Team performance is a ubiquitous area of inquiry in the social sciences, and
it motivates the problem of team selection -- choosing the members of a team
for maximum performance. Influential work of Hong and Page has argued that
testing individuals in isolation and then assembling the highest-scoring ones
into a team is not an effective method for team selection. For a broad class of
performance measures, based on the expected maximum of random variables
representing individual candidates, we show that tests directly measuring
individual performance are indeed ineffective, but that a more subtle family of
tests used in isolation can provide a constant-factor approximation for team
performance. These new tests measure the "potential" of individuals, in a
precise sense, rather than performance, to our knowledge they represent the
first time that individual tests have been shown to produce near-optimal teams
for a non-trivial team performance measure. We also show families of
subdmodular and supermodular team performance functions for which no test
applied to individuals can produce near-optimal teams, and discuss implications
for submodular maximization via hill-climbing.
%0 Journal Article
%1 kleinberg2015performance
%A Kleinberg, Jon
%A Raghu, Maithra
%D 2015
%K combinatorics optimization
%T Team Performance with Test Scores
%U http://arxiv.org/abs/1506.00147
%X Team performance is a ubiquitous area of inquiry in the social sciences, and
it motivates the problem of team selection -- choosing the members of a team
for maximum performance. Influential work of Hong and Page has argued that
testing individuals in isolation and then assembling the highest-scoring ones
into a team is not an effective method for team selection. For a broad class of
performance measures, based on the expected maximum of random variables
representing individual candidates, we show that tests directly measuring
individual performance are indeed ineffective, but that a more subtle family of
tests used in isolation can provide a constant-factor approximation for team
performance. These new tests measure the "potential" of individuals, in a
precise sense, rather than performance, to our knowledge they represent the
first time that individual tests have been shown to produce near-optimal teams
for a non-trivial team performance measure. We also show families of
subdmodular and supermodular team performance functions for which no test
applied to individuals can produce near-optimal teams, and discuss implications
for submodular maximization via hill-climbing.
@article{kleinberg2015performance,
abstract = {Team performance is a ubiquitous area of inquiry in the social sciences, and
it motivates the problem of team selection -- choosing the members of a team
for maximum performance. Influential work of Hong and Page has argued that
testing individuals in isolation and then assembling the highest-scoring ones
into a team is not an effective method for team selection. For a broad class of
performance measures, based on the expected maximum of random variables
representing individual candidates, we show that tests directly measuring
individual performance are indeed ineffective, but that a more subtle family of
tests used in isolation can provide a constant-factor approximation for team
performance. These new tests measure the "potential" of individuals, in a
precise sense, rather than performance, to our knowledge they represent the
first time that individual tests have been shown to produce near-optimal teams
for a non-trivial team performance measure. We also show families of
subdmodular and supermodular team performance functions for which no test
applied to individuals can produce near-optimal teams, and discuss implications
for submodular maximization via hill-climbing.},
added-at = {2019-04-12T15:28:36.000+0200},
author = {Kleinberg, Jon and Raghu, Maithra},
biburl = {https://www.bibsonomy.org/bibtex/2ad18b5a7c187a7b0379bf948bc945542/kirk86},
description = {Team Performance with Test Scores},
interhash = {43e4ce7e5f6ee25fbb29642bcb5e0976},
intrahash = {ad18b5a7c187a7b0379bf948bc945542},
keywords = {combinatorics optimization},
note = {cite arxiv:1506.00147},
timestamp = {2019-04-12T15:28:36.000+0200},
title = {Team Performance with Test Scores},
url = {http://arxiv.org/abs/1506.00147},
year = 2015
}