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Use of data envelopment analysis and regression for establishing manpower requirements in a bank
Author(s) -
L.P. Fatti
Publication year - 2014
Publication title -
orion/orion
Language(s) - English
Resource type - Journals
eISSN - 2224-0004
pISSN - 0259-191X
DOI - 10.5784/14-0-421
Subject(s) - data envelopment analysis , work (physics) , computer science , regression analysis , regression , econometrics , operations research , linear regression , statistics , economics , mathematics , engineering , machine learning , mechanical engineering
We describe an approach towards forecasting the manpower requirements in each of the branches of a bank, based on regression models fitted to the sets of efficient branches. DEA is employed to identify the efficient branches within a category, using the numbers of employees in the different grades at each branch as input variables, and the average volumes of different types of work performed by them during a month as output variables. Forecasts of future volumes of work are obtained by fitting a model which takes into account branch and seasonal effects, as well as separate trend effects for each of the branches. The models have been tested on data from a large bank, with very encouraging results. The approach holds great promise for use towards a decision support system for managing the bank's total branch manpower requirements

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