Official Statistics

MHCLG enabled spend statistics, 2023-24: Development plan

Published 12 March 2025

Background

Purpose of this document

The Ministry of Housing, Communities and Local Government (MHCLG) is committed to the ongoing review and improvement of published statistics to ensure they are of the highest quality and public value. As Official Statistics in Development we aim to continually improve the quality, trustworthiness and value of the MHCLG enabled spend data and statistics publication. This development plan explains how we intend to do this.

MHCLG enabled spend statistics

Government is committed to improving how UK government spend is collated and reported. To meet this commitment, we have published MHCLG enabled spend data and statistics, which includes:

• MHCLG enabled spend data – a dataset of direct spend and funding delegated to local authorities by the department, provided in a machine-readable ‘tidy data’ format
• MHCLG enabled spend statistical release – this commentary summarises and explains the published enabled spend data
• MHCLG enabled spend data tables – displaying key figures used in the report in a more accessible format

Statistical classification

MHCLG enabled spend data and statistics are published as official statistics in development, a subset of newly developed or innovative official statistics that are undergoing development. We are working towards designation of these statistics as official statistics.

Development plan

The following is a list of actions that MHCLG has taken after the first release.

Actions taken to improve the publication output

• Engaged with stakeholders to understand feedback on how to improve methods and reporting, integrating feedback into future development activity.
• Conducted a review of data structures and labelling, aiding improvements to both recording and interpretation.
• Introduction of Inter-Departmental Business Register (IDBR) to improve accuracy of apportionment for business recipients and addressed any residual headquartering effects in the data.
• Updated and standardised codebase to follow best practice and allow future repeatability including refactoring report and development of a new reporting package.
• Rearchitected the approach to a more component based structure allowing for easier replication in future releases.
• Developed repeatable unit tests to maintain quality.
• Increased documentation and cataloguing of programme specific apportionment logic.
• Developed new apportionment logic options.

The following is a list of MHCLG’s expected actions following this second release.

Actions to improve the publication and underlying data going forward

• Assess and develop a roadmap to move to official statistics.
• Standardise the codebase to remove redundancy, within programme exception methods.
• Work with programme teams to further refine the apportionment logic for top priority programmes, for example including additional data sources and metrics.
• Further explore Revenue and Capital spend by segment and local authority.
• Investigate options for additional integration to automate the report production and allow routine generation.
• Update the codebase to flex with local authority boundary changes or changes to the structure and format of supporting datasets for new publication years.
• Explore the use of Revenue Outturn data instead of Core Spending Power, to ensure MHCLG spend delegated to local authorities are best reflected in these statistics.
• Continue to seek feedback from data users on how to improve methods and reporting and embed usage. Integrating feedback into future development activity and capture benefits of the dataset.
• Engage with finance colleagues to enhance and streamline data collection through finance platforms and develop a training plan to support accurate recording and understanding of contextual data.
• Assess alternative data sources to be used for the production of reporting including impacts on data quality and simplification of pipeline.
• Investigate additional sources to further enrich data and track against programme outcomes, for example further spend categorisation.