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Population and Society

What is Levelling Up and how will its success be measured?

‘Levelling Up’ is now a term used daily in the media – but what does it mean and how are we, as the statistics watchdog, going to monitor its impact? Statistics Regulator Ben Bohane discusses…

Not long before I joined OSR as a Regulator, the Conservative Party made ‘Levelling Up’ a key part of their 2019 election manifesto. It focused on challenging and changing the geographical inequality in the UK, through investment and new infrastructure to allow ‘everyone the opportunity to flourish’.

Prior to working at OSR, I taught Economics to young people as a Secondary School teacher. I found teaching young people how changes in the economy and government spending might impact on their lives – really rewarding. I think back to those young people now – do they understand what Levelling Up is amongst the media hype? How will the proposals that are outlined in the Levelling Up White Paper impact their lives and futures?

If I were to explain it to my students now, I would describe Levelling Up as a plan to eradicate regional disparities in the UK, raise living standards and provide greater opportunities to people, in communities and areas that have so far not had the success of more prosperous parts of the country.

But with confusion over the concept really means – how can we measure something for which the success means different things to different people? Back in March, OSR’s Director Ed Humpherson wrote about ‘Why I Love Evaluation’ stating that evaluation “provides evidence of what works; it supports good policy; it builds the skills and reputation of analysts; it helps scrutiny.” Ongoing evaluation of Levelling Up will be key to its success.

In OSR our focus is on ensuring existing statistics that can be used to measure the success of government policy are of sufficient trustworthiness, quality and provide public value. But also, that statistics are available in the first place. As the government highlights in the White Paper, many of the metrics that will be used to measure the success of Levelling Up are either not yet available or of insufficient quality. The clarity of what’s being measured is important if people want to track progress through data.

In OSR we’ve already been working on public interest in regional disparities and fighting for a statistical system that is more responsive to regional and local demands. We have:

Our Business Plan highlights that we have seen a growing public expectation that decisions affecting all aspects of our lives will be evidenced by trustworthy and accessible statistics. Over the coming months and years, we will continue to review new statistics and data sources from the Department for Levelling Up, Housing and Communities, Office for National Statistics and other data providers as they are developed to ensure that evidence and evaluation is at the forefront of pushing the plans forward.

Our regulatory programme for this year focuses on projects that will improve public understanding of the issues, current and emerging, that people want to be sighted on. As the statistics regulator, reviewing the statistics used in Levelling Up, we will be tracking the implementation of the GSS Sub National Data strategy and new tools such as the ONS Sub National Indicators Explorer, ensuring statistics are the best quality they can be and clearly focussed on measuring the outlined Levelling Up missions.

Statistics supported by clear analysis and evaluation will provide the evidence to measure the impacts, successes and failures of Levelling Up – and any future government policies to address regional disparities and improve people’s lives. As the government implements policies to address regional inequalities – and businesses and households respond – we will focus on ensuring that the statistics both accurately measure and live up to this ambitious long-term strategy. It is important to me as a statistics regulator that we do this. After all, the vision of Levelling Up is so important to the futures of those young people I used to teach.

Appendix 1: Background foundation work on surveys that are used to produce economic statistics

Appendix 1: Background foundation work on surveys that are used to produce economic statistics

ONS Purchases Survey statistics  (December 2019):

ONS reintroduce the survey following the National Statistics Quality Review of National Accounts to provide better information about purchasing patterns by business.

Our review found that the quality of outputs from the survey is still being improved, which reflected ONS’s own narrative that it would normally be several years before a new survey was producing statistics that could be used with confidence. It also reflected that the Annual Purchases Survey aims to collect variables that do not naturally fit with many businesses’ operational models. Our report noted the discrepancy between estimates of intermediate consumption derived from the Annual Purchases Survey and the Annual Business Survey. We said that it is an essential part of demonstrating that the quality of the statistics meets users’ needs that these differences are understood, explained well, and are used to further improve the statistics.

ONS UK Business Demography statistics (October 2020)

We reviewed ONS Business Demography statistics because we felt they should be considered key economic indicators. They are not regarded as such because they are not as good or as useful as they should be. The ONS’s business register – the Inter-Departmental Business Register (IDBR) – holds a wealth of data on the UK’s business population, some of which are used to produce business demography statistics. The remainder of which remain a largely untapped resource. In response to the COVID pandemic, ONS introduced a weekly indicator of business births and deaths and introduced a quarterly series of experimental business demography statistics. These innovations presented a platform for further development of the statistics. However some required improvements to the statistics rely on significant investment and we said that work to develop ONS’s business register should urgently be re-introduced to ensure that users’ needs for business population statistics are met. In our review we made several short-term recommendations for ONS:

  • demonstrate progress in understanding the access difficulties users are experiencing when using and linking IDBR data with data
  • publish its plans for publishing more timely business demography statistics, and its plans for developing the recently introduced quarterly experimental statistics
  • publish a narrative covering what ONS already knows about the range of key data quality issues, building on the supporting quality information provided with the new quarterly experimental statistics
  • publish its plans to restart and resource work to develop its business register

We also said in the longer term, ONS should publish a plan which includes specific actions, deliverables and a timetable that explains how it will address the improvements identified in the report, including plans for reviewing the funding of the Statistical Business Register.

ONS Annual Business Survey statistics (September 2021)

We reviewed ONS ABS and found that the significant time delay on the publication of ABS data means that the data are not always used to measure the ongoing impacts of structural and cyclical changes to the UK economy. As a result, ABS data are not fully meeting users’ needs for timely and detailed data on business performance.

We found ONS focus and priority on transforming short-term surveys means there has been a lack of investment in finance, staff, and systems and so ABS data have been unable to keep up with changing demands on their use. The lack of investment has curtailed ONS’s efforts to improve the detail and timeliness of ABS data.

We found a lack of investment has been a common theme of OSR’s recent assessments of ONS’s structural economic surveys and statistics. We strongly urged ONS to revisit the investment needs of these outputs, to ensure structural economic data are available to assess, for example, the ongoing impact of the economic shocks of Brexit and the pandemic.

Appendix 2: OSR work on regional statistics and Levelling Up

Appendix 2: OSR work on regional statistics and Levelling Up

ONS Statistics on Regional Gross Value Added (August 2017)

“Many of the R-GVA users that we spoke to cited poor timeliness as a limitation of these statistics” and “that unless the R-GVA statisticians find new sources that provide the same level of detailed information more quickly than the current sources (which they indicated to us is unlikely in the short term), the timeliness of these statistics is unlikely to change significantly”.

“ONS might do more to bring out the differences between the regions through the proportions of people in the region who are economically inactive, which can affect the GVA per head statistics and the impact of commuting on the statistics” and requested ONS “to work with its national and regional stakeholders to bolster the statistical services such as information, advice and guidance available to provide even greater insight in sub-regions (particularly new city-regions) and in preparing contextual information to aid regional and country media in interpreting the statistics”.

ONS Statistics on Regional Gross Value Added (Phase Two) (June 2018)

We asked ONS to make further improvements, for example, “investigate whether improvements in the quality of deflators by adopting regional price statistics could be achieved technically and cost-effectively taking account of expected use of the statistics and user need”. We also asked ONS to “review the best way of making quality metrics both more useable to a less expert audience and more accessible generally”.

HM Treasury Statistics on Government Spending: Country and Regional Analysis (May 2019)

We asked HM Treasury to:

  • collaborate with producers of other public finance statistics and with analysts in the countries and regions to seek views, update their understanding of users’ needs to better support the use of these statistics
  • communicate effectively with the widest possible audience to increase awareness of the statistics and data
  • present CRA data in a more engaging way that supports and promotes use by all types of users and those with interests in spending at programme and service levels (sub functional levels)
  • test the strength of user need for CRA on a ‘where-benefits’ basis, examine the feasibility of collecting data on this basis and the trade-off between enhanced functionality and increased burden on data suppliers
  • provide a clear and comprehensive account in each annual CRA publication to allocation methods, including the inclusion of links to published documents about allocation methods in respect to all ongoing major project spending
  • ensure that users are provided with appropriate insights about changes in the data. This should include helping users understand impacts on the CRA data and provide links, when applicable, to other output areas where information on Brexit impacts has already been published
  • establish a development programme for these statistics and periodically review that programme; be open about progress towards meeting priorities and objectives; and arrange for users and other stakeholders to be involved in prioritising statistical plans
  • strengthen its arrangements for reviewing requests to allow pre-release access to new people; review the current list of those with pre-release access for CRA, with a view to minimising the numbers of individuals included and inform the Authority of the justification for each inclusion

ONS Experimental statistics on Regional Household Final Consumption Expenditure (HFCE) (January 2021)

We highlighted the potential of HFCE estimates as a highly important component in fully understanding regional economies. Prior to this there were no regional estimates of the expenditure measure of GDP, except in Scotland, a topic we previously highlighted in our 2020 submission to the Treasury Select Committee’s inquiry into Regional Imbalances.

DLUHC Levelling Up Fund prospectus (March 2021)

The Levelling Up Fund prospectus included a list of local authorities by priority category.

However, initially no description of the methodology used was attached to enable users to understand how local authorities were allocated to priorities areas. A week later a DLUHC published a methodology document, but it was still not possible to recreate the full dataset used to allocate local authorities to priorities areas.

We wrote to DLUHC publicly highlighting our concerns about the transparency of data related to the Levelling Up Fund and we requested DLUHC publish data that supported the allocation of priorities areas to enhance public confidence in the decisions that were being made.

As a result, DLUHC published the Levelling Up Fund: prioritisation of places model, which showed all the steps that were taken when using data to assign Local Authorities in England, Scotland and Wales to categories 1, 2 and 3. The spreadsheet included a “data and input construction” tab which included links to the source data with explanations of the source and why it was chosen.

ONS Foreign Direct Investment (FDI)  Statistics and DIT Inward Investment Statistics (April 2021)

As a result of our review new questions were added to the quarterly and annual FDI surveys, to collect more-granular data on sub-national FDI and ONS is now publishing experimental UK sub-national FDI statistics.

NISRA BESES statistics (December 2021)

As a result of our review, NISRA will be publishing more timely imports data and has developed an interactive dashboard that provides more-granular monthly international trade data on products.

ONS Income Estimates for Small Areas statistics (January 2022)

We suggested how further value could be added by ONS understanding the needs of current non-users who require income estimates at lower levels of geography.

Users’ want to be able to aggregate estimates for lower-level super output areas into bespoke geographies, the estimates are given for middle-layer super output areas which are too large for users’ needs.

DLUHC planning applications in England statistics and at the same time Homes England Housing Statistics (March 2022)

We felt at the time it was likely that planning performance and planning reforms will in some part be included in new Levelling up legislation, given its assumed focus on local area development.

LA planning application performance at the time had also been identified as a priority departmental outcomes metric in the 2021 Spending Review.

We advised further developments to the statistics. One of these developments included sub-national commentary, which should be introduced to help explore, for example, trends in planning to support regeneration in the 20 English towns and cities prioritised in the Levelling Up white paper.

We found the statistics could be further enhanced if Homes England were to publish information about aspects of quality, for example, limitations of data sources, quality assurance checks carried out by data suppliers, and the team’s assessment of data quality against our quality assurance of administrative data (QAAD) matrix

We also asked Homes England to consider how any uncertainty in the statistics might be more clearly communicated to users, as the latest data are provisional and subject to revision.

Finally, we suggested further insight and context should be added by enhancing the narrative and analysis provided for users who wish to explore the topic further.

Appendix 3: Treasury Committee evidence

Appendix 3: Treasury Committee evidence

2019 response

Key point

There is a range of official statistics on regional economic performance. They should be considered alongside other forms of data published by Government and others.

What we said

All data, whether classified as official statistics or not, should seek to adhere to high standards of trustworthiness, quality and value (which we describe as voluntary adoption of the Code of Practice’s pillars).

Key point

There are some limitations to the current data sources, both in terms of data gaps and in terms of quality.

What we said

In our written evidence referring to regional economic data, we highlighted “the quality of regional data is affected by the granularity that the data sources can provide, and/or the timeliness of the data provision”. Regional data is more volatile than national estimates and there are significant challenges in forming regional estimates of GDP.

We said “In arriving at aggregate estimates, statisticians often combine both administrative and survey data sources….and then disaggregate to provide regional breakdowns (a top-down approach). Survey data is often limited in its depth: for example, the data used to compile R-GVA can become stretched at lower geographies, becoming increasingly volatile as it is disaggregated further.”

Key point

There is a significant use of modelled data, which apportions national data to regions using formulae, rather than directly observed data, which would be gathered at the local level.

What we said

“During our regulatory work, we received feedback from users of regional and sub-regional economic data expressing concern that they can’t tell whether the data they are using is based on observed economic behaviour or come from modelled estimates. They view data based on observed estimates as more reliable than modelled estimates”.

At our request, the ONS conducted research into how much data measuring economic growth are directly observed at a regional level and collected in a way that can be immediately and wholly assigned to a single region, and how much data are modelled to provide regional estimates.

Key point

It may be worth considering a network of regional statistical observatories, akin to the Bank of England’s regional agents, that can help provide ONS and others with better insight into regional economic issues.

What we said

We wanted to highlight the benefits of a presence outside the offices of London, Newport and Titchfield – both to better understand the dynamic of regional economies, and to be closer to users with a regional focus (like combined mayoral authorities).

2020 response

“Developments [in regional statistics] will be enabled by better access to administrative data, where ONS can provide enhanced (ideally flexible) geographies with more use of direct estimation”.

“Regional performance information published by the UK Government can be found in some departmental annual reports and accounts but is not summarised in any compendium”.

We laid out several important conditions for publishing regional economic forecasts that could be adopted to help people make judgements about the UK and regional economy.

One of these conditions was: “It would be important to communicate the uncertainties associated with any regional GVA forecasts. For example, there are deficiencies in historical GVA data. Forecasts will only be as good as the data they rely on”.

Guest blog: Improving reporting and reducing misuse of ethnicity statistics

Richard Laux, Deputy Director, Data and Analysis, at the Equality Hub discusses his team’s work in improving reporting and reducing the misuse of ethnicity statistics in our latest guest blog, as part of the 30th anniversary of the United Nations’ Fundamental Principles of Official Statistics.

In my role as the Head of Analysis for the Cabinet Office’s Equality Hub I am in the privileged position of leading the team that analyses disparities in outcomes between different ethnic groups in the UK.

The reasons for disparities between ethnic groups are complex, and include factors such as history, relative levels of deprivation, the different age profile of some ethnic groups as well as many other factors. Despite the complexity of the issues, my team and I do all we can to prevent misuse of the data and help ensure that robust and clearly explained data are furthering the debate on race and ethnicity, which is an emotive topic for many people in this country.

My team’s responsibility for this is firmly rooted in the UN Principle 4 of preventing the misuse of statistics. We do this in a number of ways that align with this principle.

One way we do this is through bringing several analyses together to paint a broad-based picture of a topic of interest. For example, when supporting the Minister of State for Equalities on her reports on progress to address COVID-19 health inequalities we synthesised a large body of research describing the impact of the pandemic on ethnic minority groups. Much of this work involved my team reconciling and reporting on different sources and drawing robust conclusions from different analyses that didn’t always entirely agree.

A second way we try to prevent misuse of data is through the clear presentation of statistics, an example being Ethnicity facts and figures. This website was launched in October 2017 and since then it has been a vital resource to inform the debate about ethnicity in the UK. It gathers together government data about the different experiences of the UK’s ethnic groups and is built around well-established principles, standards and practices for working with data like the Code of Practice for Statistics.

We try to make the content on the website clear and meaningful for people who are not experts in statistics and data. It also contains detailed background information about how each item of data was collected and analysed to help those users with more interest or expertise in statistics draw appropriate conclusions.

The Commission on Race and Ethnic Disparities report recommended that RDU lead work to further improve both the understanding of ethnicity data and the responsible reporting of it (and thereby helping to prevent its misuse). As part of this work, we will consult on how to improve the Ethnicity facts and figures website, including whether we increase the amount of analysis on the site to help users better understand disparities between ethnic groups. Some of this might be in a similar vein to Office for National Statistics (ONS) work during the pandemic on ethnic contrasts in deaths involving the COVID-19. This modelling work showed that location, measures of disadvantage, occupation, living arrangements, pre-existing health conditions and vaccination status accounted for a large proportion of the excess rate of death involving COVID-19 in most ethnic minority groups.

Of course, there can be some difficulties with data that might lead to its misuse: datasets can vary greatly in size, consistency and quality. There are many different ways that ethnicity is classified in the datasets on Ethnicity facts and figures, and these classifications can differ widely depending on how and when the data was collected. For example, people might erroneously compare the outcomes for an ethnic group over time thinking it has remained the same whereas in fact it has changed; this might happen if someone is looking at data for the Chinese, Asian or Other groups over a long time period, as the Chinese group was combined into the ‘Other’ ethnic group in the 2001 version of the aggregated ethnic groups, but combined into the Asian group in the 2011 version of the aggregated ethnic groups in England and Wales.

We also try to minimise misuse and misinterpretation by promoting the use of established concepts and methods including information on the quality of ethnicity data. Our quality improvement plan and significant contribution to the ONS implementation plan in response to the Inclusive Data Taskforce set out our ambitions for improving the quality of ethnicity data across government. We will also be taking forward the Commission for Race and Ethnic Disparity’s recommendation that RDU should work with the ONS and the OSR to develop and publish a set of ethnicity data standards to improve the quality of reporting on ethnicity data. We will consult on these standards later this year.

Finally, we raise awareness and knowledge of ethnicity data issues through our ongoing series of published Methods and Quality Reports and blogs. For example, one of these reports described how the overall relative stop and search disparity between black people and white people in England and Wales can be misleading if geographical differences are not taken into account.

We have significant and ambitious programmes of analysis and data quality work outlined for the future. I would be grateful for any views on how we might further help our users in interpreting ethnicity data and preventing misuse.

Why migration statistics matter

Like many out there I wake up every morning hoping that a way, that protects life, has been found to bring peace in Ukraine. As it says in one of my young daughter’s books, “The world’s already far too full of cuts and burns and bumps”[1].

Unfortunately, the conflict continues and people from Ukraine are fleeing. On 10 March 2022, the UN Refugee Agency (UNHCR) estimates that just over 2.3 million people have fled Ukraine since 24 February 2022. Across the UK there has been an outpouring of public sympathy for Ukrainian people forced to flee. The Government has introduced some new visa routes for Ukrainians; and debate continues among the public, in the media and in Parliament about whether the UK is doing enough to help.

As with any crisis, lots of decisions will need to be made. Decisions by individuals, by governments and by agencies and by organisations helping to support people flee Ukraine and build new lives. Data and statistics are a key part of this decision-making process. For example, to inform local and national emergency response planning, the Office for National Statistics (ONS) has published new data about the number of Ukrainian nationals by local authority and the Home Office has published the number of people applying for these new Ukrainian visa routes.

Here at the Office for Statistics Regulation (OSR) I lead on OSR’s work on migration. At the heart of my role is ensuring that data and statistics serve the public good. What does this mean in this context? It means ensuring that the best possible data are available to inform decision-making. And it also means ensuring data are publicly available to help the public understand the impact of decisions made, for example to evaluate the impact of new visa routes for Ukrainians and the impact this has on the make-up of society in the UK.

Earlier this month, we published the first in a series of reports looking at how the Office for National Statistics (ONS) is transforming the way it measures international migration. These statistics provide estimates of how many people are flowing into and out of the country from across the world and what the impact is on the number of migrants in the UK. The previous methods, based on the International Passenger Survey (IPS), had limitations so it’s great to see new robust methods being developed in a credible way and in discussion with expert users. Our report welcomes the ambitious and collaborative approach being taken by the ONS to transform the way it measures international migration and recommends some ways ONS can build on this good work. I would like to thank all those we have engaged with us as part of this work for their openness and time. I look forward to continuing this work to ensure that the transformed migration statistics are trustworthy, high quality and support society’s needs for information.

More widely we also engage with other government bodies responsible for the production and publication of statistics and data on migration. For example, we regularly engage with the Home Office, which is responsible for publishing a wide range of statistics about migrants. We have recently written to the Home Office about the publication of data on migrants arriving in Small Boats. In our letter we welcomed the Department’s plans to regularly publish additional data about this topic.

At the OSR we want our work to have an impact. That means ensuring that data and statistics are there to inform decision-making across society, the public, private and third sectors and to help hold organisations to account. This is at the heart of what I do as a statistical regulator at the OSR and at the core of our migration work. I just hope in a small way this can have a positive impact on what is happening out there in the world today.

If you would like to feed into any of our work on migration statistics please get in touch with Siobhan Tuohy-Smith.

[1] Donaldson J & Scheffler A, 2010, Zog, Published in the UK by Alison Green Books.

 

 

 

 

It’s beginning to look a lot like Census…

It may be too early to talk about Christmas for some – not for me. I have decided on the design theme, got my advent calendar, am close to finalising the Christmas menu and have started ordering gifts. I am all over it! And getting more excited by the day. 

Christmas means different things to different people, but it is certainly my favourite census related celebration. Weren’t Mary and Joseph off to Bethlehem to register as part of a census? Timely then as part of my, possibly a bit too keen, Christmas preparations, I am pleased to say we have published our phase 2 assessment reports for the 2021 Census in England and Wales and the 2021 Census in Northern Ireland. 

If you read my previous blog, you’ll know I have been leading OSR’s work on the Censuses in the UK and today is a bit of a milestone moment for me as part of this assessment. The publication of these reports is a culmination of a range of work which kicked off three or four years ago and it has been so interesting and rewarding to speak with users and stakeholders of Census data and statistics throughout –  it’s been an absolute gift!  

Our reports recognise the efforts of the Office for National Statistics and the Northern Ireland Statistics and Research Agency in delivering Census live operations and their continuing work to produce high quality, extremely valuable Census data and statistics. I wanted to take the opportunity to specifically thank all of the individuals and teams who have taken the time to engage with me and my colleagues as part of this assessment process. You have been open with us, kept us up to date with developments and have taken on board our feedback throughout the process. All the while getting on with the more important job at hand, working on Census itself. 

As we get closer to the festive season, I wish you all a well-deserved break and raise a glass of sparkling elderflower pressé to one and all.  

Related links:

Assessment of compliance with the Code of Practice for Statistics – 2021 Census in England and Wales

Assessment of compliance with the Code of Practice for Statistics – 2021 Census in Northern Ireland

A closer look at loneliness statistics

At OSR, we have always been aware of the importance of loneliness statistics on a national and local scale. In 2019, we started a systemic review of loneliness statistics to investigate the state of official statistics on loneliness in the UK. 

Initially, we found there were some significant gaps in loneliness data that were not being filled by official or national statistics. Statistics users we spoke to, such as charities focused on loneliness, told us this made it more difficult for them to carry out their core functions of preventing and tackling loneliness among the UK population.  

We heard that good quality statistics that covered local and regional geographies were needed in order for them to deliver their services, allocate funding, and in some cases, present evidence to their regional parliaments. Where official statistics were not meeting these needs, expert users were often stepping in and producing their own statistics to fill data gaps. Given this, we identified a range of specific recommendations to help improve official statistics on loneliness. 

Like many pieces of work during this period however, the pandemic made us re-think our approach. The pandemic has changed how we all think and act, including how we think about loneliness. Understanding and addressing loneliness among the population has become a focus for governments and policy makers. In response, statistics producers have had to develop their loneliness statistics to meet society’s need for information. As a result, many good developments have happened in this area and we’ve found that statistics producers have been filling in some of the key gaps we identified when we first started looking at these statistics. Our new report published today commends the efforts by statistics producers in creating statistics that better serve the public good in answer to these societal changes. 

This isn’t to say that improvements can’t still be made though. Users we spoke during the pandemic still identified some key gaps in the official statistics landscape on loneliness. We would encourage statistics producers to build on the work they had achieved in the last 18 months and to continue to take forward producing statistics that meet user needs and offer value for charities and academics in preventing and researching loneliness.  

Continuing the loneliness review was one of the first pieces of work I got when I started my placement year at the OSR last September. I’ve really enjoyed working on the report and having the opportunity to lead a review and conversations with producers. Seeing the report published on my last day at the OSR brings a wonderful and rather cyclical end to my year! The work isn’t ending with me though. As an organisation, we are looking forward to continuing working in this area and assisting producers to develop their statistics to better meet user needs. If you would like to contact us about this, please email my colleague, Emma Harrison. 

I didn’t think I’d ever be interested in population statistics, but then I came to my Census

Ok so that’s not quite true. I’ve been working with a focus on population and society statistics for the past three years here at the Office for Statistics Regulation (OSR) and I love it. Working on areas such as migration, culture, wellbeing… it is fascinating. These statistics form such an important role in people, government and decision makers understanding and planning for our society in this country.

But even with my work hat off for a second, this is such an exciting time for statistics as we near Census day in England, Wales and Northern Ireland and work continues to prepare for Scotland’s Census in 2022. The Census is so important and a unique source of data. It will be used by many different people for many different purposes. For me, I think Census data can be most valuable when it is used to support how people understand their local communities, whether it be by local councils, community groups or even school students.  I am so eager to play my part and fill in my Census return – online this time of course.

Work hat back on and I have been leading OSR’s assessment of the Censuses in the UK. Undertaking this assessment is the role OSR has when it comes to Census data and statistics. We aren’t collecting the returns or producing the data but we are working closely with the Census offices to ensure what they are doing, ultimately delivering Census data and statistics to the public, is in line with the Code of Practice for Statistics.

We collect evidence from Census offices, speak with users of Census data, make our judgements on compliance with the Code; reporting on this through our formal assessment reports and public correspondence with Census offices. That is the nuts and bolts of the assessment process. The reality of the assessment and OSR’s involvement is that we are continuously engaging with Census offices as they are developing and delivering their Census plans to support the best possible outcomes. We meet with Census offices regularly to discuss their work, share our views on their developments, and talk through how they have taken forward our findings. It has kept me busy since 2018 and will continue to do so until well after the data and statistics are published.

This ongoing conversation as part of the assessment is overlaid with a more formal reporting structure. We have completed phase 1 of the assessment and are kicking off phase 2 for England and Wales and Northern Ireland. For each phase of the assessment, the Office for National Statistics (ONS) and the Northern Ireland Statistics and Research Agency (NISRA) publish an accreditation report. These reports provide an update to Census users on how they consider the practices, processes and procedures for Census 2021 meet the standards of the Code. This provides OSR with evidence for our assessment and more importantly provides useful information on progress on the Census for all who are interested. You should definitely take a read!

We are always keen to hear from users of Census data and I have had some extremely valuable conversations with individuals and organisations to date – a big thank you if you have submitted feedback or if we have spoken in the past. As part of this second phase, we have opened up our user consultation once more . Your views and opinions are so important to help us understand what Census offices are doing well and how things could be improved. So please, do find out more and get in touch.

I hope you all are as excited as I am as we get closer to 21 March!

The people behind the Office for Statistics Regulation in 2020

This year I’ve written 9 blogs, ranging from an exploration of data gaps to a celebration of the armchair epidemiologists. I was thinking of making it to double figures, setting out my reflections across a tumultuous year. And describing my pride in what the Office for Statistics Regulation team has delivered. But, as so often in OSR, the team is way ahead of me. They’ve pulled together their own year-end reflections into a short summary. Their pride in their work, and their commitment to the public good of statistics, really say far more than anything I could write; it’s just a much better summary.

So here it is (merry Christmas)

Ed Humpherson

Donna Livesey – Business Manager

2020 has been a hard year for everyone, with many very personally affected by the pandemic. Moving from a bustling office environment to living and working home alone had the potential to make for a pretty lonely existence, but I’ve been very lucky.

This year has only confirmed what a special group of people I work with in OSR. Everyone has been working very hard but we have taken time to support each other, to continue to work collaboratively to find creative solutions to new challenges, and to generously share our lives, be it our families or our menagerie of pets, all be it virtually.

I am so proud to work with a team that have such a passion for ensuring the public get the statistics and data they need to make sense of the world around them, while showing empathy for the pressures producers of statistics are under at this time.

We all know that the public will continue to look to us beyond the pandemic, as the independent regulator, to ensure statistics honestly and transparently answer the important questions about the longer term impacts on all aspects of our lives, and our childrens’ lives. I know we are all ready for that challenge, as we are all ready for that day when we can all get together in person.

 

Caroline Jones – Statistics Regulator, Health and Social Care Lead

2020 started off under lockdown, with the nation gripped by the COVID-19 pandemic and avidly perusing the daily number of deaths, number of tests, volume of hospitalisations and number of vaccines. This level of anxiety has pushed more people into contacting OSR to ask for better statistics, and it has been a privilege to work at the vanguard of the improvement to the statistics.

To manage the workload, the Health domain met daily with Mary (Deputy Director for Regulation) and Katy, who manages our casework, so we could coordinate the volume of health related casework we were getting in. We felt it important to deal sympathetically with statistic producers, who have been under immense pressure this year, to ensure they changed their outputs to ensure they were producing the best statistics possible. It’s been rewarding to be part of that improvement and change, but we still have a lot of work to do in 2021 to continue to advocate for better social and community care statistics.

 

Leah Skinner – Digital Communications Officer

As a communications professional who loves words, I very often stop and wonder how I ended up working in an environment with so many numbers. But if 2020 has taught me anything, it’s that the communication of those numbers, in a way that the public can understand, is crucial to make sure that the public have trust in statistics.

This has made me reflect on my own work, and I am more determined than ever to make our work, complex as it can be, as accessible and as understandable to our audiences as possible. For me, the highlight of this year has been watching our audience grow as we have improved our Twitter outputs and launched our own website. I really enjoy seeing people who have never reached out to us before contacting us to work with us, whether it be to do with Voluntary Application of the Code, or to highlight casework.

As truly awful as 2020 has been, it is clear now that the public are far more aware of how statistics affect our everyday lives, and this empowers us to ask more questions about the quality and trustworthiness of data and hold organisations to account when the data isn’t good enough.

 

Mark Pont – Assessment Programme Lead

For me, through the challenges of 2020, it’s been great to see the OSR team show itself as a supportive regulator. Of course we’ve made some strong interventions where these have been needed to champion the public good of statistics and data. But much of our influence comes through the support and challenge we offer to statistics producers.

We published some of our findings in the form of rapid regulatory review letters. However, much of our support and challenge was behind the scenes, which is just as valuable.

During the early days of the pandemic we had uncountable chats with teams across the statistical system as they wrestled with how to generate the important insights that many of us needed. All this in the absence of the usual long-standing data sources and while protecting often restricted and vulnerable workforces who were adapting to new ways of working. It was fantastic to walk through those exciting developments with statistical producers, seeing first-hand the rapid exploitation of new data sources.

2021 will still be challenging for many of us. Hopefully many aspects of life will start to return to something closer to what we were used to. But I think the statistical system, including us as regulators, will start 2021 from a much higher base than 2020 and I look forward to seeing many more exciting developments in the world of official statistics.

 

Emily Carless – Statistics Regulator, Children, Education and Skills Lead

2020 has been a challenging year for producers and users of children, education and skills statistics which has had a life changing impact on the people who the statistics are about.  We started the year polishing the report of our review of post-16 education and skills statistics and are finishing it polishing the report of our review of the approach to developing the statistical models designed for awarding grades.  These statistical models had a profound impact on young people’s lives and on public confidence in statistics and statistical models.

As in other domains, statistics have needed to be developed quickly to meet the need for data on the impact of the pandemic on children and the education system, and to inform decisions such as those around re-opening schools. The demand for statistics in this area continues to grow to ensure that the impact of the pandemic on this generation can be fully understood.

Investigating social connectivity and loneliness in our changing world

Over the last few months while we’ve been social distancing, some of us have been self-isolating, and many of us have been and will continue to experience social connectivity in a different way.

Prior to the Covid-19 crisis, we started looking at statistics around loneliness and social isolation. Over the past six months we’ve been speaking with producers and users of statistics on loneliness and social connectivity to inform a systemic review. We met with statisticians and policy colleagues working on loneliness and we’ve spoken to charities, non-governmental organisations and academics interested in this area. We’ve had some really interesting conversations on the public need for these types of data, and we’ve taken on board a wide range of views.

We’ve been planning a review of loneliness and social connectivity statistics for some time, but we could not have predicted how the COVID-19 pandemic has influenced all our daily lives, and how enforced social distancing would lead us all to consider loneliness and social connectivity in terms of our own experiences.

Now more than ever, it is important that statistics and data on social connectivity and loneliness reflect the world we live in, and that this data is accessible to those who need it to provide services and support. We all need to be able to understand who is most likely to be affected by loneliness, and how social connectivity influences our lives.

It’s important that statistics provide an aggregated picture – amassing all the personal stories into a wider perspective. At their best, statistics illuminate our lives and help us understand the lives of others. But sometimes they can fail at this – they can appear impersonal, reducing the mass of experience into single arid numbers. Behind all the numbers lie human stories.

So, to mark Loneliness Awareness week, we decided that instead of talking about the big national numbers, we’d share about our own personal experiences of loneliness, connection and hope in lockdown.

Louisa – Statistics Regulator currently on Maternity Leave:

I knew that starting maternity leave and becoming a Mum had the potential to be a lonely time, but of course, I could never have guessed this is how it would turn out. We were lucky; our son was born six weeks before lockdown, and so to begin with, many of our friends and family were able to visit. However, once lockdown started, and the visits stopped, I did start to feel lonely. As lockdown has eased, I have really appreciated increased social contact, but it seems unlikely many of the activities I had planned are likely to start up again soon. For now, even at a distance,  my son enjoys having people to watch, and I am thankful that at his age the lack of wider social contact is unlikely to affect him. I think, however, understanding the impact of loneliness on new Mums, as well as the impact of limited social connectivity for older babies and toddlers, will be important.

Mark – Head of Newport Office

I’m from a generation where working from home just wasn’t a ‘thing’ so have always preferred working in the office. I find it gives order and structure to my day – and during the first few days of lockdown, it was that structure that I really missed, and had to find a way to replicate at home. I’ve found it’s important to be proactive in establishing a way to maintain an order to my day. I’m an intermittently avid cyclist so disciplining myself to get out on the bike first thing in the morning gives me that routine and gets my head clear ready for the day ahead. I’ve never been so grateful for the great spring weather we enjoyed. I’ve made a conscious effort to try to keep social interaction up during lockdown – phoning colleagues for a chat to see how they’re doing. I think it’s really important to keep talking.

Zayn – Statistics Regulator

Reflecting on the last 13 weeks – it feels like so much has happened, and at the same time, it feels like nothing has happened at all. May was the month I was most looking forward to in 2020 – it was my 21st birthday and I was invited to the film festival in Cannes. Neither of these really went how I would’ve liked them to, but I look forward to visiting Cannes in the future and turning 21 again next year (that’s how it works, right?). I guess my one wish would be to go back to the office before my placement ends, it wouldn’t feel right leaving without the chance to say a proper goodbye.

 

 

Liddy – Statistics Regulator

I’ve adapted to working from home and connecting with friends virtually, and I know this experience is very familiar to some, but very different to many others. For example, three years ago my granddad passed away which left my grandma on her own. She has a really strong support network that she would normally meet almost daily. During the pandemic she has struggled with loneliness. It has been really tough, but she’s adapted by learning how to use Zoom, distracting herself with gardening, and now she’s able to, going on socially distanced walks with her friends again.

Gemma – Statistics Regulator

Before lockdown I used to rely a lot on family for childcare as I was office-based five days a week, so losing that support quite literally overnight was hard to get used to. But they’ve still helped hugely by always being at the other end of the phone. My sons have been able to stay in contact with their friends through chatting on their games consoles, and they’ve also had some lovely phone calls from their school teachers checking that they’re ok. For me, accepting that they aren’t baking, doing arts and crafts or PE with Joe Wicks (sorry Joe!), as well as a good playlist and a cupboard full of snacks has been what’s kept us all sane!

Gail – Head of Edinburgh Office:

“Mum, I am cripplingly lonely” – a hard thing for any fourteen year old boy to admit to his mum. Social connectiveness, something my teen boys took for granted, has all but disappeared. Children across the UK, kids just like my boys, are living through an extended period of unplanned and unexpected severe isolation. Most of them will bounce back from this, as I hope mine will. Not all children will though, and it is likely that many will need support to address emotional and practical needs both in the short and longer term. We need to support this generation of children and good data can do that. Data that is up to date and accurately reflects the prevalence and type of need, not only at the level where support is needed, but which is consistent and can be joined with other data to give the bigger picture.

 

We’re also carrying out a related but separate systemic review on Mental Health statistics in England, the results of which will be published shortly.

If you’re feeling lonely and would like some advice or support, you can visit the Campaign to End Loneliness, who have recently published a blog with some guidance on how to deal with loneliness at the moment. If you’re feeling anxious or worried about Coronavirus, the charity Mind offer guidance and support on their website. Stay up to date with the latest health guidance on the NHS website.

Piecing things together

People who provide services often need to know about local variations so that they can focus efforts in the right places. We are all witnessing this first hand at the moment in how the country is responding to COVID-19, for example, with a need for detailed geographical data to help NHS planning.

The Race Disparity Unit (RDU) is a team within the Cabinet Office. It is primarily a data and statistical unit which collates, publishes and analyses UK ethnicity data, works across Government on issues where ethnicity is an important factor, and engages with external stakeholders to understand different perspectives.

When RDU talks to users of its Ethnicity facts and figures website, they tend to say two things. First, it’s a great resource. It includes a wide range of data on different topics for different ethnic groups. And it presents the data in an accessible way. This makes us feel very happy.

But they also ask for data at the local authority (LA) level. Users find that regional or national figures mask local variations. They need to know about these variations so that they can deliver the right services – which makes perfect sense across the piece: detailed geographical data about where those aged over 70 live at a local level to help provide support during COVID-19  is just one example, albeit extreme and traumatic, of this wider pattern.

This need is also true for small area ethnicity data. And the user demand for small area ethnicity data makes us feel a bit anxious, because our website doesn’t have much data for individual LAs. It does include a dashboard which shows the data we have for different geographies. But this doesn’t address the user need.

So RDU has linked together the datasets we have that include local authority data. This includes data on school performance, employment rates, and so on. It also includes data about local circumstances – for example, how deprived the area is. So far, we’ve made great progress with the prototype. But getting a range of datasets to talk to one another can be difficult. Many of them don’t follow statistical geography standards/best practice. We’ve talked about the various hurdles faced in a previous blog.

Our work on geography has made us think about how we can improve the value of the data on the website. “Value” is one of the three pillars of good statistical practice promoted by the Office for Statistics Regulation (OSR). It is hard-wired into its Code of Practice for Statistics (along with trustworthiness and quality).

First, context is everything. Statistics need to be relevant and reflect the lived experience to be most useful to a wider audience. The power of statistics is in providing insight through the aggregation of many individual data points to form a big picture. Context provides the colour for what would otherwise be a grey-scale image.

Many official statistics are not presented at ‘local’ levels. There can be good reasons for this but without this information insight is narrowed. The Code of Practice encourages statisticians to provide data at the greatest level of detail that is practicable. Anything produced at the national level is usually required at the local level. And so, it’s worth all producers thinking about what information their users need and what the data tells them.

Be curious – see what patterns are in the data, by place.

Second, the little things matter. Putting the dot in St. Albans, or not, matters. A single full stop can be the difference between two datasets automatically linking together and the need for a manual correction. And while that single full stop will never be complex to resolve, it is rarely just a single full stop. Instead it is a series of manual corrections that are a barrier to the insight gained by linking data. Metadata on the year of the geographic classification used is also valuable to those of us wanting to join datasets. Local government structural boundaries can change every few years. We would rather know in advance that some of the records won’t match, than have to play trouble-shooter later.

While ‘place’ is flexible in its degree of specificity, it is best standardised. We can link key geographic information if variables are coded consistently. Bespoke coding frames get in the way of data linkage and reduce the value of the data.

Be consistent – enable the greater value of your data to be achieved by using harmonised codes.

Third, innovation is vital. Arguably the geography prototype is ‘only’ an Excel spreadsheet. What is innovative about it is the way that it draws data together. Over time this will support a mapping function. This will help bring the data to life and to allow users to overlay different data sets at the LA level. We are already using the dataset to identify areas of policy interest and to target our engagement.

Another potential innovation – at present no more than a twinkle in RDU’s eye – is an Index of Multiple Ethnic Disparity (IMED). The IMED is analogous to MHCLG’s Index of Multiple Deprivation. It would allow users to identify those parts of the country where ethnic disparities are most pronounced, across a range of topics. If we were able to add in historical data, we would be able to look at the interplay between geography and time. There are some presentational, methodological and conceptual challenges in producing such an Index. RDU will begin to address these as we think about the use we want to make of data from the 2021 Census (see below).

Fourth, we can add value by working together, sharing perspectives and expertise. The RDU is keen to work with local authorities on the ‘geography prototype’. We are already working with Bristol City Council, which is using data to address ethnic disparities.

OSR have said that they will review the use of harmonised geographic codes and standards as part of their regulatory work. They will also provide guidance on meeting the standards of the Code of Practice. ONS’s Open Geography Portal makes it easier for data owners to use the correct classifications. Various groups can help unlock the potential of ethnicity data. These include:

All it requires is shared commitment!

The ONS has a team that supports everyone in the GSS to improve official statistics. This is the Best Practice and Impact (BPI) division. BPI encourages everyone in the GSS to share best practice. One of the ways we do this is by running champion networks, this includes a geography network. If you would like to represent your department or share a piece of work you have done please get in touch.

Fifth, more (and better) data will allow us to deliver much more value. RDU is starting to consider how to use data from the 2021 Census of Population. It will enable us to paint a far richer picture about the different ethnic groups than we can by using surveys or administrative sources. We are exploring the scope to link datasets to provide more geographical insights. And we are continuing to work with the ONS to improve the way that ethnicity is classified across government. Our goal is that in future users can compare data from different data sources directly.

This is a guest blog from Richard Laux (Cabinet Office) and Claire Pini (GSS Harmonisation Team in ONS).