Five in-depth articles dedicated to the 2025 Social Report. The third focuses on evaluation methodologies
Evaluation usually comes at the end. A project is carried out, the results are collected, they are compared with the initial objectives, and an attempt is made to determine whether the intervention has been successful. But what happens when the context changes faster than the project itself?
For several years now, the Fondazione Mondo Digitale has been systematically using Real-time Evaluation for Social Innovation (RTE4SI), an approach that integrates monitoring and evaluation into a single, continuous process. The data is not merely used to document what has happened: it is collected and analysed whilst activities are being carried out to guide decisions, introduce corrective measures and strengthen the impact. It is a seemingly technical difference which, however, profoundly alters the meaning of evaluation. Evaluation no longer means merely demonstrating, but also learning.
An educational project, for example, may reach a different audience to the one envisaged, record unexpected levels of participation, or reveal new needs. If these signals are only observed at the end, they become useful information for the future. If, however, they are picked up whilst the project is underway, they can immediately alter its course. The methodology adopted by the Foundation uses both quantitative and qualitative tools: pre- and post-project questionnaires, interviews, focus groups, participatory workshops, observation and performance indicators. But it also attempts to measure what is normally more difficult to quantify.
The model distinguishes between three value streams – social, knowledge and financial – and regards the people involved not simply as beneficiaries or stakeholders, but as individuals who participate in the very creation of value. To summarise the impact, radar charts based on 170 values linked to the Sustainable Development Goals are also used.
To support the analysis, Arin is also used: a generative artificial intelligence system focused on social issues, employed to make the information produced by the Foundation’s activities more accessible and interpretable. The stated aim is not to automate decision-making, but to strengthen people’s ability to interpret complexity.
This is perhaps the crux of the matter. The more complex social systems become, the less sufficient it is to ask, in the end: did it work or not? More dynamic questions become necessary: what is working? For whom? Under what conditions? What can we change now? Measuring whilst changing means precisely this: transforming evaluation from a final judgement into a tool for knowledge.
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