We publish forecast and actual impact across our evidence portfolio — and update it as results come in.
Within our Evidence Fund, we fund and evaluate approaches to build evidence on their impact and cost-effectiveness in coffee-growing communities.
In the spirit of transparency, we want to provide insights not only when a project has ended, but also in between: to share what we expect, to provide a basis for discussion, and to signal when the evidence will be ready.
Our Evidence Portfolio
Our Evidence Fund has supported the following organizations and approaches, past and present. Since most projects are still ongoing or in the evaluation phase, the figures are projections rather than final results.
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More InformationFor more information about the individual projects and their impact models, click on the respective project title.
How to read the numbers:
All figures use present value over 10 years, discounted at 10%, deflated to 2021 EUR.
- #Cost/HH: total program costs needed for implementation, divided by the number of program participants.
- % Income increase: income gain per household relative to median baseline annual household consumption expenditure.
- € Income increase: absolute income gain per household.
Social Return on Investment
For each funded intervention, we model income gains and cost-effectiveness based on our Social Return on Investment (SROI) methodology.
SROI allows us to make data-driven funding decisions across the funding cycle: By estimating cost-effectiveness in advance, we ensure that resources are directed toward the most promising solutions. By re-assessing cost-effectiveness after project end, we can learn what needs to be improved, scale what works and discontinue what doesn’t.
Learn more how we use SROI in our funding cycle here.
Accordingly, the projects in our evidence portfolio span two stages: some are still under evaluation, with forecast SROI and income projections based on our upfront modelling; others have initial evaluation results available to establish an evaluative SROI.
As most models are based on assumptions, we estimate the upper- and lower-bound SROI estimates and visualize their potential range. This reflects the uncertainties attached to these kinds of models. It also shows whether the model reflects a more optimistic or conservative scenario.
Click “Unblock content” to access our live impact dashboards.
To enlarge the dashboard, click the two arrows in the lower-right corner (full-screen mode).
Hover over the ranges to view more information about each project.
You are currently viewing a placeholder content from Default. To access the actual content, click the button below. Please note that doing so will share data with third-party providers.
More InformationRead more about how we calculate SROI and access our SROI Manual here.
Cost-effectiveness vs. depth of impact
In addition to SROI, we track two other dimensions: depth and scale of impact.
A high SROI signals cost-effectiveness, but relative income gains tell us whether the change is meaningful for a household — the depth of impact. Next to cost-effectiveness, this is a key outcome we aim to achieve. To assess the scale of impact we look at the number of households reached by the project.
The ideal project would score well on all dimensions, sitting in the upper-right corner with a large target group.
Click “Unblock content” to access our live impact dashboards.
To enlarge the dashboard, click the two arrows in the lower-right corner (full-screen mode).
Hover over the bubbles to view more information about each project.
You are currently viewing a placeholder content from Default. To access the actual content, click the button below. Please note that doing so will share data with third-party providers.
More InformationHow to read the numbers:
Each bubble represents one funded program.
- The horizontal axis shows the SROI — the additional household income generated for project participants per euro invested.
- The vertical axis shows the relative income gain per household in relation to the median annual baseline household consumption expenditure.
- The bubble size reflects the number of households reached: a larger bubble means more households benefit from the project.
Two cases that illustrate the range of certainty in our portfolio — and how we reason about it.
TechnoServe: Jimma Coffee Program
Ethiopia — 2021-2025
The current SROI estimate of the Jimma Coffee Program (TNS03) is estimated at 5.5. Existing data has informed our model, with important caveats: the endline for the first cohort is available but with methodological limitations and missing rigorous yield estimates for stumped trees — a key impact driver. A second evaluation round and a separate yield study are underway, with results expected by the end of 2026.
Until then, we treat the forecast with caution and will update the model once new data arrives. This iterative refinement is part of how we work.
Learn more about the project.
Village Enterprise: HARVEST
Ethiopia — 2025-2029
With a forecast SROI of 2.2, this project sits at the lower end of our current portfolio — but a lower SROI does not mean a weaker project. The evidence base is among the strongest we have: two RCTs in rural Uganda and Kenya provide a well-documented income effect. The conservative forecast reflects a deliberate choice: we apply the lower end of the evidence range as our base case. Under more optimistic but empirically grounded assumptions, the SROI could reach 5.5.What we are testing here is whether a graduation approach proven in Uganda and Kenya delivers similar results for coffee-farming households in Ethiopia — a question the ongoing RCT will answer.
Learn more about the project — including how we measure spillover effects.
Village Enterprise: HARVEST
Ethiopia — 2025-2029
With a forecast SROI of 2.2, this project sits at the lower end of our current portfolio — but a lower SROI does not mean a weaker project. The evidence base is among the strongest we have: two RCTs in rural Uganda and Kenya provide a well-documented income effect. The conservative forecast reflects a deliberate choice: we apply the lower end of the evidence range as our base case. Under more optimistic but empirically grounded assumptions, the SROI could reach 5.5.What we are testing here is whether a graduation approach proven in Uganda and Kenya delivers similar results for coffee-farming households in Ethiopia — a question the ongoing RCT will answer.
Learn more about the project — including how we measure spillover effects.
A higher SROI does not automatically mean a better program.
Each number is a starting point for discussion.
Evidence-based iteration: the case of TechnoServe
Not every project delivers what we hoped for. Our earliest investment with TechnoServe — the Sidama Coffee Program (TNS01) — did not achieve the impact we had set out to generate. Through our SROI analysis we understood a structural constraint: stumping is the main driver of income gains in this model, but the required adoption levels were almost impossible to reach in this context. With small farm sizes, households would need to stump a large share of their trees — a risk most households could not absorb.
Together with TechnoServe, we used these insights to redesign the approach for the successor project, the Jimma Coffee Program (TNS03): selecting a region with larger farm sizes, building stumping incentives and beekeeping as an additional income source into the programme design.
The Jimma Coffee Program is currently in evaluation, with first results informing an updated forecast SROI of 5.5. The remaining uncertainty sits with yield outcomes and adoption rates — our assumptions on both are being tested as the evaluation progresses.
Read the full learning article: Same Approach, Different Outcomes: What We Learned from Sidama & Jimma
Join the learning process
We share findings as they emerge, invite feedback and believe that early conversations shape better outcomes.
If you are a funder, a coffee company, or an organisation working in coffee-growing communities — we want to hear from you. We regularly share portfolio updates with interested funders and welcome early conversations about co-funding or knowledge exchange.