The name of the article used in this paper is,” Measuring bank branch performance using data envelopment analysis (DEA): The case of Turkish bank branches, by Mehmet Hasan Eken and Suleymen Kale”. The main claim and goals of the article is how to come up with a good performance model, which measures the potential improvement capabilities and relative efficiencies of most branches. The finding of this article is on how a good performance model will shape up a bank into becoming a better performer by identifying where their strengths and weaknesses are and then working hard to make sure they have been fully implemented. The other finding behind the article is how banks in Turkey and their branches’ profitability and production aspects develop. When analyzing the two aspects, that is; the profitability and production of a bank, it becomes apparent that the sizes of a particular bank as well as its scale efficiency are inter-related in one way or the other. This is because in both methods, the features in terms of ratio of the output to the input in both cases that have been classified according to their various areas and sizes and they have related propensities. Nevertheless, the method used in finding data stated in the article is by looking at the method of production and applying output tailored CCR and BCC theories, their situations and enhancement capabilities.
I agree with Eken & Kale, (2010) that when the size of a bank branch increases, its scale competence increases with respect to the production scale of the bank branch. On the other hand, effectiveness decreases with an increase in size (Eken & Kale, 2010). This means that the larger bank branches as well as the other relative smaller bank branches in Turkey ought to have special consideration and attention. Another important aspect when comparing the two aspects is the fact that the performing characteristics of the bank branches becomes better especially after incorporating the profit efficiency score together with the production scores. For that reason; each regional bank requires its own unique handling since branches with a low profit efficiency-low production turnover ought to become evolved into having a high low profit efficiency-low production turnover within the region (Eken & Kale, 2010).
A Data Envelopment Analysis being non parametric, it makes use of other resources for example measuring the performance, which can be used for other expenditures as well as personnel performance. A good DEA stands for good decision making within a banking branch as well as coming up with a good profitability approach analysis (Eken & Kale, 2010). This is because such strategies measure the efficiencies that would be used in maximizing the available resources so as to ensure that the branches in particular obtain maximum profits in the end. Using another approach, which is the operational approach it tends to incline more on how the bank branches perform and in particular the efficiencies involved while converting the bank’s deposit ration analysis (Eken & Kale, 2010).
A good DEA system also ensures that a banking branch considers its inputs and outputs before venturing into risky business opportunities such as money lending (Eken & Kale, 2010). The inputs and outputs being considered in according to me have been included in the benchmark branches of the Turkish bank branches and consequently, provide a platform of learning more about the branches. In the end, a production approach model provides a suitable scrutiny of a banking branch’s success in terms of producing adequate and reliable deposits as well as managing the loan allocation program thus; good decisions are made (Eken & Kale, 2010).
Based on my findings from the report, the efficiency of a good and production improvement capability depends on good management preferences as well as intermediation efficiency very seriously when studying and measuring banking performance (Eken & Kale, 2010). Having good banking performance indicates that there is profitability effectiveness, the operational tasks are carried out in an efficient and effective way and both production and operational efficiencies can be combined into one single model (Eken & Kale, 2010). In the findings from the report by Eken & Kale (2010), employing different Data Envelopment Analysis methods have different aspects therefore; incorporating numerous dimensions. Each of the efficiency dimensions constitutes of means and ways of further analysis (Eken & Kale, 2010).
In support to the numerous studies regarding banking efficiency in specific branches, measuring banking performance is easier and more reliable as compared to branch efficiency. This is due to the fact that banking data is easily assessable to the public at all bank levels, hence increasing the chances of a particular bank branch to become more reliable and accountable. Previous DEA techniques studies conducted prove that there were performance measurement inefficiencies, which were aimed at minimizing the operational costs of the banking branches by exploring the most favorable operational structure (Eken & Kale, 2010). Recent studies of the same illuminate brighter and different perspectives of the DEA techniques as opposed to the other studies. The new studies have raised awareness regarding the different branch operational dimensions and the various methods put into place to ensure that the integrated DEA application system works perfectly (Eken & Kale, 2010).
In my opinion and after an in-depth scrutiny, raising awareness has provided important data for the management of the banking institution to carry out the required steps in implementing the various strategies in dealing with the problems that arise. Such steps of improving dimensional performance include operational profitability and efficiency, and internal quality service. The relationship between profit efficiencies and operational efficiencies has drawn many similarities because both dimensions allow us to see which among the dimensions is superior and which one is inferior to the other. The other similarity as per my opinion is the fact that there exists positive links between the profit efficiency as well as the operational costs. The same similarity can be observed when one compares the operational efficiency of a banking branch and the transactional efficiency within the same banking branch (Eken & Kale, 2010). In the end, one finds out that there is co-relation between quality service, profit competence and operational competence (Eken & Kale, 2010).
After much analysis and examination, I commend the scholarly work conducted by Eken and Kale in coming up with this report on the use of DEA in analyzing banking performance. Both production and profitability effectiveness have similar tendencies despite the fact that the two variables are grouped into different sizes and regions. In the assessments, it is evident that the branch size and its level of competence are inter-related. However, the banking services should reflect on placing the ratio of the output to the input turnover and production ratio on balances so as to reveal the individual banking branch’s distinctiveness. Another thing to consider in relation to Data Envelopment Analysis and branch segmentation is the fact that the Turkish banks ought to bear in mind that there are emerging challenges that are supposed to be incorporated and thus the need for future analytical studies and more so in relation to benchmarking of the diverse banks and their banking branches.
Eken, M. H. & Kale, S. (2010). Measuring bank branch performance using Data Envelopment Analysis (DEA): The case of Turkish bank branches. African Journal of Business Management, 5(3), pp. 889-901.