Improving cross-organisational collaboration in UK regional data

Improving cross-organisational collaboration in UK regional data

Summary

This work seeks to fill a critical gap in our understanding of how different organisations collaborate when producing and using regional economic and socioeconomic data in the UK.

Stakeholders such as the UK’s Office for National Statistics (ONS), Devolved Governments and Local and Combined Authorities have different mandates, priorities and resource constraints. This can make collaboration challenging when developing datasets with the appropriate level of geographical coverage, timeliness, granularity and comparability.

This research will use tools from systems thinking, interviewing stakeholders to understand their different perspectives and co-designing system-wide solutions to enhance and strengthen cross-organisational collaboration across the UK’s statistical system.  The Office for Statistics Regulation (OSR) is supportive of this work.

This work is funded by the University of Strathclyde’s Institutional Funding for Research Culture Award, Cultures of Collaborative Research (Wellcome Trust) and the Strathclyde Business School Cross-Disciplinary Research Fund.

Methods

This research will use tools from the systems thinking literature, undertaking qualitative interviews with:

  • UK Government Departments, Devolved Governments, the ONS
  • Local and Combined Authorities, Public Bodies
  • Analysts supporting Urban, Rural and Remote Communities
  • Researchers and other stakeholders involved in producing and using regional data

Interviews will discuss experiences of and views on cross-organisational collaboration when producing and using regional socioeconomic data in the UK. There will also be optional follow-up participation in co-designing solutions.

Participate in this research.

Impact

We hope that the project outcomes will strengthen collaboration between organisations, contributing to more integrated and comprehensive data practices across the UK’s statistical system.

Ultimately, this can support evidence-based decision-making and more efficient resource distribution.

People

Le Nguyen

Project partners

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