Informating HRM: a comparison of data querying and data mining

Abstract

Beyond mere automation of tasks, a major potential of Human Resource Information Systems (HRIS) is to informate Human Resource Management (HRM). Within current HRIS, the informate function is realised based on a data querying approach. Given a major innovation in data analysis subsumed under the concept of 'data mining', possibly valuable potentials to informate HRM are lost while overlooking the data mining approach. Therefore our paper aims at a conceptual evaluation of both approaches. We therefore discuss and evaluate data mining as a novel approach compared to data querying as the conventional approach to informating HRM. Based on a robust framework of informational contributions, our analysis reveals interesting potentials of data mining to generate explicative and prognostic information. Thus data mining enriches and complements the conventional querying approach. Furthermore, recommendations for future research are derived in order to deepen the knowledge on the contributions of data mining to informate HRM.