|
Dash, D. P. (1999). Vocabulary of agency: Development and
assessment of a generic conceptual framework to guide action-oriented research
in multiple domains [PhD Thesis]. |
Chapter 4
Family
of Management Systems Literature
4.1
Introduction to the Review
The family of action
research literature reviewed in Chapter 3 does not exhaust the entire range of
literature on how a research-orientation and an action-orientation might be
combined in a systematic way. The present chapter reviews the family of management
systems literature where the conceptualisation of action-oriented research
seems to have taken a unique direction characterised by the variously
interpreted notion of a system.
The label management
systems refers to a growing body of academic literature using systems ideas
(e.g., ideas of system—open and closed, boundary, elements and relations,
complexity, communication, control, self-regulation, hierarchy, structure,
emergent property, evolution, etc.) to study and address the problems of
management in organisations and society. This literature is usually identified
within broader category labels such as ‘systems approach’, ‘systems thinking’,
‘systems movement’, ‘systems research’, ‘systems practice’, ‘systems theory’,
‘systems and cybernetics’, etc. Some commentators have used the label ‘systems
movement’ to refer to the broad intellectual landscape within which this
literature has flourished (e.g., Checkland, 1981; Flood and
The review will focus on
the conceptual elements discussed in the literature which might be used later
to build a general conceptual framework to guide action-oriented research. It
is not the aim to describe a number of management systems approaches in detail
covering the associated tools and techniques, their strengths and weaknesses,
etc., but to focus on how an approach reconciles an action-orientation within
research (or even a research-orientation within action). Special
attention will be paid to ideas which address the difficulties of action
research discussed in the previous chapter.
4.2 Systems
Movement
There seem to be many
different interpretations of how and why the systems movement has emerged. It
has been linked with an awareness about the need to study the
interconnectedness of phenomena and perhaps also of the mechanisms that
generate the phenomena (e.g., Ackoff, 1981; Capra, 1982; Churchman, 1979; Flood
and
The movement is generally
traced back to the 1940s (although it is known that the Russian thinker A.
Bogdanov had pre-empted some of the systems ideas between 1912 and 1917)
(Capra, 1997, Chapter 3). Early work on systems was done in two somewhat
distinguishable traditions of inquiry, namely general systems and cybernetics.
One of the core notions of the general systems tradition was that of an open
system (von Bertalanffy, 1950; also see Systems Theory at
http://www.ccens.com/systhe.htm). Similarly, one of the core notions of the
cybernetics tradition was that of control (Ashby, 1964; Wiener, 1961;
also see Homepage of W. Ross Ashby at
http://www.gwu.edu/~asc/biographies/ashby/ashby.html; Wiener: Ideas at
http://www.well.com/user/mmcadams/wiener.html). The notions of homeostasis
and self-regulation were discussed in both the traditions, as the
notions were found to be of potentially more general (and perhaps,
inter-disciplinary) interest than commonly recognised among researchers at that
time.
Both the traditions seemed
to evince an interest in studying a general set of problems of research
obtaining in a wide range of disciplinary fields. The group of scientists who
had formed the International Society for General Systems Research in
1954 (see International Society for the System Sciences pages at
http://www.isss.org/) utilised the open system notion in studying a wide
range of phenomena, including biological, organisational, and social phenomena
(Emery and Trist, 1965; Katz and Kahn, 1978). The defining characteristics of
open systems (namely importation of energy, throughput, output, cycles of
events, negative entropy, information input, steady state or dynamic
homeostasis, differentiation, integration and co-ordination, and equifinality)
were instantiated in separate areas of inquiry. It seemed as if the language
of general systems was capable of unifying knowledge from different disciplines
and fostering transfer of knowledge among them. It seemed to provide a way of
abstracting domain-independent knowledge from a set of domain-specific
knowledges. A major product of this type of approach was the
conceptualisation of ‘living systems’ (Miller, 1978). This attempted to
abstract the defining characteristics of living systems from seven different
domains (namely the domains of cell, organ, organism, group, organisation,
society, and supra-national system). This type of activity within the systems
movement has sustained an interest in studying general systemic principles
manifest in different phenomenal domains, and applying these principles in
finding and rectifying dysfunctions that might reduce a system's effectiveness
in achieving its purposes (see, e.g., Applications of Living Systems Theory at
http://www.newciv.org/ISSS_Primer/asem05jm.html). It was generally expected
that this type of strategy should result in the development of a corpus of
knowledge (e.g., about living systems) and an increased ability to
diagnose and improve, or design, systems in different domains.
The research perspective
involved here might be compared with the more traditional research perspective.
For example, the characteristics of living systems might be seen as part of the
natural order of things; once discovered these can be used
for various practical purposes. These characteristics do not seem to depend
upon the values (or the actions) of either the researcher or the user of
the result. Such a system, even if artificially designed, might thereafter
behave as if it were a part of the natural order of things, although it might
require some kind of maintenance effort.
That some systems could
pursue their own values (goals or purposes) was a crucial issue within the
tradition of cybernetics (Ashby, 1964; Wiener, 1961). Early cyberneticians had
shown that apparent goal-seeking behaviour might arise out of a feedback
structure, e.g., that of an ‘error-controlled regulator’. Such a structure
would involve a ‘black box’ which transforms inputs into outputs, a
‘controller’ that compares the outputs with a ‘target’ parameter and computes
(using a model of the ‘black box’) how the inputs should be altered in order to
reduce the error between the output and the target, and supplies that input to
the ‘black box’. Ashby and Wiener had highlighted the generality of the
principles of cybernetics in studying goal-seeking behaviour in a wide range of
phenomena—‘in the animal and the machine’.
Later on, the language of
cybernetics was used to study patterns of regulatory behaviour in many domains
including organisational and social domains (e.g., Bateson, 1979; Beer, 1979;
1985). Over the years, there has been a spectacular expansion of the field of
cybernetics and applications have been found in a wide range of areas, e.g.,
robotics, computing, bio-medical applications, environmental studies,
management, social planning and administration, economics, international
relations, etc., accounts of which have been reported in various systems and
cybernetics journals (see Cybernetics and Systems Journals page at
http://pespmc1.vub.ac.be/JOURNALS.html). The interest of cybernetics in
studying the various implications of self-regulation have been manifest
in these applications.
A cybernetically
self-regulating system might or might not be a part of the natural order of
things. It might have to be designed, for example. But, once a self-regulating
system is designed (or brought forth into the world) it might thereafter be
seen as part of the natural order of things, and therefore, could be observed
as such by an outside observer. Of course, such a system might also require
some kind of maintenance effort. Applications and explorations of cybernetic
thinking in certain domains (e.g., human knowing, co-ordination systems,
organisational design, social administration, etc.) have indicated the need for
conceptualising alternative forms of interaction between an observer and a
system. In one such form of interaction the system might be capable of
observing itself and/or observing the outside observer, i.e., it might be an observing
system (von Foerster, 1984). The contemporary discussion on second-order
cybernetics pays attention to this type of system and interaction among
such systems (Cariani, 1993; von Foerster, 1984; Glanville, 1993; Reyes, 1995,
Chapter 3; Umpleby, 1990; 1991; 1994; van de Vijver, 1992; de Zeeuw, 1993a;
also see Cybernetics & Human Knowing: A Journal of Second Order Cybernetics
& Cyber-Semiotics at http://www.db.dk/dbaa/sbr/cyber.htm). The issue of
whether anything like a part of the natural order of things emerges from such
an interaction has been discussed in this area.
In both the traditions
of the systems movement (i.e., general systems and cybernetics) discussed
above, there appears to be an interest in either discovering or postulating
(and designing) a system with stable characteristics such that it displays (or
acquires) a status equivalent to the natural order of things. This could be interpreted as their
‘scientific’ orientation. That might be the reason why the systems approaches
needed no great justification to be applied to numerous practical situations
requiring some kind of improvement. There have emerged organisations
specialising in providing consultancy and training in applying management
systems approaches with a view to improve organisations and communities (see,
e.g., Phrontis Limited at http://www.phrontis.com/). However, applied systems
work has brought in issues which have necessitated further elaborations of
systems thinking. That is what one notices in the contemporary literature of
management systems. This literature has revealed certain issues in using
systems notions to achieve local outcomes (valued by some client). Whether and
how such applied work might produce some kind of research outcome as well will
be the focus in the present review. Some of these approaches that present a
more or less contemporary picture of management systems thinking will be taken
up for review in the next section. The main aim will be to explore further how
applied systems work inter-relates action-oriented and research-oriented
interests together.
4.3
Management Systems Approaches
4.3.1 Operational Research/Management
Science
Operational
Research/Management Science (OR/MS or OR) consists of an ever growing set of
methods and tools to effect improvements in the conduct and co-ordination of
operations, typically within organisations. This interest is borne out by the
military roots of OR, the interests of the professional societies promoting OR
(starting with the OR Society in the UK, founded in succession to the
Operational Research Club which was set up in 1948, see
http://www.orsoc.org.uk/ors/index_f.html), and applications of OR in private
and public sector organisations in many countries of the world (see OR/MS
Societies and Regional Groupings at
http://www.maths.mu.oz.au/~worms/soc/soc.html).
There were many precursors
to OR/MS in the arena of systematic support to the activity of co-ordinating
organised work. The double entry system of book-keeping developed by the
Italian mathematician and friar Luca Pacioli in 1494; Charles Babbage’s work on
industrial productivity in the UK during the 1830s, the scientific
management approach of Frederick Taylor in the US since the 1890s, and time
and motion study (especially the work carried out for the cotton textile
industry in the UK by the Shirley Research Institute from the 1920s onwards)
could be mentioned among them (Duckworth, 1962, p.12; Keys, 1991; Kirby and
Capey, 1998; see http://www.arthurandersen.com/ for the history of accounting).
A significant amount of
work has been (and is being) done to review the origins of OR and its
developments before, through, and after the period of the second world war
(e.g., Keys, 1991; Cook and Shutler, 1991; Ranyard, 1995; Kirby and Capey,
1998). These as well as text books and guide books on OR (e.g., Duckworth,
1962; Ackoff and Sasieni, 1968; Budnick, et al., 1988; Hillier and
Lieberman, 1990) have characterised OR by its emphasis on modelling the
real situation in order to identify optimal states/levels of an
operation.
It is the purpose here to
consider how OR adapts the task of science/research to make itself useful in an
operational situation. OR workers have tried to give various interpretations to
the term ‘research’ in OR. Daellenbach, et al. (1983) have stated:
"It is not scientific research, with its connotation of advancing
fundamental knowledge in some science. … The objective is to improve the
effectiveness of the system as a whole" (p-1). Hillier and Lieberman
(1990) have argued that OR involves creative scientific research into the
fundamental properties of operations. They have used the formulation of Ackoff
(1956) to argue that the implementation of an OR solution might itself be a
test of the hypothesis that the conclusions (solutions) obtained from the model
are also valid for the real problem.
OR texts have emphasised
the importance of carefully observing the real problem situation (e.g., Hillier
and Lieberman, 1990). There does not appear to be much debate within the early
OR literature regarding what constitutes data in an OR study although
disquieting concerns have been expressed (e.g., Churchman, 1970). Statements
obtained from primary and secondary sources within the client organisation
(Graham, 1984), and perhaps also from outside, seem to constitute data for OR
modelling. One of the characteristic features of OR is the way these data are
used. The data are used for the purpose of modelling. An OR model is
meant to be a ‘model of the system’ (e.g., Duckworth, 1962, p.19); it is supposed
to ‘represent the system’ (e.g., Ackoff, 1956); and it is usually a ‘formal
model’ (Pidd, 1991). The information created out of the model is typically
called a ‘solution’ in the idiom of OR. The ‘solution’ of an OR model refers to
a specific state of the system, or a specific set of outputs of the
model given a specific set of inputs. It is that state (or that set of inputs
and outputs) which is supposed to be of special interest to the client
organisation—the state that the client organisation might not have identified
without the contribution of the OR study.
It is sometimes expected
that the activity of OR will result in the generation of knowledge regarding
‘the fundamental properties of operations’ (the expression is from Hillier and
Lieberman, 1990, p-5). There is something like a ‘body of knowledge’ in OR
which is transferred in professional training, and which continually grows by
encompassing new formal models of operations, modelling and solution
strategies, as well as consulting skills. OR has strongly emerged as a profession
in the
Churchman (1970; 1979) has
highlighted what he labels as the ‘irrational’ side of the profession,
mentioning the problems of ‘observing a system’, ‘peculiar mixture of attitudes
about data’, problem of identifying the ‘whole relevant system’, ‘deeper
problem of morality’, opposition to ‘political power structures’, and
inflexibility associated with institutionalisation of the profession. Ackoff
(1979) has highlighted various inadequacies in the overall scheme of OR,
pointing out the difficulties of ensuring the reliability of data,
simplifications involved in modelling, short life span of optimal solutions,
omission of aesthetics, OR’s ‘pretension’ of interdisciplinarity, and its
failure to take all stakeholders into account. That everything might not be
going well with the profession of OR, can be gleaned from some of the recent
studies concerning the state of the profession (e.g., Fildes and Ranyard, 1997;
Ranyard, et al., 1997; Ranyard and Fildes, 1998). Discussions about the
characteristics of OR have appeared consistently in the literature for over
more than two decades now (e.g., Dando, et al., 1977; Jackson, et al.,
1989; Jackson and Keys, 1987; Keys, 1991; 1997; Rosenhead, 1989; White and
Taket, 1996.) One of the outcomes of these discussions about the nature of OR
has been the emergence of what is now labelled as ‘Soft OR’ (Rosenhead, 1989),
which retains the professional model of OR but introduces new features into the
methodology.
The following issues
might be noted here from the point of view of this review. OR is interested in
action, in the sense that it is client-oriented. The objectives of the client
determine (though not entirely) what system is to be modelled, what data are to
be collected for the purpose, and finally what state of the system is to be
identified as the most desirable given the client’s objectives. OR is also
interested in research, at least in two different senses. Firstly, at the level
of the local, OR is interested in identifying the particular state of the
chosen system that would be the most satisfactory in fulfilling the client’s
objectives. Secondly, OR is also interested in strengthening its body of
knowledge, i.e., its library of formal models, solution procedures, and its
general vocabulary, in an ongoing way. OR/MS certainly appears to offer an
approach for action-oriented research—one that highlights the role of formal
models in achieving client-oriented results as well as results of wider
professional interest.
4.3.2 Soft Operational Research
As mentioned before, Soft
Operational Research (Soft OR) emerged as a response to deal with certain
problems with the OR/MS approach (Rosenhead, 1989). It was noticed during the
1970s that the traditional OR approach seemed to work well under certain
conditions; e.g., it worked where,
All these point to the
difficulties associated with OR practice. There is the problem of identifying
what constitute legitimate data in certain situations (e.g., involving
‘ill-structured problems’, ‘wicked problems’, or ‘messes’) (Simon, 1973).
Similarly, Soft OR casts doubts on the possibility of a single uncontested
representation of a problem situation, thus putting the classical OR notion of
modelling in jeopardy. Traditionally OR had served clients like defence
organisations, private and public sector organisations, etc., which were formal
organisations with rather well-defined structures of roles and relationships.
When OR was taken to non-traditional clients such as ghettos, youth clubs,
housing co-operatives, community service organisations, etc., there was a
difficulty in applying the methods of OR (Rosenhead and White, 1996). Even
within formal organisations, sometimes ‘ill-structured’ problem situations (e.g.,
strategic problems) seem to emerge that make it difficult to apply traditional
OR techniques (Rosenhead, 1996).
Soft OR seeks to resolve
this difficulty by introducing something else into the situation that might
make the situation again like the traditional, whereupon traditional OR might
be applied. What is typically introduced is problem structuring. It has
been argued that sometimes problem structuring (or ‘issue structuring’) might
itself be an adequate support to the client, implying that it might not be
followed up with more conventional OR modelling.
Different kinds of ‘problem
structuring methods’ (PSMs) have been proposed in Soft OR (Rosenhead 1989;
1996). Some of the methods presented in the literature are: Hypergame Analysis,
Interactive Planning, Metagame Analysis, Robustness Analysis, Soft Systems
Methodology (SSM), Strategic Assumption Surfacing and Testing (SAST), Strategic
Choice Approach (SCA), and Strategic Options Development and Analysis (SODA).
From the variety of these methods, it would seem that Soft OR might be a broad
and general approach to tackle ill-structured problem situations. Therefore, it
might be more appropriate for this review to discuss Soft OR in general terms
rather than focusing on the specific methods. (One of the methods, i.e., SSM,
is reviewed separately, in Sub-section 4.3.7, as it seems to have been given
special attention in the literature, independent of its association with Soft
OR.)
A study of these ‘problem
structuring methods’ indicates some of their general characteristics (Rosenhead
1989; 1996). These methods visualise a situation in which there is usually a
‘facilitator’ (or a team of ‘facilitators’) and a client group—typically
involving multiple actors, having multiple or unclear priorities, multiple
perceptions and uncertainties about the nature of the problems to be addressed,
and multiple viewpoints and uncertainties about what would amount to a
satisfactory solution. Soft OR methods seem to intervene in this situation with
an aim to improve interaction and co-operation among actors, reduce differences
in terms of perceptions, preferences, priorities, etc., guide constructive
debate among the actors, develop images of desirable future for all the actors
involved, orient the actors towards some desirable direction for action, etc.
In this effort, different methods seem to contribute differently. Hypergame
Analysis focuses on a better appreciation of the differences among the actors.
Interactive Planning helps in developing images of the ideal future. Metagame
Analysis structures the interaction among the actors such that there is some
coherence in terms of preferences. SSM also structures the interaction among
participating actors in order to generate and guide constructive debate
especially about feasible and desirable changes in the situation. SAST provides
a method for guiding constructive debate about strategies and assumptions with
the aim of reducing the differences by mutual adjustments. SCA helps
participants identify priority areas by exploring the interconnectedness among
decisions and enables them to develop action plans. SODA uses the device of cognitive
mapping to help participants externalise their perceptions about the
problem situation and develop constructive debate about actions to be taken.
Robustness Analysis helps the actors maintain useful flexibility while planning
for the future despite uncertainties and changing environments.
The approach of Soft OR has
been compared with the ‘process consultancy’ approach used within the Organisational
Development (OD) literature (Rosenhead, 1989, p.348). Both Soft OR and process
consultancy recognise and emphasise the existing experience and knowledge of
the participants as a resource in transforming the group, situation, or
organisation. The general strategy used by both approaches is to promote
interaction among actors, socialise and purposefully organise the knowledge
previously fragmented among the participants, promote thinking and dialogue,
and generate commitment towards action. In order to highlight the
distinctiveness of Soft OR methods in comparison with OD, Rosenhead has argued
the following:
Each
member of the PSM family incorporates as a core element the explicit modelling
of cause-effect relationships. This gives PSMs their unambiguous operational
research identity. It distinguishes them, for example, from non-OR modes of
group working, such as organisational development (Rosenhead, 1996, p.120).
It might be worthwhile to
notice that the type of ‘explicit modelling of cause-effect relationships’ in
the more conventional OR is expected to produce models that ‘represent the
system’, but Soft OR seems to produce a different type of model. For example,
the advocates of SODA have clarified the nature of the models they are
concerned with:
…
we were concerned with finding means of understanding and representing
explicitly the way individuals perceive their world, that might be helpful to
them in permitting a self-conscious reflective dialogue with their own thinking
(Eden, et al., 1979, p.104).
Interest in Soft OR has
revived an earlier interest in exploring the relationships between OR and the
social sciences (see Journal of the Operational Research Society, 44,
6, Special Issue on the Interface between OR and the Social Sciences, 1993).
One of the aims of this exploration is to identify the conditions for
successful interventions, so as to sustain ‘systematic improvement’ in the
field of operational research (Eden, et al., 1993, p.532). Among the
various areas of the social sciences, the study of ‘facilitated work groups’
appears to be of particular relevance to Soft OR (Phillips and Phillips, 1993).
Following the insight in this area of research, the facilitator seems to have a
more active role than a conventional researcher. The facilitator becomes a
participant in the group that s/he is facilitating and plays an important role
in influencing the process so as to make the group work effectively.
From this, it would seem
that Soft OR might be action-oriented in two different senses. Firstly, Soft OR
is client-oriented, as is traditional OR. The outcome of a Soft OR exercise is
expected to be useful locally, to the satisfaction of the client body. But,
there might be a second sense in which Soft OR is also action-oriented. The
Soft OR facilitator is not limited to the somewhat passive role of collecting
data and producing representational models. The facilitator has to actively
influence the group process in order to make the group become more like a
collective capable of acting in solidarity. In every instance of a Soft OR
application, there is the expectation of a local outcome that would be valued
by the clients, e.g., a structured issue, a decision, a plan, a strategy, etc.
Additionally, there is also the potential of an expansion in the tools and
techniques for group facilitation, a developing understanding of the conditions
of success of the Soft OR approach, and a progressive elaboration of the
general vocabulary used in Soft OR type of work, in an ongoing way. As a
possible approach to action-oriented research, Soft OR seems to highlight the
importance of the researcher’s action in actively creating a collective
capable of acting in solidarity.
4.3.3 Systems Analysis and Systems
Engineering
The term ‘Systems
Engineering’ is said to have become current in the 1950s (Checkland, 1981;
1989), although quite complex technological systems had been built by people
over the ages (e.g., ships, irrigation systems, urban settlements, etc., in
ancient civilisations, and later, railway systems, power generation and
transmission systems, telephone networks, etc.) Systems Engineering strives to
conceptualise in a systematic fashion the general pattern of conceiving,
designing, and implementing systems of this type. The process generally starts
with the specification of the purpose to be served by the object or system.
Systems Engineering then works back from these specifications to design a
system that would achieve these specifications using minimum resources, in an
efficient and effective manner, without too many negative side effects.
Jenkins (1969) has
described the Systems Engineering approach in detail. The notion of ‘system’
seems important in his account. In this scheme of things, a system could be
designed to achieve an overall objective. Systems could have multiple
objectives which might be mutually conflicting in some cases, necessitating
certain compromises. A system would typically form part of a hierarchy of
systems, in which there might be interaction between systems at the same level
and at different levels. The functioning of a system would depend on these
interactions.
The notion of
‘engineering’, in Systems Engineering, refers to designing, constructing,
‘knitting together’, and operating ‘works of public utility’. That makes
Systems Engineering the activity of conceiving, designing, constructing,
‘knitting together’, checking, and operating individual systems so that jointly
they perform efficiently and effectively as an overall system in pursuit of the
prescribed objective.
The role of a systems
engineer has been compared with that of a general medical practitioner who is
supposed to look after the general health of patients, but might seek
specialist medical knowledge from time to time (Jenkins, 1969).
The distinctiveness of
Systems Engineering, over engineering per se, seems to lie in the
broader view it takes in dealing with questions of operational efficiency and
effectiveness. It seems to be focused on optimising overall criteria,
associated with the functioning of a system. Another distinctive feature of
Systems Engineering is that the approach might be extended to apply over a
range of different ‘systems’, from technological to organisational and societal
systems.
The process of Systems
Engineering can be visualised in terms of four stages, although these might not
necessarily be sequential (Jenkins, 1969):
(i) Systems Analysis:
This stage involves a definition of the system to be engineered. It involves
identification of various sub-systems and their interactions, and the wider
system which contains the system being engineered. The objectives of the wider
system clarifies the role and responsibility of the system being engineered.
This helps clarify the objectives of the system being engineered as well as
performance criteria for the system. If objectives cannot be clearly defined in
the beginning, analysis can start with a working definition which might be
reconsidered later if possible.
(ii) Systems Design:
This stage involves building a model of the system that is being engineered.
The model is built for the purpose of designing actions that will optimise the
system. The model is used to compute the values of the performance criteria
under different modes of operation, and an optimum solution is sought. A
control system is designed to maintain optimal operation of the system under a
varied range of conditions, so that the overall reliability of the system’s
operation would remain at a desirable level.
(iii) Implementation:
Construction of the designed system is undertaken at this stage. It is
necessary to ensure that system builders understand the design in order to deal
with uncertainties that might arise during implementation. Various kinds of
project scheduling support might be provided to the system builders at this
stage.
(iv) Operation: At
this stage, various kinds of support are provided to the users of the system.
Documentation about the system, user manuals, training, etc., are usually
provided. Performance of the system is assessed from time to time.
Re-optimisation might be needed after a period of time. Continued improvement
of the system might be needed in a changing environment.
The sort of thinking
embodied by Systems Engineering was also incorporated by a whole group of
approaches for systematically achieving prescribed aims in an efficient and
effective manner. Many of these approaches were developed during the 1950s and
1960s and were used in areas of engineering, planning and management, public
administration, etc. ‘Systems Analysis’ refers to a class of these approaches
said to have been initiated by the RAND Corporation although later developed by
many different groups (Checkland, 1981; 1989; Miser, 1995; Miser and Quade,
1985; 1988; see Classic RAND Research page at http://www.rgs.edu/Classic.html).
Quite like Systems Engineering, Systems Analysis also starts with the statement
of an objective or a set of objectives. The steps followed typically involve
the identification of alternative systems for achieving the objectives, estimation
of the resources required by each of these alternative systems, use of models
to assess the efficiency and effectiveness of these alternatives, and choice of
one alternative on the basis of some preference criteria.
Both Systems Analysis
and Systems Engineering provide a general way of thinking about practical
situations requiring the creation of a system that achieves some pre-defined
purpose. This highlights their action-orien]\=tation. The research-orientation
might be seen in their use of systems and cybernetics ideas (e.g., system,
sub-system, environment, self-regulation, control, etc.). Research results
might be expected with respect to the general characteristics of this
particular class of systems, the methods of their optimisation, the conditions
of their smooth operation, etc. One of the research results to be taken up
later in this review (in Sub-section 4.3.7) pertains to the need for extending
the research vocabulary associated with Systems Analysis and Systems
Engineering to make it more suitable for applications dealing with managerial
systems in organisational and social situations (Checkland, 1981, Chapter 5;
1989). As a potential model for action-oriented research, Systems Analysis and
Systems Engineering highlight the importance of following a particular image
of systems (i.e., those which can be designed, built, and operated to
accomplish specified objectives) in conducting practical projects.
4.3.4 Organisational Cybernetics
Organisational Cybernetics
has emerged as a management systems approach by adopting cybernetic notions for
the purpose of organisational and social management, especially by focusing on
the Viable System Model (VSM) postulated by S. Beer (Beer, 1979; 1985; Espejo
and Harnden, 1989; Espejo, et al., 1996; Flood and Jackson, 1991a;
Jackson, 1991). Besides the VSM, there seems to be a wider discourse on social
and organisational cybernetics, around the notions of sociocybernetics,
autonomy, autopoiesis or self-production, self-organisation, second-order
cybernetics, observing systems, etc. (Achterbergh, et al., 1997; Geyer
and van der Zouwen, 1986; Jantsch, 1980; Willke, 1990; see The Challenge of
Sociocybernetics at http://pespmc1.vub.ac.be/Einmag_Abstr/FGeyer.html and
http://www.unizar.es/sociocybernetics/indice.html; Autopoiesis Related Web
Sites at http://server.snni.com/~palmer/autopoiesis/websites.htm). However,
from the point of view of management systems, the VSM still seems to remain an
important instrument in the operationalisation of the organisational cybernetics
approach and has produced a substantial body of management systems literature
(the journal Systems Practice devoted a Special Issue to this topic in
1990, Volume 3, Number 3). Besides, the current literature related to the VSM
seems to reflect some of the ideas of the wider cybernetics discourse (e.g.,
Harnden, 1990). This review will primarily focus on the VSM-related literature
in organisational cybernetics.
Beer has defined
cybernetics as ‘the science of effective organization’ (Beer, 1975, p.425). In Beer’s
version of organisational cybernetics, the role of scientific object is played
by the notion of ‘viable system’, the postulated archetype of effective
organisation. A system is said to be viable if it is able to adapt effectively
to environmental changes although the changes are unforeseen. The background
research and thinking behind such a notion has been presented in the literature
(Beer, 1979; 1984). The VSM might be taken as an elaborate and formal
description of the necessary components of a viable system, starting with the
notion of an operational element (said to be a basic potentially viable
system) consisting of an operation (O), in which is embedded a management unit
(M), an environment (E) in which both are embedded, and a process of variety
engineering between O and M, and O and E (Beer, 1979, Chapter 4). Using a
notion of recursion, the model visualises that a viable system might
include a collection of operational elements—together referred to in the model
as System 1. A management unit is visualised for the entire System 1 (i.e., the
collection), containing Systems 2, 3, 4, and 5, each having specified roles and
orientations. This management unit, containing Systems 2, 3, 4, and 5, would
look after the co-ordination of operational units (System 2), control and
regulation of the affairs of the System 1 giving it a here-and-now orientation
(System 3), interaction with the outside environment of the System 1 giving it
a future orientation (System 4), and dealing with issues not dealt with by any
of these, e.g., steering a balance between the here-and-now and the future
(System 5). These systems and their interactions are elaborated within the VSM,
including the necessary communication channels operating between them (Beer,
1979; 1985).
Many applications of the
model have been reported (e.g., Espejo and Harnden, 1989). The most common type
of application of the model seems to be in diagnosis (e.g., to assess whether a
given organisation contains all the elements of the VSM or not). The model has
also been applied in designing information systems (e.g., Murthy, 1994) and
designing a management structure for complex computer networks (Latin, 1991).
The applications have also included studies in which the role, mission, and
structure of entire organisations have been clarified using the model (e.g.,
Flood and Zambuni, 1990; Leonard, 1989). Viable systems thinking has also
yielded useful insights for organisational theory, e.g., in reinterpreting the
notion of organisational effectiveness (Schwaninger, 1990).
In the recent literature of
organisational cybernetics, there seems to be an exploration of alternative
uses of the model. There seems to be a new emphasis on the use of the VSM
vocabulary in a conversational process within an organisation (Harnden, 1990)
and its use as a ‘tool for self-constructing organizations’ (Espejo, 1996).
This exploration is expected to indicate alternative ways of translating the
insights of VSM into organisational contexts, rather than imposing the model on
the organisational members.
This area of
organisational cybernetics seems to offer many insights for a richer
comprehension of action-oriented research. Its reliance on the field of
cybernetics is one of its strengths. The manner in which the basic cybernetic
notion of a ‘self-regulating system’ is extended and generalised in terms of a
‘viable system’ is noteworthy. This does highlight the possibility of deriving
a formal model (i.e., the VSM) based on a general notion (i.e., ‘viable
system’) and the possibility of instantiating the formal model in material
terms in order to realise local results for specific clients. Obviously, the
process might not be as straightforward as it sounds. There could be many
uncertainties, speculations, and unknowns involved in it. The literature also
indicates the possibility of the general notion becoming something like an
imposition in a local situation (
4.3.5 Socio-Technical Systems Thinking
Herbst (1974) traces the
development of Socio-Technical Systems thinking to the coal mining studies
carried out in the 1950s in the
Trist and Bamforth (see
Herbst, 1974, Chapter 1), who had reported the first coal mining study in 1951,
had interpreted the situation through a model that introduced the basic notion
of a socio-technical system. According to them, the quality and the
quantity of output in any work organisation depended on two distinguishable
aspects of the organisation: the technological system and the social structure
of the work system. They viewed the psycho-somatic disorders, and interpersonal
and inter-group conflicts observed in the organisation as a consequence of the
social structure of the work system. They hypothesised that the social structure
of the work system was partly influenced by the technological system. This led
them to formulate the notion of joint optimisation, i.e., optimising the
performance of the work organisation by modifying both the technical and social
systems in a suitable way. The notion of organisational choice began to
emerge after a second series of coal mining studies carried out by Trist and
his collaborators. The notion highlighted the degree of choice available to an
organisation with respect to the type of form it could take, for a given
production technology. Later in the 1960s, especially after the socio-technical
thinkers became involved with the Industrial Democracy Project of Norway
(Thorsrud, 1977), the notion of technological choice began to be
discussed.
The notion of technological
choice suggested that the production technology need not be taken as a given
for any organisation; it could be chosen from the point of view of fulfilling
certain objectives other than purely technological. This involved the notion of
the ‘social ecology of industry’. The basic search seemed to be for a way of
jointly optimising the technological and the social systems of work
organisations such that, locally, the work organisation performs
satisfactorily without creating human costs in the form of psycho-somatic
disorders, and interpersonal and inter-group conflicts, etc., and globally,
it leads to a ‘social ecology of industry’ that supports such jointly optimal
work organisations.
This type of focus led the
socio-technical thinkers to realise that organisations might be viewed as open
systems which had to survive in different types of environment, some of which
might not be passive or undifferentiated (Emery and Trist, 1965). They have
observed cases which illustrated ‘what is meant by the environment becoming
organised at the social level’. Describing the plight of a vegetable canning
company that had invested a very high amount of money in a new factory only to
find that its market share was dropping quickly while the factory was being
built, Emery and Trist have argued:
They
[the managers] failed entirely to appreciate that a number of outside events
were becoming connected with each other in a way that was leading up to
irreversible general change (Emery and Trist, 1965, p.24).
Following this line of
thinking, Emery and Trist have proposed four ideal types of organisational
environment, namely placid randomised, placid clustered, disturbed
reactive, and turbulent environments. They have argued that the
survival of an organisation would depend upon the compatibility between its
strategy and the type of environment it confronts. In the latter three types of
environment, the survival of an organisation would depend upon what other organisations
in its environment do. In the placid clustered situation, survival becomes
critically linked with what an organisation knows about its environment. But,
this strategy does not work in a disturbed reactive situation, where what one
knows can also be potentially known by the others in the environment.
Therefore, the struggle for survival would include calculating reactions of the
others, and planning counter-actions, in a game-like affair. In turbulent
environments, ‘the "ground" is in motion’, where organisational
actions and interactions might lead off in unpredictable ways, and where
actions and their results might not remain linked in clear patterns. Emery and
Trist have given an interesting proposal to deal with the vagaries of turbulent
environments. According to them, a possible solution to this is the emergence
of values that have overriding significance for all members of the field.
In this they have used the Lewinian notion of ‘power fields’. It is the
emergence of such fields which would make the environment ‘simplified and
relatively static’ again.
The development of
thought on Socio-Technical Systems suggests some fundamental insights
concerning action-oriented research. Different types of action-orientation are
involved here. Like the other management systems approaches, there is a
client-orientation. Positive local outcomes are expected from proper
organisational or technological choice. It should, for instance, improve
performance, reduce human costs, etc. But, insights in this literature indicate
how and when such local improvements cannot be sustained, e.g., in reactive and
turbulent environments. Socio-Technical Systems thinking suggests that research
should contribute not merely through local improvements, but also by indicating
how to deal with the situation where attempts at local improvements do not seem
to have the desired effect. One of the proposals is to identify methods of
interaction among organisations such that something like a ‘power field’
develops which makes the situation again conducive to the pursuit of local
improvements. This appears crucially significant in thinking about
action-oriented research especially because it highlights that a systematic
pursuit of local improvement might sometimes require interventions outside
the local.
4.3.6 System Dynamics
J. Forrester pioneered the
System Dynamics (SD) approach around 1958 (Dash, 1994; Flood and Jackson,
1991a; Forrester, 1958; Keys, 1990; see Jay W. Forrester page at
http://sysdyn.mit.edu/people/jay-forrester.html). The early formulation of the
SD approach involved the use of the concepts and ideas of Control Theory and
Control Engineering in management and decision making. The approach was aimed
at rectifying what Forrester perceived as the then prevailing tendency to view
management issues as isolated problems at isolated points in time.
Subsequently, Forrester elaborated on the potential application of SD for
decision making and policy analysis in industrial organisations (Forrester,
1961), in urban planning (Forrester, 1969), and in world-level policy issues
(Forrester, 1971, Meadows, et al., 1992).
SD is primarily orientated
towards identifying (defining), modelling, and simulating a system (e.g., a
factory, a city, an economy, or even an entire ecological system) in order to
explicate how the system might behave under different policy regimes. The SD
modelling approach makes use of notions like levels, rates, constants
(parameters), physical flows, information flows, discrepancies, delays, loops,
non-linearities, control strategies, etc. Typically, models are developed by
first developing an influence diagram (also called a causal loop
diagram), then elaborating it by means of a flow diagram, and finally
encrypting it in some appropriate computer simulation language. Many computer
applications have been developed to build SD models and simulate model
behaviour under various policy regimes. Some of the applications used currently
are Stella®, iThink® (see both in High Performance System pages at
http://www.hps-inc.com/), and Vensim® (see Vensim pages at
http://www.std.com/vensim/).
The SD approach deals with
‘dynamic systems’, i.e., aggregates of physical and abstract entities which are
distinguishable from their surrounding environment as purposive wholes and
which exhibit dynamic behaviour. The approach recognises that certain dynamic
systems might behave in a counter-intuitive manner, i.e., an unexpected manner,
especially due to the way such systems might be constituted. By trying to model
dynamic systems and simulating them on a computer, the SD approach seeks to
predict their behaviour pattern.
Many applications have been
reported in the literature, especially in the journal System Dynamics Review.
Some of the applications have been in complex forecasting, e.g., in forecasting
the year in which world petroleum oil production will reach its peak (see World
Oil Forecasting Program page at http://www.halcyon.com/duncanrc/index.html), in
improving the management of the commercial software development process (see
Software Process Modeling with System Dynamics pages at
http://www-rcf.usc.edu/~madachy/sd/), modelling ecological systems for the
purpose of planning (see, e.g., Landcare System Dynamics pages at
http://www.agfor.unimelb.edu.au/LSD/links.html), designing information and
control systems in a colliery (Wolstenholme, 1990, Chapter 7), evaluating
management information systems (Wolstenholme, et al., 1993), studying
the interactions of local structures and decision-making policies in the US
economy (see MIT System Dynamics Group pages at
http://sysdyn.mit.edu/sd-group/home.html), improving educational processes by
using SD models (see System Dynamics in Education pages at
http://sysdyn.mit.edu/home.html), etc.
One of the success stories
of SD-type feedback modelling was that of FOSSIL2, an integrated model of
energy supply and demand in the
The literature in this area
seems quite diverse. One particular strand among those distinguishable in the
literature pertains to organisational learning (Senge, 1990; Senge and
Sterman, 1992). Although some of the basic notions of the SD approach are still
used in this strand of literature, the guiding notion does not seem to be a
‘dynamic system’ any more. The focus seems to have shifted to the use of the
‘dynamic systems’ language for the purpose of creating ‘learning laboratories’:
Our
research attempts to develop learning processes aimed at (1) improving
managers’ shared mental models so that they become more systemic and more
dynamic, and (2) developing managers’ abilities to view new situations
systemically and dynamically (Senge and Sterman, 1992, p.139; also see Learning
Laboratory Projects pages at http://learning.mit.edu/pra/pro/learnlab.html).
The SD approach seems to
have a number of suggestions for action-oriented research. In its earlier form,
the SD approach sought to create value for its clients by providing them with
superior policy insights. The process was also expected to contribute to the
general fund of knowledge about ‘dynamic systems’, e.g., in terms of ‘generic
structures’, control strategies, etc. In the learning-oriented applications of
SD, clients are expected to benefit from participating in learning
laboratories, e.g., by developing dynamics-related insights, shared mental models,
etc. Even these applications are not entirely limited to local improvements. In
such applications, the power of the ‘dynamic systems’ language is demonstrated,
and the language itself might be expected to develop as a result, e.g.,
in terms of its symbols and the range of interactions it makes possible. The
‘dynamic systems’ vocabulary seems to reinforce the SD approach, whether the
approach is used for policy analysis or, more actively, for creating ‘learning
laboratories’.
4.3.7 Soft Systems Methodology
Soft Systems Methodology
(SSM) is said to be a development from Systems Engineering (Checkland, 1981;
1989; Checkland and Scholes, 1990; see SSM Internet Resource Page at
http://www.bf.rmit.edu.au:81/~andrewf/ssm-res.html ). One of the basic starting
points of Systems Engineering, i.e., the specification of the purposes to be
served by the system to be built, was found difficult to secure in a range of
situations which nevertheless required the securing of some type of
improvement. Instances of such situations were obtained in ‘messy, changing,
ill-defined problem situations with which managers have to cope in their
day-to-day professional lives’ (Checkland, 1989). In such situations, SSM seeks
to introduce a process typically described as a never-ending cycle of learning,
which might be implemented at the level of an individual or a group
representing one or more organisations, professions, communities, etc.
(Checkland, 1995).
In SSM, a situation is
viewed as a product of history of which no unique account is usually possible.
A situation is expected to contain some ‘would-be improvers’ of it, who are
likely to have various perceptions of the situation, of the purposes being
pursued in the situation (‘tasks’), and of the various things about which there
are disagreements (‘issues’) (Checkland and Scholes, 1990, p.28). These tasks
and issues are typically used in SSM to develop ‘root definitions’, i.e.,
definitions of a relevant system that is consistent with a particular view of
the situation. Each definition is then elaborated in the form of a ‘conceptual
model’, which spells out the necessary activities required to fulfil the task
identified in the root definition or to deal with the issue. It is clear from
the ever-growing literature on SSM applications that the conceptual models are
normally based on the generic notion of a ‘self-regulating system’. (See, for
example, the characteristic ‘monitor’ and ‘take control action’ activities that
constitute the feedback in the model in Figure 2.11; Checkland and Scholes,
1990, p.40).
The use of a conceptual
model in SSM is quite different from that in Systems Engineering. Unlike in
Systems Engineering, a conceptual model designed here is not meant to be
implemented and operated. It is used, alongside a number of other conceptual
models (arising out of different views in the situation) to orchestrate a type
of debate among the ‘would-be improvers’ who participate in the SSM process.
The debate requires participants to compare the conceptual models with what
they perceive the actual situation to be and arrive at an ‘accommodation’ on
what changes could be brought about in order to improve the situation.
Many applications of SSM
have been reported (Checkland 1981; Checkland and Scholes, 1990; see past
issues of the Journal of Applied Systems Analysis). Applications include
redesigning of the role, structure, and activities of a department in an
organisation (Checkland and Scholes, 1990; Chapter 3), developing a more
comprehensive way of evaluating the performance of a particular specialist
service within a wider health service system (ibid., Chapter 4),
redesigning the role and organisation of a public sector agency (ibid.,
Chapter 5), reorienting the focus and activities of a division or function
within a business and clarifying how a decision support system (DSS) might be
designed for the division (ibid., Chapters 6, 9), using SSM to define,
plan, and manage major organisational change programmes (ibid., Chapters
7 and 8), etc.
Reflecting about the role
the SSM approach plays in a project, Checkland and Scholes have commented that:
…
the role of the approach is akin to that of the cavalry in nineteenth-century
war: it can add a certain tone to what might otherwise be a vulgar brawl
(Checkland and Scholes, 1990, p.302).
Development of SSM is said
to be predicated on the difficulties of using the image of a self-regulating
system in order to address problematic organisational situations so as to
secure some improvement. The SSM literature indicates the potential of alternative
images, e.g., that of an appreciative system (Checkland, 1995; Checkland
and Casar, 1986), a learning system (Checkland, 1985), or a system of
inquiry (Checkland and Scholes, 1990, p.18).
SSM
can lead not only to purposeful action to improve a problem situation; more
generally, it also helps to orchestrate the process of ‘appreciation’ in
Vickers’s sense, sharpening views and making choices of action more explicit
(Checkland and Scholes, 1990, p. 147).
Whereas
systems engineering methodology is a system concerned with achieving
objectives, SSM is a learning system (Checkland, 1989, p.78). (The ‘is’
appearing twice in this statement might be interpreted as ‘articulates and
helps to bring about’.)
What
was found to be needed was a broad approach to examining problem situations in
a way which would lead to decisions on action at the level of both ‘what’ and
‘how’. The solution … was a system of inquiry (Checkland and Scholes,
1990, p. 18, emphasis in the original).
To the extent that an
‘appreciative system’ or a ‘learning system’ or a ‘system of inquiry’ is viewed
as a more general type of notion than a ‘self-regulating system’, SSM thinking
might be regarded as a creative enlargement of systems and cybernetic thinking
(this point has been emphasised in Checkland and Holwell, 1998a, p.158). It
seems that SSM has a lot to offer as a potential model for action-oriented
research. Unlike in the Operational Research (OR) or Systems Engineering
approaches, in SSM the client is not always a unitary authority who could
prescribe what objectives must be pursued. Therefore, in order to be
client-oriented, SSM has devised a set of action-like steps (akin to problem
structuring of Soft OR) in order to ‘add a certain tone’, or to create a
client, as it were! But unlike Soft OR, SSM emphasises a repetition of the
procedure. The repetition aims to achieve continuous learning (or
‘appreciation’) and maintenance of the ‘accommodation’ against disturbances. An
explicit ‘framework of ideas’ and a ‘recoverable’ research process are regarded
by the developers of SSM as central to any research (Checkland, 1991; 1995;
Checkland and Holwell, 1998b). (There will be occasion to review the research thinking of
SSM in more detail in Chapter 5.)
4.3.8 Critical Systems Heuristics
Critical Systems Heuristics
(CSH) (also labelled Critical Heuristics of Social Systems Design or Critical
Heuristics in short) has been proposed by Ulrich (1983; 1987). Discussions on
CSH by other writers are also available (e.g., Flood and
Like SSM, CSH also appears
to view the givenness of the purposes in Operational Research and Systems
Engineering as problematic (Jackson, 1991, p.188; Ulrich, 1988). The aim of CSH
is to help people discuss this givenness in practical situations of planning
and deliberate on what ought to be done. CSH does not provide a way
to identify ‘the right’ purpose, but does provide a method by which purposes
(or presuppositions) and their inevitable partiality might be kept constantly
under review.
CSH recognises that every
systems design involves ‘boundary judgements’, e.g., judgements with respect to
the ‘value basis’, ‘basis of power’, ‘basis of know-how’, and ‘basis of
legitimation’ involved in the design (Jackson, 1991, p.191; Ulrich, 1987,
p.279). The heuristic consists of interrogating any given design in order to
make explicit its normative bases (i.e., the four types of basis mentioned
above, typically linked with the following four categories: client, decision
maker, planner, and witness). Three types of question are framed for each of
the bases, thus resulting in 12 questions. The 12 questions are asked in two
modes: ‘is’ and ‘ought’ modes. These questions (in the ‘ought’ mode) are
reproduced below:
The answers to the
questions are expected to inform the process of argumentation between ordinary
citizens on one side and presumed ‘experts’ like planners, scientists, and
decision takers on the other.
Three key concepts are said
to inform CSH. These are: (i) Justification break-offs as boundary judgements,
(ii) a priori concepts of practical reason, and (iii) polemical
employment of boundary judgements. The 12 heuristic questions, when used in a
practical situation, make explicit the justification break-offs which are
usually hidden, using a priori concepts such as ‘value basis’, ‘basis of
power’, ‘basis of know-how’, and ‘basis of legitimation’, and are potentially
capable of being used in a polemical way—enabling ‘ordinary people to expose
the dogmatic character of the expert’s objective necessities’ (Ulrich, 1987).
CSH is expected not only to
create an advantage of argumentation for the affected people, but also to be a
tool for ‘experts’ and ‘applied scientists’ to deal critically with their
‘justification break-offs’, i.e., the point in an argumentation where the
premise cannot be justified any further. It ‘seeks to render them more
self-reflective and democratically minded with respect to their quest for
improvement’ (Ulrich, 1996b).
As
long as he does not learn to make transparent to himself and to others the
justification break-offs flowing into his designs, the applied scientist cannot
claim to deal critically with the normative content of these designs (Ulrich,
1987, p.277).
Commentators on CSH have
interpreted it as a potential contribution to the extension of the OR philosophy
(Flood and Jackson, 1991a; Jackson, 1991). CSH seeks to counter any imposition
of plans and designs and the associated rationality by one group of people over
another group of people; it aims at orchestrating a systematic debate between
opposing points of view; and it seeks to unravel the bases on which opinions
are formed. Using the language of cybernetics, it might be said that while CSH
does not deny the possibility of goal-seeking (or value-oriented) behaviour in
social situations, it does highlight the partiality of goals and values. The
remedy comes in the form of a process (that is argumentative in nature) that
would keep these goals and values under perpetual review. The image that
comes to mind is that of an ‘intelligent thermostat’ that would keep the target
temperature under constant review, not on its own, but through a process of
argumentation with the relevant others (see Sub-section 3.3.2 on Action
Science). Ulrich has provided a similar image in envisioning a
‘future-responsive management’ or a ‘future-responsive systems design’ that
requires the creation of appropriate institutional arrangements to promote
critical debate among differing perspectives about the preferred designs for
the future (Ulrich, 1994).
One
such arrangement has been suggested and practically tested by Peter Dienel
[references provided] in
Ulrich goes on to elaborate
the difficulties of argumentation within institutional arrangements like the
above where different perspectives about the ideal future encounter each other.
He has suggested CSH as an appropriate form of communication that might serve
to deal with these difficulties.
CSH seems to offer many
lessons for action-oriented research. Ulrich, the main developer of CSH, has
commented about the similarities and differences between CSH and action
research (Ulrich, 1996b) and has proposed a way to use CSH within action
research (Ulrich, 1996a). Ulrich has argued that CSH might bring some
methodological rigour into action research. From the point of view of
this review, the notion of ‘future-responsive systems design’ (or to slightly
modify it, ‘future responsive system’) is recoverable as a potentially more
general type of notion than either ‘self-regulating system’ (Ulrich, 1981;
1988) or even a ‘learning system’ (Ulrich, 1988), as the latter two types of
system do not deal with the ‘conditions of imperfect rationality’. It seems
that the sort of system Ulrich has envisaged would have the ability to learn
not ‘monologically’ but in a process of communication (or argumentation) with
the relevant others in the environment. However, for such a system to be
instantiated (e.g., in the form of a planning cell) there would be the need for
an appropriate form of communication within the system, and between the system
and its environment.
This perspective does
seem to offer a way, howsoever preliminary, to address the tension between the
local and the global in action-oriented research. Local interventions can have
effects outside the local. These effects might not always be positive for the
various relevant others in the environment. CSH suggests that the difficulty
might be handled by devising suitable forms of communication (perhaps, forms of
argumentation) within the local and between the local and its environment. The
effect of this process would be a discursively maintained boundary judgement
that guides and informs the local improvement effort.
4.3.9 Total Systems Intervention
Total Systems Intervention
(TSI) is said to be a method of operationalising the main principles of
Critical Systems Thinking (Flood and Jackson, 1991b, Chapter 16). Critical
Systems Thinking (CST) itself seems to be a result of visualising new
directions in management science (Jackson and Keys, 1987; Jackson, 1991; Flood
and Jackson, 1991a; 1991b). The first elaboration of TSI had appeared in 1991
(Flood and
Total
Systems Intervention (TSI) represents a new approach to planning, designing,
"problem solving" and evaluation. The process employs a range of
systems metaphors to encourage creative thinking about organisations and the
difficult issues that managers have to confront. These metaphors are linked
through a framework, the "system of systems methodologies", to
various systems approaches, so that once informed agreement is reached about
which metaphors most thoroughly expose an organisation’s concerns, an
appropriate systems-based intervention methodology (or set of methodologies)
can be employed. Choice of an appropriate systems methodology will guide
"problem solving" in a way that ensures that it addresses what are
found to be the main concerns of the particular organisation involved (Flood
and Jackson, 1991a, p. 45.)
From this (and also from a
detailed study of the TSI literature) it would seem that the TSI approach does
not belong to the same category as Operational Research, Systems Engineering,
Organisational Cybernetics, Soft Systems Methodology, Critical Systems
Heuristics, etc. Each of these latter approaches seems to visualise a type of
system, e.g., ‘self-regulating system’, ‘viable system’, ‘learning system’,
‘future-responsive system’, etc., or a type of systemic effect, e.g.,
self-regulation, self-maintenance, learning, ‘accommodation’, discursively
maintained boundary judgement, etc., and describe the means (methods,
methodologies, forms of communication, heuristics, etc.) of creating such
systems in a given practical context to achieve local outcomes of value to some
clients. TSI does not seem to operate with this type of a logic. On the other
hand, TSI seems to put forward a way of using judiciously the various
management systems approaches in practical situations, perhaps aiming to fill a
gap in the literature in this area. To do this, it needs a framework of ideas
that would guide the TSI way of using the systems approaches. Such a framework
of ideas, or a theory for the use of systems approaches seems to be offered by
CST, seeking for example to avoid ‘authoritarian usage [of systems approaches]
by powerful decision makers’ (Jackson, 1991, p.201)
The theory for the use of
systems approaches that CST seems to embrace involves two broad elements: (i) certain
commitments (critical awareness, social awareness, dedication to human
emancipation, complementarism at the theoretical level, and complementarism at
the methodological level) and (ii) a scheme for classifying the systems
approaches (on two dimensions: simple-complex and
unitary-pluralist-conflictual, resulting in six ideal types) (Flood and
Jackson, 1991a; Jackson 1991, Chapter 7).
As might be expected, when
there is a theory for the use of any approach, it becomes possible to disagree
with the theory by devising some alternative type of use (Cummings, 1994), or
using the approaches ‘obliquely’—to use a term coined by Flood and Romm
(1996b). In fact, most of the current discussions about TSI and CST in the
management systems literature seems to be dealing with this difficulty: How to
establish the academic and practical superiority of a ‘theory for the use of’?
One type of answer seems to suggest that there might not be any global criteria
at all (Cummings, 1994). However, certain criteria have been explored by
others. The notion of ‘learning’ has been used in order to address this
question. On this view, a version of CST is preferable because when its
prescribed ‘theory for the use of’ is followed, it would generate the ‘greatest
possible learning’ (Flood and Romm, 1996b) ¾ a claim dificult to establish. The notion of
‘flexibility’ has also been used to tackle this question. Accordingly, a
version of CST would ‘ensure maximum flexibility in an intervention’ (Jackson,
1997, p.6) ¾ again a claim
dificult to establish.
Following G. Morgan,
The literature of
TSI/CST seems to be quite instructive for thinking about action-oriented
research. If the latter is going to involve ‘methodologies’ in the sense used
in the management systems literature, it would come up against issues similar
to those debated in the TSI/CST literature. Furthermore, if action-oriented
research is going to involve general notions or vocabularies or multiple
‘frameworks of ideas’ to guide and develop research practice, it would have to
deal with the problems of methodology choice, learning, flexibility, reflective
conversation, development of languages, etc., in order to allow a concurrent
evolution of these ‘framework of ideas’ and the associated models, languages,
‘methodologies’, etc.
4.4
Management Systems and Action Research
The review set out to
explore how the two types of orientation, i.e., research-orientation and
action-orientation, intermesh within management systems thinking. The
exploration seems to have yielded a number of interesting results. These
results will be recapitulated in this section in terms of different types of
action-orientation and research-orientation recovered from the literature of
management systems. These will be used to develop the discussion about action
research presented earlier in Section 3.4.
4.4.1 Action-orientation in Management
Systems Thinking
Different types of
action-orientation were found in the management systems literature. All the
management systems approaches reviewed here are oriented towards bringing about
some improvement in a practical situation according to some relevant local
criteria. Therefore these approaches might be seen as forms of support given to
some relevant set of actors in a practical context of action. However, based on
the form of support, different types of action-orientation can be found in
these approaches. Some of the approaches strive to produce the necessary
information, knowledge, structure, system, etc., that might be used by the
relevant actors (who are being supported) according to their own purposes. Some
other approaches strive to orchestrate processes where new purposes, even new
actors, might emerge and be supported.
In the Operational Research
(OR) approach, the objectives of the client determine what system would be
modelled. Once the objectives and the system are identified, the methodology of
OR clarifies what data would be collected and finally what state of the system
would be identified as the most desirable (or optimum). In this case, the
objectives of the clients are taken as external to the form of support that is
provided. However, the Soft OR approach seeks to ‘structure’ problems (or
issues) such that the clients can come to a better understanding, an
accommodation, a decision, a strategy, etc. The Soft OR facilitator actively
influences the group process in order to make the clients become more like a
collective, capable of acting in solidarity. This is akin to the creation of a
new actor, in this case the collective actor.
Both Systems Analysis and
Systems Engineering (SA/SE) strive to contribute in practical situations by
creating a system that achieves some pre-defined purpose. The purpose is
external to the SA/SE approach; it comes from the client. In that sense, it is
similar to the OR approach. Soft Systems Methodology (SSM) in contrast strives
to produce the purposes that might be pursued in the context. It also aims at
some type of capacity building among the relevant actors so that they are able
to appreciate their situation and intervene in it in an ongoing manner, as if
to create and maintain their collective actorship.
In the applications of VSM,
the client organisation improves its fitness to deal with its environment. This
is expected to enhance the capability of the client organisation to pursue its
purposes as identified from time to time. The VSM itself does not dictate what
purposes the viable organisation ought to be pursuing. However, in the more
recent adaptations of Organisational Cybernetics, there is an interest in
producing the capabilities for new types of action, e.g., through the creation
of ‘self-constructed organisations’.
The Socio-Technical Systems
approach seeks to produce positive local outcomes by helping the client
organisation make proper organisational or technological choice. The aim is to
reduce human costs, improve performance, etc. This might be seen as a form of
capacity building within the client organisation. This type of support might
take either of the two forms discussed above. Consequently, the existing actors
might be supported through better organisational/technological systems, or new
actors might emerge through organisational change or inter-organisational
co-operation.
The System Dynamics (SD)
approach seeks to create value for its clients by providing them with
dynamics-related insights about their situation, helping them develop shared
mental models, etc. The SD-based ‘learning laboratories’ provide the
participants with a space for experimentation, understanding, learning, etc.
This seems to provide both the possibilities: supporting actors through better
observation of the dynamics of a situation and creating new actors through the
effect of learning, developing shared mental models, etc.
The CSH approach seeks to
improve the ability of its users to participate in debates about plans and
designs imposed on them. The aim is to produce new actors (e.g., a planning
cell) who keep their actions under constant critical review.
Finally, the TSI/CST type
of thinking recognises the potential contribution of the above management
systems approaches in improving practical situations. It focuses on the
difficulties of choosing the appropriate form of support in any given
situation.
The two types of
action-orientation can now be articulated:
4.4.2 Research-orientation in
Management Systems Thinking
Different types of research-orientation
are found in the management systems literature. Although the management systems
approaches are oriented towards creating some value in the context of
application, none of the approaches reviewed here guarantee any form of
success. Some of the approaches are explicit about the conditions under which
the approach might not work effectively. For example, Socio-Technical Systems
thinking indicates that organisational strategies might not work under reactive
and turbulent environmental conditions. There seems to be a critical
literature around most of the approaches, indicating where and how an approach
might or might not work (e.g., Brocklesby, 1994; Dickover, 1994; Rosenhead,
1996). There seems to be an attempt to produce new versions of existing
approaches in order to increase the chances of their success in application
(e.g., Checkland and Scholes, 1990; Flood, 1995a; Harnden, 1990). A closer look
at the literature does reveal a number of research-oriented concerns.
The OR approach seems to be
research-oriented in at least two different senses. Firstly, at the level of
the local, it is interested in identifying the particular state of the chosen
system that would be the most satisfactory in fulfilling the client’s objectives.
Secondly, the literature pertaining to the OR approach also points towards a
systematic extension of its own library of formal models, solution procedures,
and its general vocabulary, in an ongoing way. It has also maintained a
critical debate about its methodology. Adaptations to the methodology of OR can
be found within the discussion about Soft OR. This is found to be a feature of
many of the management systems approaches reviewed here. The Soft OR approach
also seems to combine an interest in producing locally relevant results with an
interest in a systematic expansion (and improvement) in the tools and
techniques for group interaction, group facilitation, etc., besides an
improvement in its general vocabulary and its basic framework of thinking.
The research-orientation of
SA/SE approaches might be seen in their use of systems and cybernetics ideas.
These approaches strive to build instances of systems which need to be
operated and maintained by people towards some practical end. Research results
from such activity might be expected with respect to the general
characteristics (and limitations) of such systems. Indeed, the
application of SA/SE approaches to managerial problems and the associated
critical debate has contributed to the research thinking in this area in a
number of interesting ways. The development of the Soft Systems Methodology
(SSM) and soft systems thinking in general is said to be a result of this. More
specifically, the ideas of ‘appreciative system’ and ‘learning system’ as a basis
for research in organisational and social situations have emerged from this.
The research-orientation in
Organisational Cybernetics derives from the field of cybernetics.
Organisational Cybernetics has extended the basic notion of a ‘self-regulating system’
by generalising it in terms of ‘viable system’. The more recent reformulations
in organisational cybernetics appear to strive for a different type of
research-orientation (see Sub-section 4.3.4). Properties like ‘viability’,
‘autonomy’, etc., are now sought to be attained through processes of
participation, conversation, and ‘self-construction’. The new contexts these
processes help create might be viewed as somewhat analogous to research
results, although grounded locally. The literature in this area seeks to
identify ways of systematically studying and improving these processes so as to
increase the chance of their success in future applications.
Socio-Technical Systems
thinking indicates how the pursuit of local improvements might be thwarted in reactive
and turbulent environments. It suggests that research should contribute
not merely through local improvements, but also by indicating how to deal with
the situation where local improvements do not seem to have the desired effect.
The proposal in this area is to identify methods of interaction among
organisations such that something like a ‘power field’ develops which makes the
situation again conducive to the pursuit of local improvements. This type of
research-orientation might be compared with the recent reformulations in
organisational cybernetics, where methods of interaction are being sought which
would bring forth certain desired types of systemic effect.
The SD approach seeks to
contribute to the general fund of knowledge about ‘dynamic systems’, e.g., in
terms of ‘behaviour patterns’, ‘generic structures’, control strategies, etc.
In the learning-oriented applications of SD, the power of the ‘dynamic systems’
language is demonstrated. The ‘dynamic systems’ vocabulary seems to reinforce
the SD approach, whether the approach is used for policy analysis or, more
actively, for creating ‘learning laboratories’ or ‘micro-worlds’.
SSM and the associated
thinking has been regarded as a creative enlargement of systems and cybernetic
thinking. It has produced a body of literature on the nature of research in the
social domain and the possibility of using alternative ‘frameworks of ideas’ in
conducting research for situation improvement. One of the main lessons from
this literature seems to be the point that these ‘frameworks of ideas’ do not
have to be veritable representations of how the world might be like, but the
frameworks should only allow a researcher to carry out research even when
different types of world are obtained. It emphasises the importance of the need
to make the framework as explicit as possible, develop ‘methodologies’ to
instantiate the framework, instantiate the framework in practical contexts,
demonstrate its contribution in such practical contexts, improve the framework
and the ‘methodologies’ in a programmatic way, etc. Besides these general
insights, the SSM literature also hints about the potential of a research
framework that might be built around the basic notion of an ‘appreciative
system’ (or a ‘learning system’ or a ‘system of inquiry’). The power of this
notion has been related to its greater generality compared to the notion of a system
as used in the SA/SE approaches. In implementing the notion of ‘appreciative
system’, SSM provides a way for the actors in a situation to function together
(as a team, or collective, as if like a new actor) by ‘appreciating’ their
context, generating ‘accommodation’ about the broader directions for action,
and generating the appropriate actions themselves. The process is supposed to
be never-ending. This implies that the emergent capacity to act together is not
self-maintaining; it requires continuous effort (e.g., learning) in order to be
maintained (and presumably developed).
The CSH literature seems to
highlight an important difficulty associated with the frameworks of ideas used
for research and action in worlds which do not conform to representational
frameworks. Sometimes, merely instantiating such (non-representational)
frameworks might amount to an imposition on some people. The traditional
research thinking deals with such issues by trying to limit itself to
representational frameworks alone. CSH seems to propose a way to deal with the
situation where the representational frameworks are not (yet) found, but some
form of systematic support to action is still felt to be necessary. The
solution proposed is to establish a degree of collective control over the
framework by designing a process of argumentation about the framework, such
that it is maintained discursively. This is the so-called ‘critical
solution’ to the ‘problem of practical reason’ in the vocabulary of CSH. It has
been claimed in the literature that such discursively maintained frameworks can
result in the creation of ‘future-responsive systems’.
The TSI/CST literature
seems to acknowledge explicitly the possibility of many research (and action)
frameworks to be used within the management systems area. It also acknowledges
the various conceptual and practical difficulties arising out of this. On the
one hand, the TSI/CST thinking might be viewed as a set of guidelines for using
various management systems methodologies in order to magnify their
research-orientation and action-orientation. For example, TSI/CST thinking
seeks to clarify that the learnings from a System Dynamics (SD) modelling
exercise is best expressed using the vocabulary of ‘dynamic systems’—one that
is associated with the framework of ideas on which SD is based. On the other
hand, referring to the more recent TSI/CST thinking, a different type of focus
might be recovered. There is an emphasis on ‘reflective conversation’ among
different frameworks of ideas, hinting at the need for new conversational
devices which can accommodate different system notions, e.g., ‘self-regulating
system’, ‘dynamic system’, ‘appreciative system’, ‘future-responsive system’,
etc., and help produce a general body of thought for the management systems
area.
An attempt is now made to
articulate different types of research-orientation within the management
systems literature based on what has been described in this chapter. It is to
be noted that the literature focuses on the need for a systematic support to
action within social and organisational situations and the need to maintain a
research-like critical debate about it with the hope of improving the chances
of the forms of support to be more successful in future applications. The
general lesson in this literature about improving the chances of the forms of
support to be more successful in future applications points either towards the
innovation of alternative forms of support or towards the improvement (and
enrichment) of the existing forms of support so as to make them more reliable,
easier to use, more robust to changing circumstances, easier to be taught, etc.
The above general lesson captures
some of the recurrent themes in the research literature pertaining to the
management systems approaches. However, for the purpose of this review, it is
also important to identify how some of the management systems approaches might
be unique and different from some others in terms of their
research-orientation. This has been done in the following paragraphs by
trying to classify what the approaches strive to achieve and improve through
research. It is to be noted that the classification presented below
constitutes one way of discussing some of the similarities and differences
among the management systems approaches. There can be alternative ways of
discussing the same. However, the following way of discussing seems to point
towards the specific contributions management systems thinking can make to the
current debates in action research—a theme taken up later in the next
sub-section.
4.4.3 Revisiting the Current Debates in
Action Research
An attempt is now made to
identify elements in the management systems literature which might be
introduced within the current debates in action research (see Section 3.4) to
enrich those debates. The debates pertaining to action research focus on the
problems of ‘normal’ research (see Sub-section 3.4.1). The gist of the problems
discussed in these debates might be expressed in terms of the following: The
so-called ‘normal’ research does not seem to ensure that its results will
always bring about improvements in how people behave and act in various
practical settings. The general approach of ‘normal’ research to focus on
observed patterns that can be expressed (in terms of laws), transferred in
scientific communications, and progressively made more and more precise through
the effect of repeated observations, is viewed as inappropriate for the types
of aim action research strives to achieve. Having rejected this approach, the
action research methods seek to orchestrate various types of interaction within
the local contexts of action so as to effect an improvement in how people
behave and act in those contexts. However, as soon as the focus shifts to
orchestrating local interactions to achieve improvements in action, the issues
of demarcation of research from other activities, the quality and durability of
the results, effects of such activities outside the local context, the need for
producing transferable results, the difficulty of conducting any critical
scrutiny of the activities and the effects, etc., emerge to the fore. This is
where the debate seems to get embroiled in the questions of ethics,
epistemology, research paradigms, dilemmas, etc.
An appreciation of the
development of the management systems literature and the current debates
therein reveals that there might be alternative ways to formulate the core
issues in the current debates in action research. To do that, it will be
necessary to re-look at the general approach of ‘normal’ research which the
action research debates seem to reject so emphatically. The so-called systems
movement (see Section 4.2) also seems to have been based on an appreciation
of the difficulties of using the normal methods of research in domains that
display interconnectedness, emergence, openness of the object of study, etc.
However, this seems to have been dealt with by introducing the notion of a
‘system’ that might not only refer to observed patterns, but also refer to
entities that might be brought forth through purposeful action (including
interaction, communication, etc.) such that the entities provide the basis (and
support) for some other purposeful action. A review of the management systems
literature reveals three general categories of such ‘systems’ being discussed
there: systems in the world, systems to generate collective action, and
systems to generate collective control over action (see Sub-section 4.4.2).
The research focus in this area then shifts from the problems of identifying
and refining observed pattern to the problems of specifying relevant types of
system and identifying and refining the methods of bringing them forth in
various practical contexts. This type of reformulation seems to overcome most
of the difficulties described in the current debates in action research. The
reformulation does not provide a direct answer to the question of how to
improve action and behaviour in a practical situation; it simply reframes the
question in ‘systems’ terms: What type of system could be brought forth
in a practical context such that it proves to be a robust type of support to
action and behaviour within that context? How to improve the methods of
bringing forth such systems when the demand for such systems arise in future in
similar or different environments? Whether it is possible to produce a
systematic body of knowledge pertaining to various types of system and the
methods of bringing them forth?
A summary of the key ideas
recovered from this chapter will be presented in Chapter 5 (see Sub-section
5.5.2). The review of literature continues in Chapter 5 to explore the possible
contributions of research to the improvement of action by delving into a wider
body of literature on research as a form of support to action.
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Appendix A |
Appendix B |