Over the last 30 years, little has changed in the world of job analysis and job
classification. Technological advances have created new options for the way data are
collected, and organizations now rely heavily on interactive online applications
(McEntire et al., 2006). However, practitioners have continued to use traditional data
collection approaches and data analysis techniques. Typically, job analysis and job
classification projects involve collecting information from subject matter experts (SMEs)
and then administering a task- or competency-based survey to collect quantitative data.
The results of this process are often communicated in a technical report that provides an
overview of the methodology and lists the critical tasks and/or competencies resulting
from the data analysis. These reports normally consist of dull text followed by lengthy,
dense tables of data which can be laborious to comprehend and difficult to put into
practice. McEntire et al. (2006) reports that job analysis data are highly underutilized,
especially in the context of complex decision making, and calls for different methods of