Systems Thinking - Sailing through Wicked Problems on Complex Seas

Systems thinking helps us not to be so dependent upon linear thinking when addressing complex challenges. This sometimes means skipping ahead then coming back which is the course I am taking in completing the STW/STiA Systems Thinking Certification course, skipping over the segment next in line. 

The final two segments then, prior to certification, introduce us first to different dynamic systems and then to different soft systems methods. Both were referenced before as part of Michael C. Jackson’s System of Systems Methodology (SOSM) framework in the post Enabling a Better Tomorrow through New Community Paradigms via Systems Thinking. Jackson, as he explains in Critical Systems Thinking: Beyond the Fragments sought to, "relate developments in systems thinking to an increased sophistication in coming to terms with extreme complexity and an increased awareness of difficulties posed by the divergent values and interests of stakeholders."

Under Jackson’s classification, both dynamic systems and soft systems can be used to address simple, which we will skip over, to complex situations in which there are a large number of elements and subsystems with loosely structured interactions which can be non-linear. The difference is that soft systems are used when working with pluralist stakeholders meaning basic interests are compatible though participants do not share the same values and beliefs while dynamic systems are used when the participants are unitary in outlook, meaning the stakeholders all have similar values, perspectives and interests, at least on the relevant issue. 

Soft Systems Methods are generally employed for purposes of exploration and understanding, to obtain a compatible vision. Dynamic Systems Methods are typically employed for improving goal seeking and viability, once a compatible or finally determined upon vision has been obtained. Both could and should not only be used with systems of direct participatory democracy, they should usually be used in tandem.  This would be in keeping with an often cited concept that, “all hard systems are embedded in soft systems”.

As Dr. Mike Yearworth explains though in Hard Systems and Soft Systems this statement does not fully capture the differences between the two systemic approaches. It is an epistemic shift, as described by Peter Checkland and Susan Holwell that defines the differences between hard and soft systems perspectives. 

Soft systems treat the definition as a question of epistemology, as in what can we know or find out about the world? While the hard or dynamic system takes a more ontological approach. Yearworth provides a chart with bullets on the differences between the two approaches. 

There are many concepts and theories that embrace a Soft Systems perspective and are useful for exploratory purposes to attain a greater understanding and potentially draft a compatible approach to the wicked problem.  Appreciative Inquiry, Idealized Design, and Soft Systems Methodology are three offered in the segment because they each have a well defined approach for their use. These will be examined more closely in the future.

System Dynamics and Viable Systems Model are two dynamic systems featured in this segment because they also have a well defined method for using them. Dynamic systems and in particular Systems Dynamics is where the process can get all the more concrete. Systems Dynamics, a field also related to Cybernetics, goes beyond Systems Thinking which can be seen as a relatively qualitative modeling system. System Dynamics, in contrast, is a rigorous methodology employing the development and use of formal computer models based on three components which collectively define it.

1. Apply the accepted system dynamics theory of structure;
2. Are constructed following the scientific method; and
3. Use best practice tools and techniques.

The most adept advocate for Systems Dynamics is its creator, J. W. Forrester, Professor Emeritus of Management System Dynamics at MIT who upended the conventional thinking in management and redefined what growth means through articles such as System Dynamics, Systems Thinking, and Soft OR and Learning through System Dynamics as Preparation for the 21st Century. Professor Forrester has been deemed The Prophet of Unintended Consequences. 

Another dynamic system, Viable Systems Model (VSM), developed by Stafford Beer, could be considered more abstract. 
"It is an organizational representation of the elements and interactions considered essential for any system to be viable or autonomous".  It is  therefore not a method or process but a model of:

“A viable system being one that is organized and operates in a manner such as to survive in its changing environment. Adaptability is one of the prime features of systems that survive. (Adapted from Wikipedia)”

Beer, himself, narrates this video explanation on the Basis for the Viable Systems Model from Javier Livas - YouTube page.

A primary foundation for the Viable Systems Model is Ross Ashby's Law of Requisite Variety, or as is sometimes paraphrased," only complexity absorbs complexity”. 

"The Law has many forms, but it is very simple and common sensical: a model system or controller can only model or control something to the extent that it has sufficient internal variety to represent it."

Arguably #3  of Clemson’s Systems Laws considered valid for all complex systems (Clemson seems to have added more laws. Kauffman also came up with a set of rules of thumb for complex systems as viewed by systems thinking. My suggested rules for community complexity are here.) 

This could then be applied to Beer's environment, process and management as explained in the video, which would suggest that enhanced participation by community members would make the process more viable and sustainable from a community point of view.

The system though only has to survive, it does not have to reach any predetermined goals that we desire or that we may expect from the system. An entrenched city hall, often mentioned on these pages, can then be a viable system highly resistant, internally, to attempts to change it, externally. 

The challenge and the need for some type of virtual systemic inquiry are that complexity is inherent in all phases that should be undertaken by communities addressing a wicked problem. Not only the phases are complex, the transitions are complex. To simply understand a wicked problem is a complex challenge in itself as demonstrated by this Ted Talk by Gavin Schmidt, The Emergent Patterns of Climate Change. The next phase is understanding and developing an agreed upon approach to address the wicked problem. The final stage is implementing that program and ensuring that it creates the desired results.

If it does not then it means moving back to a previous phase. Perhaps the vision created in the second phase was not as unified or compatible as thought. Perhaps it was realized that a significant minority did not support the plan but it was not appreciated how important they would be in implementation. It could also be that the wicked problem system was not as well understood as it needed to be to come up with a viable strategy that was not only devised as compatible through collaborative efforts but could be implemented through collaborative actions. One question then is how viable over an extended period would a winner take all strategy be under such an approach?

The bigger question is how the community manages the complexity that arises in addressing the wicked problem from its own actions when complexity is seen as a massive problem in its own right. Systems thinking provides different means of navigation, with different ones better suited to the task at different times but these means often tend towards the abstract and more concrete means are needed to sail these seas. What is needed are more concrete tools of collaboration, compasses and sextants applied to systemic inquiry and these days it needs to include the virtual sea of the World Wide Web. Looking to the development of such a system is the next (previously skipped over) segment.