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A Decision Making Model for Human Resource Management in Organization

By:   •  October 4, 2018  •  Article Review  •  903 Words (4 Pages)  •  37 Views

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Journal Critique

Mishra, S. N. & Lama, D. R. (2016) “A Decision Making Model for Human Resource Management in Organizations using Data Mining and Predictive Analytics”, International Journal of Computer Science and Information Security (IJCSIS), Vol. 14, pp. 217-221.

​Human Resource refers to the policies, practices and systems that influence employees' behaviour, attitudes and performance. The roles of HRM are to analyze and design work, HR planning, recruiting, selection, training and development, compensation,

Performance management, employee relations and records data. The authors proposed two (2) models for decision making for every HRM to handle and perform their tasks accurately the Data Mining and Predictive Analytics. The authors define Data mining as widely considered for extracting insights from to make decisions. Mining of data that has been reliable technology which contributes a deeper understanding of data for decision making. The article stated that it has gains a lot of significance in the society as it helped to make prediction methodologies easier in various fields. They also describe Predictive Analytics as being used to make predictions about unknown future events. They stated predictive analytics as an analyst guided subject that studies data patterns to make forward looking predictions and can make compound reports by assessing several data patterns and also convey answer that guide to what succeeding action.

In the article “Decision Making Model for Human Resource Management in Organizations using Data Mining and Predictive Analytics” the authors features the use of technology in various human resource functions especially in decision making and strategy. The authors specify the use of Data mining and Predictive Analytics as decision making model that can be helpful in improving success and efficiency of HR system that will improve business outcome. Data mining as extraction of data and organizes employees that will help HR in personnel selection and talent management. Then, data that extracted from data mining will be a variables used to provide a predictive model. The authors emphasize that predictive analytics studies data patterns to make forward looking predictions that delivers answers that guide to what will be the next action. The article displays some steps and methodology that can be used in classifying data which can be apply in decisive techniques into functioning of HR. Every step was identified and the rule itself on the HR in order to find express decision. The authors also gives C4.5 and other techniques that can be used in the classifying potential precision for talent management. There’s also an architecture of proposed HR decision system model with a graph that describes the flow on how to get decision by the use of data mining and predictive analytics. Human resource as the collector of data then mining of material in order to produce insights from HRs’ data and obtain facts after plotting of the pattern through produced rules. Next, was predictive model and followed by predictive decisions.

The authors emphasizes that data mining and predictive analytics are much desired techniques for decision making for human resource management in organizations. That there must be a participation of technology in decision making for the HR management in outcome technology can influence

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