Our client, Helsingin Diakonissalaitos, is a significant social actor and a public-benefit foundation committed to supporting vulnerable individuals and promoting human well-being. Together with its subsidiary, Rinnekodit Oy, the foundation provides impactful social and healthcare services for people in need of special support.
A key part of their work also includes development projects and future-oriented work. As part of this, the organization runs participatory future workshops with clients of Helsingin Diakonissalaitos and Rinnekodit. The materials generated in these workshops are a vital part of the foundation’s development efforts, helping them improve services and respond more effectively to people’s needs.
Challenge
Helsingin Diakonissalaitos faced a significant challenge: the large volume of data generated by these workshops was difficult and time-consuming to analyze. They needed a solution that would enable more efficient and versatile analysis of this valuable material, making the creation of final project reports smoother. This would also free up more time for what matters most — connecting with people and developing services.
A key requirement was that the analysis be based on futurist Sohail Inayatullah’s Futures Triangle theory, and that past and future reports remain comparable with each other.
Solution
We designed and implemented a custom GPT model for Helsingin Diakonissalaitos using ChatGPT. The model was trained on workshop data from all seven customer groups during a defined period and was specifically tailored to apply the Futures Triangle theory as the foundation for its analysis. This theory provides a structured framework for exploring future perspectives and ensures that analyses are systematic and consistent.
The customized GPT model enabled Helsingin Diakonissalaitos to:
Conduct analysis independently: The team could carry out the analysis on their own, maintaining full control over the process.
Ensure data security and ethical integrity: All analysis was conducted securely within the organization — a critical requirement when handling sensitive data.
Deliver theory-driven analysis: Grounding the analysis in the Futures Triangle ensured quality, consistency, and comparability across reports.
Outcomes
With the custom GPT model in place, Helsingin Diakonissalaitos was able to significantly streamline their analysis process. The team could interact with the model, compare needs and perspectives across different customer groups, easily extract relevant quotes, and draw conclusions on specific themes or workshops.
This saved time in the analysis phase and allowed the team to focus more on what truly matters: engaging with, listening to, and supporting people.
Furthermore, GPT enabled a richer representation of participants’ voices in the final report — their words and perspectives could be highlighted and integrated more meaningfully.
Helsingin Diakonissalaitos was able to leverage the results of the workshops more effectively — conducting deeper societal analyses, making better-informed decisions for communities and individuals, and using the model to ideate new projects and services that align with the needs and wishes voiced in the workshops.
