Abstract
Applying competency models to identify and develop capabilities of civil servants is now a leading strategy for every government. However, an ideal competency model usually contains too many intended competencies, impeding implementation. Recently, some scholars and experts argued that there is a maximum of eight competencies for effective assessment. Hence, how to simplify a set of competencies becomes an important issue. This study is presented as a test case to extend practical applications of rough set theory (RST) in the human resource field of Government. A well-known data mining technique, RST is a relatively new approach to this problem and is good at data reduction in qualitative analysis. Hence, the rough set approach is suitable for dealing with the qualitative problem in simplifying a set of competencies. This paper slimmed a set of competencies using RST, thus helping the Taiwan Government to better understand the perceived competency levels of its civil servants. Using the rough set analysis, this paper successfully reduced the numerous essential competencies into a more compact set, by omitting low-consensus competencies.
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