Data use promises and practices: exploring Scottish local government data work culture

Brown, Lucy (2024) Data use promises and practices: exploring Scottish local government data work culture. PhD thesis, University of Glasgow.

Abstract

Data has always been used in the work of local government. Now, changes in the scale of (digital) data and technological affordances to derive insights from that data are changing the culture of data work. The data work changes are occurring in the context of pressure to ‘transform’ and be a better government. This study explores how local government public service delivery staff across six local authorities in Scotland experience these changes in calls to be data-driven and smart for reasons of ‘digital transformation’. Empirical data was collected via 55 personal-professional accounts of working with data through digitalisation and in pursuit of public service delivery transformation. This new data supported a predominately qualitative analysis, complimented by a short survey, and extensive policy review.

The discipline of e-Government has produced academic outputs about information and technology usage in governmental settings since the Internet mainstreamed in the 1990s. This study focuses on the underattended-to concept of data itself within e-Government research, utilising a relational ontology to account for intricacies in the practice of data use at work at the local government level. A novel conceptual lens of ‘data use’ is developed and applied, to enable classification of varied types of work using data alternatively for reporting or intelligence purposes in local government operational activities. The framework categorises data use as preparatory and substantive, differentiating the quality and value of data use in service of the two main functions: reporting and intelligence. Through the use classification and epistemic expectations of data, where the broad data “promise” meets in-work practices, the thesis addresses the central aim to identify what characterises local government data work culture in Scotland, UK. This culture is found to be uneven, imbued with opportunism, inconsistency and paradox.

By focusing on the experiences of distinct data users, as operational public service professionals, the research draws attention towards requisite interpretive effort of public service specialists during their work in public services provision, highlighting ways that such effort is under-supported and misunderstood. Reporting remains the predominate purpose of data use in Scottish local government. In seeking public service delivery transformation through data, intelligence applications are necessary, with interpretation occurring through the values and purposes of varied types of data workers acting in service to the public. From exploration of data workers’ practices, the study identifies six expectations of data, which constitute the overarching data use “promise”, and explores the extent to which this is achieved. Additionally, four fundamental factors are identified that alternatively support or limit data use for public service delivery transformation. It is concluded that there is over-attendance to data and technology in data use practice, at the expense of human elements. More support is required for local government workers to advance data work for public service related intelligence, building on operational workers’ expertise by affording the time needed for intelligence work, alongside nurturing professional curiosity and enabling creativity.

• Item Type: Thesis (PhD)
• Qualification Level: Doctoral
• Additional Information: Supported by funding from the Leverhulme Trust. Author's publishing name: Lucille Tetley-Brown.
• Keywords: Data use, data work, data culture, local government, digital transformation, public services, Scotland.
• Subjects: H Social Sciences > H Social Sciences (General); J Political Science > JS Local government Municipal government
• Colleges/Schools: College of Social Sciences > School of Social and Political Sciences
• Funder's Name: Leverhulme Trust (LEVERHUL)
• Supervisor's Name: Wessels, Professor Bridgette and McNulty, Mr Des
• Date of Award: 2024
• Depositing User: Theses Team
• Unique ID: glathesis:2024-84823
• Copyright: Copyright of this thesis is held by the author.
• Date Deposited: 15 Jan 2025 16:27
• Last Modified: 15 Jan 2025 16:27
• Thesis DOI: 10.5525/gla.thesis.84823
• URI: https://theses.gla.ac.uk/id/eprint/84823