The recruitment and retention of talented faculty is critical to instructional quality and the growth and enhancement of research at higher education institutions. At the same time, these institutions are challenged with the need to recruit and retain administrators to ensure continuous operations and to facilitate progress toward the mission of the institution. There are various approaches to examining salary equity, each addressing different research questions.
The purpose of this poster is to display a suite of decision support tools that were developed to answer specific questions regarding annual wage increases and to explore if groups of administrators and faculty members were not correctly compensated. Technologies were employed to provide a flexible tool for evaluating salary information at various levels of detail to provide a comprehensive analysis.
There are many data sources available to researchers and methods by which to conduct salary studies. The initial challenge in approaching this study was gaining an understanding of the various data sources and the potential information these data sources might provide, as well as their limitations. There were several analytical paths attempted, but after limitations of data sources were reached, creative solutions were developed to provide subject matter experts a suite of data tools that provide data visualization and various levels of detailed comparisons using data available from the state.
This poster will describe the various data sets initially employed in initial studies and their potential use. Finally, solutions developed that provided subject matter experts with decision support tools will be showcased. The challenges in data collection, visualization, and maintenance will be explained.
The salary equity analytical tools were developed using MS Visio 2003 and Excel 2003. Base SAS 9.3.1 SP 3 code is written to compile data in a form that was usable in both Visio and Excel PivotTables.
This presentation is intended for institutional researchers interested in learning about various salary equity data sources and their potential uses as well as decision support tool development.
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