One way to estimate completion times of a person or organization is to compile a list of their own past predictions and actual outcomes, and compute in each case how much longer (or shorter) the actual time to completion was in relative terms.
Since an outcome that took 100% longer than predicted (twice as long), and an outcome that took 50% shorter (half as long) should intuitively cancel out, the geometric mean has to be used to compute the average. In the previous case that would be the square root of the product of those two factors, (2 * 0.5)^(1/2)=1. In that case we should multiply future completion estimates by 1, i.e. leave them as is.
That only works if we have some past history of time estimates and outcomes. Another way would be to look at prediction markets, should one exist for the event at hand. Though that is ultimately a way of outsourcing the problem rather than one of computing it.
One way to estimate completion times of a person or organization is to compile a list of their own past predictions and actual outcomes, and compute in each case how much longer (or shorter) the actual time to completion was in relative terms.
Since an outcome that took 100% longer than predicted (twice as long), and an outcome that took 50% shorter (half as long) should intuitively cancel out, the geometric mean has to be used to compute the average. In the previous case that would be the square root of the product of those two factors, (2 * 0.5)^(1/2)=1. In that case we should multiply future completion estimates by 1, i.e. leave them as is.
That only works if we have some past history of time estimates and outcomes. Another way would be to look at prediction markets, should one exist for the event at hand. Though that is ultimately a way of outsourcing the problem rather than one of computing it.
I like it! In addition, I suppose you could use a topic-wide prior for those groups that you don’t have much data on yet.