What do we mean by intelligent transparency?
At its heart intelligent transparency is about proactively taking an open, clear and accessible approach to the release and use of data, statistics and wider analysis. There are three core principles which combine to support intelligent transparency: equality of access, enhancing understanding and analytical leadership. Intelligent transparency is at the core of many of the practices outlined in the Code of Practice for Statistics.
Why is it important?
Statistics and data should serve the public good. They should allow individuals to reach informed decisions, answer important questions and provide a mechanism for holding governments to account. Statistics and data also underpin successful implementation of government policies, and individuals’ views on the effectiveness of policy decisions.
Transparency and clarity support public confidence in statistics and the organisations that produce them and minimise the risk of misinterpretation of statistics and data.
For many who see the publication of numerical information by governments, the distinction between official statistics and other data, such as management information or research, may seem artificial. Therefore, it is important to consistently adopt a transparent and accessible approach to communicating data, statistics and wider analysis.
When governments take an open approach to statistics, data and wider analysis about themselves and the policies they implement, such as demonstrating transparency with data that is in the public interest, they can support public confidence in both the data, and the policy decisions based on them.
What does unintelligent transparency look like?
Unintelligent transparency could come in a few different forms. For example, there could be a complete lack of published data to support a statement or claim. There could also be unclear sources for quoted figures – so numbers are used but can’t be scrutinised because we don’t know where they come from or how they have been compiled. Finally, unintelligent transparency could also involve unclear methods, definitions, or limitations and what these mean for how the data should be interpreted and used.
Who is intelligent transparency relevant for?
Intelligent transparency is relevant for all those collecting, using and data, statistics and wider analysis across governments and public bodies. This ranges from analysts, through to policy-making and operational staff and communications teams. Everyone has a role in ensuring that transparency and clarity underpin their important work and we would encourage a default approach of transparency first.
What is OSR doing to support intelligent transparency?
We in OSR continue to champion transparency and equal access to data, statistics and wider analysis.
We are engaging with analysts, policy-makers and the communications function across government, and the civil service’s most senior leaders, to advocate intelligent transparency. We are also engaging with the wider community outside of government to develop networks committed to and advocating for intelligent transparency. We have further engagements planned over the summer and autumn.
We are continuing to build our evidence base, highlighting good examples and understanding more about barriers to transparency. In the state of the statistics system 2021/22 report we highlighted some good examples of improvements the transparency and equality of access to statistics.
We also continue to intervene on specific cases where we deem it necessary, guided by the UK Statistics Authority’s interventions policy.
And through our work on analytical leadership, we advocate that governments should show leadership by truly recognising the value of government analysis as an asset for informing public life, as well as for policy and decision making. In this way, analysis which addresses society’s key questions should be published as standard, with clear insights to support understanding by different audiences, in ways that enhance appropriate understanding, and support confidence in accurate interpretation.
How can users of data and statistics help to encourage and support intelligent transparency?
We’re under no illusion: OSR can’t resolve this on our own. Whether an organisation or individual user of data or statistics produced by governments or public bodies we need your help.
Be an advocate for intelligent transparency. Question the data you see. Does it make sense? Do you know where it comes from? Is it being used appropriately?
You can raise concerns with us via firstname.lastname@example.org – our FAQs about how to raise an issue set out what to expect if you raise a concern with us. We’d also love to hear from other organisations with an interest in transparency.
And you can keep up to date with our work via our newsletter.
How can analysts, statisticians, communications and policy colleagues in individual teams help support intelligent transparency?
Champion intelligent transparent in your team, your department and your individual work. You can ensure that intelligent transparency underpins your individual work. You can build up relationships with those in the data, policy and communications publication chain to ensure everyone understands what intelligent transparency is and how to go about implementing it. We have published regulatory guidance for the transparent release and use of statistics and data to help with this.
You can also raise any concerns you may have with your Head of Profession for Statistics. They will be able to support and advise you on any transparency-related issues, and on issues relating to the Code more generally.
We are also always here to support producers, so do reach out to us if you would like to discuss any issues at email@example.com
Being transparent often seems to involve lengthy commentary regarding the limitations of our data.
Intelligent transparency is not about promoting lengthy explanations. It is about being open in releasing your information and being frank in its narrative. If you decide that a longer explanation may be useful in enabling more complex analysis to be presented clearly, it is always worthwhile writing plainly, considering how the audience will understand it and be encouraged to read it. If there are key limitations which users need to be aware of to appropriately use and understand the data, then it is important to make these clear, succinct and visible. You may need to think carefully about exactly how your data are presented if there is a high risk of misinterpretation due to limitations.
Analysts often have minutes to address the transparency issue and so it sometimes becomes a question of transparency after the event. How can this be addressed?
Ideally data to support any public statement should be published in advance or at the same time as the statement is made, with a clear explanation of strengths and limitations. We would encourage all producers of data, statistics and wider analysis to consider what processes and plans they can put in place in advance to minimise the risk that this doesn’t happen. We would urge analysts to think early in the policy process about the data and statistics needed to support policy development and when they will need to be published to support decision-making. Also to build relationships with policy communications and other analysts interested in the data. We would also urge others in government, including communications and policy colleagues and senior leaders to bring analysts in early when developing new policy.
However, we recognise that on occasion unpublished data are referred to unexpectedly. In these instances, the information should be published as soon as possible after any statement has been made – ideally on the same day as the analysis should already be available and a grid slot should not be required, given the data have already been quoted. This can be done via an ad-hoc release. For example, the Department for Work and Pensions has a page dedicated to ad hoc statistical analyses.