Intelligent Transparency FAQs

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 regulation@statistics.gov.uk – 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 regulation@statistics.gov.uk


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.

Draft Guidance: Collecting and reporting data about sex in official statistics

Introduction

Data on an individual’s sex is a commonly asked for or recorded variable in official statistics. Some producers of statistics are making changes, or considering making changes, to the data they collect and report about sex. This guidance details what producers should consider when collecting and reporting data about sex, to meet the expected standards of trustworthiness, quality and value, as outlined in the Code of Practice for Statistics.

As the regulator of official statistics, it is not for us to define what data about sex are collected across the statistics landscape. The UK statistics landscape is complex, with a variety of different data and statistics being produced. Equally, the needs of people using data and statistics can be extensive and varied. This means there can be valid reasons to produce measures based on different classifications or definitions depending on the question the producers are trying to address through the statistics. Our role is to ensure that statistics serve the public good and meet society’s needs for information; we do this by ensuring statistics producers develop and produce statistics in line with the Code.

Work is underway across the Government Statistical Service (GSS) to develop and support the use of harmonised measures of sex and gender in data collection across government. Some of this work will include guidance on what form of data collection and disaggregation is most appropriate in different circumstances. The Office for Statistics Regulation (OSR) supports this work and will continue to engage with producers as it develops.

OSR’s expectations of producers when collecting and reporting data about sex

As a producer, if you are currently collecting and reporting data on sex or are considering making changes to how you do so, it is important that you do so with clarity, being transparent about the reasons for your judgements and decision making throughout. You should explain to users what and how data are being collected and support the appropriate use of the statistics.

Below we summarise our expectations of producers when collecting and reporting data about sex, under each pillar of the Code.

Trustworthiness

  • The collection and reporting of statistics about sex should support a legitimate public interest and be done in the least intrusive way. Those producing and releasing statistics should be impartial and independent and demonstrate sound judgement.
  • Producers need to understand what data they can legally collect about an individual’s sex and comply with relevant legislation, as well as considering any relevant nationally- and internationally-endorsed guidelines.
  • The privacy and identity of individuals must be protected at all times during data collection, storage, analysis and reporting. This includes being clear and open with individuals providing information about how their information will be protected, applying relevant security standards to keep data secure and using appropriate disclosure methods when releasing statistics.
  • Producers should understand the public debate on data about sex and ensure their statistics stay relevant to a changing society. This means statistics should be regularly reviewed, with users and other stakeholders involved to help prioritise any development plans. Where producers identify user needs that may be impacted by how data on sex are collected, they should consider how they can meet those needs in their work programme, working collaboratively where appropriate, including with relevant subject experts.

Quality

  • Producers need to ensure data and statistics stay relevant to a changing society and are of sufficient quality. This means that the statistics should be based on appropriate data and methods.
  • Producers must have a good understanding of, and clearly explain, the sources of data about sex they are using and how these are collected. This applies to survey and administrative data sources; both the question(s) used, and the way that these are completed (i.e. whether data are self-reported or completed by another individual – an interviewer or an operational official, for example) can influence the exact nature of data collected and whether this is a mixture of sex registered at birth, self-identified sex, lived gender and others.
  • Producers should ensure that data are collected in a respectful way and understand any risks to data quality or survey response when asking for sensitive information from a person.
  • Producers cannot always design or change administrative systems which enable public services to be delivered. But they should seek to understand the systems, including any risks and biases that may arise from the way the systems collect and categorise data.
  • Uncertainty in the source data should be identified and the extent of any impact on or limitations of the statistics should be clearly reported. For data about sex this may be particularly relevant when considering data at smaller sub-group levels.
  • Producers should be clear about definitions or terminology they use, and these should be harmonised to be consistent and coherent with related statistics and data where possible. The terms ‘sex’ and ’gender’ should not be used interchangeably in official statistics.

Value

  • Statistics should meet their intended uses and should inform public debate. To achieve this, producers must seek to understand their whole user base and the questions that users want to be able to answer with their statistics.
  • Where an evolving or new user need has been identified, statisticians should consider whether the data that inform the statistics can and should be enhanced to better capture this information. This could mean, where feasible, seeking to build relationships with external data suppliers so that producers have the opportunities and means to influence data collections. Where a user need cannot currently be met, producers should explain why this is the case, and anything that can be done to help these users.
  • Decisions about whether to continue, discontinue or adapt statistics about sex should be made in discussion with users and other stakeholders. If a change is made to data collection, or if information about a data collection practice emerges which makes it clear that the nature of the data may have been previously misunderstood, a clear explanation of the change should be published, with evidence of the rationale and, wherever possible, the analysis that informed the change.
  • Collection and reporting of data about sex is a sensitive and potentially divisive topic and there may be times when producers are unable to meet the requests of everyone who has an interest in their statistics. In these cases, it is more important than ever to be transparent and open about the decision-making process and the evidence used to inform the choices that have been made, particularly in relation to any areas of contention.

A worked example: recording and reporting of sex in criminal justice statistics

Criminal justice statistics are important statistics which help the public understand the nature of incarceration in their country.

There are examples within official statistics relating to criminal justice across England and Wales and Scotland where breakdowns of the data are presented by sex, with data marked as ‘female’ and ‘male’. The data used to produce the statistics comes from the court system in each country. It is recorded by an operational officer and this means there can be variation in the way data about sex is captured across the system. This means it is not possible to know what definition of sex is being captured. This can, in turn, place limitations on how some criminal justice statistics can be interpreted and used.

In this instance, it is hard for the statisticians to change the administrative systems, but they can understand them. OSR would expect producers of the statistics to:

  • understand the nature of the data they are currently using to produce their statistics
  • clearly state how data about sex are gathered
  • clearly explain any terminology in the statistics – the Ministry of Justice does this well in its Statistics on Women and the Criminal Justice System publication, and in the associated technical guide
  • have robust quality assurance measures in place
  • clearly explain any limitations of the data and the impact these have on the statistics and their use. In addition, we would encourage producers to build relationships with their data suppliers, so that they can have the conversations to seek change where there is an identified need, and it is feasible

Finalising the guidance

We published this guidance on collecting and reporting data about sex in official statistics as draft and welcomed comments from statistical producers and other stakeholders. Thank you to those who shared your views with us.

In the coming months we will be reviewing all the feedback we received before finalising the guidance.

If you have any questions, queries or further feedback as we go through this process we would be happy to hear from you. Please email us.

Statistical leadership: Making analytical insight count

Executive Summary

This report sets out the findings from our review of statistical leadership. It looks at how statistical leadership can be strengthened across government.

Strong statistical leadership is essential to ensuring statistics serve the public good. Many decisions draw on statistics published by governments across the UK. Successful implementation of government policies can be dependent on public confidence in the data and messages shared by government. Individuals need to be confident in the data and associated narratives in order to make decisions which impact on their lives, business, or charities.

Governments need to be role models for statistical leadership. They need statisticians who can show leadership within the profession and across their organisations, and officials who can champion the use of evidence and be confident in engaging with analytical experts. All those with public facing roles must be capable of communicating messages drawing on data to support public confidence in data and how they have been used.

The report is intended to act as a starting point for further engagement. We will be engaging widely across analytical and other professions and plan to provide a progress update to this report in 2022. If you have feedback or would like to discuss any aspects of this report please contact us.