Peer Group Analysis: For Administrators Only? Association of Institutional Research Forum San Diego, California May 29 – June 1, 2005 Tara R. Warne, Associate Research Analyst, University of Missouri System Kathy Schmidtke, Graduate Assistant, University of Missouri System D. Lanette Vaughn, Associate Research Analyst, University of Missouri System Kathleen Leonard-Getty, Institutional Research Assistant, University of Missouri-Columbia
Why study peer group analysis? Accountability Resource Allocation External/internal requests Organizational learning?
Literature Review Modern comparative analysis developed in 1980s utilizing statistical analysis (Terenzini) Used primarily for financial purposes Expanded to use a wide range of performance indicators –Graduation rates, employment rates, retention, salaries, enrollments, and faculty productivity
Literature Review (cont’d) Three different types of peer groups –Aspirational, peer, predetermined Peer analysis is subject to a number of limitations –Descriptive data insufficient –Varying definitions of variables –Can limit institutional creativity –Meaningful use of peer group analysis
Research Questions What do we want comparative data to tell us? Do peer analyses drive institutional change processes, in particular, organizational learning? Why or why not?
Methodology Large Midwestern public Doctoral Extensive institution Qualitative Case Study Approach N = 10 upper, middle, and lower administrators Grounded theory
Theoretical Frameworks Political (Bolman & Deal) –Competition for resources –Coalitions with differing missions Learning organization –Double-loop learning (Argyris & Schön) –Defensive reasoning (Argyris) –Phenomena → Data → Information → Knowledge (Bagshaw)
Argyris’ Double loop learning
Bagshaw’s Plant Structure Phenomena Data Information Knowledge
Findings Institutional Context –Comparative reports required by upper administration for resource allocation –Original allocation model abandoned –Reporting requirement retained –Reporting adapted based on divisional needs
Findings (cont’d) Three Overarching Themes –Broad view of institutional data –Use of data –Organizational change
Broad View of Institutional Data Administrators emphasize comparative data Mid-level administrators view comparative data as nested
Use of Data Contribution of department to campus Resource allocation Internal goal setting and evaluation Desired uses Challenges
Organizational Change Fiscal outweighs performance Internal competition Leadership
Conclusions Information used from peer group analysis –Level of teaching, research, and service –Support for greater resource allocations –Effectiveness and productivity Double-loop learning Defensive learning
Implications for IR Saupe (1990) –Objective, systematic, and thorough –“the wisdom, integrity, and courage possessed by those who share the responsibilities of governance” used to make decisions Volkwein (1999) –Internal vs external duality Bagshaw (1999) –Learning inhibited institution –Phenomena → Data → Information → Knowledge –“Shape the intellectual expectations of the leadership”
Discussion and Questions
Contact information Tara R. Warne (573) Kathy Schmidtke (573) Kathleen Leonard-Getty (573)