In the traditional data envelopment analysis(DEA)structure, the efficiency score for one decision making unit(DMU)is calculated by measuring the distance of the evaluated DMU to the best practice frontier. Recent researches have provided the reasonability of considering the worst practice frontier as a supplement to the traditional DEA techniques. The existing researches take only one type of frontier into account, and they cannot compare the evaluated DMU with both the best and the worst performing DMUs. A DEA-based procedure is developed to consider the best and the worst frontiers in the same scenario where the ratio of two distances(RDS) measure is proposed. The principal application of this approach is for ranking, and, as a complement tool,for performance evaluation. The proposed approach can be used in a wide range of applications such as the performance evaluation of employees and others. Finally, a bookstore data set is used to illustrate the proposed approach. In the traditional data envelopment analysis (DEA) structure, the efficiency score for one decision making unit (DMU) is calculated by measuring the distance of the evaluated DMU to the best practice frontier. Recent researches have provided the reasonability of considering the worst practice frontier as a supplement to the traditional DEA techniques. The existing researches take only one type of frontier into account, and they can not compare the the DMU with both the best and the worst performing DMUs. A DEA-based procedure is developed to consider the best and the worst frontiers in the same scenario where the ratio of two distances (RDS) measure is proposed. The principal application of this approach is for ranking, and, as a complement tool, for performance evaluation. The proposed approach can be used in a wide range of applications such as the performance evaluation of employees and others. Finally, a bookstore data set is used to illustrate the proposed approach.