Reducing imprecision in a human resource database through rough set theory

This study deals with decision-making using replicated and inconsistent data, relating to the universe of Human Resources, within a domestic/local financial institution. Replication occurs because of technical and/or economic questions, and seeks to meet the corporate and departmental requirements of such an institution. As research methodology, direct observation of such inconsistencies was used as well as a simulation based on actual data which would reflect replication with inconsistencies. Application of a multi-criteria method became necessary in view of the need to render the decision-making process rational, and was transformed into an element that stimulated this study. The method used was Rough Set Theory (RST), inasmuch as there existed no other information on the occurrence of such inconsistencies. An algorithm was developed to indicate the major data sources and was subsequently implemented into a software to facilitate research of such sources.