Since the ‘Earth Summit’ in 1992 in Rio de Janeiro, the concept of sustainable development has been widely discussed and implemented globally. This paper proposes a quantitative tool, Data Envelopment Analysis (DEA), that can support decision makers in assessing the efficiency of implementation of the sustainable development policy. The example of such analysis is presented by assessing the efficiency of implementation of the sustainable development policy of twenty two European Union Member States in 2005–2015. DEA (and more specifically the Slack-Based Measure) showed an improvement in the efficiency of most of the Member States in 2015 as compared to the results achieved in 2005. This outcome sent a positive and motivating signal for the continuation of activities in the area of sustainable development implementation. The method used in the study also has determined the weak areas that still exist in inefficient countries and indicated the action that should be taken to improve their efficiency. DEA enables an objective comparison of the results measured using this method and may therefore be considered by EU Member States as well as other organizations, including local governments responsible for the implementation of a sustainable development policy as a useful tool facilitating an objective assessment of the effects of their work.

Data envelopment analysis (DEA) is a popular and universal method for examining the efficiency with which decision-making units (DMUs) transform multiple inputs into multiple outputs. However, DEA has its limitations, one of them being its decreasing discriminatory power when the number of analyzed DMUs is insufficient or when there are too many variables (inputs/outputs) describing them. When resigning from any of the variables is impossible or undesired, or when the number of units cannot be increased, CI-DEA, a method proposed in this article, proves to be helpful. It consists of replacing the inputs and/or outputs of the studied DMUs with a smaller number of composite indicators. The aggregation of variables is not based on subjective decisions of the analyst, but depends solely on correlations that exist among variables. The construction of the CI-DEA model makes the interpretation of the results unambiguous and easy. The reliability of the results obtained with CI-DEA have been confirmed by extensive simulation studies performed under conditions of predetermined real-efficiency of DMUs. The usefulness of CI-DEA on real data has been demonstrated on the example of the efficiency assessment of the digitalization in the life of the Generation 50+ in 32 European countries.