This is an interesting model—but what level of analysis do you think is best for answering question 7? One could imagine answering this question on:
the vacancy level at the time of hire decision (I think Bob would be 80% as impactful as the frontrunner, Alice)
the vacancy level at the time of posting (I predict that on average the runner-up candidate will be 80% as the best candidate would be at this org at this point in time)
the position level (similar, but based on all postings for similiar positions, not just this particular vacancy at this point in time)
the occupational field level (e.g., programmer positions in general)
the organizational level (based on all positions at ABC Org; this seems to be implied when an org sets salaries mainly by org-wide algorithm)
the movement-wide level (all EA positions)
the sector-wide level (which could be “all nonprofits,” “all tech-related firms,” etc.)
the economy-wide level.
I can see upsides and downsides to using most of these to set salary. One potential downside is, I think, common to analyses conducted at a less-than-organizational level.
Let’s assume for illustrative purposes that 50% of people should reach the state specified in question 4 with $100K, and that the amount needed is normally distributed with a standard deviation of $20K due to factors described in step five and other factors that make candidates need less money. (The amount needed likely isn’t normally distributed, but one must make sacrifices for a toy model.) Suppose that candidates who cannot reach the question-4 state on the offered salary will decline the position, while candidates who can will accept. (Again, a questionable but simplifying assumption.)
One can calculate, in this simplified model, the percentage of employees who could achieve the state at a specific salary. One can also compute the amount of expected “excess” salary paid (i.e., the amounts that were more than necessary for employees to achieve the desired state).
If the answer to question 7 is that losing the top candidate would have severe impact, one might choose a salary level at which almost all candidates could achieve the question-four state—say, +2.5 SD (i.e., $150K) or even +3 SD ($160K). But this comes at a cost, the employer has likely paid quite a bit of “excess” salary (on average, $50K of the $150K salary will be “excess”).
On the other hand, if there are a number of candidates of almost equivalent quality, it might be rational to set the salary offer at $100K, or even at −0.5 SD ($90K), accepting that the organization will lose a good percent of the candidates as a result.
I suspect you would then have a morale problem with certain employees running the numbers and concluding that they were seen as considerably more replaceable than others who were assigned the same level!
You can fix that by answering question 7 at the organizational or movement levels, averaging the answers for all positions. Suppose that analysis led to the conclusion that your org should offer salaries at this position grade level based on +1 SD ($120K). But you’re still running a 16% risk that the top candidate for the position with no good alternative will decline, while you’re not getting much ROI for the “excess” money spent for certain other positions. You could also just offer $150K to everyone at that level, but that’s harder to justify in the new world of greater funding constraints.
In sum, the mode of analysis that I infer from your questions seems like it would be very helpful when looking at a one-off salary setting exercise, but I’m unsure how well it would scale.
This is an interesting model—but what level of analysis do you think is best for answering question 7? One could imagine answering this question on:
the vacancy level at the time of hire decision (I think Bob would be 80% as impactful as the frontrunner, Alice)
the vacancy level at the time of posting (I predict that on average the runner-up candidate will be 80% as the best candidate would be at this org at this point in time)
the position level (similar, but based on all postings for similiar positions, not just this particular vacancy at this point in time)
the occupational field level (e.g., programmer positions in general)
the organizational level (based on all positions at ABC Org; this seems to be implied when an org sets salaries mainly by org-wide algorithm)
the movement-wide level (all EA positions)
the sector-wide level (which could be “all nonprofits,” “all tech-related firms,” etc.)
the economy-wide level.
I can see upsides and downsides to using most of these to set salary. One potential downside is, I think, common to analyses conducted at a less-than-organizational level.
Let’s assume for illustrative purposes that 50% of people should reach the state specified in question 4 with $100K, and that the amount needed is normally distributed with a standard deviation of $20K due to factors described in step five and other factors that make candidates need less money. (The amount needed likely isn’t normally distributed, but one must make sacrifices for a toy model.) Suppose that candidates who cannot reach the question-4 state on the offered salary will decline the position, while candidates who can will accept. (Again, a questionable but simplifying assumption.)
One can calculate, in this simplified model, the percentage of employees who could achieve the state at a specific salary. One can also compute the amount of expected “excess” salary paid (i.e., the amounts that were more than necessary for employees to achieve the desired state).
If the answer to question 7 is that losing the top candidate would have severe impact, one might choose a salary level at which almost all candidates could achieve the question-four state—say, +2.5 SD (i.e., $150K) or even +3 SD ($160K). But this comes at a cost, the employer has likely paid quite a bit of “excess” salary (on average, $50K of the $150K salary will be “excess”).
On the other hand, if there are a number of candidates of almost equivalent quality, it might be rational to set the salary offer at $100K, or even at −0.5 SD ($90K), accepting that the organization will lose a good percent of the candidates as a result.
I suspect you would then have a morale problem with certain employees running the numbers and concluding that they were seen as considerably more replaceable than others who were assigned the same level!
You can fix that by answering question 7 at the organizational or movement levels, averaging the answers for all positions. Suppose that analysis led to the conclusion that your org should offer salaries at this position grade level based on +1 SD ($120K). But you’re still running a 16% risk that the top candidate for the position with no good alternative will decline, while you’re not getting much ROI for the “excess” money spent for certain other positions. You could also just offer $150K to everyone at that level, but that’s harder to justify in the new world of greater funding constraints.
In sum, the mode of analysis that I infer from your questions seems like it would be very helpful when looking at a one-off salary setting exercise, but I’m unsure how well it would scale.