presenting a hybrid approach based on two-stage data envelopment analysis to evaluating organization productivity

measuring the performance of a production system has been an important task in management for purposes of control, planning, etc. lord kelvin said :“when you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meager and unsatisfactory kind.” hence, management knowledge is measurable science and if we can’t measure each subject we can’t control it so management is impossible. we know, the major criteria performance is productivity and we should be able to measure it. data envelopment analysis (dea), as an evaluation method, can estimate the relative efficiency of organizations systematically. the efficiency of an organization can be benchmarked by using dea. dea presents a model for evaluating the performance of a set of comparable decision making units (dmus). in this paper we developed a new model for calculating productivity with two-stage data envelopment analysis.