Official Statistics

Government grants statistics development plan

Published 31 March 2022

1. Background

1.1 Purpose of this document

Cabinet Office and the Government Grants Management Function (GGMF) are committed to the ongoing review and improvement of its published statistics to ensure they are of the highest quality and public value. As part of this commitment, we (GGMF) will publish ongoing statistics development plans.

We aim to continually improve the quality, trustworthiness and value of the Government Grants Statistics publication. This development plan explains how we intend to do this.

1.2 The Government Grants Register and Government Grant Statistics

Government is committed to increasing transparency, enabling taxpayers to hold the state to account both on how their money is being spent and how decisions are made which affect their lives.

To meet this commitment, we publish Government Grants Statistics which includes:

The Government Grants Register - a dataset of grant spending across government; covering general and formula grants at both scheme and award level.

The Government Grants Statistics Bulletin - This document explains and contextualises the published grants data. Published alongside this bulletin is a set of statistical tables, displaying all figures used in the report in a more accessible format.

1.3 Statistical classification

Government Grants Statistics are published as Official Statistics.

Government Grants Statistics were published as experimental statistics for the first time in 2021. We have now removed the Experimental Statistics designation.

Previous publications were published as transparency data, except financial year 2018 to 2019 which was published as management information.

2. Development Plan

The following is a list of GGMF’s actions to improve these statistics to date and expected actions over the next year.

2.1 Actions taken to improve the publication and underlying data since the previous release

Improving this publication

GGMF has taken the following actions to improve the grants statistics publication:

• Removed the “Experimental Statistics” label from this publication.
• Announced the publication month 1 year in advance.
• Published further documentation of the underlying data quality and the methodology for producing the publication. See Quality and Methodology information (QMI) document published alongside this release.
• Worked to understand our users:
  • Reviewed the feedback gathered through the user consultation released as part of the last publication.
  • One known user of grants data is 360Giving who provide an open data standard for grants data. GGMF has engaged with 360Giving throughout the production of these statistics to ensure that the published awards data meet this standard, and will continue to ensure we meet this requirement in future publications.
• Produced and published this document to demonstrate our compliance with the Code of Practice for Statistics.

Improving the grants data

GGMF has taken the following measures to improve the underlying grants data:

• Launched the new version of the Government Grants Information System (GGIS) for use by departments, with increased levels of data validation.
• Included automated audit trails in the new version of GGIS to allow us to track any changes to the data, and monitor ongoing quality and completeness improvements.
• Included data from external data sources (such as companies house and charities commission) in the new version of GGIS, to verify the our grant recipient data and enable greater consistency in future.
• Performed regular data cleaning on our recipient database, enabling us to identify organisations that we are confident are the same despite some slight discrepancies in our award level data. We have combined the data for these duplicated recipients as appropriate, therefore facilitating more accurate recipient level analysis.
• Working alongside departments, we have updated our comprehensive Government Grants Data Standard that specifies the data required in GGIS.
• Improved automated processes for highlighting data quality issues to departments, including a data quality dashboard, allowing regular feedback and monitoring during data collection.
• Improved our reproducible analytical pipeline (RAP) for the process of getting from the data to the publication using the coding language Python.
• Provided additional analytical assistance to departments to improve data quality and completeness.
• Provided training to and engaged with departments regarding GGIS and the new data standard.
• Developed specific plans with individual departments where needed, to ensure they can continue to meet these data requirements and improve data quality.

2.2 What we will do

In order to improve this publication in future, we plan to:

• Continuing to engage with users of the data and the GSS Good Practice Team and integrate further feedback. (Ongoing)
• Continue to provide training to and engage with department users regarding GGIS and the new data standard. (Ongoing)
• Continue to develop specific plans with individual departments where needed, to ensure they can continue to meet these data requirements and improve data quality. (Ongoing)
• Review the improved recipient data and add recipient level analysis to future publications as appropriate (Ongoing).