Separating the wheat from the chaff: An intelligent sales recruitment and benchmarking system

Abstract: The need for computer-based intelligent techniques for recruitment and retention of employees in a highly competitive global market has grown significantly in the last decade. Salesperson recruitment is a critical task for most organisations. Existing approaches for salesperson recruitment primarily rely on filtering of applications based on selection criteria followed by interviews. Some organisations also include personality testing based on psychometric techniques. The high turnover of salesperson in the industry suggests limited success of these procedures. Additionally, existing approaches lack benchmarking methods. In this paper we describe design and development of an intelligent sales recruitment and benchmarking system (ISRBS) for recruitment and benchmarking of salespersons. ISRBS design represents operation of the findings and outcomes based on actual field studies and random surveys of salespersons as well as development of models for measuring independent and dependent variables related to selling behaviour. The main contributions of the paper are (i) Developing an on line selling behaviour profiling technique based on integration of intelligent system techniques like expert systems and fuzzy sets, psychology based selling behaviour model, and AHP techniques, and (ii) an objective and novel selling behaviour benchmarking technique to facilitate modelling of organisation based benchmarks and cultural fits. An earlier version of this system has been commercially used in the industry in Australia. ISRBS integrates psychology based selling behaviour model with artificial intelligence techniques and soft computing methods for selling behaviour profiling and benchmarking. [Copyright &y& Elsevier]