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Using Data Envelopment Analysis to Transform Data Into Information: Academic Department Efficiency at a Public University
AuthorJanes, Brady J.
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Institutions of higher education amass incredible amounts of data. Analyzing the data in a way that can improve decision making is an integral part of complex operational and management processes, including resource allocation, programmatic development, and planning. Traditionally, higher education have lagged in its use of the data in operational and management processes (Desouza & Smith, 2016; Siemens & Long, 2011). This study examined the use of the analytical method, data envelopment analysis (DEA), to determine the efficiency of academic departments over the period 2008 to 2014. Data envelopment analysis was a method developed by Charnes, Cooper, and Rhodes (1981) and designed to measure the relative efficiency based on inputs and outputs of decision making units (DMUs). The purpose of this study was to explore the efficiency of academic departments in a public, Carnegie classified tier one, high research, comprehensive doctoral university with balanced arts and sciences undergraduate instruction. The inputs considered for this study were total research expenditures, state appropriated budgets, and operational budgets. The outputs considered were graduate and undergraduate degrees granted, full time equivalents (FTE) produced, student credit hours generated, scholarly works, and amount of grants awarded. An output-oriented, multi-stage DEA model was used to determine the efficiency scores of 16 academic departments or DMUs. Both constant returns to scale (CRS) and variable returns to scale (VRS) methods were used in DEA calculations. The efficiency results, descriptive data, departmental slacks results, and peer department comparisons were considered in determining the factors contributing to the efficiency and inefficiency of each DMU. Malmquist indices were used to measure the shifts in efficiency over time.Seven of the 16 academic departments were identified as efficient throughout the time period, 2008 to 2014. The remaining nine academic departments were identified as inefficient in at least one year throughout the period. The factors contributing to efficiency were undergraduate degree completers and operating budgets. Other factors that contributed to inefficiency of departments were scholarly publications, graduate degree completers, and instructional outputs. The examination of efficiency scores over time and the respective results generated, such as input and output targets and productivity indices, provide a means for assessing departmental efficiency and determining areas for improvement. Results may be one aspect of institutional decision making and planning about academic direction and resource allocation to ensure ongoing academic excellence.