Data Mining in Human Resources

Data Mining in Human Resources

Marvin D. Troutt (Kent State University, USA) and Lori K. Long (Kent State University, USA)
DOI: 10.4018/978-1-59904-951-9.ch142
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Abstract

In this paper, we briefly review and update our earlier work (Long & Troutt, 2003) on the topic of data mining in the human resources area. To gain efficiency, many organizations have turned to technology to automate many HR processes (Hendrickson, 2003). As a result of this automation, HR professionals are able to make more informed strategic HR decisions (Bussler & Davis, 2002). While HR professionals may no longer need to manage the manual processing of data, they should not abandon their ties to data collected on and about the organization’s employees. Using HR data in decision-making provides a firm with the opportunity to make more informed strategic decisions. If a firm can extract useful or unique information on the behavior and potential of their people from HR data, they can contribute to the firm’s strategic planning process. The challenge is identifying useful information in vast human resources databases that are the result of the automation of HR related transaction processing.

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