Soft Systems Methodology for Organisational Problem-Solving - Coursework Example

Soft Systems Methodology (SSM) Introduction In business and social environments, problems and issues are inevitable and therefore success lies in countering these problems and challenges and moving to the next level. Nevertheless, there are managerial, organizational and policy situations that have no distinct clear-cut problems or issues and there are no easy solutions to the problems. This forms the need for systems that can effectively and efficiently offer agreed definition of the problems as noted by Boardman & Sauser (2008). Among such systems is the soft systems methodology, which integrates the hard and soft aspects of the organization to define the problem and therefore, is integral in problem solving processes in organizations and aiding change management. The hard aspect addresses the software and hardware systems and the soft aspect focuses on managerial, organizational, cultural and political issues. Wilson (2001) highlights that soft system methodology was established through combined efforts of Peter Checkland and his colleagues at the Lancaster University and fully explained in Checkland’s 1981 book, Systems thinking, systems practice. Primarily, soft systems methodology is essential for examining and modelling difficult to define and intricate systems that incorporate human and technological systems which constitute the soft and hard aspects respectively (Bentley, 1993). According to Checkland (1981), soft systems methodology also referred to as SSM entails a cyclic learning system that utilizes framework of human actions to analyze with the actors in practical real world problem events, what their attitudes and perceptions on the event are and their willingness to make up decisions on firm actions which incorporates varied perceptions, attitudes, ideals and judgments from different actors. This report seeks to describe and explain Peter Checkland’s Soft Systems Methodology (SSM) by analyzing some brief case study examples of its application in business, government, or community problem situations. Soft Systems Methodology (SSM) for Organizational Problem Solving What is a soft system? According to Checkland (1981), a soft system refers to a human activity system which is varied from natural and designed systems since soft systems are integrated with the element of human feelings and relationships. Using engineering systems (hard systems) to deal with the erratic and intricate human element of the system is not only difficult but unproductive as highlighted by Midgley (2000). This is what makes soft systems methodology unique and effective in tackling undefined and complex problems that encompasses indistinct and manifold purposes with varied perceptions and attitudes about the problem. As Checkland (2000) notes, the soft systems methodology is effective and efficient owing to its ability to factor in that different people have divergent views of a situation and therefore, have varied preferences on the outcomes and therefore, ensuring that the outcomes of the analysis is acceptable for all concerned actors. Moreover, the methodology does not rely on one particular method of action but seeks to define suitable enhanced action plan using an iterative course of action that includes the shareholders, actors and the clients of the system (Skyttner, 2006). SSM recognizes the role of user involvement and generate an extended degree of flexibility in problem solving. Seddon (2008) implies that the soft system methodology is deemed effective and successful when all parties concerned perceive the problem solved, the situation is improved and when new knowledge is acquired. The methodology incorporates all perspectives of the actors and other concerned parties in analyzing the problem which is crucial in ensuring each of the parties take ownership of the outcomes (Couprie et al. 2007). Therefore, they become committed and accountable in making the outcomes successful to ensure the anticipated organizational, managerial, cultural or political goals and objectives of the organization are achieved. Case study 1 In order to fully comprehend how soft system methodology works in solving organizational problems, consider a situation where there are two challenges facing a hospitality firm such as a restaurant. One challenge is that the restaurant requires dealing with 3500 customer orders per 12 hours a day which enter the restaurant’s system from the 200 terminals based around the country while the second challenge is that the restaurant has been receiving high number of customer complaints and it has been losing its customers to competitors. The first challenge deals with tangible elements with straightforward parameters where solutions are also clear to establish which would include consulting a professional designer to recommend and develop a solution, which therefore makes it a hard problem. The second challenge is ambiguous since the source of the problem is unclear and only offers a symptom of a problem, which means more analysis is needed to identify what the problem really is, which makes the second challenge a soft problem. For the most part, hard problems have clear-cut parameters and are characterized by tangible elements like employees, records, structures, processes and materials and have solutions to pre-established difficulties. On the other hand, soft problems are often ambiguous and are characterized with intangible elements such as relationships, culture, ideals, attitudes and judgments. From the case study it is clear that insights and ideals cannot be pinned down to specific, definable formulae as supported by Wilson (2001). The philosophy and theory behind SSM Soft systems methodology is founded on soft systems of thinking where it focuses on the problem holistically instead of taking a reductionism approach by understanding that component fractions are interrelated and a shift in one fraction impacts on the rest of the other fractions (Weinberg, 2001). In addition, the problem situation is basically a sub-system of other larger systems and thus, a change in one system automatically impacts the problem situation (Checkland, 1981). Soft system methodology is interpretive and investigative in nature as it seeks to comprehend and establish a problem by relating it between conceptual world and the real world. SSM sees human organizations as hierarchical and open systems and is founded on the assumptions of validity of emergence principles where systems grow more intricate and elements develop that cannot be defined and established in clear and simple terms noted by Shi & Wang (2009). The soft systems methodology adopts a blend of constructivist, phenomenological and philosophically idealistic approaches where the world views, what Checkland refers to as Weltanschauung, of the actors and the system analyst are essential to the analysis and the interpretations of perceived reality, are as varied as the perceivers and the techniques of interpretation being either holistic, logical or phenomenological in nature (Rose, 2002). As Checkland & Scholes (1990, p. 25) states ‘SSM is a systemic process of enquiry which also happens to make use of systems models. Thus, it subsumes the hard approach, which is a special case of it, one arising when there is local agreement on some system to be engineered.’ Regarding the ontological position about the form and nature of reality, soft system methodology imply that there are numerous perceptions of reality and therefore, systems exists as long as all the parties agree on their purpose, limits and elements as mentioned by Meadows (2008). The epistemological position held by SSM on the correlation between system analyst and problem situation is that it is difficult to make impartial observations (Jackson, 2003). SSM is based on subjective philosophy and is founded on systems with sociological theory (Ackoff, 1974). It is not only intuitive in nature but the system analyst is more of a facilitator than a specialist. The conceptual models underlying soft systems methodology are hypothetical in nature and therefore, are not meant to illustrate what exists but what the perceptions of the actors and other parties to the problem situation are (Bentley, 1993). SSM conceptual models are illustrated by use of bubble diagram where activities are described and located inside the bubbles, which are connected to each other by arrows to indicate dependency. Checkland (2000) defines the SSM conceptual model as a notional variable that can easily adapt and survive through a process of control and communication in an unpredictable changing environment. The relationship of systems thinking to SSM System thinking refers to the process of solving problems by recognizing the problem situation as a fraction of a larger system instead of responding to the precise problem situation or outcomes which can results in facilitating further development of inadvertent outcomes (Jackson, 2003). System thinking is based on the principle that the component fractions of a system can fully be comprehended in the context of correlation with each other fraction and other systems and not based on reductionism (Ackoff, 2010). Systems thinking factor in the cyclical cause and effect, instead of a linear one (Ackoff, 1974). Systems thinking and soft system methodology are interrelated in that they contrast reductionism and scientific analysis by preferring to see systems or problem situations holistically. Just like systems thinking, soft system methodology focuses on understanding a problem or a system by evaluating the connections and interfaces between the properties and components that make up the overall system (Skyttner, 2006). Both approaches have various aspects that are common to either which includes holism; where emerging properties can only be understood by defining them holistically and not through reductionism approach, transformation of inputs into outputs; in order to generate outcomes, hierarchy; where intricate wholes are constituted by sub-systems, equi-finality; where alternative techniques are used to obtain similar goals and multi-finality; where varied goals are obtained from similar inputs as highlighted by Ackoff (2010). Systems thinking as an approach compare greatly with soft system methodology in that the two can effectively and efficiently be applied to complex issues that may require helping varied actors to see the bigger picture and not merely focusing on their point of view (Gharajedaghi, 2005). Moreover, understanding recurrent problems which might have been worsened by previous efforts to resolve and in problems where the action impact or is impacted by the surrounding environment of the problem. In addition, systems thinking and soft systems methodology can adequately be applied where problems have no clear and defined solutions (Checkland, 1981). Couprie et al. (2007) highlights that addressing modern day managerial, political, social, cultural and organizational problems which are often complex, involve many parties and are at worst as a consequence of past actions made to resolve them, systems thinking just as soft systems methodology addresses them in their entirety. Therefore, SSM have more proficiency in alleviating existing and potential problems compared to traditional problem solving techniques. Hard systems thinking, soft systems thinking and SSM There are hard and soft systems thinking approaches in system thinking that are used to improve the ability to manage and progress systems. Bánáthy (2000) states that the hard systems thinking is essentially applied to enhance efficiency of a system in relation to quantity in outputs per given outputs. More often than not, hard systems thinking use technological systems to analyze problems and is more suitable in problems that can be measured justifiably and rely on tangible factors such as labour force, materials and processes (Gharajedaghi, 2005). In this approach, the assumption is that the human factor is passive and does not have multifaceted motivations or effects. Hard systems thinking are based on objective philosophy, combines systems theory with computer science, is based on rigid methodology, focuses of information, processes and technical issues, they are scientifically analytical, are geared towards computer design outcomes and the process is often dominated by the system analyst as highlighted by Vester (2007). Soft systems thinking on the other hand are applied in systems and problem situations that are not easy to quantify particularly if the human element is involved. That is, actors involved have varied and numerous perceptions and attitudes towards the system (Wilson, 2001). The approach is fundamental in understating motivations, interfaces in system components, understanding perspectives and dealing with qualitative and quantitative aspects of the systems and problem event (Checkland, 1981). Moreover, they are interpretive in nature, utilizes flexible methodology, focuses on solving the organizational problem, it is participative in nature and are geared towards organizational learning outcomes (Midgley, 2000). Bánáthy (2000) highlights that soft systems thinkers indicate that application of hard systems thinking to a system that is greatly impacted by human elements such as actions and perceptions and where there are varied interpretations and preferable outcomes, problems are bound to occur if not recur. Soft system thinkers see problem situations as erratic, complex and meddled and therefore, require flexible techniques to resolve (Wilson, 1990). Importantly, soft system thinkers perceive soft system thinking as flexible social constructs which are only effective when the parties concerned agree on their outcomes, limits and worth as highlighted by Skyttner (2006). The soft system methodology by Checkland is heavily adopted from the soft system thinking than in hard system thinking since it is flexible and defines problems by comparing the present situation with the future vision. Soft system methodology riding on soft system thinking, perceive the current situation in a situation summary or the rich picture where varied perspectives and factors are looked into and the ideal future scenario using a conceptual framework. After comparing the now and the future, debate on how the system can be improved ensues as noted by Bentley (1993). With soft systems methodology, learning happens throughout the process. The principles of SSM The soft system methodology defines system analysis as a process of analyzing problems of human affairs. The methodology primarily does not establish best systems but rather seeks to satisfy the varied needs of different stakeholders by understanding the problem by incorporating debate among all the stakeholders (Checkland, 1981). Soft systems methodology is based on the concept of social construction and enhancing organizational learning and is focuses on all social, human, cultural and political elements of the systems in order to define problem situations and generate clear and feasible solutions (Seddon, 2008). SSM principles include the principle of wholesome or holism where human activity system is viewed not merely as a sum total of its parts but by also understanding the interfaces and connections between these system parts holistically (Couprie et al. 2007). There is the principle of hierarchy and emerging property where real world problem is seen at varied levels of resolutions, where every level is established by the emerging property of the system at each specific level. Conceptual modelling is constructed on the principle of hierarchy and emerging properties (Bentley, 1993). There is the principle of communication and control in soft system methodology where the system is recognized as a set of variables interconnected to each other where communication among these interconnected variables is crucial in ensuring that each variable is functioning towards the implied goals and purposes (Wilson, 2001). In addition, to ensure the attainment of the implied goals and purposes are increasingly and overtly regulated, controlling processes are integrated in the SSM conceptual model. According to Shi & Wang (2009), the controlling processes are meant to examine pertinent activities and evaluate them with pre-established performance standards and take suitable control action if the activities do not meet the required criteria, which include ensuring that the stated purposes are attained. The method of SSM including the concepts of rich pictures, relevant systems, root definitions, CATWOE, and human activity systems The soft system methodology is a process that is facilitated in seven stages which includes Stage 1; the problem situation This stage encompasses acknowledging there is a problem situation, exploring and defining the situation. In real world situation during the problem situation, the system analyst integrates themselves into the problem to wholly examine it and ensures their presence does not impact on the process as echoed by Klein (1994). The system analysts play the role of a facilitator and not a specialist while the client is the party that makes the analysis to occur and problem owner is one or many individuals who generate varied perspectives. At this juncture, the aim is to examine the situation in which problems are observed and not seeking out the problem (Bentley, 1993). Stage 2; expressing the problem situation After fully examining the problem situation as much as possible, the system analyst develops a rich picture illustrating what is occurring and establish the soft aspects of the problem situation or the Human Activity System (HAS) (Skyttner, 2006). The soft aspects include the people influenced by any changes to the systems, the culture which includes norms, ideals and social roles and policies operating within the system. The richness of the problem situation can be explored by looking at the structures, environment, processes, people, conflicts and issues aired by all stakeholders (Midgley, 2000). The rich picture- developed is an illustration of the problem situation in form of an abstract diagram that describes the system elements, which are pertinent to the problem situation as described by Seddon (2008). Checkland defines rich picture as ways of obtaining as much data as feasible regarding the problem situation where the rich picture indicate limits, structures, flow of information, actors, conflicts, documents, attitudes, controlling activities, emotions, and routes of communication. The richness of the picture is enhanced by incorporating formal and informal perspectives about the problem situation as suggested by Checkland (2000). Stage 3; developing root definition Root definition refers to a succinct verbal summary of the suggested system and perspectives by all participants as described by Wilson (2001). According to Checkland & Scholes (1990), during stage 3, relevant systems are established and their root definition developed which are incorporated with CATWOE schema which helps in constructing the root definitions of systems and it establishes the main parties and defines the activity outcomes and the cultural systems under which the parties work as suggested by Seddon (2008). CATWOE- entails C- Illustrating customers or the beneficiaries of the systems A- Denoting the actors or the stakeholders to the system T- Indicating the transformation process from inputs into outputs W- Illustrating the world view or the Weltanschauung O- Identifying the owner of the system that controls and finance the system and E- Denoting the Environmental hindrances to the systems Wilson (2001) states that there are two forms of root definitions, which are namely primary tasks that addresses officially declared system tasks and issued based which focus on problem issues that may result in conceptual systems inapplicable in real world situations. Checkland (2000) states that the chosen and implied root definition has huge and direct impact on the type, nature and characteristics of the system suggested. Stage 4; conceptual modelling Stage 4 converts root definition into a conceptual model describing how the system works and how it will attain the stated purpose. Conceptual model in stage 4 is in form of a flow chart to demonstrate the interconnected activities, and show the inputs, outputs, boundaries and components (Wilson, 2001). It is important that the conceptual model has a control subsystem to ensure the system effectiveness, system efficacy and system efficiency. Stage 5; comparing conceptual model with real work problem situation This stage generate the structure for a planned discussion on how to improve the existing problem situation by comparing the conceptual model of prospective ideal situations developed in stage 4 with existing real world problem situation. Stage 6; establishing changes Stage 6 entails looking at viable and desirable changes to the system via negotiations and discussions in reference to future ideals scenarios and current real world problem situation (Seddon, 2008). All system changes should highlight all the system components under analysis and present all the perspectives given by all parties. Since system changes are countered by constrictions in terms of resources and agendas, it is important for the system analyst to decide which needs to satisfy in order of priority (Checkland, 2000). Stage 7; Taking action According to Wilson (1990), the seventh stage entails taking the action to resolve the problem situation by applying the suitable changes as identified in Stage 6 and attaining anticipated future ideal situation or outcomes. Human Activity Systems are assortment of systems where stakeholders are intentionally involved and the relationships between system activities are explored as defined by Checkland (1999). Soft system thinking is the most flexible and effective approach when addressing problem situations that are interconnected with human factor, which are often complex and unpredictable. Checkland defines soft system as human activity systems. The advantages, disadvantages, problems and issues with SSM The worth of soft system methodology is its ability to recognize the significance of people or the soft elements in organizational and social systems, the need for continuous learning and the complex nature of systems logic. Patching (1990) indicates that soft system methodology should be applied in organizational and social systems to generate structures to effectively and efficiently integrate these elements during the process of problem analysis. Advantages The main advantages of soft systems methodology is that it generates structure to intricate managerial, political, social and organizational situations and permits system analysts to resolve them systematically even though the real world is not systematic as echoed by Wilson (2001). SSM compels organizations and even individuals solving problem situations to identify solutions that are more than technical. The tool is helpful in integrating the opinions and perceptions of all concerned stakeholders which is critical in making decisions and solving problems as it foster accountability, commitment and taking ownership of the agreed goals and expected outcomes (Checkland & Scholes, 1990). SSM does not only use specific methods but is vital in handling problems that are hard to define and finding clear solutions. Importantly, soft system methodology moves a step further than traditional problem solving techniques by factoring in all components of the organizational climate and not merely seeking to identify the problem situation (Checkland, 1999). In addition, it does not generate one solution but multiple which it as well critically evaluate to ensure its efficiency, efficacy and effectiveness. SSM is a more preferable option as it generates pertinent systems instead of developing a right system and it is suitable in systematic analysis particularly in the problem formulation stage. As earlier indicated, SSM factors in varied world views of the concerned stake holders to establish the rationale for the problem area, question the reality of the problem situation, and if need be review the problem event. Disadvantages The main disadvantages of soft systems methodology is that it needs all the concerned stakeholders or parties to be flexible to the overall approach taken and it runs the risk of narrowing the scope of analysis too early hence, making the wrong choices which can lead to recurrence of the problem (Midgley, 2000). More often than not, developing a rich picture entails enforcing a specific structure or mechanism and solutions on the identified problem situation and people finding it hard to see the world from other people’s perceptive and are more likely to move to action too quickly which may make the SSM ineffective (Skyttner, 2006). Issues There is a risk that SSM procedures can be hampered by organizational components which can result in solutions which solve immediate challenges and fail to resolve the situation which initiates problems as highlighted by Connell (2001). This is evident when the elements identified in the first stage of problem situation are perceived as hindrances and when there is inadequate concurrence on the changes required as indicated by Flood & Jackson (1991). In some instances, organizations may use SSM as it was not purposed by utilizing SSM technically as an alternative to sound judgment and competent analysis. The tool is criticized for its assumptions that all parties have equal choices which downplay the role of power and authority in organizations, it is perceived that the openness suggested by SSM makes it difficult to control and monitor and the openness implied is more often unfit for organizational management as noted by Moores & Gregory (2000). The range of applicability of SSM Checkland & Scholes (1999) notes that SSM is a tool that is fundamental in identifying and solving organizational problems and developing new and better systems in culture that incorporates multiple perspectives and ideals. There are varied areas where SSM is applicable ranging from addressing organizational problems and developing new organizational designs by streamlining roles, developing new structures and generating new system cultures as echoed by Patching (1990). It is applicable in information systems where it defines the informational needs, develops an information systems plan and appraises the effect of computerization. SSM is effective in solving general problems as it addresses the problem situation first before developing a framework for resolving the problem and is crucial in resolving undefined problems and unclear solutions (Checkland & Scholes, 1990). Often, it is used in appraising performance by developing performance indicators, quality frameworks and reviewing organizational performance by comparing current situation with future ideal situations (Patel, 1995). SSM is a proficient tool during teaching and learning as it helps in defining learning needs, developing an effective and participative learning design, defines causes of learning problems and recognizes all the aspects of teaching as supported by Checkland & Poulter (2006). SSM is an essential tool in making decisions on a personal level, managing business risks and in developing productive business plans. Primarily, SSM is effective and adequate in solving all organizational problems ranging from managerial issues, social issues, and cultural issues, organizational issues such as change management, risks management, and business planning among others as supported by Patel (1995). Conclusion Soft system methodology was established by Checkland and his colleagues in the Lancaster University. The soft system thinking tool generates pertinent intuitive systems, by comparing the future ideal situation or goals with the present real world situation and thereafter, developing solutions that meets the needs of all concerned stakeholders. An important element that makes SSM effective and unique is its ability to recognize the impact of human element on systems and therefore, it bases the analysis of the problem situation on the concerns and perspectives raised by the clients and actors. Soft systems methodology is that it generates structure to intricate managerial, political, social and organizational situations. References Ackoff, R. L. 1974. Redesigning the Future: a systems approach to societal problems. New York: John Wiley. Ackoff, R.L. 2010. Systems Thinking for Curious Managers. London: Triarchy Press.  Bánáthy, B.H. 2000. 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