Data Envelopment Analysis (DEA) is an approach to assess the relative
efficiency of organizations using multiple inputs to produce multiple
outputs. This assessment is made from the standpoint most favourable t
o each organization. If an organization is not well enveloped, in the
sense that it is not comparable to a sufficient number of other organi
zations (called referents), DEA may understate inefficiency. A lower b
ound on the efficiency measure may be obtained by requiring that the o
rganization being evaluated be compared with at least k non-redundant
referents. For any feasible choice of k, the procedure proposed here s
elects the most favourable set of referents, and guarantees a greatest
lower bound on the efficiency measure, thus usefully complementing th
e information provided by conventional DEA.