Research objectives and summary findings

Disclaimer: Within this report, we aim to portray the views of participants and to reflect their words as closely as possible. The findings that are presented therefore reflect the opinions and experiences of a range of individuals and may not be shared by others within the same or other institutions, including the Office for National Statistics. Some quotes have been edited for language and grammar to improve accessibility, without changing the content or meaning.

Research objectives

The Office for National Statistics (ONS) held roundtable discussions and in-depth interviews with senior representatives from the devolved administrations, central government, local government, and academic and learned society organisations.

The roundtables focussed on:

• understanding gaps in the available equalities data
• whether and why certain groups are not included, recognised, or represented fully in the data and the potential impacts of this under-representation
• existing initiatives to address data gaps
• the required steps to improve inclusivity

Summary findings

Six lenses for viewing inclusivity were used for reporting findings which include engagement, concepts, methods, data, insights and learning from best practice. This section contains brief summaries of the findings under each of these lenses.

Participants advised that work is needed to improve trust in government and how personal data are collected and shared. The need for transparency in both data sharing and usage, as well as visible action resulting from data collected, were identified as areas for improvement. Utilising long-term engagement strategies with under-represented communities to maintain dialogue and allow time to build trust was seen as an important step to address these concerns.

Concepts used to collect and categorise data were discussed within a range of contexts. Issues with definitions and classifications were raised. These included perceived outdated and inconsistent use of definitions, which can result in a lack of comparability. Additionally, there may be inadequate representation within response options, so research participants must select options with which they do not identify. To address these concerns, participants suggested conducting appropriate reviews of concept definitions to keep up with the changing nature of society, as well as the development and consistent use of harmonised standards reflecting society today.

Insufficient sample sizes were said to lead poor granularity, hindering intersectional analyses around under-represented groups and preventing breakdowns by personal characteristics and local level geographies. A need for more inclusive data collection methods was highlighted, to reach under-represented groups. These issues were perceived as leading to specific groups being invisible within the data. Oversampling of under-represented groups was suggested, as well as developing strategies to reach people who are routinely excluded from data collection pathways.

Several issues with data were identified, including time lags, data gaps, access to existing data and a lack of personal characteristics data within administrative datasets, which were said to inhibit effective policy decision-making. Improving access to the data through user-friendly platforms was recommended, as well as improving the profile and usability of admin data.

A lack of insight into the needs and issues facing specific communities was said to hinder inequalities from being addressed. The way that data and statistics are presented was also said to undermine public understanding and access to the information. Qualitative research to gain insight into the lived experience of under-represented groups was proposed to better understand the priorities and needs of different population groups. It was also advised that exploration into how research findings are understood and how dissemination can best facilitate understanding is needed.

Use of best practice examples to inform data collection, analysis and dissemination practices in UK data was perceived as suboptimal. This was said to be a result of a lack of data sharing and poor communication across government and organisations. Establishing a cross-organisation statistics user group was recommended to improve statistical awareness and the use of statistics in the UK, particularly regarding equalities data.