Peer Group Analysis: For Administrators Only?

Association of Institutional Research ForumSan 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

http://thoughthorizon.com/archives/000277.php

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) 884-6674warnetr@umsystem.edu

Kathy Schmidtke(573) 884-2241schmidtkek@missouri.edu

Kathleen Leonard-Getty(573) 882-4078gettymk@missouri.edu