The Development of the Holon Planning and C osting
Framework for Higher Education Management
1G ary Bell, "Maggie Cooper, ‘Mike Kennedy and ‘J on Warwick
‘South Bank University °City University
School of Computing, IS and Maths Department of Computing
Borough Road Northampton Square
London SE1 0AA London EC1V OHB
Tel: 44 020 7815 7498 Tel: 44 020 7477 8416
Email: bellgaa@ sbu.ac.uk Email: maggie@ soi.city.ac.uk
Abstract
This paper discusses the emergence of the Holon Planning and Costing Framework for
Higher Education management. We briefly discuss the key concepts that underpin
management of the university system in the United Kingdom. An outline of the dominant
HE planning approach is undertaken and criticisms are produced to suggest that an
alternative is needed. We believe most mathematical techniques used for planning can
be linked with Hard Systems Thinking (HST). Therefore, the essence of HST is
highlighted, and a serious weakness identified, to explain the development of soft
methodologies and Soft Systems Thinking (SST). We outline the distinguishing features
of SST and key characteristics of the Soft Systems Methodology. Additionally, a
significant limitation of this methodology is highlighted to justify the need to combine it
with the Goal/Question/Metrics methodology. The combination of these two
methodologies has been called the Holon Methodology, which was originally designed as
an informal software process improvement approach. We advocate the view that an
informal approach to controlling and improving HE management is needed; this will
empower the relevant academics and administrators. This complements the view that
there is a need for a systemic approach to HE planning. Therefore, we combine the
Holon Methodology (rooted in SST) with the System Dynamics technique (rooted in HST)
to produce the Holon Planning and Costing Framework. An outline of the work that is
currently being undertaken to establish this planning framework is given.
“I keep six honest serving-men:
(They taught me all I knew)
Their names are What and Where and When
And How and Why and Who.”
(Rudyard Kipling 1912)
1. Introduction
The United Kingdom (UK) education system is evolving to meet the shifting demands of
society. Over the last two decades UK employment patterns have changed significantly,
and there is a need for a more highly trained and educated workforce. Moreover, this
workforce must continuously update its skills to meet changing requirements of the
labour market. Recognition of the environmental changes that affect the Higher
Education (HE) system initiated the Dearing Report (Dearing 1997). We outline key
aspects of this report for it underwrites UK government strategy for the HE system and
influences our research. Successive governments have provided most of the funding for
the HE system. In the last decade or so these governments have demanded greater
university accountability for public scrutiny, which has led to an emphasis on
management practices. Trow (1994) coins the terms ‘hard’ and ‘soft’ managerialism
which characterise the different government and university management approaches
respectively. We discuss the underpinning concepts of these two forms of management.
An overview of the fundamental components of the dominant HE planning methodology
that is associated with soft managerialism is provided. Galbraith (1998a) highlights the
limitations of this approach to justify the use of the System Dynamics (SD) (Forrester
1961) technique. Further criticisms are adduced from the work of Simon (1979, 1976)
and Ackoff (1979) to reinforce the view there is a need for a systemic approach to HE
planning.
Galbraith (1998b, 1989, 1982) has developed a number of SD models over the years,
which demonstrate the usefulness of the technique through highlighting its explanatory
strengths, i.e. ‘the how’ and ‘the why’. Furthermore, he has identified several archetypal
structures (Senge 1990) that operate within Queensland University. However, Galbraith
did not work closely with key stakeholders ensuring relevant problems, i.e. ‘the whats’,
are examined. We consider this to be a limitation of his innovative work. The absence of
stakeholder participation is considered to be a fundamental weakness of hard systems
thinking when investigating social situations. SD is usually associated with hard systems
thinking, but Lane (1994) argues there is a need to combine SD with a soft methodology.
Soft methodologies are linked with soft systems thinking. We provide a description of the
essence of hard and soft systems thinking. A brief overview of Soft Systems
Methodology (SSM) (Checkland 1981) is given, for it has been argued that it should be
synthesised with SD (Lane and Oliva 1998).
We will identify a significant drawback of SSM to justify the need to combine it with the
Goal/Question/Metrics (GQM) methodology (Basili and Rombach 1988) which is
underwritten by representational measurement theory (Fenton 1991). We will show that
merging GQM and SSM gives a distinctive new soft approach - the Holon Methodology
(Bell et al 1999b). The Holon Methodology was originally designed as a post-mortem
approach. It identifies the problems associated with a completed software project from
the perspective of the development team. Therefore, we consider the methodology to be
an informal Software Process Improvement (SPI) approach (Bell et al 1999b). An
overview of the key stages and methods of the methodology is provided. However, the
method taken by Dearing (1997) to produce a vision for the HE system prompted our
redesign of this methodology.
The redesigned methodology is considered to be a soft teleological approach. We outline
the fundamental parts of a soft teleological approach. A weakness of the redesigned
methodology is highlighted to justify the use of SD, leading into the development of the
Holon Planning and Costing Framework. The Framework is used to assist in continuous
planning and costing for the School of Computing, Information Systems and
Mathematics (SCISM) at South Bank University. Finally, completed and on-going work
using aspects of the framework are briefly described.
2. Overview of the Dearing Report
Over the last few decades, governments have commissioned major reviews of the higher
education system in order to address specific challenges. In the later part of the last
century there has been a significant decline of traditional heavy industries, e.g. coal and
railway industries, and the notion of ‘job for life’ has diminished. However, new ‘high
tech’ organisations have appeared which require a highly trained and educated workforce
to meet present and future challenges. The shift in employment patterns and rapid
technological changes have created new problems for the HE system.
Dearing (1997) was given the opportunity to make recommendations on how the
purpose, shape, structure and funding of the HE system should develop over the next 20
years. He investigated the current state of the HE system and its wider context, i.e. its
relationship with society. Dearing argued that the UK must create a ‘Learning Society’,
committed to learning throughout life. He envisioned HE as making a distinctive
contribution to the development of a leaming society through teaching, scholarship and
research. He derived 93 recommendations to achieve this vision of a higher education
system for the learning society and many of them have been implemented.
3. Hard and Soft Managerialism
In the last decade or so UK governments have demanded greater accountability in the
quality and cost of universities and that this should be available for public scrutiny.
Hence, the emergence of ‘managerialism’ in the governance and direction of universities.
Trow (1994) believes that hard and soft managerialism concepts are applied to HE
institutions. Hard managerialism generally involves people from government and business
who are resolved to reshaping and redirecting universities through funding formulas and
other mechanisms, e.g. criteria to assess teaching quality. Trow contends that business
models are central to hard managerialism, for they assist in transforming universities into
organisations similar enough to ordinary commercial companies to be assessed and
managed in similar ways. The Higher Education Funding Council for England (HEFCE)
implements and oversees government policies for the HE system. Furthermore, HEFCE
works closely with the Research Assessment Exercise (RAE) team and the Quality
Assurance Agency (QAA). The RAE team examines the quality of research within
different institutions to guide the distribution of public funds. The QAA investigates
different aspects of teaching quality, which also affects university funding. We consider
these bodies to be an integral part of the hard managerialism concept.
Soft managerialism involves senior administrators and appropriate academics in the
universities. The soft concept views managerial effectiveness as an important component
in the provision of higher education of quality at its lowest cost, and is focused around the
idea of improving the efficiency of the institution. We therefore review the dominant
approach to HE planning, and highlight weaknesses that question its efficacy in achieving
the aims of soft managerialism.
4. The Dominant Higher Education (HE) Planning Approach
Galbraith (1998a) identifies the dominant HE planning approach that is associated with
soft managerialism. The key parts of the approach are: a strategic plan; performance
indicators (PIs); mathematical models; and artificial structures. A strategic plan usually
entails a mission statement and related strategic aims, e.g. excellence in teaching and
leaming, which fulfils it. These strategic aims are treated separately and expressed in
terms of goals, which are assessed through the use of Pls. Furthermore, regression
models and spreadsheets use the collected data for forecasting and budgeting purposes.
A university is divided into faculties each containing a number of schools or
departments. Galbraith sees these groups are used as artificial structures to facilitate
competition for resources at the university level. The underpinning argument is that
schools in competition will optimise their efforts, thus, optimising the overall
performance of their faculties. Maximising faculty performance in turn optimises the
total performance of the institution, therefore, meeting government objectives that may
lead to further funding.
Galbraith (1998a, 1998b) highlights several limitations with the dominant HE planning
methodology to justify the use of SD. Most importantly, the strategic aims are treated
separately, and related goals are individually assessed through Pls, e.g. a goal to increase
research output may be expressed as numbers of papers in two years. However,
improvements needed to ensure a goal is achieved could have an adverse affect, e.g. a rise
in research effort may reduce teaching quality.
Ackoff (1979) contends that managers are not confronted with problems that are
independent of each other, but with situations that consist of dynamic, transient and
complex problems that interact with each other. He calls such a situation messes.
Furthermore, he states:
“Messes are systems of problems, the sum of the
optimal solutions to each component problem taken
separately is not an optimal solution to the mess. The
behaviour of a mess depends more on how the solutions
to its parts interact than on how they act independently
of each other.”
(Ackoff, 1979)
We contend that if every faculty and school have their own mission statement and
objectives then dysfunctional behaviour will arise. The notion that dysfunctional
behaviour can emerge from well-intentioned actions is associated with the Camegie school
of thought, which recognises that there are severe limitations on the thinking and
reasoning power of the human mind. The principle of bounded rationality was formulated
by Herbert Simon as the basis for understanding human behaviour in complex systems.
The principle of bounded rationality states:
“The capacity of the human mind for formulating and
solving complex problems is very small compared with
the size of the problems whose solution is required for
objectively rational behaviour in the real world or even
for a reasonable approximation to such objective
rationality”
(Simon, 1979)
Furthermore, the bounded rationality principle provides a basis for developing a theory of
organisational behaviour. Simon further wrote:
“Organisation theory is centrally concerned with
identifying and studying those limits to the achievement
of goals that are, in fact, limitations on the flexibility
and adaptability of goal striving individuals and groups
of individuals themselves”
(Simon 1976)
We contend that the dominant HE planning methodology used to achieve the aims of soft
managerialism is inappropriate, and indeed may cause dysfunctional behaviour, because it
concentrates on maximising the performance of an individual faculty/school/centre, which
may have an adverse affect on others. An holistic approach is needed. Ackoff (1979)
argues that effective management of messes requires a systemic approach to planning.
Galbraith (1998a) proposes the use of SD as an alternative HE planning approach.
Moreover, Morecroft (1985, 1983) demonstrates that the concept of bounded rationality
is directly represented in feedback structure, which is central to SD. Hence, SD may
prevent the emergence of dysfunctional behaviour through investigating the systemic
consequences of various decisions.
5. Galbraith’s SD Work in HE Planning
Galbraith (1998b) has identified many system archetypes which appear at various
hierarchical levels and different parts of the university. For example, figure 1 is a causal
diagram that represents research funding allocation between two competing units. The
positive loops highlight that an increase in the productivity of a research unit will lead to
resource gains, which enables further productivity and thus further gains. The negative
loops are essentially regulating or balancing in their effects. The top negative loop
highlights that a rise in the productivity of research unit A will contribute to the total
research output produced by all the units. However, resources gained per individual
product is reduced, which decreases the resources assigned to a unit A, which in tum
reduces the productivity of A.
Resource gains +
on for Units A
Units A's Total resources
research ¥ available for
productivity distribution
a
Total research ——|—_* Resource gain
Other units ——————_»
un productivity of per individual
all units product
+ Y ear delay
Units B’s + .
research
productivity SD)
Lo esource gains
for Units B
Z +
Figure 1: Causal Representation of Research Units Competing for Limited Funds (taken
from Galbraith 1998b)
Galbraith sees this as a version of the ‘tragedy of the commons’ because there exists a
‘commons’ or a limited resource shared amongst a group of competing units and the units
dictate their own actions in order to maximise their own gains from the common resource.
The common resource becomes less productive per individual demand as units work
harder for less and less.
He demonstrates the usefulness of the SD technique for HE planning through highlighting
its explanatory strengths, ie. ‘the hows’ and the ‘the whys’ of system behaviour.
However, he did not work with any key decision-makers at Queensland University. This
is a significant limitation of his research, because the findings, though interesting, had little
impact on the planning of the university. We contend it is important to work with
stakeholders in order to identify the relevant problems, i.e. ‘the whats’, which need to be
examined. Moreover, model ownership must be achieved through passing verification and
validation tests to the satisfaction of the stakeholders.
Verificati on +Validation =Model Confidence = Model Ownership = Meaningful Insights
Hence, the insights from the SD model have meaning that may facilitate action. Clearly,
there is a need for a soft methodology to complement the SD technique for the purpose
of HE planning.
6. The Essence of Hard and Soft Systems Thinking
We contend that SD is a hard methodology that is associated with hard systems thinking,
while soft methodologies are linked to soft systems thinking. It is important to highlight
the essence of hard and soft systems thinking to justify the development of the Holon
Planning and Costing Framework.
Hard Systems Thinking
Checkland (1981) considers systems engineering and RAND systems analysis as hard
systems methodologies, because both are systematic in the sense that they proceed in a
rational and well-ordered manner. Moreover, he highlights the essence of their approach
to real-world problem solving.
“there is a desired state S,, and a present state,S,, and
alternative ways of getting from S, to S. ‘Problem
solving’, according to this view, consists of defining S, and
S, and selecting the best means of reducing the difference
between them.”
(Checkland 1981)
He argues that the distinguishing characteristic of all hard systems thinking is the belief
that real-world problems can be investigated in this way. We believe that most hard
methodologies are goal-orientated and assume the problem, i.e. ‘the what’, is given for
the goal state S;, e.g. to build a product to meet certain requirements, the usual objective
is find the best way of building the product to meet the requirements i.e. ‘the how’.
Mathematical techniques such as regression analysis can investigate alternative ways to
achieve state S;
We contend that SD can be applied to this type of real-world problem solving.
Furthermore, a key feature of SD is its explanatory strength, whereby it can produce the
best means, i.e. ‘the how’, to achieving S, and ‘the why’. Therefore, we consider SD to
be associated with hard systems thinking. We contend that the identification of the
problem, i.e. ‘the what’ is a significant weakness of hard systems thinking, and argue that
there is a need to combine SD with a soft methodology.
Soft Systems Thinking
When investigating social situations the problem, i.e. ‘ the what’, cannot be assumed as a
given. Stakeholders may have different views of what are the most important problems
that must be solved in order to improve the situation. Soft methodologies began to
emerge with the aim of attempting to assist in understanding the perspective of the
stakeholder, which may lead to relevant improvements in the area of concern.
We believe some soft methodologies use systems as mental constructs to help the
stakeholder’ facilitator make sense of a situation. Additionally, the frame of reference of
the modeller changes from observer to facilitator in order to understand stakeholders'
points of view. Most soft methodologies can be associated with soft systems thinking.
Bell et al (1999a) argue that the main aim of the soft systems thinker is to identify state So
problems, i.e. ‘the whats’ relevant to that social situation which require solving or
controlling, to produce a desired state S;. A brief overview of SSM is undertaken because
it is an important methodology and it has been argued that it should be combined SD
(Lane and Oliva 1998).
7. Soft Systems Methodology (SSM)
SSM (Checkland 1981) emerged from systems engineering. It is a systems-based general
learning methodology (see table 1) for investigating and improving a problem situation.
Stage Stage Objective
1and2__| Attempt to build the richest possible picture of the situation.
5 Aims to describe the nature of the chosen system.
4
5
Produces conceptual models of the defined system.
Compares conceptual model with actual situation in order to generated
debate with the stakeholders.
6 Outline possible changes that are desirable and feasible.
if Involves taking action based on stage 6.
Table 1: Key stages of SSM
DeMarco (1982) states that:
“You cannot control what you cannot measure”
(DeMarco, 1982)
Bell et al (1999a; 1999b) contend that the lack of use of metrics within SSM is a
significant methodological limitation. Furthermore, they believe the identification of
relevant problems and the metrication of them leads to more informed decision-making.
8. The Holon Methodology
Various Software Process Improvement (SPI) frameworks and methodologies assume all
issues of software quality revolve around the development process (survey in Bell and
Glijinis, 1997). Moreover, these SPI approaches are underpinned by representational
measurement theory (Fenton 1991). A formal definition of measurement is:
"Measurement is the process by which numbers or symbols
are assigned to attributes of entities in the real world in
such a way as to characterise them according to clearly
defined rules. The numerical assignment is called the
measure."
(Fenton et al 1995)
Measurement is concerned with capturing information about attributes of entities. An
entity can be an object, e.g. a product, or an event, e.g. a process. The attribute is the
feature or property of the entity that is of interest, e.g. effort, is an attribute of a process.
Basili and Rombach (1988) believe software metrics programmes have failed because
they have ill-defined objectives. To address this, Basili, with the collaboration of various
researchers, developed a goal-orientated measurement approach called GQM. Bell et al
(1999b) contend that GQM does not provide any guidelines or methods for identifying
problems and goals as perceived by key stakeholders of a software project. They contend
there is a need to augment GQM with a soft methodology that assists in identifying such
stakeholder problems which may require metrication. Merging SSM and GQM gives a
distinctive new soft approach - the Holon Methodology.
Checkland (1986) prefers to use the word “holon” rather than “system” for it highlights a
distinctive approach to investigating a social situation. Checkland attributes the word
holon to Koestler, who used it to express the principle of hierarchical structure. We
consider a holon to be an abstract representation of a social situation that captures all
problems. The methodology is used as a framework to discover relevant problems from
a stakeholder point of view, which are organised in a layered structure. We use Ackoff’s
analysis of the systems thinking method to support this framework. We originally
conceived the Holon Methodology as a post-mortem approach that improves the software
development process through examining completed software projects. An outline of the
key stages of the post-mortem approach is given.
Post-mortem Approach
The approach has four stages: Framing, Enquiry, Metrication and Action (see figure 2).
A preliminary interview with the person who has initiated an interest in the Holon
Methodology is undertaken in the framing stage. The enquiry stage aims to identify the
problems as perceived by the stakeholders. The metrication stage attempts to resolve the
identified problems to enable metrics to be collected through the use of the GQM
methodology. In the Action Stage templates are used to collect the software metrics,
which are stored in a website that is internal to the organisation. The data collected
increases the quantitative visibility of the situation and should facilitate stakeholder
action. Bell et al (1999b) have undertaken a case study that used three stages of the
methodology with an experienced software designer and developer.
(Burrell and Morgan 1979)
Enquiry Stage
2b.
Identify * the must” and "the
want’ problems
nubpemg onppxLow] UL,
opens
pe Gojarauerng
Hard Systems Thinking External W old
3.
Metrication Stage
3a. 3B.
Structuralisation
Validation
Tt
‘Action Stage
-— TB.
Mathematical -
ose Metrics Collection
Metrics Website
LL
Framing Stage
Avo,
uonay jog pur wstOR REAL
Templates
Figure 2: The Four Stage Model of the Holon Methodology (Bell et al 1999b)
Soft Teleological Approach
The method used by Dearing (1997) to produce a vision for the HE system prompted the
redesign of the Holon Methodology; we consider it to be a soft teleological approach. A
range of senior academics, industrialists and politicians were invited to join the ‘national
committee of inquiry into higher education’ chaired by Dearing. They investigated the
problems, i.e. ‘the whats’, associated with the current state S, of the HE system and
relevant environmental issues. The committee then constructed a vision of a desired state
S, for the HE system to meet the needs of a ‘learning society’, and finally agreed
recommendations, i.e. ‘the hows’, to achieve this vision.
Bell et al (1999a) believe the updated Holon Methodology, to be a ‘soft teleological
approach’ (see figure 3) with six stages, but four essential parts. The first part aims to
highlight the problems associated with the state of the current situation (So) as viewed by
the stakeholder. The second part identifies the most important problems to be solved ina
vision of a future state (S;). The third part lists the problems, e.g. no understanding of
recruitment costs, and a number of goals are identified, e.g. to understand academic
recruitment effort. Questions are developed to characterise each problem, e.g. how many
hours of academic input are required for student recruitment, and the generated metrics
are used to assess the problem. The fourth part involves improving the situation through
informed systemic decision-making in order to achieve the vision. Bell et al (2000) discuss
the redesigned methodology, and include a hypothetical case study investigating the
admissions process, in order to highlight the strengths and weaknesses of the Holon
Methodology.
Figure 3: Overview of the Key Parts of a Soft Teleological Approach
We believe the updated Holon Methodology has two significant strengths. Firstly, it
assists in developing a desirable vision of a future state S;. Secondly, a relevant metrics
programme can be derived through the approach.
9. Holon Planning and C osting Framework
We contend that an informal SPI approach to controlling and improving HE systems is
most appropriate, complementing a systemic view of planning. The underlying principle of
the Holon Planning and Costing Framework is:
To identify an agreed future and to design ways of bringing it about within cost
constraints
The Holon Planning and Costing Framework combines a soft methodology (Holon) and a
hard technique (SD). The Holon Methodology addresses ‘the who’, ‘the what’, ’the
where’ and ‘the when’ type questions at the current state So, and generates a vision of a
desired state Si. Additionally, this produces a relevant metrics programme, and the
collected metrics can be used as dynamic behaviour patterns. The explanatory capability of
SD tackles ‘the how’ and ‘the why’ type questions. Table 2 illustrates the most important
traits of this framework.
An holistic view of a situation.
The use of a soft methodology to enable the capture of the stakeholders’ point of view.
Controlling the effects of hounded rationality.
The researchers’ role as facilitator.
Development of a desirable and feasible vision.
Creation of a relevant metrics programme.
Emphasis on the SD model ownership problem.
Producing the ‘best solution’ to achieve the vision given the cost constraints.
The continuous use of an SD model for examining various ‘what-if’ scenarios.
wloo}a]o}an}is} oo}
Table 2: Key traits of the Holon Planning and Costing Framework (adapted from Bell et al
1999c).
The Holon Planning and Costing Framework is being applied within SCISM at South
Bank University in an exploratory case study. A review of QAA and the RAE literature
has assisted in the identification and labelling of the relevant holons, i.e. ‘the where’. We
have identified relevant academic and administrative staff, i.e. ‘the who’, participants in
the planning process. Individual and group meetings have been held to identify the
problems, i.e. ‘the whats’, associated with the current state Sp of SCISM. This has led to
the formulation of an agreed desired state Sj, i.e. the vision (see figure 3), and an
appropriate metrics programme (Warwick et al 2000a).
We believe that to ensure model ownership various verification and validation tests must
be applied throughout the planning process. Warwick et al (2000b) have produced a table
of verifications and validations, which are selected depending on the objective of the
meetings. Further consultations are scheduled in order to develop a SD model to the
satisfaction of the stakeholders. In this way, the insights gained from the SD model will be
meaningful to them, which should facilitate action to improve the situation and achieve the
agreed desired vision. We consider this work as the initial part of a continuous planning
and costing programme.
10. Conclusion
The Rudyard Kipling quotation (following the abstract) confirms our view that soft
methodologies complement hard techniques, because they examine different types of
questions. We believe the Holon Planning and Costing Framework addresses all the
questions identified by Kipling. Furthermore, we contend that representational
measurement theory (Fenton 1991) cements soft and hard systems thinking.
This altemative planning approach should assist in improving teaching and research
quality given the cost constraints for it aims to empower the stakeholders. We believe the
framework needs maturing through practice, in order to highlight its deficiencies. It is
likely that the underpinning theory and its practice may be strengthened through broader
interdisciplinary research encompassing Psychology, Software Engineering, Servo-
Mechanics Theory and Organisational Behaviour.
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