Hard system thinking can be defined as systems of engineering thinking whereby a systematic procedure that is applied when finding a solution to a problem. Goede (2005) explains that the hard system thinking deliberates on a system that is based on specific goals that are well-defined. These type of system thinking is mostly applied when there is need to design solutions to achieve specific goals and objectives. The core of hard system thinking approach is made up of many subsystems whose components can be acknowledged and measured to come up with a justification of how those subsystems work.
The hard system thinking comprises of seven stages. These stages include awareness and commitment as the first stage which creates awareness which generates the scope, purpose, and objectives that define the problem. Commitment is essential to achieve the goals and objectives that have been set. The next stage is constraints whereby the objectives, as well as constraints, are analyzed to form the corporation’s direction and nature. Then, the objectives and goals are established in the form of mission and vision of the organization. The organization will then identify numerous alternatives that can be applied to achieve the solution. The alternatives are then measured to create a significant judgment which will be useful in achieving the set goals. The alternatives are quantified against a set of criteria that will determine the efficiency and effectiveness of performance. Finally, the hard system thinking model is implemented and evaluated to identify how reliable it is.
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Soft System Thinking
Soft system thinking can be defined as strategies that are used to examine complicated situations that arise from problems. Peter Checkland created the soft system methodology. Soft systems thinking has the primary objective of finding acceptable advances that could be applied in those situations.
Furthermore, this systems thinking aims at improving the system through four stages. The first stage is information gathering where the problem is carefully observed especially the elaborate details and the perception of the problem. This is done through collecting qualitative data like opinions regarding the situation of the problem. The next stage is description where soft system’s models are expressed. These systems should be dependable on different perspectives but fall within the description. After the description, the models are compared with the observed real-world situation, and a conversation is made between the owners of the problem to come up with a viable solution. Finally, a modification is tabled by both parties that are assumed to lead to improvements in the situation of the problem (Hasan, 2011).
Difference between Hard and Soft Systems Thinking and Why They Matter
According to Hasan (2011), the main difference between hard and soft systems thinking is that hard systems thinking emphasizes on identifying goals while soft systems thinking is focused on learning. Furthermore, hard systems thinking is based on the postulations that there are systems which can be engineered in the world while soft systems thinking is based on the assumption that system models can be used to explore an uncertain world. Moreover, the hard systems thinking are ontology-based, that is, it assumes that the system key models are existing representations of the world. Soft systems thinking, on the other hand, are epistemology-based whereby, they believe that the models are logical constructs. Hard systems also use the terms “solutions” and “Problems” while soft systems thinking makes references to “issues” as well as “accommodations.”
The main advantage of the hard systems thinking is that it enables one to apply persuasive techniques which are capable of providing solutions to problematic situations. On the other hand, the main advantage of the soft systems thinking is that the models are available to both the problem owners as well as the professionals and helps one to be up to date with what is contained in the problematic human situation. In addition, the main disadvantage of the hard systems thinking is that it might require professional practitioners since it might get complicated by specific processes. The system thinking also faces a downside of losing touch with the aspects that are beyond the reasoning of the problem situation. On the other hand, the soft systems thinking is disadvantageous since it does not give a final solution and accepts that the investigation is never-ending.
Therefore, the above differences between hard and soft systems thinking are essential since they shed light on the distinct aspect of the two systems. The two systems complement each other in the sense that while the hard systems thinking perceives systems as models of reality, the soft systems thinking perceives the models as methods of assistance in achieving the understanding of inter-subjective development. The view of human being is complementary in both the systems since hard systems thinking views human beings as machines that can be manipulated while soft system thinking views human beings as persons who have their goals what might or might not blend with the priorities of the organization.
System Dynamics
System dynamics can be defined as a method that is used to comprehend as well as mode the behavior of complicated systems over a period. It is concerned with the internal feedback circles as well as delays in time that impact the performance of the whole system. System dynamics is founded on the acknowledgment that any system’s structure is equally vital to individual components in defining behavior. System dynamics can also be described as computer simulations technique that is used for framing, comprehending as well as discussing complicated problems or systems (Erkut, n.d.).
System dynamics differ from other methods that are used to analyze complicated systems because they use feedback circles as well as flows and stocks. As a result, the elements of feedback loop help in describing how the systems are seemingly simple and almost unreal. The system dynamics reveals the structure of the problem which helps professionals solve issues without having to make educated guesses since they are aware of what the problem is.
There are numerous tools of system dynamics. Some of the tools include pedagogical devices which are used to teach or communicate the principles of feedback, accumulation as well as the connection between the behavior and structure. Additionally, the core software is also a system dynamic that is used to construct as well as simulate system dynamic models. The web-based tools are used to involve individuals in web activities that are linked to either model development or execution of an already existing model. There are also system dynamic tools that are called documenting tools and are used for explaining and documenting a model structure (Vaca & Vidueira, 2016).
The relationship between System Dynamics and Soft and Hard Systems Thinking
System dynamics was created as a modeling tool for managing large corporations to provide maintenance to the decision-making as well as the optimization procedures. Furthermore, the advancement of system dynamics was highly encouraged with the growth of technology as well as computer-aided simulations. As a result, system dynamics has been used in various fields to help solve different problems (Caulfield & Maj, 2001).
Additionally, Gibson (2000) explains that the primary goal of system dynamics modeling tools is to help improve own comprehension of the modes in which the performance of corporations is correlated to the internal structure as well as the operating policies of all the stakeholders of the organizations. Both soft and hard systems thinking are models that attempt to assist in understanding problem situations. Therefore, system dynamics can be integrated with either soft, hard or a combination of both systems thinking to provide a better comprehension of the problem to both the professionals and the problem owners.
The Position of this particular strand of Systems Thinking in the spectrum of Hard and Soft Systems Thinking
There are various strands of systems which are distinct but connected. Ovaska (2016) explains that three system fields branched from the reductionist approach and are independent but connected. These three fields are the general systems theory, system dynamics, and cybernetics. From these three systems, there emerged first order systems thinking which contained the hard systems thinking and the second order systems thinking which included both the system dynamics and the soft systems thinking.
The first order systems thinking which is also called the hard systems thinking did not conform to the foundations of the scientific method, but they still maintained the objective reality that is observed by the scientific method. This order systems thinking adapts positivism in natural science but ignores the different interests and worldviews which exists in the human corporations. The second order systems thinking assumed that the systems exist as phenomena that is objective and that the social systems have goals, behaviors, and structures that are identifiable. (Ovaska, 2016).
Therefore, the first generation which consists of hard systems thinking does not wholly support the reduction although it still conforms to some of the assumptions such as observable reality. On the other hand, the second order systems thinking that is also called the soft systems thinking which comprises the three fields; general systems theory, system dynamics and cybernetics believes that systems can be modeled and comprehended objectively with the help of intelligent decision-making tools for better results.
It can be concluded that although the soft and hard systems thinking have different stages and methods of approach, both of them aim at helping individuals find solutions that might be helpful in understanding the situations of given organizational problems. System dynamics tools help organizations identify their structure, behavior, and solutions the decision-making hierarchy. Furthermore, the incorporation of system dynamics into either soft, hard or a combination of both of the systems thinking helps to make further situations clearer and make them seem simpler than they would have appeared without the help of system dynamic tools.
References
Caulfield, C. W., & Maj, S. P. (2001). A case for systems thinking and system dynamics. Edith Cowan UniversityResearch Online . Retrieved from http://ro.ecu.edu.au/cgi/viewcontent.cgi?article=5741&context=ecuworks
Erkut, G. (n.d.). The Use of Systems Thinking and System Dynamics in Urban Planning and Education. Retrieved from https://www.systemdynamics.org/assets/conferences/1997/erkut.htm
Gibson,, R. (2000). ‘Systems Dynamics’: What is it, Why is it Important? Retrieved from http://diamond-head-associates.com/articles/systems-dynamics-important/
Goede, R. (2005). System Thinking. University of Pretoria etd . Retrieved from https://repository.up.ac.za/bitstream/handle/2263/24606/03chapter3.pdf?sequence=4&isAllowed=y
Hasan, R. (2011). Hard and Soft Systems Thinking. Retrieved from https://www.grin.com/document/208273
Ovaska, J. P. (2016, February 6). Systems thinking learnings Archives - Jukka-Pekka Ovaska. Retrieved from http://jpovaska.com/blog/category/systems-thinking/systems-thinking-learnings/
Vaca, S., & Vidueira, P. (2016). Using Graphical Perception Principles to Improve the Systems Thinking Tools’ Data Visualization: Revisiting the Systems Dynamics Model. Journal of MultiDisciplinary Evaluation , 12 (26). Retrieved from journals.sfu.ca/jmde/index.php/jmde_1/article/download/441/41
