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In an organization, employment test is an identical sequence of queries to evaluate employee’s knowledge, expertise, aptitudes, or other individualities. Using supervisory evaluations as a criterion to evaluate tests can have its own repercussions. Validating tests tend to emphasize abstract thinking skills, decision-making ability, with evaluation of good and bad decisions or personality profiles . I believe there can be bias results in employee evaluations depending on selection rate of a demographic group, such as, whites vs. blacks, or males vs. females, and it is over estimated, if the evaluation rate of the majority group is significantly lower. Unreliable information is under-estimated, because, when there is mutual trust between supervisor and employee, the rating is greater, not lower .
Data mining in human resource management is used to find the most significant and valued employees within an organization. Data Mining is underestimated in evaluation through social networking because, as stated by , managing talent involves human resource planning that regards processes for managing people in organization, and Data mining can be used efficiently in talent forecasting in HRM. The feature that is overestimated in social networks is on the future of software that can identify which employee is more valuable, and which employee is on the periphery of the organization.
When the supervisor evaluation and social network evaluation disagree about the accessed performance of an employee, then, a leader, with knowledge on the ideas that are circulated through large number of people and departments in the organization must be recognized in the organization. This leader would have the most reliable, valid, and less biased information about the employees, and would provide a subjective impression than a supervisor to assess the performance of each and every employee.
Hart, A., & Sheldon, G. (2007). Employment Personality Tests Decoded: Includes Sample and Practice Tests for Self-Assessment (illustrated ed.). Career Press.
Hayton, J. (2011, July). Do social networks influence performance appraisals? Retrieved from james-hayton.com: http://www.james-hayton.com/?p=39
Huang, R., Yang, Q., Pei, J., Gama, J., & Meng, X. L. (2009). Advanced Data Mining and Applications:. Springer.