The major advantage of Data Envelopment Analysis (DEA) is to reduce multivariate data to a single key performance indicator (KPI). However, this KPI is just one element to determine the (economic) situation of a Decision-Making Unit (DMU), e.g. a bank. Beside this, DEA offers a wide range of information about the observed DMU(s). Similarities or dissimilarities within the set of DMUs can be graphically explored by visualized representations – intuitively as well as analytically. This may discover valuable knowledge for decision support.
The purpose of this contribution is to exemplify a Data Envelopment Analysis for the banking sector and extend it by the aforementioned visualization. To compute the visualized representations we use the multivariate method of Multidimensional Scaling. The example includes two different perspectives: First, we will give an overview of the whole set of banks, e.g. from the perspective of an authority. Second, we will enter the perspective of a single bank. In both cases, a substantial interpretation of the results is given.