Soft Systems Methodology and Its Applications

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Introduction

Soft Systems Methodology (SSM) refers to an intellectual general tool for dealing with actual-world problematic conditions. It is the outcome of the progressing feat study, which Brian Wilson and Peter Checkland among others have carried out for more than thirty years to offer a structure that will assist those using it tackle the form of chaotic problem conditions that do not have a formal problem description. In other words, a tool that introduces some form of structure in abstract situations: situations that otherwise do not have a description, especially in the field of management.

Therefore, to get into its manner of operation and use, it is crucial to explicate the arena on which it lays, viz. the field of management. There is a necessity of comprehending management in its extensive sense. As a result, the association is valid with a number of conditions, where an individual or a group of individuals should establish an alteration progression (a transformation) in the actual world, with the intention of bettering a difficult condition that they could be residing in, at any given time. Through difficult conditions, it is predestined that an individual understands that a number of items are not going in the right way and require being advanced (Yang 2010).

In accordance with Soft Systems Methodology, and discernment of the onlooker(s) regarding the actual world is personal and relies on the worldview (viz. weltanschauung) the onlooker(s) accept to identify the observable fact in the actual world. On this note, a thing that can be incorrect for a particular individual could be right or satisfactory for another individual. It entirely relies on the viewpoint or worldview under observation (Jae, Hyoung & Hyoung 2008). This paper tackles Soft Systems Methodology as well as issues surrounding this subjectivity. General idea concerning Soft Systems Methodology

There exists a common misapprehension that Soft Systems Methodology is a tactic for exclusively tackling soft problems (that is, difficulties that engage cultural, mental, and social constituents), perhaps due to the use of the word “soft” in the taxonomy of the name “Soft Systems Methodology”. On the contrary, Soft Systems Methodology does not make a distinction between hard and soft problems; it only offers a different technique of handling conditions recognized as difficult.

The softness or hardness does not represent the fundamental quality of the difficult condition being dealt with. Rather, the softness or hardness is a characteristic of the manner those engaged deal with the condition, the lenses through which a condition is viewed. Every condition observed as difficult has both soft and hard constituents (Patel & Patel 2003). The very idea of difficulty is reliant on a human being taking it as such; actually, as the old adage goes, “every coin has two sides”. For instance, a terrorist to a given man may be a freedom fighter to another; it is all about perception. Soft Systems Methodology differentiates itself from hard schemes advances in the manner it tackles the idea of the system (Petrovic 2012).

As a result, in hard systems techniques when individual talks of computer coordination, knowledge coordination, telecommunications coordination, or transportation coordination, the individual talks about these like bounded bodies with a physical being that can be officially explained or designed to accomplish a given intention. On the contrary, Soft Systems Methodology treats the idea of a system like an epistemological instead of the ontological body, to be exact, as an intellectual construct applied for human comprehension. If we take for instance a given establishment like a system, we can illustrate this establishment like a system to create a return, or a system to change raw resources into business merchandise, or a system to offer employments to the neighbouring society, or a system to contaminate the surroundings.

Relying on the point of view embraced, there will have an extremely different comprehension of this given establishment. Of all these explanations, none is correct or incorrect; they are simply different manners of accepting what is carrying on (Zhang 2010). This necessitates becoming mindful of given points of view and principles, and these sequentially verify the features of the condition understood as being a component of the system of regard. For example, if some people are attempting to comprehend this establishment as a system to change raw resources into business merchandise, they are probable to comprise the suppliers of raw resources and the clients that purchase the merchandise in the comprehension of this system.

Nevertheless, if other people consider the establishment like a system to offer employments to the local society, they are liable of comprising various components, for instance, the regional transport infrastructure that lets members of the society access the establishment. On the same note, reliant on the point of view people draw various boundaries just about what they recognize the system to be (Zhang 2010).

History of Soft Systems Methodology

In the year 1966, a group of intellectuals from the University of Lancaster developed Soft Systems Methodology in a bid to solve situations that appeared rather abstract. Professor Gwilym Jenkins led the group into designing what appeared vague and far-fetched at the time. This group came up because of their efforts to deal with management difficulty situations by means of a systems engineering move. According to Hanafizadeh and Aliehyaei, as the group would establish, “Systems Engineering, which had been used hitherto to address technicalities, was somehow inapplicable in the field of management” (2011, p.346).

Nonetheless, it was established that unitary description like that, which comprises the difficulty, was frequently not there in organisational difficulty situations, where various stakeholders frequently have extremely different outlooks on the component of the difficulty. Soft Systems Methodology has obtained its reputation and acknowledgement through the efforts of Professor Peter Checkland, who came into the group in the year 1969 after being selected as the Professor of business systems (Checkland 2000).

Dr Wilson that had joined the group in the year 1966 directed the accomplishment study programme via ISCOL (the consulting arm of the university) starting in the year 1970. Soft Systems Methodology lends itself mainly well to handling difficult conditions, where those engaged do not have a general concurrence on the component of the problem, and that requires to be dealt with. In conditions like those (for instance, the way to carry out business in a sustainable manner or the best way to manage drug abuse), many diverse points of view might exist. In addition, different ideals, and values around the most significant features of the condition and the way to deal with them might arise.

Those different aspects observed as difficult tend to be exceedingly interconnected; altering one feature is probable to have secondary effects on other features (Loffler, Tschirky & Kijima 2009). It is essential thus to extend a complete comprehension of those interconnections involving the different features of the difficult situation. Like a systemic methodology, Soft Systems Methodology seeks to assist its users in building up an improved comprehension via an iterative erudition course. The idea of accommodation requires being differentiated from the perception of consensus. The idea of accommodation distinguishes that, this aspect is an extremely exceptional situation in most actual-world conditions, and that most of the instances individual requires can merely be partly met by joint suggestions.

The Seven-Phase Approach of Soft Systems Methodology

The initial edition of Soft Systems Methodology like a seven-stage tactic printed in ‘Systems Thinking, Systems Practice’ by Checkland has ever since been featured in the works of Checkland. Nonetheless, the seven-phase representation is increasingly widely applied and extensively taught since its stepwise character makes it effortlessly teachable (Salahat, Wade & Ul-Haq 2009). Most significant, the representation has an obstruction running across it to distinguish stages involving the actual world, on top of the line, systems judgment, underneath the line, and the obstinacy to the technique.

The seven phases are:

Going into the difficulty situation
Articulating the difficulty situation
Creating root descriptions of applicable systems
Construction of Theoretical Forms of Human Action Systems
Evaluating the forms with the actual world
Identifying transformations that are pleasing and feasible
Proceeding to better the actual world condition

The operations of the process arise from the reality that phases two through four are at all times an iterative progression. The stakeholders (described as Customer, Owner, and Actors) take part in an argument directed by the facilitator/forecaster. In the course of this argument, different root descriptions (concise accounts of suitable systems) and theoretical models are proposed, customized, and extended until a pleasing form is attained by agreement. This representation then structures the foundation for the actual world transformations (Liu et al. 2012).

CATWOE

The group at the University of Lancaster suggested numerous standards that must be specified to make sure that a particular root description is thorough and all-inclusive (Basden & Wood-Harper 2006). These standards are reviewed in the CATWOE as shown below:

Clients- the receiver or victims of this given system
Actors- the people accountable for executing this technique
Transformation- the change brought about by this technique
Weltanschauung (that is, Worldview) – the given worldview that validates the subsistence of this technique
Owner- those in power to eradicate this system or transform its considerations of performance
Environmental constraints – the external restrictions taken by this technique take like a given.

This type of scrutiny elucidates what the customer of the tactic is attempting to accomplish (Basden & Wood-Harper 2006). By clearly acknowledging these points of view, the customer of the tactic is forced to deem the influence of any suggested transformations on the people engaged.

Theoretical Models of Human Action Systems

Figure 1. A Soft Systems Methodology style Theoretical Model

Soft Systems Methodology Theoretical Models of the Activity Systems of people (theoretical Models) are conjectural; they are not meant to signify what subsists, but to stand for the point of view of a stakeholder. This aspect is frequently misinterpreted. Actually, “Figure 1 does not seek to demonstrate the way rice is cooked; no, it underscores the process of cooking rice or at least how it ought to be cooked according to stakeholders” (Jacobs 2004, p.141).

Theoretical Models acquire the appearance of bubble illustrations in which explanations of actions are included in the bubbles. There is a connection of bubbles to one another by arrows (Paucar-Caceres & Pagano 2009). The purpose of the arrows is to signify logical reliance. The wash rice action “in Figure 1 is thought to be rationally reliant on the actions obtain water and obtain rice…this connection of rational addiction is transitive, viz. if cook rice is reliant on wash rice, which is then reliant on obtaining rice, subsequently cook rice is reliant on obtaining rice” (Jacobs 2004, p.142).

Fundamentally, this could seem to match with what is called, in official judgment, theoretical syllogism. Nevertheless, there has been defiance to a correlation with logic, and there has been an argument that theoretical models of Soft Systems Methodology are not rational in any logic of the word. Theoretical models in the works of Checkland are generally restricted to a small sum (five to nine) of bubbles. In addition, at all times, the main actions in conformity to Cybernetics are complemented by bubbles signifying check and manage systems. Whereas the principal authors of Soft Systems Methodology demonstrate a high extent of resemblance in their descriptions of the early phases of the technique, significant diversity starts to emerge at the theoretical model construction phase.

Results and applications of Soft Systems Methodology

Universal descriptions of Soft Systems Methodology are extremely diverse. There has been “delineation of Soft Systems Methodology as a studying platform; an element of a new idea for function investigation” (Christis 2005, p.18). Nevertheless, such assortment is to be anticipated taking that it seeks to deal with any sort of informal soft problem in every organizational or public perspective. Soft Systems Methodology acts as a studying system since it assists a greater comprehension of the problem condition on the division of those involved.

With an emphasis on the worldviews of the people concerned in the problem condition, Soft Systems Methodology can produce different kinds of outcomes. The problem may simply vanish as the consequence of an agreement. An informal resolution may result, for example, concurrence to take on a new function for the business. A third likelihood is that, “the difficulty becomes formal, where a soft problem turns into a particularly hard problem” (Christis 2005, p.22). Soft Systems Methodology has been applied comprehensively in knowledge systems investigation and plan, and a number of knowledge systems textbooks take Soft Systems Methodology wholly as a systems investigation and plan method.

Soft Systems Methodology for information systems investigation and planning

The applications of Soft Systems Methodology in information system planning are numerous and different (Petkov et al. 2008). A number of the most noteworthy methods include the following:

Checkland and Holwell

This method applies the Soft Systems Methodology at the face part of the knowledge systems planning scheme. Their schemes have been involved in the restructuring of a knowledge systems section, the assessment of knowledge systems and building up information systems policy. Their effort does not pull out into software engineering but is restricted to examining the extent and facilitating the organization of knowledge systems planning scheme (Beckford 2002). Like so, it has been moderately free from condemnation.

Information Requirements Analysis

Information Requirements Analysis (IRA) “sets out to determine client needs in terms of information by coming up with theoretical models including hundreds of bubbles” (Bergvall-Kåreborn 2002, p.36). The models constructed are employed to obtain information groups and plan action to action to action information courses on a template called a Maltese cross. Information Requirements Analysis connects unswervingly to software planning and has used in the construction business processing systems (Bergvall-Kåreborn 2002).

Different from the Checkland and Holwell schemes, where models stay at a theoretical stage, IRA aims at constructing models for the planning of knowledge systems that can offer information regarding actual-world entities and occurrences (like stock management systems). There has been an argument that IRA representations do not have the rational power to signify cause and outcome and thus, an information system constructed from them cannot signify happenings in the real world.

The application of Information Requirements Analysis has nevertheless not been restricted to construction transaction developing systems. For instance, the IRA was employed in carrying out a review of an investigation method for improving efficiency and competence in a given area of strategising called protective services (Kinloch et al. 2009). Soft Systems Methodology was employed to extend a situation model applicable to protective services that, in conjunction with information groups for every one of the Soft Systems Methodology actions and theoretical channels of performance, was applied to investigate the effectiveness of Microanalysis by evaluating information content (Sewchurran & Barron 2008).

Multiview

Multiview aims at front ending Soft Systems Methodology onto setting up software engineering techniques like information engineering. Multiview constructs theoretical Models and gets Statistics Flow Diagrams, in addition to Entity-association models from them. Bergvall-Kåreborn (2002) notes, “Multiview connects directly to software planning and has relevance in the construction of operation processing structures” (p.44). The Multiview theoretical Models are not hypothetical and seem to symbolize things in the real world. Whereas this hinders some of the conceptual problems obtained in the IRA, it mislays some of the benefits of traditional Soft Systems Methodology and unwraps a set of difficulties obtained in other information structure planning methods.

Logico-linguistic Modelling

This method applies logically developed theoretical models for information elicitation and depiction (Yan & Yan 2010, p.140). This method has used in information-based system planning. Whereas Logico-linguistic Modelling triumphs over the difficulties in the shift from the theoretical model to computer symbols, it does so at the cost of creating the stakeholder built models much more intricate. There has been an argument that, the advantages of this difficulty are dubious and that this modelling process is much tougher to apply.

Conclusion

This paper has exemplified the approach of using Soft Systems Methodology to difficulties in building project management, particularly those information management difficulties that are not easy to comprehend and hard to execute (Baroudi & Metcalfe 2011). It includes the seven-phase approach of soft systems methodology and its application in dealing with the perplexing situations that include human, managerial, and practical aspects. Soft Systems Methodology promotes collective learning and is best as a collective judgment-making progression. The methodology is reinforced by the dynamic contribution of various stakeholders and partakers; moreover, it supports common ownership of the difficulty solving procedure. To sum it up, Soft Systems Methodology could be proposed where a business is seeking to realize transformations in workplace background and change into a learning establishment.

Reference List

Baroudi, B & Metcalfe, M 2011, ‘Prequalification: Using systems to problem dissolve’, Project Management Journal, vol. 42 no. 2, pp. 51-62.

Basden, A & Wood-Harper, A 2006, ‘A philosophical discussion of the root definition in soft systems thinking: an enrichment of CATWOE’, Systems Research & Behavioural Science, vol. 23 no. 1, pp. 61-87.

Beckford, J 2002, ‘Part four: Methods, tools and techniques: Chapter 29: Stakeholder participation’, Quality (Routledge), vol. 1 no. 1, pp. 288-302.

Bergvall-Kåreborn, B 2002, ‘Enriching the model-building phase of soft systems methodology’, Systems Research & Behavioural Science, vol. 19 no. 1, pp. 27-48.

Checkland, P 2000, ‘Soft systems methodology: a thirty year retrospectiveReproduced from Soft Systems Methodology in Action, John Wiley & Sons, Ltd, Chichester, 1999. ’, Systems Research & Behavioural Science, vol. 17 no. 1, pp. 11-58.

Christis, J 2005, ‘Theory and practice of soft systems methodology: a performative contradiction?’ Systems Research & Behavioural Science, vol. 22 no. 1, pp. 11-26.

Hanafizadeh, P & Aliehyaei, R 2011, ‘The Application of Fuzzy Cognitive Map in Soft System Methodology’, Systemic Practice & Action Research, vol. 24 no. 4, pp. 325-354.

Jacobs, B 2004, ‘Using Soft Systems Methodology for Performance Improvement and Organisational Change in the English National Health Service’, Journal of Contingencies & Crisis Management, vol. 12 no. 4, pp. 138-149.

Jae, E, Hyoung, K & Hyoung C 2008, ‘Proposing rhizomatic systems methodology: extending Churchman’s pragmatism to post-structuralism’, Systems Research & Behavioural Science, vol. 25 no. 2, pp. 291-303.

Kinloch, P, Hulya, F, Francis, M & Taylor, M 2009, ‘Supporting crime detection and operational planning with soft systems methodology and viable systems model’, Systems Research & Behavioural Science, vol. 26 no. 1, pp. 3-14.

Liu, W, Meng, W, Mingers, J, Tang, N & Wang, W 2012, ‘Developing a performance management system using soft systems methodology: A Chinese case study’, European Journal of Operational Research, vol. 223 no. 2, pp. 529-540.

Loffler, K, Tschirky, H & Kijima, K 2009, ‘Embedding enterprise science into SSM for improving innovation systems in technology-based companies’, Systems Research & Behavioural Science, vol. 26 no. 6, pp. 675-687.

Patel, D & Patel, S 2003, ‘The Cognitive Process of Problem Solving: A Soft Systems Approach’, Brain and Mind, vol. 4 no. 2, pp. 283-295.

Paucar-Caceres, A & Pagano, R 2009, ‘Systems thinking and the use of systemic methodologies in knowledge management’, Systems Research & Behavioural Science, vol. 26 no. 3, pp. 343-355.

Petkov, D, Petkova, O, Andrew, T & Nepal, T 2008, ‘On the process of combining soft systems methodologies and other approaches in systemic interventions’, Journal of Organisational Transformation & Social Change, vol. 5 no. 3, pp. 291-303.

Petrovic, S 2012, ‘Critically Generated Knowledge – the Triple Loop Learning Result’, Management (1820-0222), vol. 1 no. 62, pp. 73-82.

Salahat, M, Wade, S & Ul-Haq, I 2009, ‘Application of a Systemic Soft Domain-Driven Design Framework’, World Academy of Science, Engineering & Technology, vol. 57 no. 1, pp. 476-486.

Sewchurran, K & Barron, M 2008, ‘An investigation into successfully managing and sustaining the project sponsor–project manager relationship using soft systems methodology’, Project Management Journal, vol. 39 no. 1, pp. 56-68.

Yan, Z & Yan X 2010, ‘A revolution in the field of systems thinking—a review of Checkland’s system thinking’, Systems Research & Behavioural Science, vol. 27 no. 2, pp. 140-155.

Yang, J 2010, ‘An approach applying SSM to problem situations of interests conflicts: Interests-coordination SSM’, Systems Research & Behavioural Science, vol. 27 no. 2, pp. 171-189.

Zhang H 2010, ‘Soft systems methodology and ‘soft’ philosophy of science’, Systems Research & Behavioural Science, vol. 27 no. 2, pp. 156-170.

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