An Intelligent Prediction Of An Employee's Counterproductive Behaviour

Abstract

Knowledge management, despite concerted attempts by information technology professionals, is not only about only storing knowledge on computers. It is an approach towards management that seeks to ensure that the knowledge in play in an organization's sphere of operation is appropriate for its purposes. Ensuring the appropriateness of knowledge entails examining an organization's objectives and the processes that shape the knowledge in play. Information technology plays a supportive role in knowledge management. It captures and stores knowledge into knowledge repositories. At the same time, it also improves access to knowledge stored in knowledge repositories. Terabytes of data are generated everyday in many organizations. To extract hidden predictive information from large volumes of data, data mining techniques are needed. This paper examines and discusses methods to extract information from polygraph data. To develop a stable work force with dependable work habits, it is important to find the right people for the job. Concerns about honesty and concerns about dependability on the job should be a primary focus in pre-employment screening. Knowledge management in association with risk management approaches, we need to consider three aspects of human behavior, individual productive behavior, workgroup productive behavior and counterproductive behavior. The most commented upon human behavior associated with risk is often counterproductive behavior. Much has been said about pre employment testing to detect counterproductive behaviors. Various tools have been employed to help detect counterproductive behaviors including the use of polygraph techniques. Polygraph Counterproductive Behavior Index Profile will be developed to help identify employee’s whose behaviors, attitudes, and work-related values are likely to interfere with their success as employees – consisting of 17 questions used in pre employment polygraph testing. These 17 questions covered 10 major areas to be tabulated into the Polygraph-Counterproductive Behavior Index Profile namely theft propensity, illegal drug use, alcohol use, work history, work attitude, customer service, fundamental data, credibility, computer abuse and sexual harassment. Scale score of 1 to 10 will be developed which will be further divided into 3 major areas of concerns, namely little or no concerns, concerns and serious concerns. Lower scorers are of little or of no concerns. Medium scorers are of concerns while higher scores are of serious concerns.