Efficient Data Mining Techniques to Enhance Hr Activities

Topics: Human resource management, Human resources, Data mining Pages: 8 (2797 words) Published: February 2, 2011
Recently, research in Human Resource (HR) activities that are embedded with Data Mining Techniques can solve unstructured and indistinct decision making problems. Human Resource Management (HRM) activities can facilitate to take fair and consistent decisions, and to improve the effectiveness of decision-making processes. Besides the challenges for HR Professionals to manage the organizational decisions and talents, especially they have to ensure that the selection of a right person, providing training to develop the skills, positioning the right person at right job at the right time, assessing the performance and appraising the personnel. Basically, HRM is a comprehensive set of managerial activities and tasks concerned with developing and maintaining a competent workforce – human resource. HRM aims to facilitate organizational competitiveness; enhance productivity and quality; promote individual growth and development; and complying with legal and social obligation. Besides that, in any organizations, they need to compete effectively in term of cost, quality, service or innovation. All these depend on having enough right people, with the right skills, deployed in the appropriate locations at appropriate points in time. Nowadays, in HRM field among the challenges of HR Professionals are selecting the skilled persons, providing training to the recruited people, placing the person in a right position, and performance appraisal. These tasks involve a lot of managerial decision, and which it is sometime very uncertain and difficult to make the best decisions. In reality, current HR decision practices depend on various factors such as human experience, knowledge, preference and judgment. These factors can cause inconsistent, inaccurate, inequality and unforeseen decisions. As a result, especially in promoting individual growth and development, this situation can often make people feel injustice. Besides that, in future, this can influence organization productivity. In Human Resource Management, to perform various activities are said to be challenges of the Top HR management. These challenges can be managed by using Data Mining techniques in order to select and recruit the skillful personalities, providing training to then people in the organization by classifying them into corresponding groups, placement and performance appraisal schemes. For that reason, this work aims at identifying the efficient Data Mining techniques to fulfill the above said challenges. Need and Importance of Data Mining Techniques in HR Activities: In the previous session, we discussed about various HR Management activities, which can play a vital role in the decision-making and improvement of the organization. In order to perform the above-discussed activities manually, it is tricky which may lead to more time and cost consumption. Selection is the one of the primary and crucial HR activity that is to be carried out by the HR Professional as the right people can only serve the organization well and work for the improvement, if an unskilled person is selected for an important position in any organization, then it leads to many major consequences that may harm to the organization. Data Mining techniques can be embedded and utilized in the Selection process when the organization has a huge requirement. Now a days, recruitment drives conducting by most of the IT companies a huge number of students want to participate in the interviews, in this case the selection of the right person’s application at the first level to written test process can consume more time and also it requires more Human Resources. In order to minimize the process and for effective and efficient output, we can identify and propose some of the efficient Data Mining Classification techniques which can be the best. This can be implemented to any type of recruitment scenario. After the Selection process is effectively completed then the next step is the...
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