Designing Performance Management Systems in
Academic Institutions:
a Dynamic Performance Management View
Abstract
This paper illustrates how to design and implement performance management systems in
universities by identifying and modeling those factors impacting on academic performance
through a dynamic performance management view. Particularly, combining performance
management with System Dynamics modeling may allow academic decision-makers to better
identify key-performance drivers for pursuing a sustainable performance improvement in
universities. In the second section of the paper, a number of examples based on empirical
findings from a field project aimed at designing a dynamic performance management model for
the University of Palermo are discussed.
Key-words: Academic institutions, performance measurement and management systems,
accountability, dynamic performance management view, field project.
1. Introduction
In the past two decades the Italian academic system has been affected by a number of
law reforms, aiming at fostering an improvement of University performance, through
the introduction of a set of parameters, based on which public funds are allocated.
Such policy has only partially achieved successful results. In fact, several problems
have arisen because of the introduction of performance standards by the Italian Ministry
of Research. Among such problems, there are: a “means-ends inversion” and a bounded
attention of policy-makers in both time and space.
Improving performance management and accountability in academic institutions
implies the understanding of a more complex system than a simplistic set of parameters
used for the allocation of Ministerial funds. Such system should, rather, embody the
organizational structure and processes, and encompass the interactions of the University
actors with several stakeholders in the external environment. Namely, key-performance
indicators and corresponding drivers, as well as strategic resources affecting them must
be properly tracked and managed by decision-makers. Furthermore, delays and nonlinearities often significantly affect the accumulation and depletion of strategic
resources, and the associated performance drivers and end-results.
Such dynamic complex context requires that proper “lenses” are adopted to manage
performance and foster accountability from inside the institution, first of all. The
emphasis on a performance management approach, focused on the characteristics of the
organizational system, requires that controllers and organization designers in Academic
institutions produce an effort to understand problems/issues and opportunities that
mostly characterize their own organization, rather than only applying external schemas
designed by a Ministerial institution.
Based on the described conceptual framework, the aim of this paper is to illustrate
how to design and implement performance measurement/management systems in
universities by identifying and modeling those factors impacting on academic
performance through a dynamic performance management view. Namely, combining
performance management with System Dynamics modeling allows academic decisionmakers to better identify key-performance drivers for pursuing a sustainable
performance improvement in universities.
The second section of the paper is devoted to discuss a number of examples based on
empirical findings from a field project aimed at designing a dynamic performance
management model for the University of Palermo.
2. Research background
Academic institutions have recently been affected by significant reforms aimed to
improve their own performance levels. The reason for these reforms has been inspired
by various factors, such as budgetary restrictions imposed by national Governments and
the “marketization” of the Higher Education sector (Clark, 1998; Deem, 1998).
Regarding this, the ordinary funding allocation carried out by the National
Governments is strictly dependent on the performance that each academic institution
achieves. Particularly, academic performance is assessed by the Ministry of Education
on the basis of specific criteria and parameters which, above all, tend to measure
intangible outputs and outcomes, such as quality in education and research activities,
efficiency, effectiveness, internationalization and impact on the community.
This has led universities to increase their autonomy and accountability to
successfully perform and compete in a worldwide competitive system. Both autonomy
2
and accountability have involved greater emphasis on performance measurement and
management (Lapsley & Miller, 2004).
On this concern, an important factor to sustain performance improvement and
accountability processes in universities can be recognized in their own Planning and
Control (P&C) systems. In order to support an academic performance improvement
according to a sustainable P&C perspective, it appears necessary to design strategic
P&C systems capable in enabling decision-makers to successfully steer universities
towards their goals achievement (Salter & Tapper, 2002; Broadbent, 2007). As
suggested by Otley (1999), P&C systems provide information that is intended to be
useful to managers in performing their jobs and to assist organizations in developing
and maintaining viable patterns of behavior.
In this perspective, a pilot project aimed to outline factors impacting on
organizational performance and to model them through a dynamic performance
management view, has been started in collaboration to the Rectorate and the CEO office
board of the University of Palermo (Italy).
The aim of this paper is to show the conceptual framework behind this project and
to discuss its first empirical findings. Particularly, the paper aims to demonstrate how
tracking the feedback relationships between end-results, performance drivers and
strategic assets in an academic institution, can significantly improve the ability of its
decision-makers to manage and measure organizational performance.
In addition, identifying administrative products, mapping the underlying processes
and matching them to key-responsibility areas is a major component for developing a
System Dynamics (SD) model-based performance management approach. SD models
may support decision-makers in identifying those policy levers on which to act to
undertake sustainable performance improvement programs in universities.
Developing SD models also supports decision-makers in Academic Institutions to
better recognizing and measuring key-performance indicators and the factors impacting
on them. Simulation also supports one in distinguishing possible trade-offs between
short- and long-term expected outcomes from adopted policies and underlies a feedback
structure to monitor the causes of actual results.
3
3. On the causes and implications of the latest academic reforms in Italy
Over the last ten years, the Italian academic system has undergone a series of reforms
which have deeply changed the way of running public universities.
The causes underlying such reforms are essentially due to two macro phenomena
which have highlighted the unsustainability of an outdated system:
–
the economic crunch that Governments have faced for some time;
–
the competitiveness – at both national and international level – of the Higher
Education sector, which found Italian universities unprepared.
As for the first phenomenon, the economic crunch has pushed Governments to
improve investment allocation towards all public sectors (e.g., education, healthcare,
infrastructures). This has involved a significant cut in financial resource transfers from
central bodies to local authorities and has also delayed the enforcement of national
development plans. The critical state of public finance has speeded up the
implementation of reform processes. On this concern, given the increasing tightening of
public funds, the reform has aimed at allocating public funds according to a
performance-based ranking among institutions operating in the same sector. Such a
mechanism – which aims to increase public organizations’ performance – has thus
implied a rise of competitiveness among universities at national level: universities have
now to focus on performance management in order to improve both quality of
products/services
supplied
to
customers
and
expenditures
rationalization
(Saravanamuthu & Tinker, 2002; Adler and Harzing, 2008; Marginson & van der
Wende, 2009).
As for the second phenomenon, the growing competition among universities has
determined a “marketization” of the Higher Education and, as a result, universities are
now seen as “business-focused organizations”. To Amaral & Magalhães (2002: p. 6)
“education is no longer seen as a social right; it has become a service”. Students started
to be seen as customers or clients and universities viewed as service providers, that want
to meet their client’s needs and expectations (Meek, 2003). As far as the subject of
university “marketization” is concerned, the metaphor of the “Ivory Tower” by Powell
& Owen-Smith (1998) appears meaningful: according to such metaphor, as universities
are gradually identified with commercial richness, they also lose their uniqueness in the
4
society. Universities are any longer seen as the “ivory towers” of intellectual activities
and truth thoughts, but rather as enterprises run by arrogant people aiming at capturing
as more money and social influence as possible. In such a context, the poor
competitiveness of most Italian universities has clearly come out, particularly in
comparison to other Countries’ best practices (e.g., USA). Actually, the rapid
development of a Higher Education “market” has pointed out several critical issues
related to managing academic institutions which, in most cases, were unprepared for the
challenges introduced by a competitive environment (Neely, 1999; De Boer &
Goedegebuure, 2001). Such phenomenon tackles an improvement in reputation which
may bring new investments for both research and educational activities: concerning this,
the past substantial investments of public resources towards the Higher Education sector
have not resulted in an equivalent quality of research and teaching (Bleiklie, 2001).
Furthermore,
the
competitiveness
of
the
academic
system
reflects
the
competitiveness of its country. In fact, by focusing efforts on the interaction between
research, education and professional training, a national economic system may refine
those assets and strengths allowing different “production systems” to compete with their
rival economies. In this respect, innovation, technology and professional competences
are unanimously considered as the only driving forces capable to face global challenges
in the long-term, specifically in those well-developed economies where competition is
no more based on the cost of inputs or on economies of scale (Czarniawska & Genell,
2002).
Therefore, innovative changes within the Italian academic system are leading
university management bodies to discuss their current and outdated managing systems
in order to ensure a successful survival throughout time.
4. Italian university public financing: the performance-based funding system
In Italy, the law concerning Italian university public financing has changed over the last
twenty years and, as a result, has strongly modified university management 1. Actually,
following Great Britain pilot scheme, a number of changes have taken place all over
Europe trying to harmonize the different academic systems in order to face education
1
Law 537/1993; Law 244/2007; Law 133/2008; Law 240/2010.
5
globalization challenges based on both higher competitiveness and customer satisfaction
orientation (Jongbloed & Vossensteyn, 2001; Dill & Soo, 2005).
In particular, the measures adopted in Italy have been oriented to a decentralization
of power from the Ministry of Education to universities, by (1) enlarging their financial
and management/organization autonomy, (2) promoting accountability in internal and
external communication processes, and (3) making decision-makers aware of their
responsibilities along the hierarchical scale. Both autonomy and accountability have
involved greater emphasis on the design of performance measurement and management
systems in universities. Therefore, autonomy and performance measurement have been
introduced as complementary aspects on which a total changing process is based.
Namely, the increase in autonomy has involved a major overhaul of public
university funding system. Public funding (i.e., transfers from the Ministry of
Education) represents the most important source of financing for Italian universities. On
this regard, reforms have aimed to link the financial resource allocation system to the
performance measurement of each university in order to reward those institutions
resulting “virtuous”, by allocating a higher amount of public funds.
In the past, the public financing system provided resources to universities to
accomplish a widespread “Welfare State” task oriented to ensure a satisfying and
homogeneous performance level in educational activities. Such financing system was
independent from efficiency, effectiveness and quality levels reached by academic
institutions in providing educational services and research outputs towards end-users.
Nowadays, Italian universities operate in a new context characterized by a strong
competitiveness as a result of the new public financing system that allocates resources
on the basis of a performance-based ranking: in other words, the performance of each
university is yearly assessed by the Ministry of Education which, subsequently,
distributes the largest part of public funds to top ranked universities. Such mechanism is
based on a meritocratic principle of resource allocation and, at the same time, its
application encourages a performance alignment among all national academic
institutions in terms of education quality, research output and management efficiency
(Agasisti & Catalano, 2007; Bolognani & Catalano, 2007).
6
Therefore, the academic competitiveness is based on the performance level that each
university is able to reach and on the resulting capability to obtain more funds (the socalled performance-based funding system). This means that the adoption of a rewarding
system aims at putting in competition public universities to achieve not only financial
resources, but above all increasing performance levels which may improve educational
services towards citizens (Keenoy & Reed, 2008).
Particularly, the academic performance is measured by the Ministry of Education
through a set of indicators which takes into account not only research and education
activities, but also other critical issues, e.g., the level of internationalization, the ability
to manage strategic resources, the capability to be funded by external financing bodies
and sponsors.
4.1 Critical issues on the ministerial performance-based funding system: the need
for implementing sustainable development-oriented indicators
In Italy, university performance indicators adopted by an external evaluator and funder,
like the Ministry of Education, are based on “macro” measures. They provide limited
information which make highly ambiguous and partial any effort aimed to understand
and diagnose academic performance. In fact, the Ministry of Education essentially
focuses individual financial measures and other isolated statistical data, as surrogates of
“good performance”, with a aim to generate incentives and competition for funding
among universities. For instance, one of the indicators to measure teaching quality
refers to the credits gained by students because of the exams sustained within their own
curriculum of study. However, an unintended result related to the use of only this
measure, as an indicator of “good performance” in teaching, is that – in order to get
more funds - universities may adopt loose students’ evaluation schemes. Though in the
short-term this policy might work, in terms of higher cash flows, in the long run it might
compromise both educational quality and university reputation2.
2
Other examples of ministerial indicators are: the number of graduates with regular curricula length, the
amount of funding from external financing bodies, the average number of fellowships per doctorate
programme, the fraction of fellowships externally-funded for doctorate programmes, the ratio between the
working graduates after a year from their degree achievement and the total number of graduates in the
same year, the number of credits earned during non-academic activities, the percentage of foreign
students enrolled in degree courses, the percentage of foreign students enrolled in doctorate programmes.
7
Ministerial parameters are mainly focused on output, rather than outcome measures
(Ammons, 2001: p. 12-14) and related processes. Such myopic and bounded view may
result into a simplistic performance assessment, that may lead to distorted or wrong
short-term evaluations, if observed under a perspective of university sustainable
development 3.
Potential risks of inconsistency in ministerial assessment may regard the following
issues (Cosenz, 2011):
–
allocating more funds to universities that have shown a better performance is likely
to weaken the competitiveness of other universities. As a consequence, it may
enlarge the imbalance in the quality of the academic activities carried out by the
latter in comparison to the former. Though this rule can be acceptable as a principle
to encourage good performance, it might be questioned if one considers that
“knowledge” is a public good;
–
the outcome indicators, used by the Ministry of Education to measure the ratio
between the quality of training and the employment rate of graduates from each
university, do not take into account the features of the geographical areas where
universities are located and this may involve a socio-economic imbalance in the
development of regions;
–
the ministerial effort to increase competitiveness in the academic sector and to lead
Italian universities towards higher performance levels in education and research,
should be accompanied by a parallel action aimed to promote the streamlining of
both bureaucratic procedures and supporting activities carried out by back-office
units;
–
the ministerial performance measurement system mainly focuses on the short-term
and, therefore, it may not be consistent with broader goals of university sustainable
development.
Even though the above issues reveal a limited and incomplete assessment
framework of academic performance, the design of performance measurement systems
For instance, focusing efforts on the search of high-volume and value funding of research projects
from external institutions in the short-term – regardless the strategic relevance for future research
of the findings emerging from such projects – could jeopardize the allocation of resources to more
long-term innovative projects.
3
8
cannot overlook ministerial guidelines and criteria. In fact, excluding ministerial
parameters from the set of performance measures adopted by universities runs the risk
of diverting academic decision-makers’ attention on those measures leading to stable or
increasing funding from the State.
However, a “sustainable development”-oriented performance measurement system
should also include a wider range of indicators – in respect to the restricted range of
ministerial parameters – based on which decision-makers may evaluate the progress
resulting from the adoption of a given strategy or emerging problems that require proper
analysis/diagnosis and reaction. This means that universities need a systemic and
selective approach in identifying a balanced mix of indicators to support strategy
design/implementation and performance management (Boland & Fowler, 2000).
For instance, indicators that universities should set in order to affect their decisionmakers’ behavior towards competitiveness can refer to:
–
quality of education, research, management and supporting activities (Dearlove,
1998). On the one hand quality has to be measured by comparing the delivered
“product/service” to end-users’ expectations (e.g., availability and professionalism
of front-office workers, exhaustiveness of teaching contents, relevance of
publications, size of classrooms). On the other hand, quality has to be assessed by
considering the efficiency level reached in administrative processes (e.g., mistakes
in handling workload, waste of consumption materials, equipment breakdowns);
–
time, referred to both end-users’ expectations on academic service provision (e.g.,
average waiting time in university administrative offices, delays in class scheduling,
delays in updating curricula) and to production processes related to the efficiency
level (e.g., time to complete administrative procedures, waiting time for payments
and reimbursement, wages payment delays);
–
productivity, considered as the ratio between achieved outputs or outcomes and
resource consumption (e.g., the average number of publications per single
researcher or department);
–
flexibility, which represents the organization ability to timely adapt to external
changes with a minimum waste of resources (e.g., average time to implement new
administrative procedures, study programs and syllabus, assessment systems).
9
Designing a performance measurement system entails not only a nominal definition
of expected results, but also their measurement, through proper indicators. A
performance measurement system may represent a fundamental tool to support
decision-makers in university management (Neely et al., 2004). It also acts as a
coordinating mechanism, supporting organizational units to better interact with other
units located on both lower hierarchical levels and on a same level.
Therefore, performance measurement is an integral part of a wider strategic
management activity aimed at reaching a sustainable development in the academic
service delivery (what) and its underlying processes (how). High-quality academic
performance and sustainable development cannot be only conceived as the outcome of
legislative reforms. Rather, their achievement depends on the use on a regular basis of
strategic performance management tools tailored to the needs of academic institutions
and to their organizational critical factors. This means that performance assessment
must be oriented to support an enhancement of those critical success factors creating
value in academic activities (Van de Walle & Van Dooren, 2010).
5. Designing academic performance management systems: from a financial
equilibrium to a value creation perspective
As a consequence of the described changes, new performance management models are
needed (Miller, 2007; Parker, 2002, 2011).
A prevailing view of managerial performance has traditionally been focused on the
financial balance between expenditures and collections with the goal to pursue a
financial equilibrium (Fitzgerald, 2007; Sporn, 2003; Modell, 2001; Pendlbury &
Algaber, 1997). However, such a perspective today seems to be too bounded. In fact,
though financial equilibrium is a fundamental principle to observe in any organization,
evaluating performance requires a focus on also other perspectives related to the quality
of programs and the outcomes from undertaken policies (Chenhall & Langfield-Smith,
2007). Therefore, not only financial balance, but also value creation (Moore, 1995) for a
wide range of stakeholders should be the building block for a sustainable university
organizational model (Guthrie & Neumann, 2007; Parmenter, 2007; Cave et al., 1997).
In academic institutions, value creation processes encompass several organizational
units interacting to deliver “products/services” to external clients (e.g., students,
10
enterprises, scientific community). Such units cannot be identified only in relation to the
front-office and peripheral levels. They are rather related to back-office and central
levels too. A lack of coordination between different units involved in the delivery of
“products/services” may substantially limit the capability of an organization to generate
value. This is particularly crucial for universities (Weick, 1976; Reponen, 1999). Here,
a potential risk of structural dualism can affect the physiological interaction between
Rectorate/Central offices and Schools/Research departments.
In order to overcome such risk, proper efforts should be made on different
organizational levers, to foster coordination. Relevant means to pursue such goal can be
related to organizational design (e.g., in term of organizational structure and
coordinating mechanisms) and performance management systems. Regarding this,
setting performance measures to drive the behavior of central and back-office units
towards the desired outcomes, plays a key role. This is not an easy task, since it implies
an understanding of the critical processes generating value in delivering such services.
Therefore, a focus on only front-office units to measure performance in satisfying
“customer” needs, often based on only surveys, is a too bounded approach (Bianchi,
2010; Broadbent, 2007; Propper & Wilson, 2003).
In order to set performance measures fostering the generation of value, according to
an outcome and sustainable development perspective in academic institutions, critical
factors to focus are (Bianchi, 2009a; Bianchi, 2010):
–
“products/services”, “clients” (i.e. users) and the underling administrative processes
leading to such services;
–
the end-results measuring final targets, and corresponding performance drivers, to
promptly detect and affect the symptoms of change in performance. Such indicators
should provide a basis to settle proper incentive mechanisms, driving managers’
efforts towards desired outcomes;
–
both responsibility areas and policy levers to affect results.
In this respect, a sustainable academic service delivery system should primarily take
into account:
(1) how a given set of “products/services” is delivered;
11
(2) who is accountable for the achievement of results directly and indirectly associated
to the provision of “products/services”;
(3) where and when to intervene through proper corrective actions to bring back
universities towards pre-set goals achievement.
In the next sections of this paper, an analysis of the above critical factors will be
developed.
5.1 Mapping the value chain of academic service supply
Regarding university management, the identification of “products/services” and
“clients” provides an important key to outline an approach aimed to affect academic
performance according to a value creation perspective4. An administrative “product”
may take a different connotation as a function of the “client” to whom it is delivered
(Pitman, 2000). In fact, if we focus on an external client (i.e., on those
people/institutions/stakeholders operating outside the university), then it is possible to
identify a final “product” or, more frequently, a package of final products that is
demanded. For instance, a bachelor degree is a final product, whose logical premise for
a student (seen as a “client”) is linked to the provision of a package of final products
which are logically and sequentially related each other5.
In order to supply a final product to an external client, back-office units are expected
to deliver a set of “instrumental” products to their internal clients. Internal clients are
those back-office units which receive from the units operating backwards in the value
chain leading to the final product, those products/services that will be further processed
by them to make progress in the supply of services to an external client.
Therefore, performance in delivering an “instrumental” product affects the
performance of the internal “client” receiving such product. This, in turn, influences the
It is worth remarking that, if one refers to academic services, by “product” it is possible to mean a result
generated by the fulfilment of a process or a combination of processes, in favour of a given “client”. By
“client” we mean, instead, an entity (either an individual, or group of people, or a front/back-office
organizational unit, or other institutions) who benefits from a given “product” delivered by administrative
processes.
5
For instance, the issue of an identification code and its related certificate; the issue of a certificate of
enrolment to a new academic year or of the approved syllabus; the transcript of records; the provision of
internships.
4
12
performance of the other internal “clients” who are sequentially located along the
academic value chain leading to the delivery of the “final” product.
Competitive advantage, as well as end-users’ satisfaction, mostly depend on both
quality and efficiency resulting from the development of “instrumental” products.
Figure 1 displays the logical relation between “administrative” products, as
described so far.
INSTRUMENTAL PRODUCTS
Internal client
(back-office)
External client
FINAL PRODUCT
Fig. 1 – Logical hierarchies among different administrative “products” referred to
“clients”.
Based on the discussed framework, figure 2 shows that, if one refers to a given
“final” product, it is possible to identify a system of products resulting from the
fulfillment of administrative processes by each organizational unit whose only “clients”
are internal in a given university. Such a top-down approach (which gradually moves
from synthesis to analysis)6, implies a more selective search of relevant data to track
academic performance. Moving backwards in such analysis, i.e. from final to
instrumental “products”, allows academic decision-makers to: (1) frame the
performance management cycle leading to “final” products, (2) make performance
drivers explicit and (3) promptly change policies to drive a university towards
sustainable development.
6
A top-down approach contrasts with a bottom-up approach which, starting from analytical elements,
moves towards synthesis. This latter emphasizes the use of statistical methods designed to collect data
and information which, starting from the analysis of different organizational units performance, are meant
to reach an overall measurement system able to express the university global performance. Nevertheless,
such data acquisition would lead to a random collection of information characterized by a lack of both
selectivity and systemic perspective on performance achievement processes. Consequently, such
approach may limit academic decision-makers in steering universities according to a sustainable
development perspective.
13
UNIVERSITY
ORGANIZATIONAL
UNIT A
Administrative
products
ORGANIZATIONAL
UNIT B
ORGANIZATIONAL
UNIT C
Internal client
Internal client
External client
Administrative
products
Administrative
products
Final product
Fig. 2 – The identification of “clients” and “products” within the academic value chain.
For instance, the ‘Undergraduate Students Prospectus’ is a final product that a
university delivers to its potential enrolling students (i.e., external clients) as a result of
administrative steps underlying critical factors impacting on university outcomes. Such
critical factors can be identified in relation to internal clients and corresponding
“instrumental” products, as well as to the processes carried out by back-office units
located along the value chain. If we consider instrumental products in a chronological
sequence, we may identify the following: course syllabus outline delivered by
Departments to Faculty Boards; study programs delivered by Faculty Boards to the
Academic Senate; curriculum proposal approved by the Academic Senate and sent to
the “Education” central unit; ‘Undergraduate Students Prospectus’ duly recorded and
delivered by the “Education” central unit to potential enrolling students.
For each administrative “product” delivered to external and internal “clients”, the
identification of factors impacting on related academic performance requires a mapping
effort concerning:
(1) underlying processes and activities;
(2) involved responsibility areas;
(3) related available policy levers, and allocated resources;
(4) performance indicators (fig. 3).
14
STRATEGIC
RESOURCES
External client
ACTIVITIES
UNIVERSITY
RESPONSIBILITY
AREAS
PROCESSES
-Education;
-Research;
-Administrative back-office;
-Supporting activities.
ADMINISTRATIVE
PRODUCTS
Internal client
PERFORMANCE
INDICATORS
Fig. 3 – A framework to link university back-office and central units to front-office and
peripheral units in the delivery of “products/services”, according to a value generation
perspective.
5.2 A three-dimensional perspective to frame performance in academic institutions
A three dimensional framework can be adopted in order to operationalize the previous
analysis. Three inter-connected views are relevant to manage academic performance
(Bianchi, 2009b; 2012); they are:
(1) an “objective” view;
(2) an “instrumental” view;
(3) a “subjective” view.
The “objective” view implies that products generated by the fulfillment of
administrative processes are made explicit. As previously remarked, such an approach
requires that a backwards analysis, aimed at identifying final/instrumental products and
related external/internal clients, is adopted.
The “instrumental” view allows decision-makers to identify end-results and
performance drivers. Related to them, it also supports decision makers to understand
how strategic resources allocation may affect performance. It also explores how
strategic resources are in turn influenced (i.e. increased or depleted) by end-results.
Particularly, this perspective aims at defining a set of measures with regard to both
performance drivers and end-results. Possible examples of performance drivers related
to the management of academic institutions can be those which measure the promptness
in updating curricula, the effectiveness of academic equipment (e.g. number of
breakdowns) or the employees’ satisfaction. In order to affect such drivers, each
15
responsibility unit is expected to build up, preserve and deploy a proper endowment of
strategic resources (Ewell, 1999).
The “subjective” view provides a synthesis of the previous two perspectives, since it
makes explicit – as a function of pursued results – processes and activities to be
undertaken, together with related objectives and performance targets to be included in
the budgets of each organizational unit. This view requires that performance measures
associated to academic services delivery are made explicit, and then linked to the goals
and objectives set by decision-makers operating in different organizational units.
The following figure provides a synthesis of the three dimensions of performance
management as above described.
Strategic resources
Activities
Performance
drivers
Processes
End-results
Objective dimension
Instrumental dimension
Objectives
Subjective dimension
Products
Internal client
External client
Fig. 4 – Three views for designing a performance management system in academic
institutions.
6. Designing a system for academic performance measurement: empirical results
emerging from a pilot project in the University of Palermo
The University of Palermo (UNIPA), Italy – established in 1805 – is made up of twelve
faculties, operating in Western Sicily also through the branches located in Trapani,
Caltanissetta and Agrigento. Since 2008, UNIPA has started a renewal in organizational
processes, to increase the quality of teaching and research activities, and also to foster
efficiency.
To this end, a change in the organizational structure was made. Today, UNIPA is
organized around the following organizational units:
(1) Education;
16
(2) Research & Development;
(3) Economy and Finance;
(4) Human Resource;
(5) Technical Services;
(6) Property and Patrimonial Estate;
(7) Legal Affaires;
(8) Network Services.
On April 2010 a pilot project aimed at designing a performance measurement
system has started. Both Rectorate and peripheral Administrative staff are involved in
the project. Based on empirical findings emerging from such endeavor, the next section
of this paper will outline the findings that have emerged so far in the design of
performance indicators related to the ‘Education’ and ‘Research & Development’ units
of UNIPA.
Fig. 5 describes an example of dynamic performance management framework
focusing the university image and financial resources. Particularly, such a framework
illustrates a set of measures in relation to both performance drivers and end-results
regarding four administrative products, i.e. “publications”, “enrollments”, “graduation”
and “graduated students employment”. Both responsible academic structures and
management areas are identified with reference to each product.
17
ACADEMIC
STRUCTURES
DEPARTMENTS
MANAGEMENT
AREAS
SCIENTIFIC RESEARCH
PRODUCTS
PUBLICATIONS
Liquidity
STRATEGIC
RESOURCES
CENTRAL OFFICES & FACULTIES
Researchers
Libraries
Electronic
database
Submitted articles per researcher per year
------------------------------------------------------Planned articles per researcher per year
Actual time to develop research projects
---------------------------------------------------Planned time to develop research projects
PERFORMANCE
DRIVERS
UNIPA
image
Citations
Researchers’
skills
Actual research quality
---------------------------------------------------Competitors’ research quality
Published articles
---------------------------------------------------Submitted articles
Curricula
Human
resources
JOB PLACEMENT
GRADUATED STUDENTS
EMPLOYMENT
GRADUATION
Unipa enrolled
students
Liquidity
Enrolled
students
Lecturers’
skills
Lecturers
Laboratories,
electronic
database &
equipment
Δ Submitted
articles
Δ Authors’
citations
Δ Published
articles
Cash flow
Δ UNIPA
image
Graduates
UNIPA
image
Human
resources
Agreements with
enterprises
Actual UNIPA image
---------------------------------------------------Competitors’ image
Avg. time to complete curricula
---------------------------------------------------Standard time to complete curricula
Innovative curricula
---------------------------------------------------Total existing curricula
Unipa students graduated in time
---------------------------------------------------Total Unipa graduates
Time to promote curricula
------------------------------------------------------Standard time to promote curricula
UNIPA students graduated in time
---------------------------------------------------Avg. competitor Universities students
graduated on time
Total graduates at work
---------------------------------------------------Total graduates
Teaching & tutoring time
---------------------------------------------------Planned teaching & tutoring time
UNIPA graduates at work
---------------------------------------------------Avg. competitor UNIs graduates at work
New enrolled students at UNIPA
---------------------------------------------------New enrolled students at competitor UNIs
UNIPA authors’ citations
---------------------------------------------------Avg. competitors authors’ citations
END-RESULTS
UNIPA PLACEMENT OFFICE
EDUCATION
ENROLLMENT
Published
articles
FACULTIES & CENTRAL OFFICES
Placement agreements with enterprises
---------------------------------------------------Planned placement agreements with
enterprises
Graduates at work after 3 years
---------------------------------------------------Total graduates
Actual UNIPA image
---------------------------------------------------Competitors’ image
Δ UNIPA
image
Δ Enrolled
students
Cash flow
Δ UNIPA
image
Δ Graduates
Δ UNIPA
image
Δ employed
graduates
Δ Agreements
with enterprises
Fig. 5 – A three dimensional approach to frame performance at UNIPA: an example
focused on image and liquidity.
In designing such a framework, a systemic perspective of the University has been
adopted to underline how end-results of a given product provision contribute in
enhancing (or depleting) strategic resources of another one located downwards the value
chain. The main focus has been oriented to both UNIPA image and liquidity.
In addition, performance drivers are identified in correspondence to end-results,
whereas related strategic resources are made explicit for each selected product.
Particularly, performance drivers are ratios between a current state (resource) and a
benchmark, which affect performance, usually through a normalized graph function
(Bianchi & Rivenbark, 2012)7. Benchmark values may come from competitor standards
or expected targets as set up in internal strategic planning processes 8.
Performance drivers are different from performance indexes. Performance indexes are synthetic
measures of the quality or state of the system. They do not affect performance. Implying that an
improvement in such indexes generates an improvement in other variables underlies inverting
between causes with effects.
8
Neely et al. (1995) argue that benchmarking is used as a means of identifying improvement
opportunities as well as monitoring the performance of competitors. They also cite Camp (1989) as
having the most comprehensive description of benchmarking: benchmarking as the search for
organization best practices that lead to superior performance. In terms of performance management,
however, Neely et al. cite Oge & Dickinson (1992) who suggest that organizations should adopt closed
loop performance management systems which combine periodic benchmarking with ongoing monitoring.
As a result, closed-loop performance management systems are able not only to provide the measure
7
18
The design of the above framework started from identifying end-results related to
each selected product. Respectively, we identified:
- change in submitted articles, change in published articles, change in UNIPA
authors’ citations, change in UNIPA image and cash flows, as results of the
publication process;
- change in enrolled students, change in curricula of study, change in UNIPA image
and cash flows, as results of enrollments;
- change in both graduated students and in UNIPA image, as results of graduations;
- change in employed graduated students, change in agreements with enterprises and
in UNIPA image, as results of graduated students’ employment.
Subsequently, the design of performance drivers has been based on those factors
affecting the above end-results. On this concern, referring to ‘publications’, the ratio
between submitted and planned articles per researcher per year and the time to develop
research projects influence the change in submitted articles. Such indicator, that
measures researchers’ productivity, also affects cash flow since it basically impacts on
the ministerial index used to allocate public funding towards universities. The UNIPA
research quality compared to its competitors’ quality9 influences the change in both
articles published in scientific journals and UNIPA authors’ citations. The ratio between
published and submitted articles together with the ratio between UNIPA and
competitors authors’ citations are drivers of the change in university image. In addition,
we linked the described performance drivers to their related strategic resources.
Namely, these latter are: liquidity, researchers and their skills, published and submitted
articles, citations, libraries and scientific database.
Concerning ‘enrollments’, the ratio between UNIPA and its competitors image, the
ratio between innovative and existing curricula, and the time to promote curricula,
influence the change in enrolled students. The ratio between innovative and existing
curricula also affects the change in UNIPA image. The ratio between new enrolled
students at UNIPA and at competitor universities may generate more cash flows
related to the performance of each organizational unit, but also to explain how their distinctive
performance contributes to the overall academic result.
9
The research quality may be measured by comparing actual and planned research findings or by
the ratio between UNIPA and competitor universities high-ranked publications.
19
through enrollment fee payments. Again, performance drivers depend on a set of
strategic resources, which include: UNIPA image, curricula of study, human resources,
liquidity and UNIPA enrolled students.
As for ‘graduations’, we identified four performance drivers. The relative time to
complete curricula and the relative teaching and tutoring time affect the change in
graduates. On the other hand, the ratio between UNIPA students graduated in time and
total graduates and the ratio between UNIPA and competitor universities students
graduated in time, influence the change in UNIPA image. In this case, strategic
resources to be used to improve performance are: UNIPA enrolled students, lecturers
and their skills, laboratories and other education equipment.
Regarding the ‘employment of graduated students’, the ratio between actual and
planned placement agreements with enterprises affects the change in employed UNIPA
graduates. The UNIPA image is influenced by both the ratio between graduates at work
(calculated also after three years from graduation) and the total graduates, and the ratio
between UNIPA and competitor universities graduates at work. The ratio between
UNIPA and competitor universities image impacts on the change in agreements with
enterprises. These performance drivers may be affected through the following strategic
resources: UNIPA image, UNIPA graduates, placement agreements with enterprises,
human resources.
7. Framing the performance of fund raising processes at UNIPA: a dynamic
performance management view
An academic performance management system can be useful to steer universities
according to a sustainable development perspective. Actually, several factors – such as
management complexity, resistance to changes, uncertainty and turbulence from the
external environment – strongly limit academic decision-makers in understanding
management
control
results
and,
consequently,
make
strategy
design
and
implementation quite problematic.
Namely, the dynamic complexity underlying academic institution management
represents one of the main causes for the unsatisfying performance levels achieved so
far by Italian universities (Cepiku & Meneguzzo, 2009). On this regard, a major
implication of dynamic complexity refers to a difficult identification of the drivers
20
related to the processes impacting on academic institutions. This problem is also due to
the adoption of a static and bounded approach to performance management systems, as
described in sections 3 and 4.
Empirical results emerging from translating current performance management
approaches into practice reveal that a static analysis of value creation processes does not
take into account time delays existing between the adoption of a given policy and its
related effects, and provides a limited contribution to improve strategic learning
processes of academic decision-makers.
To overcome such undesired effects, management practice can be supported by
combining performance management systems with SD models10. As a wide range of
research and studies prove, the SD methodology is applied to different disciplinary
contexts as it can analyze dynamic complexity of social systems through sketching and
using conceptual and simulation models aimed at interpreting phenomena. Particularly,
in the described project to model performance at UNIPA, SD modeling has been used to
provide decision-makers with proper lenses understanding the feedback-loop structure
underlying organizational performance, and to identify alternative strategies to adopt so
as to change the structure for performance improvement (Morecroft, 2007; Richmond,
2001; Ritchie-Dunham, 2001; Warren, 2008). As strategic learning tools, SD models
can be properly linked to financial models to support the performance management
cycle (Bianchi, 2002; Bianchi, 2012) according to a dynamic perspective (Bianchi &
Montemaggiore, 2008). As Fitzgerald (2007) remarks, “measurement is not an end in
itself. To be effective it must be part of a feedback control system where corrective
action is taken within the process – and results are fed back into consideration of future
strategy”.
In this section, a dynamic performance management perspective related to the
UNIPA “Research & Development” area will be described. In order to frame critical
issues related to short- and long-term performance attainment of this area, our analysis
has been focused on the following final products:
(1) scientific publications;
10
An in-depth overview of System Dynamics methodology can be found in Forrester (1961) and Sterman
(2000).
21
(2) patents and academic spin-off;
(3) fund raising through research projects funded by external calls for application;
(4) fund raising through research partnerships with external financing bodies;
(5) PhD programs set-up and implementation.
To design dynamic performance management models related to such ‘products’, we
have adopted the approach described in previous sections.
In the “Research & Development” area, one of the most important goals is
improving the capability of the University to attract external funding, e.g., by
submitting research proposals to the European Commission calls. Here we will focus
our analysis on an insight model framing the delivery of a specific ‘product’ related to
the “R&D” area, i.e. the agreements with external financing bodies to raise funds for
research activities. Actually, the capability of a public University to attract research
funds from external institutions plays an important role in the annual performance
evaluation conducted by the Italian Ministry of Education and Research (MIUR).
As discussed in the previous section, image is a strategic resource affecting the
capability of a university to invest in specific research projects. Image is likely to affect
the behavior of a number of stakeholders, which can influence university cash flows
(e.g., enterprises, banks, and public sector organizations).
The main actors playing a crucial role in promoting, searching and developing
funded research projects to be run jointly with third party organizations at UNIPA are:
(1) the academic departments and (2) the administrative fund raising office. This latter
directly reports to a first level unit called “Institutional Research”. These bodies are
used to undertake a number of initiatives to develop new contacts and start agreements
with third-party organizations (e.g., organizing events and meetings to advertise
research activities, legal and technical assistance in drawing up agreements).
The key-processes related to an agreement with external financing bodies can be
described as follows:
(1) promotion of University research activities;
(2) preliminary negotiations and research project proposals between academic
departments and external institutions;
22
(3) research project set-up and definition;
(4) final agreement stipulation;
(5) research project funding management and operation;
(6) research project scientific management and development.
The strategic resources mostly affecting performance in managing such processes
are:
–
financial resources the University invests in fostering research skills development
(i.e., training), hiring new academics (i.e., lecturers, researchers, assistant-associatefull professors, PhDs), and purchasing new equipment (e.g., scientific database);
–
University and its key-players’ image;
–
academics using ‘relational capital’ to attract external investors in new research
project partnerships (Stewart, 1997);
–
research skills;
–
research equipment, i.e. laboratories, scientific database, libraries, etc;
–
both submitted and published articles, together with related citations.
A proper use and coordination of such strategic resources can allow UNIPA to
affect end-results by targeting a number of performance drivers. Here, the following
drivers have been identified: (a) the ratio between research funds acquired by the
external bodies and total funds allocated by UNIPA for research activities; (b) the ratio
between published and submitted articles, (c) the ratio between UNIPA authors’
citations and competitor universities citations, (d) the researchers’ productivity defined
the ratio between papers and researchers per year, (e) the perceived research quality
resulting from the ratio between actual and planned research findings. Among these
parameters, only the first one is adopted by the Italian Ministry of Education to measure
University performance, while the others are introduced to improve performance
measurement effectiveness and, as a result, to support strategic learning processes of
academic decision-makers.
23
Fig. 6 – A dynamic performance management view model of fund raising processes.
Fig. 6 depicts a dynamic performance management insight model that highlights the
main feedback loops in relation to UNIPA fund raising processes.
Particularly, the reinforcing loop R1 shows how an improvement of University
image positively influences – other conditions being equal – the acquisition of new
research contracts with external funders, which may foster again an improvement of
image.
Loop R2 shows how an increase in liquidity directly affects investments in research
skills development. This may improve the research quality indicator (i.e., the ratio
between actual and expected research findings) and, consequently, increases new
publications on high-ranked journals. Such increase in publications directly affects the
number of citations reached by UNIPA authors. This, in turn, positively affects the ratio
between UNIPA and competitor universities citations. Such ratio positively influences
University image. Again, this may imply new research agreements with external
investors providing funds to carry out joint research activities. Also, external funds
invested in research activities positively affect the ministerial parameters (namely, the
ratio between research funds acquired by external bodies and total funds allocated by
24
UNIPA for research activities). This leads to higher public funding and, therefore,
liquidity.
As described regarding loop R2, financial investments may also be focused on both
hiring academics and purchasing new equipment: as showed in loop R3 and R4, this
increases academic staff (i.e., researchers, scholars, professors) and research equipment
which affect the research productivity indicator. As a result, fostering productivity may
generate more new articles to be submitted to high-ranked journals. In this case,
submitting more articles to high-ranked journals positively contributes in collecting new
publications. On the one hand, a higher stock of publications positively affects citations
and its related driver (i.e., the ratio between UNIPA and competitor universities
citations). On the other, it may improve the ratio between published and submitted
articles (see loop R5). Both ratios directly influence the University image, whose
improvement may provide new research agreements with external funders. More
external funding to research activities positively influence ministerial indicators and
allow UNIPA to obtain more public funds, which generate liquidity.
Similarly, the loop R6 remarks that, by using ‘relational capital’, academics may
directly contribute in collecting new contracts with external investors and, therefore,
raising more public funds generating more liquidity.
On the other hand, an increase in liquidity allows academic decision-makers to
invest in hiring more academics; this involves an increase in total salaries paid by the
University and, consequently, a decrease in liquidity (B1).
As illustrated by loop B2, UNIPA invests its liquidity also to finance research
activities. This may reduce the ratio between external and internal funds invested to
research. A decrease in the ministerial parameter directly affects public funding
allocation towards UNIPA, which again feeds into liquidity.
Loop B3 addresses the connection between UNIPA and its competitors. Particularly,
an increase in research contracts between the University of Palermo and external
funders weakens the performance-based ranking of the other Italian competitor
universities. According to the ministerial performance-based funding system, such a
circumstance may lead to decreasing public resource allocation towards such
universities. Therefore, a lower ranking of other Italian universities may involve a
25
stronger reaction aimed at counteracting such a phenomenon. In other words, Italian
competitor universities will be more focused on adopting counteracting policies to be
more competitive. As a result, competitor universities counteracting policies may imply
a reduction in the public funding allocation towards the University of Palermo. This
determines ceteris paribus a decrease in liquidity and, eventually, a reduction of
investments in research skills development. The impoverishment of research skills
directly influences the quality of research activities; this may obstacle an improvement
of UNIPA image, which feeds back into research contracts between the UNIPA and its
external funders.
Loop B4 illustrates that investments in both acquiring new research equipment and
hiring academics impact on researchers’ productivity that increases the number of
articles to be submitted for publishing. More submitted articles negatively affect the
ratio between published and submitted articles which, in turn, directly influences the
University’s image. An improvement of image causes an increase in new research
agreements with external funders whose contribution directly impacts on the ministerial
parameter. This may lead to collect more public funding that, eventually, enables the
University of Palermo to accumulate more liquidity to be invested again.
Loop B5 implies that an increase in University image may involve new research
contracts with external funders and, as a result, more external funds towards research
activities that improve ministerial indicators. This causes a negative impact on the
performance-based ranking of competitor universities which, in turn, put a major effort
in adopting counteracting policies aimed at increasing their authors’ citations, in order
to negatively impact on the ratio between UNIPA and its competitors citations. A
decrease of such indicator directly influences UNIPA image.
8. Conclusions
As a result of the recent reforms which have implied radical changes in running Italian
public universities, this paper has outlined a dynamic performance management view to
design and implement performance management systems aimed at pursuing sustainable
development in academic institutions. Such an approach is necessary to tackle possible
undesired effects which may stem from a bounded view in designing university
management systems based only on ministerial performance measures. By using a value
26
creation perspective, this paper has addressed the need to design performance
measurement/management systems which may balance short- and long-term, and
support a better coordination between front-office and back-office units, as well as
central and peripheral structures.
This paper has also emphasized how modeling feedback relationships between endresults, performance drivers and strategic resources, may support decision-makers in
managing and measuring the performance of academic institutions. In addition, the
intent to link back-office units to front-office in performance evaluation, has led us to
remark how crucial is identifying administrative products, mapping the underlying
processes and matching them to key-responsibility areas. Actually, the identification of
processes, internal clients and related products, available resources, policy levers, and
responsibility areas, provide the backbone for an effective implementation of
performance improvement programs in academic institutions.
Combining SD models with performance management enables decision-makers to
better identify and measure key-performance indicators and to effectively influence
policy levers to pursue a sustainable development in universities.
The application of such approach to UNIPA has been discussed in the second
section of the paper.
Further research will be necessary to develop more applied knowledge on academic
performance management systems. However, on the basis of the analysis hereby
presented and related empirical results, it seems realistic to expect further improvements
in our research according to the logical framework here described.
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