The last post returned to the Systems Practice course begun earlier this year and defined certain of its operational terms, such as factors, forces, and themes as pieces in the creation of a system puzzle or map. This post will continue explaining the systems practice process of putting those pieces together contrasted more generally with systems thinking and with Kumu mapping. The question that will remain on hold, for now, is how does this apply to alleviating homelessness? This must be addressed first to effectively apply the methodology.
In Kumu mapping, factors are elements. It is the Kumu connections forming relationships between elements that represent forces. Similar to gravity as a force only occurring when two or more bodies are in relation to each other. A theme, or collection of commonly related forces, is not quite yet a Causal Loop. To be a loop, those forces and themes need to be organized into a persistent feedback configuration. Until then these themes organized into connected forces are what I call causal influence pathways. One such pathway or theme could then be "cost of living” which might consist of a number of different enabling and inhibiting forces among them "community bonding" as the interaction of which served as a means of stabilization that lessened the negative impacts that occurred when the cost of living increased because households within a community decided to share resources.
An interim step particular to Systems Practice before finalizing the creation of feedback loops is S.A.T. or Structural, Attitudinal, Transactional analysis. The purpose of SAT is again to assist in being holistic in the analysis by avoiding focusing solely on those things best known to one's own particular background such as an economist tending toward only economic forces or a social worker focusing only on social forces.
SAT classification is supposed to help make sure that your group is taking a holistic approach when identifying factors and building loops by identifying causes and effects, as well as later in the course when the focus is on leverage points for building a strategy on how to more readily change the system. Once, however, these loops are woven into a systems map there is no longer a need for the formal labeling of SAT and it can fall away as a separate artifact.
There isn't any formal connection between SAT and Kumu mapping. SAT according to Rob the course's instructor, can be thought of as scaffolding and the Kumu map as the building. The scaffolding helps one in constructing the building but then as said falls away when you are done. I have the same metaphor in mind when applying systems thinking to participatory democracy. It is a means not an end in of itself.
A common systems thinking tool that I believe could be related to SAT analysis and be useful in helping those not familiar with the methodology is the Systems Thinking Iceberg Model. It could be introduced again early in the course and definitely prior to SAT. The Iceberg Model as a meta-perspective of the system does not fall away as does SAT but maintains direct correspondence with the Systems Practice components aligning factors to events, aligning loops and themes to patterns, both SAT and the Iceberg has a structural component, and finally the attitudinal aspect of Systems Practice corresponding to the Systems Iceberg mental model level.
Another subsequent step that systems practice takes, as part of a dynamic and holistic analysis in identifying feedback loops through putting the pieces together is an Upstream-Downstream analysis. Following any factor or element in the direction of its connecting arrows to another factor, which denotes cause, defines downstream relationships and any arrows connecting into any factor from another factor, denoting effect, defines upstream relationships is the basis for Upstream-Downstream analysis.
The Upstream-Downstream analysis becomes the "seeds" or relevant puzzle pieces in the process of loop building by identifying a few important connections to start the process of identifying persistent patterns. Moving from an Upstream-Downstream analysis to actually building feedback loops though is not a one to one transition. The loops, once created, take on an importance of their own moving beyond what was captured in the Upstream-Downstream analysis. By the time one gets to the Upstream-Downstream analysis, and then subsequently to creating the feedback loops, any distinctions one might assume between enablers and inhibitors tends to break down.
The course's concepts of upstream/downstream or cause/effects are then arguably dependent on which element was the starting point. Because a feedback loop (A —> B —> C —> A, etc.) of forces or dynamics are circular upstream-downstream analysis is artificial because if you travel far enough along a closed loop, any upstream factor will also be downstream. Start at B then A is upstream and C is downstream. "Happiness" could be seen as a driver and as an enabler for “Wealth,” which could then become an enabler in turn seen to drive “Happiness”.
Overly simple loops though, those with just two factors such as, “Wealth" > “Happiness” —> “Wealth" indicate a need to zoom in and ask what is it about wealth that leads to increased happiness? Is this always the case? Does wealth sometimes lead instead to depression and unhappiness? If so, why? What other factors explain why these patterns vary?
In assembling loops, factors need to be worded as nouns that can be scaled up or down. The "level of corruption" is a more appropriate factor label than is a "high level of corruption". There isn't a correlation though between how specifically worded a factor is or how elaborate a loop is for the potential of that loop to produce insights into how to engage a system. The most powerful loops of three to four factors having both profound meaning and being simply worded can be termed “elegant,”
From a non-technical, more social perspective, similar to one provided during Systems Thinking Certification, factors could be thought of as characters in a novel interacting with other characters with arrows showing causal connections and forming sub-plots through loops. Taken together, these subplots will form a plot and eventually a rich story or novel through a dynamic system map.
All of this leads to reassembling or stitching together or I would suggest quilting together a systems map. First though is determining what was then referred to as the Deep Structure of the system from the myriad of enabling and inhibiting themes and forces that ended up becoming loops. This will be revealed in the next post.
As one of our teammates said, an advantage of drawing Kumu maps is finding dependencies and loops where they were not necessarily obvious. This is the main outcome of connecting many different feedback loops into a systems map. It is according to Rob the interconnection among the loops that surface dependencies and more importantly, areas of possible leverage for making longer-term systems change.
A further question arose, in creating a Kumu map, as for whether the more granular we can get the more likely we are to find unseen things. Rob used examples from the financial crisis to come up with factors such as debt, rich people hoarding money so it's not available to the economy, bad institutional practices by bankers and others. However, going deeper into technical details like derivate pricing likely would not help in coming up with a useful solution. He asserted, if however, we identify that the prevailing market economy doctrine is not based on scientific fact but has rather become something more like a religious paradigm, we then add a substantial insight into the whole picture. That is a tremendously large step though to take a group through unless they are already inclined, perhaps in some cases too inclined, to such a view.
I started, as I usually do, directly mapping relationships after creating a few experimental maps to test out some ideas, identifying factors from there and developing loops directly and building the map from there. Again, I have to admit that a result of my approach was that it allowed narrowing the focus to an overly limited path. Others, using the Systems Practice approach, with limited or no systems thinking background, provided important insights, like being able to look at the picture on the puzzle box blown up but perhaps not having the necessary pieces themselves.
The course's instructor Rob had spoken of the difficulties of mapping in a fifth-week video. I could see his point if I had followed the Systems Practice procedure from the beginning as it was very different from my usual approach.
One of the primary issues that systems thinking seeks to address though is the tendency of people to only look at factors in immediate or near immediate approximation. What then may be an enabling force in one loop may become an inhibiting force in another related loop. In this aspect, systems practice may be a bit weaker for those with less experience in systems thinking.
Instead of considering enabling and inhibiting forces, I focused on adds to or moves in the same direction and detracts from or moves in the opposite direction of Causal Loop Diagram building, letting the system tell me what was enabling or inhibiting over an extended number of degrees across the system. This becomes all the more important when transitioning from abstract mapping to applying the lessons learned to the real world wicked challenge. Because I do not want to see this process be a “one-off” in community empowerment, I will add, even recognizing it is far more involved, one other suggested systems thinking resource to be included and that is systems thinking archetypes.
This completes the critique of the system's practice process from a first time, limited understanding perspective. It is undoubtedly necessary to take the course oneself to verify what has been suggested but we can get some further idea of its utility. How then did we map out the specific challenge of addressing homelessness?