1. 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

2. Why study peer group analysis? Accountability Resource Allocation External/internal requests Organizational learning?

3. 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

4. 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

5. 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?

6. Methodology Large Midwestern public Doctoral Extensive institution Qualitative Case Study Approach N = 10 upper, middle, and lower administrators Grounded theory

7. 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)

8. Argyris’ Double loop learning http://thoughthorizon.com/archives/000277.php

9. Bagshaw’s Plant Structure Phenomena Data Information Knowledge

10. 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

11. Findings (cont’d) Three Overarching Themes –Broad view of institutional data –Use of data –Organizational change

12. Broad View of Institutional Data Administrators emphasize comparative data Mid-level administrators view comparative data as nested

13. Use of Data Contribution of department to campus Resource allocation Internal goal setting and evaluation Desired uses Challenges

14. Organizational Change Fiscal outweighs performance Internal competition Leadership

15. 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

16. 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”

17. Discussion and Questions

18. Contact information Tara R. Warne (573) 884-6674 warnetr@umsystem.edu Kathy Schmidtke (573) 884-2241 schmidtkek@missouri.edu Kathleen Leonard-Getty (573) 882-4078 gettymk@missouri.edu