Benchmarking is a process by which many aspects of an educational program can be compared between similar institutions. Although this term arises from the practice of cobblers (see Box 21.2), the definition of benchmarking that is more familiar today was developed in the early 1980s at the Xerox Corporation in response to increased competition and a rapidly declining market (Camp, 1989). Universities adopted benchmarking to improve administrative processes and instructional models through comparison with peer institutions (Chaffee and Sherr, 1992; Clark, 1993) as part of an ongoing and systematic process of improvement (Kempner, 1993). Benchmarking has become an important driver of continuous improvement in universities across the western world, and is now firmly on the agenda for veterinary education (AAVMC, 2011, recommendation 6.2).

A review of the benchmarking literature shows that there are four kinds of benchmarking: internal, competitive, industry, and best in class. Internal benchmarking can occur at large, decentralized institutions where there are several organizational units that conduct similar processes. Competitive benchmarking analyzes processes against peer institutions that are competing in similar markets. Industry benchmarking extends competitive benchmarking to a larger, broadly defined group of competitors (Rush, 1994). Best-in-class benchmarking uses the broadest application of data collection from different industries to find the best practices available (e.g., for delivery of information technology support). The selection of benchmarking type depends on the desired outcomes, the process(es) being analyzed, and the availability of data and expertise at the institution. (It should be noted throughout this chapter that we consider institutions, higher education institutions, universities, and organizations as interchangeable terms in describing the parent entity and as reflecting the wide scope and applicability of benchmarking.) The increase in all types of university benchmarking in the past two decades has been made possible by the exponential increase in data collection and management within universities.

Benchmarks and standards are commonly understood terms with a particular meaning in higher education (Judd and Keith, 2012; Judd, Pondish, and Secolsky, 2013). A benchmark is used to measure performance against a specific indicator of outcomes (e.g., staff–student ratios, minority student attrition, graduate employment rates), providing a metric of institutional achievement of its mission. A broad definition (Wikipedia, 2016) suggests that businesses benchmark by comparing their processes and performance measures with similar companies, with an objective to improve specific productivity metrics, such as quality, time, and profit margin. Strategic management initiatives can then be instituted to improve performance and productivity against benchmarks.

In contrast, a standard is a predetermined minimum level of acceptable performance (Judd, Pondish, and Secolsky, 2013). A standard is based on judgment and experience, yet can be validated by external experts, including accreditation agencies (Judd and Keith, 2012). In universities, student success is determined once individual standards are met or exceeded (e.g., “Day One” veterinary surgical competencies), while the percentage of successful students in each cohort could be a criterion by which institutions benchmark performance. Veterinary accreditation bodies, such as the American Veterinary Medical Association (AVMA, 2016) and the Royal College of Veterinary Surgeons (RCVS, 2016), seek evidence that the curriculum equips students with entry-level professional competence, and that all graduates achieve the required standard (Yorke, 1999). The standards-based comparisons used in accreditation have attracted criticism for stifling innovation in veterinary education (Eyre, 2011). In contrast, lenient interpretations of the AVMA Council on Education (COE) standards for veterinary clinical education and research, and the lack of a learning environment focused on high-quality contemporary science in teaching and research, are key criticisms leveled at new distributed models, which some commentators believe to threaten veterinary educational outcomes (Marshak, 2011). The peak international veterinary education accreditation bodies have increased their role in defining standards over the past two decades, and commenced a voluntary process of international harmonization of standards and processes, with a high level of agreement in the Day One skills joint accreditation site visits from 2010, and an international standards rubric adopted in 2014 (Massey University, n.d.). However, accreditation does not compare institutional performance, therefore there is a place for systematic competitor benchmarking to drive continuous improvement in veterinary education.

University rankings are now influential proxy measures of quality, driving the choices of potential students and employers, and influencing government and university priorities. The first subject-specific global ranking for veterinary schools, the QS World University Ranking (QS, 2015a), was released in 2015. University rankings emphasize research metrics (i.e., citation impact of publications, grant income) and prestige (e.g., number of Nobel laureates), with little bearing on education quality. The most respected include Shanghai Jiao Tong University Academic Ranking of World Universities (ARWU, 2016), The Times Higher Education (2016) World University Rankings, and the National Taiwan University Ranking (NTU Ranking, 2016). The QS World University Ranking balances citation impact and productivity with a broader emphasis on graduate outcomes and reputation with employers and peers. The first QS veterinary school ranking reported a spread of top 50 performance across the United Kingdom, United States, Canada, Australia, New Zealand, and Europe, with all top 20 schools accredited by RCVS, AVMA, Australasian Veterinary Boards Council (AVBC, 2016), European Association of Establishments for Veterinary Education (EAEVE, 2016), or multiple bodies (QS, 2015b). Benchmarking is a more powerful tool than the pursuit of rankings for improving veterinary education, because it drives a proactive, constructive focus on achieving the best performance appropriate to the mission of the university (Marmolejo, 2016).

Improved research performance has been fostered in the United Kingdom (the Research Assessment Exercise, now the Research Excellence Framework) and Australia (Excellence in Research Australia, ERA; Australian Research Council, 2016) through government benchmarking, with rewards for top-performing disciplinary groups. Benchmarking activities across all areas of university operations are undertaken by members of elite research universities, such the Group of Eight in Australia, the American Public Land-Grant Universities, and the Russell International Excellence Group in the United Kingdom (Russell Group, 2016). Leading institutions foster a culture of “research-led” teaching, seeking to ensure that students realize benefits from engagement with research and leading researcher groups. However, the relationship between quality teaching and research, while often promoted, is not direct and requires institutional strategies to be effective (Schapper and Mayson, 2010). Student and employer stakeholders in veterinary education place the greatest emphasis on professional competence and perceive less relevance in research. Top veterinary schools have responded to the rewards for research productivity and quality in the United Kingdom (HEFCE, 1997) and Australia, and to international rankings, with capacity-building investments in facilities, staff, and programs. This shift in focus and resources could threaten high-cost disciplines such as veterinary science, and limit the capacity of veterinary educators to improve continuously on educational outcomes (Camp, 1989).

This chapter will describe the process of benchmarking and what factors should be considered prior to undertaking a benchmarking exercise in veterinary education, with a focus on curriculum, learning, and student outcomes. Models of benchmarking for quality learning and student outcomes are used to illustrate the processes and procedures required, the tools and support available, examples of their use, and the ways in which benchmarking findings can best drive reflection and improvement.

Despite the majority of positive recommendations for using benchmarking and successful examples of its current use, there are critics of its applicability to higher education. There is an opportunity cost in time and resources. Critics argue that it marginally improves existing processes, is applicable only to administrative processes, is a euphemism for copying and stifles innovation, and can expose institutional weaknesses (Brigham, 1995; Dale, 1995). These concerns are largely unfounded, because benchmarking can radically change processes (if warranted), apply to both administration and teaching, and adapt not “adopt” best practices; furthermore, if a benchmarking code of conduct is followed, confidentiality concerns can be reduced. The American Productivity and Quality Center Code of Conduct (APQC, 2016a) calls for benchmarking practitioners to abide by stated principles of legality, exchange, and confidentiality.

Collaborative benchmarking commences with agreement on what to benchmark and which processes to adopt. It starts with the end in mind: the common goals of university education for the veterinary profession. These are defined in each school’s statements of the intended knowledge, skills, and attitudes of graduating veterinarians, known as program learning outcomes (Biggs and Tang, 2011). They are designed to address the accreditation curriculum standards, and the national and international competencies – for example, NAVMEC (2011) and the OIE (2012) Core Curriculum and “‘Day One Graduates” Competencies – situated within the context and mission of the individual institution. Review of curriculum maps reveals the underpinning design and instruction methods used to achieve the intended learning outcomes. Curriculum structure is central to education quality, because comprehensive, effective development of program learning outcomes is essential in professional disciplines like veterinary science. Employers expect that all graduates will be competent in solving veterinary problems through the application of scientific knowledge, technical skills, and professional behaviors (McNally, 1999; Heath and Mills, 2000).

Benchmarking of achievement in the complex, scientifically dense veterinary curriculum is a challenge, particularly in professional, ethical, humanistic domains. The danger is to concentrate on aspects amenable to measurement, neglecting those that are hard to evaluate reliably, despite their importance for professional success. Examples of successful curriculum benchmarking and development projects in Australia and New Zealand have engaged all disciplinary leaders in animal welfare, pharmacology (Office for Learning and Teaching, 2013a), and communication (Office for Learning and Teaching, 2013b), as a group, to review and develop best practice curriculum resources (e.g., veterinary pharmacology, “one welfare”) collaboratively. Veterinary accreditation has increased the requirements for comprehensive assessment of students’ application and integration of knowledge, skill, and behavior through direct observation measures, particularly in clinical disciplines, for instance objective structured clinical examinations (OSCE; Wikipedia, 2016b), direct observation of procedural skills (DOPS; RCPCH, 2016) or mini clinical examples (mCEX; Baillie and Rhind, 2008).

When looking specifically at the curriculum, there are several approaches that may be used to benchmark. Specifically, standards-based benchmarking seeks to determine how good student performance needs to be to meet the learning outcomes (see Stake, 2004). To answer how much is good enough requires that a point on the skill or ability continuum is determined that represents proficient attainment for students or graduates for QA (e.g., the COMPASS tool, which benchmarks speech pathology skills, reported by McAllister et al., 2011). For intra-institutional benchmarking of student learning outcomes, defining such a benchmark requires some form of standard-setting. The field of standard-setting in educational measurement is based on judgment and in some rare instances can be empirical, employing different methodologies to accomplish this purpose (see Pitoniak and Morgan, 2012). It should also be noted that accreditation bodies are increasingly setting the skills that students must attain before graduation (Day- One Competencies) and defining the level of competence required for graduation (UGC, n.d.).

A second type of curriculum benchmarking establishes a criterion of performance growth or progress over time using baselines (ASQ, 2011). A third type of curriculum benchmarking can assess indirect measures of student learning, such as the National Survey of Student Engagement (NSSE, 2016). The relationships identified between students’ experience of learning and the quality of their learning are important to recognize, because engagement is vital if students are to transform their knowledge and understanding during their studies. As a consequence, student engagement is an important leading measure in predicting the future impact of curricula and teaching on student achievement.

Standards of veterinary training are monitored in Australia and New Zealand by the veterinary registration bodies that oversee accreditation (AVBC, 2016). There is a national standard, the Australasian veterinary graduate attributes (GA), on which each institution bases its program learning outcomes, and these reference RCVS and OIE Day One skills. Prior to the AVMA’s introduction of outcomes assessment (Simmons, 2004), accreditation visits had a focus on inputs, including teaching hours, curriculum structure, facilities, access to animals, and caseload for practical experience. Accreditation has shifted to the evaluation of program, student, and institutional outcomes, although the requirement to report on inputs continues for AVBC/RCVS. Effective outcomes assessment requires evidence of review, which can take the form of benchmarking and then effective action to address identified deficits, with ongoing monitoring. Accreditors now seek evidence of graduate “fitness for purpose,” including indicators of employment, career impact, and professional retention. An International Accreditation Working Group was formed to harmonize standards and support the demand for “global” accreditation visits of RCVS, AVBC, AVMA, and EAVE, and it developed a rubric for site visit assessments.

There are a number of resources available to support and/or undertake benchmarking, many of which are online. The American Productivity and Quality Center benchmarking user’s guides are available via an online portal (APQC, 2016b), although this is more targeted at business than educational institutions. Benchmarking tools were designed by the US National Association of College and University Business Office (NACUBO, 2016) for educational institutions (Kempner, 1993). Benchmarking can also be performed independently by an external service provider, such as the European Association for International Education (EAIE, 2014). Subject external examiners with internationally recognized expertise review courses and moderate assessment within their field, following a set of guidelines at University College Dublin (UCD, n.d.). This is a form of direct outcomes assessment, sought by professional accreditation bodies, which will also identify areas requiring improvement compared to external benchmarks.