Getting Started with Data for Place-Based Initiatives

Place-based initiatives require a tailored approach to data. Learn about the process involved from leading experts in a Queensland context.
place-based initiative frameworks

Why data?

Place-based initiatives (PBIs) need to use data to help them understand and describe the issues in place, design and test initiatives, measure their impact, and report to communities and stakeholders, including funders.

This Fact Sheet was developed with and by leading place-based initiatives* as a part of the Data Catalyst Network, a network that brings together data experts of the Australian not-for-profit sector to collaborate and break cycles of disadvantage experienced by Australian youth.

The starting point is to guide practitioners in place on building a shared understanding of the ‘how to’ of accessing, collecting and using data for the purpose of shared measurement and shared decision-making.

Below are the seven interconnected components and practices that support PBIs use data to share, learn, and act to enable shared decision making and measurement. These help PBIs to think about what they need to know about data.

data place-based initiatives

Telling the Story or Problem Solving with Data

PBIs should begin by embedding their approach in a broader storytelling or ‘problem-solving’ framework.

The key to working with data is first identifying the challenge or opportunity the PBI is addressing, then thinking about what data is needed to understand the challenge, devise a plan, and share the results.

PBIs may be well placed to integrate complementary qualitative data and lived experience with broader population quantitative data, apprehend, and interpret local contexts and complex realities more accurately than external researchers.

PBI Data Framework not-for-profits place-based initiative

Data types

Most PBIs are accessing and using data, and they are also creating or sourcing techniques, tools, practices and resources to support them. Thinking about ‘data buckets’ helps to plan for shared measurement and decision-making.

place based initiatives data buckets

Data Framework principles

Place-based data considerations to be included in a data framework.

Area

What needs to be included in the framework

Population Data Bucket

  • List of evidence-based populations measures across the life course and domains of wellbeing
  • Catalogue of populations data assets (open/closed) and list of who the data custodians and how to access the data
  • Data access request (shell template)
  • Data dictionary
  • Links to data platforms (ACWDA, QFCC, QCOSS, etc.)
  • Log to collectively identify data gaps- scope and test instruments for new data assets (social inclusion)
  • Tips and templates to support developing questions to ask
  • Data storage and governance requirements

Service Data Bucket 

  • List of the types and granularity of service level data to explore (demand, quantity, quality, demographics, engagement, outputs, funding, participation, unmet, workflow etc.), including practice support in interpreting the data
  • Links to policy, strategic and practice guidelines, data manuals
  • Data collection guide, including definitions, tools, templates (Gladstone)
  • Data collection templates
  • Data sharing agreement templates

Community Data Bucket

  • Supports in generating and accessing community voice and wisdom
  • List of methodologies and platforms (including examples) for collecting
  • Consent form template
  • Tips and uses of social media in gathering community intelligence
  • Survey tools and templates (with a list of key questions and validated questions)
  • Tools and supports for analysing qualitative data
  • Ethical considerations tips and checklists
  • Techniques to support feedback
  • Storage, privacy and sharing of community intelligence

Research Data Bucket

  • List and links to research, research institutes, peak bodies for different content area expertise
  • Tools and tips for searching and collecting research (google scholar etc), including the different types of research
  • Tools on how to combine data sets for analysis and insight generation
  • Explanation on the role of research including tools and tips for using research to build collective understanding
  • Research partnership MOU templates

Exchanging Knowledge

  • Data sharing agreement templates-How to put in place appropriate government structures
  • Data maturity model that articulates the different data needs at different stages of initiative maturity.
  • Tools, methods and platforms (such as AI) for analysis and storage of data
  • Consideration checklist (eg who has access)
  • Sharing what matters for different audiences - tips on how to visualise data for different audiences- Graphical reporting templates and examples
  • Tips on addressing bias and assumptions
  • Content register log of PBIs data projects (ie homelessness, first 1000 days) to allow for peer connection and learning

Learning and Acting Together

  • Tips, practical examples, and practice support in how to connect and use data to empower communities led decision making (art and heart)- quality continuous improvement
  • Context and maturity of models
  • System mapping tools and examples for connecting data
  • Problem solving canvases

Principles

  • Describe the key principles and explain what this looks like in practice
  • Key areas for principles to cover include - relational no transactional (trust), courageous, strength-based, collaborative, shared ownership and management, no data without narratives, focus on learning, simple and flexible, data at the right time, data sovereignty, protecting the space for deliberation, embracing an active role for qualitative data, focusing on data close to the problem

Conditions

  • Description of the capabilities needed in place
  • Data governance - to support how PBIs in generating, receiving, holding, storing, and absorbing data

Enablers

  • A list of mindsets and skills needed to support PBIs across the different stages of PBI data maturity
  • Skills list that can support PBI recruitment of data positions
  • Links to organisations and their data skills, including examples of how PBIs have utilised external supports

Data framework resource links

These are the main national and Queensland resources to support PBIs in using data, identified in consultation with Queensland-based initiatives.

*We’d like to thank our partners for contributing to this resource, including Restacking the Odds, Logan Together, yourtown, Gladstone Region Engaging in Action Together, Mission Australia, Department of Treaty, Aboriginal and Torres Strait Islander Partnerships, Community and the Arts, Childrens Health QLD, Nexus Foundation Partners, Griffith University, QCOSS, University of the Sunshine Coast, Infoxchange, Hand Heart Pocket, Department of Social Services, Department of Health, Brisbane North PHN Southern Moreton Bay Islands, SEER Data, Thriving Queensland Kids Partnerships.

Tools, techniques and resources that can support the use of data in place-based initiatives 

Population Data Bucket

Data Access and Platforms

Population Data Bucket

Indicators

Service Data Buckets

Community Data Bucket

Research Data Bucket

Exchanging Knowledge

Learning and Acting Together

Principles

Conditions

Enablers

AI

Learn about the full process involved in the creation of a tailored, place-based initiative framework 

Find a comprehensive document that demonstrates the co-design process to build a data framework for place-based initiatives that will give you a deeper understanding of what place-based initiatives need to know about using data here.

 

Learn via case studies 

Learn about place-based initiative frameworks from stories of success. Restacking the Odds has been supporting better outcomes for Logan's children and families. Read how they've facilitated shared decision-making and the principles of a shared framework. 

Restacking the Odds Case Study

 

 

 

 

 

 

 

 

 

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