Standards for Official Statistics in the Code of Practice for Statistics underscores the vital need for data and statistics to be communicated in ways that are plain for users to understand and support their use.
Clear communication involves effective data presentation and visualisation, key information about what the numbers mean, appropriate context to support interpretation, and an openness to consider the receiver of the information and to strive to better meet their needs.
The Standard
9. Producers must clearly present the statistics to support appropriate interpretation, collaborating with other producers and experts to develop fuller insight for key topics – so that the public can have confidence that the statistics support understanding and use
9.1 Release relevant, clear statistics, data and related information that are suitable for different types of users
9.2 Communicate the statistics in a way that helps users understand issues and support them to make appropriately informed decisions. Provide a clear description of the main messages with suitable data visualisations
9.3 Provide comparisons to support interpretation and signpost other relevant statistics, including within the UK and internationally. Explain the consistency and coherence with other related statistics and sources
9.4 Explain how the statistics add value and serve the public good, to demonstrate and help users and potential users understand how they could inform decision making
9.5 Aid understanding by highlighting potential misinterpretations. Clarify the meaning of the statistics when they are used inappropriately
9.6 Collaborate with other producers across the UK and subject experts to provide appropriate context and insight on the statistical topic
9.7 Give advance notice of material changes to the content of releases, such as the removal of data tables or variables, and any change in the frequency of release
9.8 Consider new ways to present data where appropriate. Improve ways of disseminating and presenting the statistics. Look to better meet the needs of different types of users and potential users
Questions to consider
1. Support understanding
How are you supporting different types of users to understand the statistics? Are there other ways to better capture or represent the key messages?
2. Clarity
What is your approach to ensure that messages are clear and use as simple language as possible? Have you received any feedback about the clarity of the statistical release that highlights any misunderstandings on the part of users, for example, are the statistics appropriately described by the media?
3. Coherence
Do you signpost to other relevant statistics? How are these presented? Are you clear about the similarities and differences between the statistics?
4. Comparability
How do you support users to make comparisons to gain a deeper insight? Are there better ways to present important comparisons?
5. Collaboration
Have you worked with other producers or expert users recently? Are there areas you can collaborate to provide further insight on important topics?
Related guidance
Office for Statistics Regulation:
- Approaches to presenting uncertainty in the statistical system
- Dashboards
- Comparability framework tool
Government Statistical Service (GSS):
- Writing about data
- Communicating quality, uncertainty and change
- Data visualisation: charts
- Data visualisation: colours
- Data visualisation: dashboards
- Making analytical publications accessible
- Releasing statistics in spreadsheets
- The ONS content style guide: a guide to communicating statistics
- Coherence of statistics
UNECE:
Good practice examples: Presenting information clearly
Blogs
- DWP: Presenting data: 5 tips for making your data understandable
- Cabinet Office: Communicating the quality of ethnicity data
- Analysis Function: Finding ‘good’ numbers: my secondment to the BBC
- OSR: Communicating data is more than just presenting the numbers
- OSR: Whose line is it anyway? Why the misleading presentation of statistics cannot be dismissed as just a matter of opinion
Case studies
- Office for Health Improvement and Disparities (OHID): Turning knowledge into action
- GSS: Providing new statistical insights during the pandemic
- Defra, Home Office, NISRA, ONS: Clarity and insight in government statistical outputs
Good practice examples: Communicating uncertainty
Blogs:
- OSR: How to communicate uncertainty in statistics
- OSR: Ed Humpherson reflects on why communicating uncertainty is a constant challenge for statisticians
- OSR: Revising GDP: The challenge of uncertainty
Case studies:
- Office for National Statistics: Effectively Communicating Uncertainty in GDP
- National Records Scotland: Communicating uncertainty for Scotland’s Census 2022; a case study from National Records of Scotland
Good practice examples: Dashboards and infographics
Blogs:
- OSR: From Trend to Tool: Elevating Dashboards with Trustworthiness, Quality and Value
- OSR: Is a picture really worth a thousand words? – Do’s and don’ts of infographics
Case studies:
Good practice examples: Collaboration between producers
Blogs:
Case studies:
- Scottish Government: Providing clear insights through visible collaboration
- DWP: Enhancing insights and coherence through collaboration