Applying data driven decision making to rank vocational and educational training programs with TOPSIS

In this paper we present a multi-criteria classification of Vocational and Educational Programs in Extremadura (Spain) during the period 2009–2016. This ranking has been carried out through the integration into a complete database of the detailed information of individuals finishing such studies together with their labor data. The multicriteria method used is TOPSIS together with a new decision support method for assessing the influence of each criterion and its dependence on the weights assigned to them. This new method is based on a worst-best case scenario analysis and it is compared to a well known global sensitivity analysis technique based on the Pearson's correlation ratio. •A data-driven multi-criteria decision-making approach is presented.•8 different criteria were applied whose values were computed from a real dataset.•The information is enriched by real data instead of being based on questionnaires.•A new technique for assessing the influence of the different criteria is included.