We are a global learning ecosystem of weavers who are advancing the practice and profession of weaving thriving learning ecosystems! We envision a world in which every neighborhood, network and organisation is living for universal wellbeing (of self, society and nature).
This session centred on evidence as the “litmus test” for whether a weaving project is actually working. Dr. Muñoz Piña argued that weavers have a social responsibility to test their hypotheses against reality, ensuring that time and resources are truly delivering well-being.
Key Learnings
The Tyranny of KPIs: Key Performance Indicators often become the objective themselves, distracting from the actual goal. For example, in micro-credits, a “90% repayment rate” was seen as a success (KPI), but evidence later showed it didn’t actually lift people out of poverty (the real goal).
The “Counterfactual”: To know if your weaving made a difference, you must compare your group with a “with and without” group (a control group). Without this, you might take credit for changes that would have happened anyway (e.g., city-wide drops in energy use).
Mixed Methods: While quantitative data (numbers) tells you what happened, qualitative data (interviews/stories) tells you why. In a smart-billing study, numbers showed energy savings, but interviews revealed that simple “tips” were more effective than “neighbor comparisons.”
Internal vs. External Validity: What works in one context (e.g., Bangalore) might not work in another (e.g., Mexico City). Weaving requires constant “pointillism” — gathering data from many locations to see the full systemic picture.
Social Responsibility: Gathering evidence is an act of accountability. It ensures that the trust, funding, and time invested by a community are not being wasted on ineffective processes.
Key Actions
Identify the “Deep Purpose”: Before choosing metrics, ask all stakeholders (including the “silent voices” like farmers’ families) what they actually want to achieve, rather than just what can be easily counted.
Look for Natural Experiments: If you can’t run a formal trial, find a “mirror” or comparison group — another region or organization that isn’t using your methods — to see if your weaving is the true cause of change.
Embrace “Permanent Skepticism”: Always ask, “What else could explain this result?” and “What would have happened if we did nothing?”
Listen to Emergent Results: Don’t just look for what you planned to happen. Pay attention to unexpected side effects, both positive and negative (e.g., a project intended for education might actually boost the local furniture economy).
Communicate Failures for Redesign: Use evidence of “non-success” not as a reason to cancel projects, but as a map for how to redesign them (e.g., shifting micro-credits toward those with demonstrated entrepreneurial skills).
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References
Key Figures:
Dr. Carlos Muñoz Piña (Speaker): Universidad del Medio Ambiente and Director of Global Research at the World Resources Institute (WRI).
Esther Duflo: Nobel Prize winner in Economics (referenced for her work on Randomized Control Trials and micro-finance).
Abhijit Banerjee: Co-recipient of the Nobel Prize (referenced alongside Duflo).
Concepts & Methodologies:
Randomized Control Trials (RCTs): The scientific method of testing policy effectiveness.
Counterfactual: The “parallel world” scenario used for comparison.
Internal/External Validity:** Concepts from research design regarding the applicability of results.
Case Studies:
Micro-finance in Hyderabad: How repayment didn’t equal poverty reduction.
Smart Billing in Bangalore: How city-wide data revealed the true impact of energy-saving tips.
Watershed Restoration in Brazil: How coaching vs. training affected funding success rates.
Knowledge Base Categories: 1) Funding & Strategy 2) Weaving Methods
We are a global learning ecosystem of weavers who are advancing the practice and profession of weaving thriving learning ecosystems! We envision a world in which every neighborhood, network and organisation is living for universal wellbeing (of self, society and nature).
