A Novel Data Mining Study to Spot Anomalies in Organizations: A Human Resources Management Case

Gokhan Silahtaroglu and Pelin Vardarlier
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Gokhan Silahtaroglu: Istanbul Medipol University, Turkey
Pelin Vardarlier: Istanbul Medipol University, Turkey

International Journal of Business and Administrative Studies, 2016, vol. 2, issue 4, 89-95

Abstract: Organizational behavior is one of the most important assets of an organization; it may be used to increase business value and profitability. Although it comes to life itself with the contribution of the sector, leadership, environment, market conditions and competition, unemployment etc. there must be some ways to lead or direct an organizational behavior.However, it is not practical to monitor and control an organizational behavior in detail by bare eyes. For example, a Chief Executive Officer (CEO) cannot observe the abrupt changes happening daily in a multi-million dollar global company, yet she longs for a tool to whisper into his/her ear what is happening in the organization and if there is an anomalous condition in the organization. Technology-wise, we are not away from building a system to learn, understand and monitor the organizational behavior and give alarms or signals to top management when the system perceives an extraordinary condition. This is doable with machine learning algorithms which is a model of Artificial Intelligence (AI). In the literature there are plenty of machine learning algorithms which have been proved that they work or learn very well. Both supervised and unsupervised algorithms may be used to learn an organizational behavior and detect anomalies in the behavior. In this paper, we propose a novel system to build a data warehouse with the data available in an organization and design it in a way that it can be used for learning the organizational behavior by machine i.e. computers. The system we propose may be used to spot daily, weekly or monthly changes in the organizational behavior. These changes may have positive or negative effects on the performance of organizations, so this system may also be used as a decision support system for top management. When necessary feedback is given to the system, it may also develop or learn new features to interpret the effect of the change on the overall performance of the organization. The system may also be used to compare the changes in the organizational behavior on yearly basis. Nevertheless, it is a useful tool to track, learn and monitor the interactions of each employee in the system. In the study the human resources management has been used as a sample model in order to detail the proposed system.

Keywords: Data Mining; Anomaly Detection; Employee Behavior; Organizational Behavior (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:apa:ijbaas:2016:p:89-95

DOI: 10.20469/ijbas.2.10001-4

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