Integration of analytic hierarchy process and data envelopment analysis for assessment and optimization of personnel productivity in a large industrial bank

Research highlights? We assess and optimize productivity of personnel in a large private bank in Iran. ? An integrated algorithm based on data envelopment analysis and analytic hierarchy process is proposed for assessment and optimization purposes. ? It is concluded that the most branches inefficiencies are due to high teaching hours and lack of work quality. ? It is shown that number of personnel, discipline, personnel operation in the organization, and skills and capabilities are critical indicators so that even the smallest undesirable changes in these indicators have the most influences on the bank branches' efficiency. This paper presents an integration of analytical hierarchy process (AHP) and data envelopment analysis (DEA) for assessment and optimization of personnel productivity in a large private bank. In this algorithm the effective personnel operation indicators are evaluated by the management which is usually in qualitative forms and converted to quantitative forms by using AHP. Then, the ranking and efficiency of the organization will be assessed and optimized by DEA. Principal components analysis (PCA) and numeral taxonomy (NT) are applied to verify and validate the ranking results of the DEA method. We applied this algorithm in various branches of the Bank of Industry and Mine in Iran. The proposed framework may be used to study and optimize personnel productivity in large banks. This is the first study that integrated DEA and AHP for optimization of personnel productivity in large banks based on both qualitative and quantitative indicators.