A practical common weight multi-criteria decision-making (MCDM) methodology with an improved discriminating power for technology selection is introduced. The proposed MCDM methodology enables the evaluation of the relative efficiency of decision-making units (DMUs) with respect to multiple outputs and a single exact input. Its robustness and discriminating power are illustrated via a previously reported robot evaluation problem by comparing the ranking obtained by the proposed MCDM framework with that obtained by the cross-efficiency analysis, which is a well-known data envelopment analysis-based methodology. The results indicate that the proposed methodology enables further ranking of data envelopment analysis-efficient DMUs with a notable saving in computations compared with cross-efficiency analysis. Finally, the proposed MCDM framework is extended to incorporate ordinal as well as exact outputs, and an application is presented to illustrate the methodology.