Executive summary: Open Philanthropy explains how it uses back-of-the-envelope calculations (BOTECs) to estimate the cost-effectiveness of grants across focus areas like global health, lead exposure reduction, animal welfare, and effective giving, illustrating their approach through detailed examples and emphasizing both the utility and limitations of these rough but decision-critical models.
Key points:
BOTECs clarify expected impact by estimating a grant’s social return on investment (SROI), helping Open Phil determine whether a grant clears its cost-effectiveness threshold — currently ~2,000x in “Open Phil dollars” for Global Health and Wellbeing grants.
The models vary by grant type — DALYs averted for health, suffering reduced for animals, or funds raised for effective charities — and may be forward- or backward-looking depending on available data and theory of change.
BOTECs guide but don’t dictate decisions; qualitative factors like leadership, track record, and unusual upside are also considered, and multiple BOTEC versions test the robustness of conclusions across different scenarios.
Examples illustrate application and nuance: A tuberculosis R&D grant modeled to avert nearly 20,000 deaths annually showed a 3,000x SROI; a lead detection method grant had an expected 6,500x SROI; an effective giving org cleared a 2x bar for fundraising ROI; and a broiler welfare campaign surpassed the animal welfare team’s separate bar.
Open Phil adjusts BOTECs over time as new information arises — for example, reassessing speedup timelines or success probabilities post-grant — and openly acknowledges uncertainties, estimation challenges, and speculative assumptions in modeling.
The post invites community feedback and aims to demystify Open Phil’s quantitative thinking, while signaling that BOTECs are one tool among many in a broader evaluative process.
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Executive summary: Open Philanthropy explains how it uses back-of-the-envelope calculations (BOTECs) to estimate the cost-effectiveness of grants across focus areas like global health, lead exposure reduction, animal welfare, and effective giving, illustrating their approach through detailed examples and emphasizing both the utility and limitations of these rough but decision-critical models.
Key points:
BOTECs clarify expected impact by estimating a grant’s social return on investment (SROI), helping Open Phil determine whether a grant clears its cost-effectiveness threshold — currently ~2,000x in “Open Phil dollars” for Global Health and Wellbeing grants.
The models vary by grant type — DALYs averted for health, suffering reduced for animals, or funds raised for effective charities — and may be forward- or backward-looking depending on available data and theory of change.
BOTECs guide but don’t dictate decisions; qualitative factors like leadership, track record, and unusual upside are also considered, and multiple BOTEC versions test the robustness of conclusions across different scenarios.
Examples illustrate application and nuance: A tuberculosis R&D grant modeled to avert nearly 20,000 deaths annually showed a 3,000x SROI; a lead detection method grant had an expected 6,500x SROI; an effective giving org cleared a 2x bar for fundraising ROI; and a broiler welfare campaign surpassed the animal welfare team’s separate bar.
Open Phil adjusts BOTECs over time as new information arises — for example, reassessing speedup timelines or success probabilities post-grant — and openly acknowledges uncertainties, estimation challenges, and speculative assumptions in modeling.
The post invites community feedback and aims to demystify Open Phil’s quantitative thinking, while signaling that BOTECs are one tool among many in a broader evaluative process.
This comment was auto-generated by the EA Forum Team. Feel free to point out issues with this summary by replying to the comment, and contact us if you have feedback.