Data Envelopment Analysis (DEA) has been proven as a popular and practical data-oriented methodology for evaluating the relative efficiency of Decision-Making Units (DMUs) which utilize multiple inputs in order to produce multiple outputs. In the present work, we develop an alternative model to simultaneously address the two concepts relevant to the previously neglected aspects of DEA: cross-efficiency and flexible measure. To do this, considering the conventional DEA model, we try to classify the flexible measures with the aim of achieving the maximum possible cross-efficiency score of all DMUs, without restricting it to the maximization of the simple efficiency of individual DMU. Additionally, we build the formulation for the implementation of above approach and provide a numerical example to validate the approach.