Brainstorming for data source identification is a structured group creativity technique that brings together diverse participants to generate a wide range of ideas about where and how to find relevant data for a specific analytical policy problem. Facilitated sessions encourage participants to build on each other’s suggestions, explore both conventional and unconventional sources, and use visual tools like mind maps or affinity diagrams to organize and expand upon the ideas generated. By deferring judgment and fostering an open, collaborative environment, brainstorming helps uncover data sources that may otherwise be overlooked, ensuring a more comprehensive and innovative foundation for policy analysis. This process not only stimulates creative thinking but also enables teams to quickly surface, evaluate, and prioritize potential data sources, supporting evidence-based decision-making.
Suggested Plan for Group Brainstorming to Identify Data Sources for Analytical Policy Analysis
Purpose:
To systematically identify relevant, reliable, and available data sources that will inform an analytical policy analysis, using structured group brainstorming techniques.
1. Preparation
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Define the Policy Problem:
Clearly articulate the policy issue, objectives, and the key questions that the analysis must address. This focuses the brainstorming on data relevant to the analytical goals[5][3]. -
Assemble a Diverse Group:
Include staff, key partners, stakeholders, and, where possible, community representatives who bring varied perspectives and knowledge about potential data sources[1][3]. -
Gather Materials:
Prepare chart paper, markers, digital collaboration tools (if remote), and any relevant background information or previous data lists[1].
2. Structured Brainstorming Session
A. Introduction (10 minutes)
- Brief the group on the policy problem, objectives, and the importance of identifying comprehensive data sources.
- Outline the session’s structure and encourage open, judgment-free idea sharing[2].
B. Individual Idea Generation (10 minutes)
- Ask participants to spend a few minutes individually listing all potential data sources they can think of, considering both traditional (e.g., government reports, surveys) and non-traditional (e.g., social media, administrative data, stakeholder feedback) sources[4][5].
C. Group Sharing and Expansion (20 minutes)
- Go around the group, with each participant sharing one idea at a time, while a facilitator records all suggestions on a visible board or digital platform.
- Encourage building on others’ ideas and exploring less obvious sources, such as competitor data, open data portals, or community-generated information[2][4].
D. Prompted Exploration (10 minutes)
- Use structured prompts to ensure breadth:
- What quantitative data (e.g., statistics, metrics) is available?
- What qualitative sources (e.g., interviews, case studies) could be useful?
- Are there relevant data from other sectors, regions, or countries?
- What unpublished or informal data might exist within organizations or communities[5][1]?
3. Prioritization and Gap Analysis
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Cluster and Categorize:
Group similar data sources and categorize them (e.g., administrative, survey, big data, qualitative)[5][4]. -
Assess Relevance, Availability, and Reliability:
Quickly evaluate each source for its relevance to the policy question, accessibility, and trustworthiness[5]. -
Identify Gaps:
Note areas where data is missing or insufficient, which may require new data collection or alternative approaches[5][3].
4. Documentation and Next Steps
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Record All Outputs:
Document the full list of suggested data sources, including notes on their strengths, limitations, and any follow-up actions needed (e.g., verifying access, seeking permissions)[1][5]. -
Feedback and Validation:
Circulate the compiled list to participants and other stakeholders for validation and additional suggestions[3]. -
Plan for Data Collection:
Develop a work plan for obtaining, processing, and analyzing the prioritized data sources as the next step in the policy analysis process[3][4].
Summary Table: Key Steps
| Step | Purpose | Example Activities |
|---|---|---|
| Preparation | Focus and organize the session | Define problem, assemble group |
| Brainstorming | Generate diverse data source ideas | Individual listing, group sharing |
| Prompted Exploration | Ensure breadth and depth | Use prompts for types and sectors |
| Prioritization & Gap Analysis | Focus on actionable, relevant sources | Cluster, assess, identify gaps |
| Documentation & Next Steps | Ensure follow-through and completeness | Record, validate, plan data collection |
Tips for Success:
- Use visuals (charts, sticky notes, digital boards) to keep ideas visible and spark further creativity[2].
- Encourage participation from all group members, including quieter voices.
- Consider follow-up sessions or online surveys to capture additional ideas after the meeting[1].
This structured, participatory approach ensures a comprehensive and relevant mapping of data sources, laying a strong foundation for evidence-based policy analysis[1][5][3].
Sources [1] [PDF] PARTICIPATORY POLICYMAKING - Goldman School of Public Policy https://gspp.berkeley.edu/assets/uploads/page/GSPP_Participatory_Policy_Toolkit_Version_1.pdf [2] Brainstorming with Data: How to Turn Insights into Innovation https://www.newhorizons.com/resources/blog/data-driven-brainstorming-strategies [3] Turn Data into policy https://www.datatopolicy.org/navigator/turn-data-into-policy [4] Strategic Policy Development Through Data-Driven Insights - LinkedIn https://www.linkedin.com/pulse/strategic-policy-development-through-data-driven-insights-bryce-undy-qu3ef [5] [PDF] Guide to Policy Analysis | ETF (europa.eu) https://www.etf.europa.eu/sites/default/files/m/72B7424E26ADE1AFC12582520051E25E_Guide%20to%20policy%20analysis.pdf [6] 8 Best Practices for Mastering Data-Driven Strategy - 180ops https://www.180ops.com/blog/best-practices-for-mastering-data-driven-strategy [7] Nominal Group Technique (NGT) - ASQ https://asq.org/quality-resources/nominal-group-technique [8] [PDF] Basic Methods of Policy Analysis and Planning http://surjonopwkub.lecture.ub.ac.id/files/2019/01/Basic_Methods_of_Policy_Analysis_and_Planing.pdf [9] Eliciting patient-important outcomes through group brainstorming https://pmc.ncbi.nlm.nih.gov/articles/PMC6360192/ [10] 30 Effective Brainstorming Techniques for Teams To Try | Indeed.com https://www.indeed.com/career-advice/career-development/brainstorming-techniques [11] Foundations of Policy Analysis | Intro to Public Policy Class Notes https://library.fiveable.me/introduction-to-public-policy/unit-4/foundations-policy-analysis/study-guide/crUWSnTqaamH1mro [12] Brainstorming Sessions: Agenda Template + Best Practices https://www.wudpecker.io/blog/brainstorming-sessions-agenda-template-best-practices [13] Phase 3: Collecting and Analyzing Data - NACCHO https://www.naccho.org/programs/public-health-infrastructure/performance-improvement/community-health-assessment/mapp/phase-3-the-four-assessments [14] Analytical techniques | College of Policing https://www.college.police.uk/app/intelligence-management/analysis/analytical-techniques [15] 7 Brainstorming Rules for Stronger Collaboration - IDEO U https://www.ideou.com/blogs/inspiration/7-simple-rules-of-brainstorming [16] Top Policy Analysis Tools for Better Public Policy - Number Analytics https://www.numberanalytics.com/blog/policy-analysis-tools-public-policy [17] Brainstorming in Design Thinking: Best Practices & Challenges https://voltagecontrol.com/blog/brainstorming-in-design-thinking-best-practices-challenges/ [18] [PDF] A Framework for Analyzing Public Policies: Practical Guide http://www.ncchpp.ca/docs/Guide_framework_analyzing_policies_En.pdf [19] [PDF] Public Policy Analysis - Political Science - University of Florida https://polisci.ufl.edu/wp-content/uploads/sites/147/PUP6009-Robbins-1-2.pdf [20] [PDF] Structured Analytic Techniques for Improving Intelligence Analysis … https://www.stat.berkeley.edu/~aldous/157/Papers/Tradecraft%20Primer-apr09.pdf