Introduction

Introduction

This data strategy provides a framework for using data to drive planning, decision-making, and public service delivery in [CITY]. [VISION STATEMENT].

This strategy will ensure data supports our core values of:

• [CORE VALUES]

Problem statement

Currently, [CITY]’s approach to data is reactive and ad-hoc, limiting our ability to effectively respond to the changing needs of residents and public officials.

[CITY] uses data in an ad-hoc and reactive manner because of:

1. How it currently organises its data:
   1. data management is not transversal
   2. there is limited understanding of what specific dataset exists
   3. data reuse is ad-hoc, there is a lack of common platforms and processes to support it
   4. there is a lack of confidence, incentives and trust to reuse data
   5. there is a lack of common standards and identifiers for data
   6. data collection is often paper-based and ad-hoc
2. How it currently operates its digital/data work:
   1. data does not fully meet the needs of decision-makers
   2. data does not fully meet the needs of service delivery teams
   3. the culture of data use is immature and not effectively distributed throughout the organisation
   4. the adoption of modern agile ways of working and iterative delivery is limited
   5. that tools and processes for analysing data are not optimised
   6. there is a need to build better internal communication around data matters
   7. there is a lack of guidance on how to start and run a data-related project
   8. funding for new data work is ad hoc and not related to user needs or a central vision.
   9. there is a lack of strategic intent in decisions about the adoption of new technology and build vs buy

Theory of change and outcomes

The aim of this strategy is to help [CITY] make decisions about how to use and manage data, and ensure the right capabilities are in place, so it can deliver its policy objectives and meet the needs of residents. This strategy acts as a guide for all levels of leadership, management and operations in the municipal government, as well as external partners, residents, and organisations.

This strategy is based on the following theory of change:

Reorganising the data value chain and introducing new ways of working in [CITY] will help the municipality deliver on the vision set out in the [STRATEGIC PLAN] and create significant value in each of the [STRATEGIC PLAN].

The outcomes the strategy is seeking are as follows:

1. Data as a managed public resource
   • Data is recognised as a strategic asset across departments.
   • Foundational datasets are catalogued and actively maintained.
   • Residents and businesses benefit from open, accessible, and high-quality municipal data.
   • Data is representative, inclusive, and free from bias, ensuring equitable benefits across all residents.

2. Data-driven decision making & insights

• City officials and partners use data for proactive rather than reactive planning.
• AI, predictive analytics, and real-time dashboards improve decision-making.
• Participatory data platforms allow public engagement in decision processes.
• Municipal decisions proactively consider the needs of marginalised communities through GESI-informed data insights.

3. Data governance & standards

• Municipal officials understand and comply with data standards.
• Interoperability frameworks allow seamless data integration across systems.
• A structured framework ensures responsible AI and emerging technology adoption.

4. Data capabilities & infrastructure

• A city-wide data exchange platform is implemented for secure, standardised sharing.
• Data-driven projects receive sustainable funding linked to municipal priorities.
• Cloud, open-source, and modular solutions enable future scalability.
• Municipal officials are trained in GESI-aware data practices, and participatory data governance structures ensure inclusive representation.