I'm on a faculty search committee in a large department at a large university. We can typically recruit 4-6 new faculty per year. We would like to recruit the "best" faculty available each year, regardless of their focus. Best is highly subjective, so we have a search committee to help rank candidates.
Here's the problem: our field has several sub-disciplines. If we were a math department, this would be something like algebra, geometry, topology, applied math and combinatorics. Faculty on our search committee tend to rank people in their sub-discipline higher, and others lower. This is likely due to a mix of faculty finding their own field most interesting and important, leading to bias in rankings, and also an intentional desire to recruit people to their own area to get more good colleagues.
The result is that our largest and noisiest areas usually win, so we keep recruiting people in these areas. It would actually be even better if we could recruit people into areas where we aren't currently as strong, to improve the breadth of our department, but these candidates seldom have advocates.
Is there a good game-theoretic approach to ranking or voting for candidates that would help us find optimal candidates regardless of their sub-discipline? Our faculty, generally, are of good will and want to do well for the department, so if we can give them good guidance I'm hopeful they might follow it.