Thanks for publishing such a detailed set of figures. If we are looking at the fundraising ratio, my preference is to use a realistic (though uncertain) estimate of both expected total impact and counterfactual costs. I’d rather be roughly right than precisely wrong.
Using that method it looks like you anticipate moving $780,000 as a result of your work over the last 2.5 years and had full counterfactually adjusted costs of $580,000. To me both of those look like reasonable estimates with fairly narrow error bounds around them—my 80% confidence interval would be a factor of 2 in either direction.
I guess this is an old debate, but not including these effects guarantees that your number is really wrong, at least if you are doing something fairly innovative. You end up accurately estimating a largely irrelevant number.
Perhaps you could get an external party who would be less biased in favour of your project to analyse this kind of thing? In the for-profit world this happens when you try to get external investors. I think this is relevant to your next project—if you don’t consider gains from experimentation you could choose something too conservative (though perhaps that is offset by people’s general overconfidence).
Thanks for publishing such a detailed set of figures. If we are looking at the fundraising ratio, my preference is to use a realistic (though uncertain) estimate of both expected total impact and counterfactual costs. I’d rather be roughly right than precisely wrong.
Using that method it looks like you anticipate moving $780,000 as a result of your work over the last 2.5 years and had full counterfactually adjusted costs of $580,000. To me both of those look like reasonable estimates with fairly narrow error bounds around them—my 80% confidence interval would be a factor of 2 in either direction.
Of course even better would be to think about how big any innovative approaches you’re pioneering could become at full maturity (https://80000hours.org/2015/11/take-the-growth-approach-to-evaluating-startup-non-profits-not-the-marginal-approach/). I think that would get a much higher ratio than the numbers above, but forecasts like that are much easier for an insider to make than someone like me with little tacit knowledge.
I think that sort of approach leaves far too much room for bias/optimism. It would be hard for me to take a number generated this way seriously.
I guess this is an old debate, but not including these effects guarantees that your number is really wrong, at least if you are doing something fairly innovative. You end up accurately estimating a largely irrelevant number.
Perhaps you could get an external party who would be less biased in favour of your project to analyse this kind of thing? In the for-profit world this happens when you try to get external investors. I think this is relevant to your next project—if you don’t consider gains from experimentation you could choose something too conservative (though perhaps that is offset by people’s general overconfidence).