Collecting Data on Social Enterprises 2025

Data storage 2.4 2.5Effective data storage is essential to maintaining confidentiality, ensuring ethical data use and safeguarding survey respondents. Research teams must establish clear policies and procedures to protect collected data while allowing for meaningful analysis. Key considerations include: –Data use and confidentiality: Collected data must only be used for purposes agreed upon by respondents. It should not be shared with third parties or used for marketing unless explicit consent has been obtained. –Access and aggregation: Raw data should remain accessible only to the research team. Findings should not be published in an aggregated form unless respondents have consented to their data being shared. –Consent and safeguarding: All survey participants must provide formal consent, either in writing or verbally, before their data is used. They should be fully informed about how their information will be utilized at every stage of the research process. Additionally, research teams should implement a basic safeguarding policy to address any issues related to participant or team safety. When developing data-sharing practices, resources such as the European Union (EU) Code of Conduct for Data Sharing in the Social Economy21 can provide valuable guidance. This code, co-created by stakeholders in the European social economy, offers best practices, ethical guidelines and templates for transparent data usage. While some elements may need to be adapted for different contexts, its core principles remain widely applicable. By adhering to these best practices, research teams can ensure responsible data management while building trust with participants and stakeholders. Data presentation and publication Effectively presenting research findings ensures that insights are accessible and actionable. Data collected on social enterprises can be shared in various formats tailored to different audiences, from policy-makers and academics to social enterprises themselves. Key methods of data presentation include: –Reports: Comprehensive documents, such as country-specific reports (e.g. “The State of Social Enterprise in Ghana”)22 or network reports, providing in-depth analysis and context. –Summary infographics: Visual summaries distilling key findings into digestible formats suitable for social media, presentations and quick reference. –Interactive data visualizations: Tools that allow users to explore the data independently, cross-reference variables and analyse trends in a dynamic way. –Academic collaboration: Partnering with academic institutions to facilitate further research through controlled data-sharing agreements. –Open-source data: Making anonymized, aggregated datasets available for public download (in .xls or .csv format) to encourage broader analysis and innovation. –Respondent feedback: Providing participating social enterprises with tailored, benchmarked insights, fostering a reciprocal learning experience where they can compare their performance with peers’. By utilizing a mix of these approaches, research findings can reach a broad audience and contribute to a deeper understanding of the social enterprise sector. Collecting Data on Social Enterprises: A Playbook for Practitioners 14