Some Issues in Building System Dynamics Models for
improving the Resource Management Process in
Higher Education
Michael Kennedy & Chris Clare
Information Management and Modelling Group
School of Computing, Information Systems and Mathematics
South Bank University
Borough Road, LONDON SE1 OAA, UK
Tel: (+44) 171 815 7416; Fax: (+44) 815 7499; e-mail: kennedms@sbu.ac.uk
Key words: Resource Management, System Dynamics, Higher Education, Finance
Abstract
This paper examines issues in the Resource Management process in Higher
Education Institutions. It discusses factors that should be incorporated in a system
dynamics (SD) model designed to assist in policy analysis regarding Resource
Management issues. It builds on a previous paper regarding Quality Management
and various pilot studies described at previous conferences by the authors and others.
Resource Management is an important issue for Higher Education Institutions. In the
UK, various structures have been established or proposed to attempt to measure the
resources deployed and the impact on quality. Many issues remain controversial
however: who are the stakeholders and what should be their relative importance ?;
what should be the relationships between resources devoted to research and
teaching?; what is the impact of changing resource levels on academic and support
staff, accommodation, equipment, learning resources and information technology?;
what is the impact of various management styles?; how can we define "quality"?
The paper assesses the potential usefulness of SD in exploring resource issues. A
conceptual model of the ' Resource Management Process’ in higher education settings
is presented.
1. Introduction
The UK higher education sector has a turnover of over £11 billion and employs more
than 250,000 people. Today, one in three school-leavers go on to higher education
compared to one in seven in 1985 and one in ten in 1962. By the year 2003, the
number of UK students starting full-time first-degree courses will have increased by
an estimated 25% compared to today's figures. Participation rates still vary
dramatically between different social groups however.
Institution expenditure on buildings and estates represents 12% of total expenditure
across higher education, the second biggest single component of their costs. The total
estate has been valued at £30 billion. Universities and colleges face an estimated
funding shortfall of £350 million in the current session and £565 million in 1999-
2000, rising to at least £2 billion a year in 20 years time. In the last six years, the
amount of money invested for each student has fallen in real terms by 28%.
It is expected that uses of technology will increase dramatically throughout the sector,
demanding significant investment and initially increasing the pressure on both staff
and systems (Dearing, 1997). Institutions, which adopt an integrated approach to their
technology infrastructure, will benefit from savings in cost and time and from
increased efficiency compared to those universities, which fail to implement a
coherent systems strategy.
Resource Management in Higher Education has been highly controversial in the UK.
Since the 1980s there has been a political process involving the government, and the
Universities. Cave et al. (1997) state that, "Government determined to bring to bear on
higher education the principles it was seeking to install across the public sector: strong
central direction; accountability for the economic, efficient and effective use of
public money; the measurement of performance against outcome criteria and the
substitution of the concepts and methods of management for those of administration
or professionalism."
This political process led to the Jarratt Report (1985), which recommended that
universities must work to clear objectives and achieve value for money. Jarratt also
made far-reaching recommendations about the governance and management of
universities. Cave et al. (1997) state that, "Universities had long been regarded as
diarchies in which the power of the collegium, as represented by Senate and the
academic autonomy of individual teachers, worked in tandem with the hierarchy
embodied in the vice-chancellor, deans and heads of departments ....Jarratt now
proposed institutions’ Vice Chancellors would, in turn, become chief executives,
overseeing the corporate management of the university."
This debate between the "managerialists", favouring strong central direction and the
"collegiumists", who see the university as a community of scholars continues. Some
of the criticism of the Dearing Report (1997) centres on the contention that the
committee implicitly adopted the "managerialists" mindset (see, for example, Blake,
Smith & Standish (1998) in "The Universities we need — Higher Education after
Dearing")
Issues of Resource Management in Higher Education Institutions cannot be separated
from issues of quality and standards. Diana Green (1994) stresses that since the mid-
1980s, public interest in and concern about quality and standards has been intensified
by the increasing attention given by successive British governments to reforming
higher education. The reasons for this growing concern are:
* Rapid expansion of student numbers against a backlog in public expenditure.
¢ The general quest for better public services.
+ Increasing competition within the educational 'market' for resources and students.
* The tension between efficiency and quality.
+ Managing institutions of higher education is a complex task in maintaining their
effectiveness. Institutional managers have a crucial role to play in relation to quality in
the following ways:
¢ Finding ways of using the institution's resources to better effect and generate
more resources.
¢ Being accountable to the wider society, through use of effective means of
assuring academic standards.
¢ Developing improved systems of strategic planning and _ institutional
management.
2. Resource Management Issues in Higher Education
2.1 Identifying the Stakeholders & Customers
Whereas the stakeholders of many commercial organisations can be easily identified,
a university's stakeholders fall into four distinct groups, according to Clare (1995).
Firstly, the students of the institution are stakeholders (as well as its product). They
look to the institution to provide a service in the form of a course of study leading to a
recognised qualification and a general educational benefit. Recent informal interviews
carried out at South Bank, indicate that the applicant of the late 1990s is far more
discerning about their course of study and the host institution than their predecessors.
Part of the reason is the awareness of graduate unemployment which leads students to
seek courses that will minimise the risk of unemployment. The severe pressure on
student finance (including the recently introduced student fees), leading to the
necessity to take out loans or be subsidised by parents also tends to focus the mind
towards looking for value for money.
The second category of stakeholders are the employers of graduates and diplomates.
Their needs for well qualified, well educated and adaptable employees in the shape of
new graduates have to be satisfied. Success in this area reaps other benefits such as
investment by employers in research, development, consultancy and short courses
with the institution. Here, a careful balance needs to be struck. The natural instinct for
the "old" universities was to build courses around the latest theoretical research;
indeed this has been the standard approach for many years and can be seen to have
been successful in providing the UK with first rate scholars. The direct needs of
industry have often been seen as being satisfied with direct training courses that are
not the province of the universities. "New" universities (ex-Polytechnics), on the other
hand, have always sought to try to satisfy some of the needs of industry directly as
part of the degree and diploma courses they offer. Over the years, they have managed
to develop a balance between up-to-date material that will enable the graduate to
become immediately useful to an employer, and material designed to provide a firm
under-pinning, to enable the student to be able to adapt to future changes in the
industry or in technology.
The third group of stakeholders are the Government (via the funding councils), local
Government and Government agencies (the Research Councils, Training and
Enterprise Councils etc.). For the foreseeable future, these bodies will be the major
providers of funds to a university. Consequently, they should be regarded as
stakeholders with needs to be satisfied. The main way in which this is currently
achieved is by the institutions recruiting to target, graduating quality students,
completing the funded research and so on.
The final group of stakeholders for the services of a higher education institute is the
wider community. Each institution has obligations (although it may not have realised
them) in the areas of:
(i) access to the facilities of the institution for the local community
(ii) contribution to the wider academic community
(iii) providing services to the international community via the enrolment of
overseas students, collaborative research, consultancy and other projects
(iv) the welfare of society in general.
2.2 Resourcing Streams
The resourcing of operations of UK universities comes from a variety of sources, but
these can be broken down into three main categories: the main grant, research
funding, and other income.
2.2.1 Main Grant
The bulk of the funding for the "new" universities and a considerable proportion of
the funding for "traditional" universities arrives in the form of an annual grant from
the Government, administered by the appropriate "Higher Education Funding
Council". The grant covers notional funding for teaching activities, for research, and
in some cases, for special initiatives, such as widening access. In addition to the main
grant, the Funding Councils occasionally provide limited funds for capital projects
such as buildings or technical equipment.
The part of the grant for teaching costs is based on the numbers of students enrolled
on the courses offered by the university. There are four "price groups", designed to
reflect the different costs of teaching technical as opposed to non-technical subjects.
The grant is set on target recruitment numbers which, if they are not met, can lead to
some of the teaching grant being withheld. Along with the actual teaching grant, each
student recruited generates a fee to be paid by the student or a sponsor. Although the
fee is the responsibility of the student as opposed to the central government, its
generation is tied closely to recruitment and can therefore be considered alongside the
teaching funding.
The research element of the grant is based on the results of the periodic Research
Assessment Exercise (RAE), where a programme of peer review results on a grade
being assigned to the different areas of research in the university. If the grade is above
a certain base level, the department attracts funding based on the grade and the
number of active researchers within the department.
Despite the grant being calculated in a transparent way and to strict formulae, there is
no requirement for the university to allocate the grant in the same (or indeed similar)
proportions; the university has freedom to allocate the grant as it sees fit.
2.2.2 Research Grants
These grants can be central government funds (for example from the UK Research
Councils), European initiatives (such as the EU Sth framework) or direct research
grants from industry. In all cases, they will be based on specific proposals for a fully
costed research project or programme. A major debate in higher education circles
around research grants concerns the charging of overhead costs. The degree to which
overheads can be recouped depends on the funding source, and in many cases these
are thought to be inadequate. Many research projects use accommodation, equipment,
technical and administrative support which should be covered by appropriate
overhead charges. In the absence of such charges, these supporting activities are
funded by the main grant.
2.2.3 Other Income
This is the term used for income from such activities as Consultancy, short and full-
cost courses, the hire of university facilities, and the activities of any trading arm that
the university may operate. In many cases, the problem of overheads mentioned above
is less severe because the university is able to charge reasonable overheads to what
are, in the main, commercial customers. There is an expectation that while the
majority of the funds will go to the unit that generated the income, a reasonable
proportion will be retained by the centre to supplement the main grant income.
3. Survey of Current Higher Education Approaches to Resource Planning.
3.1 Problems with Current Methods
The main problems identified as being associated with the current methods Ashworth
and Harvey (1994) and Walkin (1992) are:
* Accuracy: Here the main emphasis is the extent to which people should believe in
the figures obtained from computations of quantitative issues.
* Costs: The methods outlined above are costly and thus many organisations are not
able to have continuous implementation policies carried out.
* The methods are not able to measure both qualitative and quantitative issues
together and this is foreseen as a major problem.
3.2 Input /output models
The Problems with most input /output models, such as those reproduced from Cave et
al. (1997) below, is that they adopt a static, linear view. They thus ignore both
dynamic interaction between the input /output factors and the nature of the
‘transformation’ taking place (in fig 1.1 in the 'Higher education sector’). They are thus
of little use when considering process improvement.
Students’ Academic Equipment ‘Consumables
Time Time and buildings
{| [| | |
Higher education sector ]
| |
Qualified Research
workforce output
Production sector
Output of final Consumption
goods and services benefits
Figure | Inputs and outputs in higher education
Source; (adapted from) Cave et al. (1997)
A somewhat more sophisticated approach is adopted by models which incorporate the
by the aggregate higher education dynamic position but many still ignore both the
nature of the dynamic interactions between the input /output factors and the nature of
the 'transformation' taking place. The example reproduced below was produced by
SAP (1997) while commenting on the Dearing Report (1997).
FINANCIALS G/L
COST CENTRES
ACADEMIC FEES
‘HEFC GRANTS =
RESEARCH RECEIPTS FUNDING EXPENDITURE { =
OTHER INCOME FROM + ¥ Lhe
CUSTOMERS ETC, ae
UNIVERSITY
nesa AA swiens BUSINESS
Reports ‘graduated
best) ~~ PROCESS
Keak PAYROLL
UNIVERSITY
HESA RESULTS PERSONNEL
Lectureras
Professors
DELIVER
EDUCATION
GRADUATES < STUDENTS
Figure 2: Higher Education Dynamics as per Dearing Report (1997)
[source http://www.sap.com/uk/ ]
3.3 Spreadsheets
Problems in the utilisation of spreadsheets were examined in Kennedy (1997), which
described our experiences in replicating spreadsheet models of investment appraisal
and higher education into a SD environment. Though spreadsheets are selected for the
vast majority of business modelling purposes (Clarke and Tobias, 1995), some
disadvantages of spreadsheets have become apparent. They have often become
unwieldy and inaccurate, but more fundamentally, they only incorporate the ‘hard’
aspects of the environment. Clarke and Tobias (1995), reported that a significant
proportion of their survey respondents claimed that spreadsheets were overly
complex, difficult to use and inflexible. Other disadvantages included lack of
robustness, lack of data security and integrity. For a modelling tool to be of analytical
and predictive use, it should reflect both the internal and external factors that affect
the way business’ operate or the ability to trace the structure and underlying
assumption in the mode. This is one of the fundamental conceptual weakness of a
spreadsheet compared to a SD environment.
3.4 Performance Indicators
3.4.1 Influence of Quality/Performance Measures and Indicators on funding
Performance indicators [PIs] are statistics, ratios and other quantitative information,
which indicate the way in which a program of study or a college is operating. The PIs
used should relate to the mission statement of the college and, over a period of time,
may confirm, or otherwise, whether the college is making progress in meeting the
objectives set out in the mission statement. They should be used not as an end in
themselves to draw definitive conclusions, but to trigger areas of concern and provide
a catalyst for further investigation. If PIs are not used to facilitate decision making and
day-to-day management, they are likely to fall into disrepute and be disregarded.
Pls have been highly controversial in the UK. Cave et al. (1997) state that, "The
explicit introduction of PIs into higher education in the UK was the product of a
highly political process involving the government, the Committee of Vice-Chancellors
and Principals (CVCP) and the then University Grants Committee (UGC). As such it
exemplified a significant dynamic in the evolution of higher education policy in the
1980s."
The main desirable features of Pls in supporting the quality management process are:
* relevant to the mission statement of the institution;
* assist in the monitoring and evaluation of the institution's activities;
* provide data by which to make judgements on resource allocations;
* assist in forward planning and decision making;
* acceptance and motivation of staff.
Although there is not, as yet, an overt connection between PIs and funding, there are
thought to be some influences.
The indicators in current use were formulated in an attempt to answer perceived
managerial issues given the information available or obtainable. In the author's
opinion, many are excessively concerned with resource utilisation without reference to
the quantity and quality of the output so obtained. When a greater understanding of
the current, basic, measures is achieved, more complex, but more meaningful,
measures should be explored, for instance, the ' Value added ' to student attainment
measured against the resource inputs utilised to achieve it.
For the categories listed under other income discussed above, the system of
performance or quality measure is the same as with any commercial activity. A
contract is formed for a piece of work which has explicit and/or implicit quality
definitions. The work is undertaken and the performance of the team can be assessed
in terms of adherence to budget and timescale and the "product" assessed for its
quality. The reputation of the team and the consequent ability to win further contracts
rests largely on those measures.
A similar situation occurs with the research grants. Whatever the source of the
funding, the project proposal would have been comprehensive in terms of the costs,
deliverables and the deadlines. There are also provisions for interim reviews of the
work and the budgets, and this is a particular feature of EU research grants. Consistent
failure to deliver on any of these fronts would have an adverse effect on future
funding applications no matter how eminent the research leader.
Feedback on these two areas is related in the way in which it influences other income
generation, research grants and the Research Assessment exercise. One of the factors
considered in the last RAE was the extent to which the research group generated
external funding in the form of research grants or contracts with industry. The degree
of importance attached to this aspect varied between subject areas but in some (such
as some engineering disciplines) it carried considerable weight. As mentioned above,
the RAE ratings certainly determine the amount of the research component in the
main grant. However, the rating signals an important quality message about the
research work of that group. Many referees to research grant applications will be
aware of the rating and will be influenced by it. In addition, the rating is likely to be
known to major companies that may be approached to fund research, development or
consultancy. Consequently, the level of activity can be influenced by the RAE rating
which itself is influenced by the funds generated.
The effect of external performance and quality measures on the teaching grants is less
direct. Each year notional targets are set for the recruitment of students within the
price groups. Although target numbers can be vired by the institution between the
price groups, differential pricing means that the virement is not on a one-to-one basis
i.e. a shortfall of one engineering student, requires almost two additional business
studies students to compensate. Once the recruitment round is complete, the current
student population forms the basis of the following year's targets. In addition to the
grant effects, each student not recruited means a loss of the fee that the student (or
their sponsor) would have paid. Consequently, recruitment to target is a crucial factor
in the financial well-being of the institution.
Students pay a significant proportion of their teaching costs and are responsible for all
of their support expenses. This means that their choice of institution is likely to be
more considered than when higher education in the UK was subject to the award of
grants to cover tuition and living expenses. Any information can inform that choice
and the recent publication of the teaching quality scores for university departments,
their research ratings and other data that can be presented in the form of "league
tables". Although at present, the teaching grant is not adjusted with reference to any of
these Pls, the funding councils reserve the right to do so. However, students who are
aware of these indicators could be influenced in their choice of which institution to
attend; and these decisions will affect the overall recruitment and therefore the
funding.
As well as the general concerns over league tables there is debate over the validity of
the formulation of individual indicators. The government's of formulation
‘employability’ is currently being hotly contested by vice- chancellors and education
secretary David Blunkett (THES, 1999). Some of the other factors that are used in the
preparation of league tables are more controversial and have, in many cases, been ill-
thought through. Examples include the staff-student ratio (SSR) and the number of
first class honours degrees awarded. A low SSR could be considered a positive aspect
(more face to face contact between students and staff) or negative (inefficient use of
resources). A university awarding a high number of "firsts" may be a highly effective
teaching institution or may be thought to have lower than average standards. Perhaps
the most controversial element concerns the entry qualifications and the retention of
the students. Institutions with a mission to widen access to higher education
necessarily take on students with non-standard entry qualifications. The majority of
these students are successful but they are a "high risk" group in that a number will not
be able to cope with a full programme. Such institutions are penalised in league tables
on both counts because in the absence of genuine measures of added value in
education, their success in adherence to their mission cannot be properly reflected.
4, Current (SD) Contributions to Higher Education
Some preliminary attempts to use System Dynamics to explore and understand High
Education planning effectiveness (Barlas and Diker, 1996) and Higher Education
Funding (Kennedy, 1997) have been made, but this paper suggests that a much more
comprehensive application may be possible. In the closely related field of quality,
Kennedy (1998a, 1998b), has examined some issues and described a prototype model
In the author’s opinion, is now an appropriate time to critique the work done to date.
The main objective of Barlas and Diker’s (1996) research is to construct an interactive
dynamic simulation model, on which a range of problems concerning the academic
aspects of a university management system can be analysed and certain policies for
overcoming these problems can be tested. More specifically, the model focuses on
long-term, strategic university problems that are dynamic and persistent in nature,
such as growing student-faculty ratios, poor teaching quality, low research
productivity. The model generates numerous performance measures about the three
fundamental activities of a university, namely, teaching, research and professional
projects.
Carol Frances and co-workers (1994) have reported on several interventions by using
system dynamics to improve planning and budgeting for higher education both to
inform public policy /State Management [Results from Arizona] and to inform
university wide policy [Results from Houston, Texas]. She has also reflected on wider
issues in 'Shaping Higher Education's Future’.
Peter Galbraith, (1998a, 1998b) has investigated the impact of managerial policy on
HE institutional performance, with particular emphasis on time delays between policy
change and the results being evident and has posed the question "Are Universities
Learning Organisations?"
Se Future Contributions of System Dynamics to HE Resource Management
The potential combination of SD to IS/IT HE management appears to lie in four areas:
Firstly, at the most basic level, in some cases it may be possible to replicate existing
models developed originally using other modelling styles or techniques. In this
domain this is normally spreadsheets. The author has described various replications of
this sort (Kennedy, 1997a; Kennedy, 1997b). This process may be of value in
convincing managers that they are not losing desirable aspects of their current
systems, in better handling any dynamic behaviour incorporated in the previous
model, in building confidence in SD models and in giving some secondary benefits
such as better documentation, but it will not generally realise the full potential of SD.
In some cases, it may allow for the incorporation of other factors (e.g. intangible
benefits) that were not incorporated before, or any dynamic behaviour known of but
not previously incorporated, in an enhanced model. It could also form the basis for a
more radical reconstruction incorporating tried and tested elements of the previous
{non SD] model.
Secondly, it is possible to produce SD models of some of the issues mentioned in this
paper. Some prototype examples (Figures 3 & 4) follow as a basis for discussion. The
requirements for such a model need to be identified and analysed effectively,
particularly as requirements change over time, as management changes its decision
styles, and staff need new operational data and information. Delays between action
and result are of particular importance.
Department of Education and
Funding Councils
(league tables,
RAE, HESA)
HE Policies
HE Funding
Performance indicators
University
z
s to Local Educational Authorit
Student fees
‘equipment levels
z
&
&
2
ar
&
2
=a
Student recruitment
Pereived Pro!
Catchment Area
Figure 3: Block Diagram of Major Feedback Structures in HE Management at an
Institutional level
f= of University by
potential students
*
Student ko rate
a a
IN
ra
Nh rs)
competing
aes pool of
Available staff recruitment
malvern) Piss = staff levels
+
/ \ Staff recruitment rate
sie hh
. oN
ie sd . Tey
HE Funding
+
tani unis“A——_
Equipment cost
Garrent research
output
Research funding
Figure 4: High Level Dynamic Hypothesis of HE Management
Thirdly, we may develop models of a business showing HE management processes
before and after a proposed process change. The anticipated value of the benefits
derived, (in terms of greater revenues, resources saved or perceived improvements in
quality or reputation), can be compared to the estimated costs. This would be of
considerable value in “Transformation” type projects.
6. Conclusion
Based on the discussion above we would propose three research themes:
6.1 Higher Education Planning: Where Next?
The objective would be to examine the theoretical justification for HE planning
approaches and tools. It would contain a review of current higher education
approaches to planning including input/output models, regression models,
spreadsheets and compare the potential of SD. It would also highlight the meta-
theoretical assumptions underpinning these planning approaches
6.2 A Critical Review of System Dynamics Models that Investigate Higher
Education Issues
The objective would be to identify relevant SD structures for incorporation in future
work, to examine the appropriateness of different styles of SD modelling in this area,
so guiding the selection of an appropriate research approach. It would describe the key
findings of previous authors (including Barlas, Frances, Galbraith, Radzicki, Saeed)
research and outline their underpinning research approach.
6.3 Highlighting Important Higher Education Management Issues
The objective would firstly be to identify “The Givens” in Higher Education e.g. in
the UK the Research Assessment Exercise [RAE]. It would then examine the various
conjectures on the way that “The Givens” influence the structure of higher education
systems and policy formulation. The work could be done at four Hierarchical Levels:
- International/National
- Regional/ Cluster
- Institutional/ University
- Departmental
a Summary
The potential value of SD for HE management is in incorporating non-linear and
iterative views, hard and soft issues, strategic objectives, and changes in educational
processes. A SD model of the resource allocation process should help management to
investigate the impact of specific policies before implementing them. This paper
shows the potential role of SD in coping with the ever-reducing resources available,
and increasing quality standards demanded of higher education institutions in many
parts of the world.
It is emphasised that this review is reported as the early stage of a long-term project.
The authors would welcome comments from these with an interest in the field,
particularly those interested in some form of continuing dialogue or collaboration.
Acknowledgements
The assistance of Ddembe Williams, Garry Bell, and Steve Fisher in preparing this
paper is gratefully acknowledged.
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