Cover page

Table of Contents

Title page

Copyright page

About AIR

Editors’ Notes

Chapter 1: How Benchmarking and Higher Education Came Together

The Quality Movement and Benchmarking

Benchmarking in Higher Education

Conclusions

Chapter 2: Internal Benchmarking for Institutional Effectiveness

Internal Benchmarking in Higher Education

Are You Ready to Benchmark?

Initial Steps

How to Benchmark

Conclusions

Chapter 3: Benchmarking and Enrollment Management

Overview

Some Notes on Benchmarking

Scope of Enrollment Management

Challenges in Interpretation of Benchmarks

What’s Not Available for Comparison with Comparable Institutions?

Conclusion

Chapter 4: Using Institutional Survey Data to Jump-Start Your Benchmarking Process

Defining Benchmarking

Relationships between Self-Assessment and Benchmarking

Institutional Researchers’ Role in Benchmarking

Relevant Institutional Survey Data for Benchmarking

Topics to be Addressed by Using Institutional Survey Data

Example of Using Institutional Survey Data for Benchmarking

Known Limitations and Issues

Concluding Remarks

Chapter 5: Learning How to Play Ball: Applying Sabermetric Thinking to Benchmarking in Higher Education

What Is Sabermetrics?

Some Common Sabermetrics

A Modest Application of Sabermetric Thinking to Higher Education Benchmarking

Conclusions

Chapter 6: Selecting Peer Institutions with IPEDS and Other Nationally Available Data

Integrated Postsecondary Education Data System (IPEDS)

Association for Institutional Research and IPEDS

Library Statistics Program

CUPA-HR Surveys and Data on Demand

Carnegie Classification of Institutions of Higher Education

UNC System Peer Requirement

Chapter 7: Benchmarking Tier-One Universities: “Keeping Up with the Joneses”

Literature Review

Methodology

Data Analyses

Results of Analyses

Conclusion

Appendix A: Variables Used in Study

Appendix B

Appendix C

Appendix D

Appendix E

Chapter 8: Taming Multivariate Data: Conceptual and Methodological Issues

People-Processing Institutions

Who’s in the Universe?

Clarifying the Question: What Is the Purpose and Who Wants to Know?

Variable Selection and Specification Issues

Proxy Variables and Weighting

Taming Multivariate Data

Technical Appendix

Chapter 9: Conclusions and Future Directions

Where It All Began

Practical Uses of Higher Education Benchmarking

This Could Really Work

Finding Benchmark Peers

Benchmarking Town and Gown

The Path Less Traveled

Index

OTHER TITLES AVAILABLE IN THE NEW DIRECTIONS FOR INSTITUTIONAL RESEARCH SERIES

Title page

THE ASSOCIATION FOR INSTITUTIONAL RESEARCH was created in 1966 to benefit, assist, and advance research leading to improved understanding, planning, and operation of institutions of higher education. Publication policy is set by its Publications Committee.

PUBLICATIONS COMMITTEE

Gary R. Pike (Chair) Indiana University–Purdue University Indianapolis
Gloria Crisp University of Texas at San Antonio
Paul Duby Northern Michigan University
James Hearn University of Georgia
Terry T. Ishitani University of Memphis
Jan W. Lyddon San Jacinto Community College
John R. Ryan The Ohio State University

EX-OFFICIO MEMBERS OF THE PUBLICATIONS COMMITTEE

John Muffo (Editor, Assessment in the Disciplines), Ohio Board of Regents

John C. Smart (Editor, Research in Higher Education), University of Memphis

Richard D. Howard (Editor, Resources in Institutional Research), University of Minnesota

Paul D. Umbach (Editor, New Directions for Institutional Research), North Carolina State University

Marne K. Einarson (Editor, AIR Electronic Newsletter), Cornell University

Gerald W. McLaughlin (Editor, AIR Professional File/IR Applications), DePaul University

Richard J. Kroc II (Chair, Forum Publications Committee), University of Arizona

Sharron L. Ronco (Chair, Best Visual Presentation Committee), Florida Atlantic University

Randy Swing (Staff Liaison)

For information about the Association for Institutional Research, write to the following address:

AIR Executive Office

1435 E. Piedmont Drive

Suite 211

Tallahassee, FL 32308-7955

(850) 385-4155

air@mailer.fsu.edu

http://airweb.org

Editors’ Notes

Benchmarking has several different uses and purposes in higher education. Some institutions use benchmarking to gauge performance internally to their own organization in regard to departmental performance. Other organizations use benchmarking to gauge their institution among external entities to improve certain performance measures in relation to a specific goal (such as increase in research expenditures or improving the national ranking of the institution).

The definition that the authors relied on in this volume of New Directions for Institutional Research is the following:

Benchmarking is a strategic and structured approach whereby an organization compares aspects of its processes and/or outcomes to those of another organization or set of organizations to identify opportunities for improvement.

In some of the chapters (Chapters 2, 3, 4, and 5) of this volume, benchmarking is used in assessment work to measure different aspects of the institution’s mission. For example, benchmarking can be used to gauge effectiveness of certain aspects of university or college instruction by carrying out assessment surveys from year to year among students or alumni. Several institutions also participate in such services as the National Survey of Student Engagement (NSSE), which provides data on surveyed students that can be utilized for benchmarking to help institutions improve aspects of their organization (NSSE, 2011). This volume shows different aspects of benchmarking from a wide variety of perspectives that institutional research offices can use for strategic planning and institutional research purposes.

Chapter 1 provides a historical context and background to how benchmarking has evolved in its usage in higher education institutions over time. Chapters 2 through 5 delve into how benchmarking can be used internally for institutions. Chapter 2 discusses institutional use of comparative analysis of different processes, results, and procedures to obtain useful metrics that can be used to improve performance for different institutional programs. Chapter 3 discusses how benchmarking is used to assist with enrollment management to attain efficiencies in relation to admissions, enrollment, and financial aid.

Chapter 4 discusses how institutions can use surveys that are completed by different entities as starting points for an external benchmarking. An institution can gauge certain performance indices against peer institutions by comparing similar survey information.

Chapter 5 shows how Sabermetrics is used to assess faculty productivity using common statistical techniques that have been used in baseball to show how they can be applied to higher education.

Chapters 6, 7, and 8 focus primarily on external benchmarking for institutional analysis. Chapters 6 and 8 used different methodologies for selecting peers for their institutions. Chapter 6 relates how institutions can use the Integrated Postsecondary Education Data System (IPEDS) for external benchmarking purposes. It also discusses the advantages of using standardized data to assist in the selection of peer institutions for external benchmarking purposes.

Chapter 7 provides a research project to determine whether or not a top-tier-ranked public institution of higher education’s linkage with their host municipality had any impact upon their rankings in U.S. News and World Report. The research methodology with the top-tier public institutions was also used to explore the same variables in public “emerging universities” benchmarked against top-tier public institutions. The authors attempted to see if any common characteristics with the linkages could be leveraged to improve their rankings in U.S. News and World Report. The research in the end revealed other findings that were not initially anticipated by the authors.

Chapter 8 took a very different approach than that in Chapter 7 by developing a statistical model to assist in determining institutional peers. The authors worked with their system colleagues to implement a strategy of minimizing the number of variables used in the statistical model in order to answer a specific benchmarking question. The authors’ goal with this methodology was to use variables that were not integral with one another or weighted, which could skew the results. The authors use a step-by-step process in the chapter to show the reader how their statistical model was developed for the purpose of benchmarking to address a specific research question.

Chapter 9 provides a summary of the volume and takes a look into how benchmarking may be used in higher education in the future.

The editors would like to thank all of the authors and personnel that worked so hard and diligently on this volume. Without researchers and support staff, this volume—and journal series, for that matter—would not be possible.

Gary D. Levy
Nicolas A. Valcik
Editors

Reference

NSSE. National Survey of Student Engagement: About NSSE. Retrieved on May 5, 2011, from http://nsse.iub.edu/html/about.cfm.



GARY D. LEVY is the Associate Provost for Academic Resources & Planning and a professor of psychology for Towson University.

NICOLAS A. VALCIK is the Associate Director of the Office of Strategic Planning and Analysis and a clinical assistant professor for the Program of Public Affairs at the University of Texas at Dallas.

1

How Benchmarking and Higher Education Came Together

Gary D. Levy, Sharron L. Ronco

This chapter introduces the concept of benchmarking and how higher education institutions began to use benchmarking for a variety of purposes.

The precise origin of the term benchmarking is unknown. However, it may have originated from the ancient Egyptian practice of using the surface of a workbench to make dimensional measurements of an object, from the mark cut into a stone or wall by surveyors measuring the altitude of a tract of land, or by cobblers measuring people’s feet for shoes. Whatever its origins, implicit in the concept of benchmarking is the use of standards or references by which other objects or actions can be measured, compared, or judged. Modern commercial benchmarking has now come to refer to the process of identifying the best methods, practices, and processes of an organization and implementing them to improve one’s own industry, company, or institution. For the sake of this chapter (and this volume) we define benchmarking as a strategic and structured approach whereby an organization compares aspects of its processes and/or outcomes to those of another organization or set of organizations to identify opportunities for improvement.

The practice of benchmarking in American business is widely considered to have originated in the late 1970’s. The literature generally acknowledges Xerox Corporation as the first American business organization to formally apply comprehensive benchmarking techniques. In his seminal book on benchmarking, Camp (1989) a former Xerox employee, described how U.S. businesses, smug in their superiority, were blindsided by the invasion into the U.S. marketplace of less expensive and often higher-quality Japanese-produced goods. Noting that Americans had no equivalent for the Japanese term dantotsu, which means striving to be the “best of the best,” Camp speculated that Americans were caught off-guard by always assuming that they were the best.

Once Xerox realized that Japanese competitors were able to sell their copiers for about what it was costing Xerox to make its copiers, they undertook a thorough examination of competitors’ processes, operation by operation. An application of the lessons learned allowed Xerox to later increase design and production efficiency, resulting in reduced manufacturing costs (Yasin, 2002). The concept soon spread to health care, human resource management, the financial service sector, telecommunications, education, and the aerospace industry (Doerfel and Ruben, 2002; Zairi, 1996). IBM, Motorola, and 3M were also early adopters of benchmarking.

Xerox also led the way in another innovative approach, termed cross-industry benchmarking. Xerox looked to L.L. Bean, a non-competitor with superior warehousing operations, to address inefficiencies in its warehousing function. Nissan/Infinity benchmarked against Disney, McDonald’s, and Nordstrom as well as Ritz-Carlton to improve their human resources and customer service (Yasin, 2002). Southwest Airlines looked to the pit crew of an Indianapolis 500 race car team, and the staff of a hospital emergency room learned how to get customer information quickly from Domino’s Pizza (Epper, 1999).

Before benchmarking, most management processes simply projected future performance from past practices, without consideration of targets or superior functional practices in outside organizations. What was innovative about benchmarking was that it established a structured process of comparison that emphasized practices over metrics (Birnbaum, 2001; Camp, 1989). That an organization might be recognized for process excellence instead of just product or service excellence was a radical concept for many businesses (Spendolini, 1992).

The Quality Movement and Benchmarking

The quality movement in the United States of the 1990s (Mouradian, 2002) ushered in a new emphasis on the use of benchmarking as a tool to gauge and improve organizational quality. Benchmarking, viewed as a process-based means to measure and enhance some aspect of an organization’s performance, is a fundamental component and tool used in varied approaches to quality enhancement (Yasin, 2002), including Total Quality Management (TQM), Continuous Quality Improvement (CQI), and the Malcolm Baldrige framework.

Total Quality Management (TQM) arose largely in the 1980s and was based greatly on the works of Deming (1986; also see Seymour, 1993). Benchmarking is often noted as a practice that grew out of the TQM movement (Achtemeier and Simpson, 2005), in part because of increased calls for accountability and performance measurement from federal and state governments. Accordingly, benchmarking processes were viewed as a means to improve performance and delivery of quality to varied “customers” (a term often spurned by those in higher education) and identifying opportunities for improvement and greater efficiency (Shafer and Coate, 1992).

The Continuous Quality Improvement (CQI) approach was derived in part from aspects of the TQM model. CQI approaches focus on organizational processes and systems and consistently improving, rather than simply maintaining organizational quality. Within CQI, benchmarking processes are used to assess current quality in an organization and to identify targets for future improvements.

Benchmarking was given a boost in 1988 when the United States Congress passed legislation to create the Malcolm Baldrige National Quality Award (named after a former Secretary of Commerce) partly as a response to the Japanese government’s establishment of the Deming Award to recognize quality in industry, but also to promote U.S. business to enhance their international competitiveness through identification of best practices and improvements in quality. The Baldrige framework set forth guidelines for organizational excellence, and incorporated the benchmarking process as an important award criterion.

In short, the Malcolm Baldrige approach is based on several criteria, or foci, used to move toward performance excellence. These criteria include leadership, strategic planning, customer focus, measurement, analysis, knowledge management (where benchmarking resides), workforce focus, and operations focus (www.nist.gov/baldrige/publications/upload/2011_2012_Education_Criteria.pdf). By the mid-1990s, benchmarking was seen as a winning business strategy, surpassing other techniques of the quality movement (e.g., TQM, CQI, and Business Process Reengineering [BPR]). Apparently, the news spread because by 1997 86 percent of companies claimed to use benchmarking in some form or another (Rigby, 1995).

Benchmarking in Higher Education

Benchmarking was optimistically greeted by higher education in the early 1990s as a positive endeavor that would help overcome resistance to change, provide a structure for external evaluation, and create new networks of communication between institutions (Alstete, 1995). Marchese (1995) included benchmarking on the list of “What’s In” in Change magazine. In 1996 the Houston-based American Productivity and Quality Center (APQC) began facilitating benchmarking studies in higher education in cooperation with the State Higher Education Executive Officers (SHEEO) and other organizations supporting higher education. At this point, benchmarking—and its focus on measuring performance—was becoming entrenched in many areas of higher education (Achtemeier and Simpson, 2005). In 2001 the University of Wisconsin–Stout became the first Malcolm Baldrige National Quality Award winner in higher education.

Over the past two decades, both the National Association of College and University Business Officers (NACUBO) and the American Council on Education (ACE) have developed awards for higher education institutions based largely on the Baldrige model. Ruben (2007), in association with NACUBO, developed a model titled “Excellence in Higher Education” that is based largely on the Baldrige criteria. More recently, the California State University system embraced this model (calstate.edu/qi/ehe/), along with dozens of individual institutions (Doerfel and Ruben, 2002).

Benchmarking activities in higher education are not limited to the United States, however. Fueled by governmental and public concerns for standards and cost-effectiveness, many nations adopted a range of approaches to higher education benchmarking. Jackson and Lund (2000) describe the substantial performance measurement and benchmarking activities undertaken in the United Kingdom since the 1980s. Similar endeavors are evident in Australia, New Zealand, Canada, Germany, and other European nations (Farquhar, 1998; Lund, 1998; Lund and Jackson, 2000; Massaro, 1998; Schreiterer, 1998). More recently, benchmarking of disciplinary learning outcomes was an integral part of the Bologna Process in an effort to create comparable and compatible quality assurance and academic degree standards across several continents (Adelman, 2009).

Despite the potential benefits, full-scale benchmarking has been undertaken by only a relatively small number of higher education institutions (in one example, Penn State undertook a comprehensive benchmarking process against other Big Ten schools; Secor, 2002). More commonly, institutions seek to improve operations more informally by identifying best practices elsewhere and then attempting to adopt those practices. Most of this activity goes unreported in the literature, and so it is impossible to determine how widespread it is.

Birnbaum (2001) asserted that what ultimately found a home in higher education was not benchmarking at all, but a “half-sibling called performance indicators and a kissing cousin called performance funding.” With the rush for greater accountability, the thoughtful processes envisioned by the concept of benchmarking were quickly replaced by a lust for quick measurement and data. As attractive as this option may be, the sole use of performance indicators ignores a basic and powerful premise of benchmarking—namely, that what is needed for improvement is to identify the processes behind the benchmarks or metrics that can lead to improved performance, subsequently demonstrated by associated benchmarks or metrics.

Types of Benchmarking. 

Like most practices, benchmarking is actually a collection of approaches and techniques that can be conceptualized as a classification scheme or a continuum of self-evaluation activities (Jackson and Lund, 2000). To begin with, benchmarking can be internally or externally focused. Internal benchmarking may be appropriate where similar operations, functions, or activities are performed within the same organization. For colleges and universities, these could be academic, administrative, or student service units and involve processes like admissions, hiring, assessment of student learning, or delivery of online instruction. Internal benchmarking may be an end in itself or the starting point for understanding processes that will be externally benchmarked. See Chapter 2 for a more detailed discussion of internal benchmarking.

External benchmarking seeks best practices outside the organization. In competitive benchmarking, the products, services, and process of an organization are compared with those of direct competitors; in comparison, functional benchmarking examines similar functions in institutions that are not direct competitors. Best-in-class or generic benchmarking seeks new and innovative practices across multiple industries to uncover the “best of the best.”

Benchmarking can also be categorized by its approach: metric, process, or diagnostic (Yarrow and Prabhu, 1999). Almost all benchmarking in higher education can be characterized as metric or performance benchmarking, which compares selected indicators or metrics among similar institutions to evaluate relative performances (Smith, Armstrong, and Brown, 1999). Metric benchmarking is limited to superficial manifestations of business practices (Doerfel and Ruben, 2002) and is restricted to those characteristics that can be quantified.

Process benchmarking, on the other hand, involves a comprehensive comparison of specific business practices with the intention of identifying those aspects of best practice that can lead to improved performance. Process benchmarking is often time consuming and expensive; few who have set out to do it have capitalized fully on its potential (Bender, 2002; Yarrow and Prabdu, 1999).

Diagnostic benchmarking explores both practice and performance, functioning as a continuous “health check” where practices that need to be changed are identified and improvement approaches are devised (Yarrow and Prabhu, 1999). Diagnostic benchmarking may have found its way into higher education via the continuous improvement processes expected by accreditors to document institutional effectiveness.

Some Applications of Benchmarking in Higher Education. 

Since the early 1990s, several large and high-profile benchmarking studies have been conducted within higher education (Jackson and Lund, 2000; Shafer and Coate, 1992). Perhaps the best-known benchmarking studies in American higher education are those conducted by NACUBO in the early 1990s (Alstete, 1995; NACUBO, 1995). The overall goals of these studies were to develop a standard set of accepted indicators and benchmarks that can be used to improve operational quality and performance, as well as relevant cost information. The initial and wide-ranging goal of the NACUBO study was to help higher education institutions identify “best practices” across varied core functional areas such as admissions, advancement/development, payroll, and so on. Groundbreaking when it was initiated, many of the data points and calculations that emerged from the NACUBO study are now routine. Moreover, some of the ideas and their financial calculations (e.g., ratios) are now included in many standard Department of Education’s National Center of Education Statistics (NCES) Integrated Postsecondary Data Analysis System (IPEDS) reports (www.nacubo.org/Research/Benchmarking_Resources/Data_Resource_Details.html).

Another classic benchmarking study in higher education is the University of Delaware’s National Study of Instructional Costs and Productivity (better known as “the Delaware Study”; www.udel.edu/IR/cost/). This study originated in the early 1990s from a need at the University of Delaware to evaluate academic programs to be curtailed during a series of difficult budget years (Middaugh, 1994), but now exists as a means for academic leaders and managers to improve program quality and efficiency. Since then, the study has evolved and grown to where it is now the definitive benchmarking study of instructional costs and productivity (Middaugh, 2001). Results provide opportunities to benchmark both internally (across colleges and departments) as well as externally (across institutions and institutional Carnegie classification).

Seybert, Weed, and Bers (2012) provide a succinct summary of other large higher education benchmarking endeavors that provide useful information for institutional researchers, including the National Community College Benchmark Project (NCCBP), the Voluntary System of Accountability (VSA; www.voluntarysystem.org), the IDEA (Individual Development and Educational Assessment) Center (www.theideacenter.org), and the many peer comparison tools available from the National Center for Education Statistics web page (nces.ed.gov). In addition, EBI (Educational Benchmarking, Inc.; www.webebi.com) also offers a variety of benchmarking endeavors covering many academic (for example, student success, first-year experience, diversity) and non-academic (for example, auxiliary services, residence hall, dining services, student unions) facets of higher education. Seybert and colleagues (2012) also provide a detailed account of the National Community College Benchmark Project (NCCP).

As Seybert and colleagues (2012) note, benchmarking has also been commonly used in survey research. There is a large range of surveys sampling student and faculty perceptions of a variety of items within higher education that provide benchmarking opportunities. Some of the largest of these include the National Survey of Student Engagement (NSSE) and its many offshoots (for example, Faculty Survey of Student Engagement [FSSE], Beginning College Survey of Student Engagement [BCSSE], Community College Survey of Student Engagement [CCSSE]; see nsse.iub.edu/, and ACT’s many student surveys [www.act.org/highered]).

Barriers to Benchmarking in Higher Education. 

Whereas benchmarking has become a staple tool for process improvement in business and industry (Southard and Parente, 2007; Stapenhurst, 2009), examples of full-scale benchmarking in higher education are scarce in the literature. It is not hard to identify reasons why benchmarking has failed to gain traction in higher education.