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Innovations in job analysis: Development and application of metrics to analyze job data
Institution:1. Department of Psychology, University of Minnesota, United States;2. Department of Psychology, Florida International University, United States;3. Department of Management and Organizations, University of Iowa, United States;1. University at Albany, United States;2. Virginia Tech, United States;3. Clemson University, United States
Abstract:Job analysis is an integral part of any human resource function. Recent advancements in technology and changing worker environments have drastically altered the means by which job analysis data are collected and stored. These changes have led to an increase in the amount of data that is collected and the potential for the data to inform complex decision making. However, due to a lack of tools available for configuring and analyzing data, human resource professionals are often unable to keep themselves abreast of changes in their workforce, make complex decisions using job data, and facilitate communication across jobs, job families or departments in their organization. As a result, advanced methods for analysis of job data are needed. Metrics are quantitative algorithms applied to job data that aid in decision making in areas such as recruitment, selection, transferability, promotion, training, and development. Metrics are a sophisticated, user-friendly approach to analyzing job data that have the potential to meet the needs of human resource professionals in today's dynamic workplace. The development of metrics, their application and benefit to human resource professionals, and their use of O?NET are discussed.
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