Data envelopment analysis (DEA) is a linear programming-based technique developed to evaluate the relative efficiency of non-profit and public sector decision-making units that use multiple inputs to produce multiple outputs. Technically, as pointed out by Joro et al., DEA and Multiple Objective Linear Programming (MOLP) aim at suggesting improvements for inefficient units based on the identification of efficient units in a certain space. In this study, DEA is used as a managerial audit tool to identify and measure inefficiencies among a set of 73 independent decision-making units within the federation's traditional accounting ratio measures. Management found that the DEA results confirmed most of the intuition on which units were unprofitable, and also pinpointed units that made a profit but were operationally inefficient. Overall, they agree with our results and on the benefits of using DEA to complement their accounting ration analysis for improving the efficiency of some of their “caisses”.
