In basic Data Envelopment Analysis (DEA) models, the weights of performance criteria are endogenously determined, assigning to each decision-making unit (DMU) its best possible efficiency score. This property is widely considered to be a major strength of the method, but it is also a source of considerable problems concerning performance assessment and performance control. Such problems result from the possibility of zero-value weights that exclude criteria from the evaluation. Unlike approaches that deal with this issue by incorporating value judgments into the analysis, we suggest a complementary balance score that is derived from the given data set. This score evaluates the extent to which a DMU avoids concentration on only some of the crucial performance criteria. One of the possible decisions resulting from a balance analysis is to reduce the set of DMUs considered to serve as benchmarks. For this case, a modified CCR–O model is presented.
