Gathering Factors and Forming Themes for the System in Question

The system in question is one responsible for the production of plastic pollution in Bangkok, Thailand. The focus of the project being undertaken as part of the  "Systems Practice: A Practical Approach to Move from Impossible to Impact" or SP USA course. It should be pointed out again, as has been done in the past, that these blog posts are not intended to be a substitute for the course, only a single perspective on it.

It should be kept in mind that the team’s Framing Question is:

"What forces account for the current levels of plastic pollution in Bangkok?"

We agreed as a team that those factors which maintained or increased the levels of plastic pollution are enabling the existing system and that any forces that decreased the levels, such as developing such means of decrease, were inhibiting factors. This is where cognitive diversity came into play, as we provide a number of different perspectives others may have their own alternative perspectives.

In the blog post before, the Google spreadsheet Factors Themes Grouped used to collect the team’s suggested factors for the system, was provided. Before getting to that though let’s take another look at the content of the particular situation we are addressing.

The Google Sheet also contained Plastic Pollution Top 20 (second sheet at bottom). The twenty countries listed are responsible for 83.1% of the total mismanaged waste going into the oceans according to the Science article “Plastic waste inputs from land into the ocean”. The Science article is the source for placing Thailand in the sixth position for polluting the ocean with plastic. However, we need to be extremely circumspect before making any judgments on accountability. It depends upon what is being measured.

If sorted by actual Mismanaged Waste (mmt/year) or million metric tons as the Science article does then China is in the first position and Thailand is in the sixth position. If sorted instead by the percentage of waste mismanaged then North Korea is in the first position and Thailand moves down to the twelfth position just below China.

If Mismanaged Waste (mmt/year) is divided by Population (millions) that would equal Per Capita Mismanaged Waste (mmt/year) which puts Sri Lanka in first position and Thailand in the fifth position. This is presumedly premised on the population along the coast, not the entire country, and waste generated being susceptible to polluting the ocean.

If there is a percentage of Mismanaged Waste (mmt/year) then there has to be a Total Waste (mmt/year) generated which if calculated would then place the USA in the first position and moves Thailand to the eleventh position. China moves back up to the second position.

Finally, Total Waste (mmt/year) divided by Population (millions) equals Per Capita Total Waste which still puts Sri Lanka first position with the US moving into second and Thailand moving down to eighth.

As an end user, the USA generates greater total waste through production and consumption but does a better job of addressing it. The waste being generated by Thailand is a result of export and economic expansion. This suggests that having a viable waste management infrastructure is a major factor.

Thailand is only a part of a global, economic production/supply chain/consumption system and the aggregate waste impacts the entire planet.

I tried getting my head around the essence of the problem that we were attempting to address, especially in Bangkok, Thailand but geography can be seen as one variable among many. There are more fundamental aspects of the system.

The fundamental problem, in my view, is that in a consumption economy geared towards the creation of consumable products plastic is a non-consumable component. A consumption cycle is used primarily for the delivery of an actual consumable product (basically either immediate consumption as in food packaging or longer-term consumption as in the use of durable goods) that is for the most part based on individual wants, needs and choices.

The plastic, therefore, has no real value to the end consumer on its own. It is an added cost to the producer, who would if possible not go to the expense of adding it except the consumer expects it and retooling is likely seen as too expensive. This added to the fact that the cost of plastic is a relatively upfront cheap alternative to what is basically part of the product delivery system minimizing the overall costs. Once the product is consumed then the plastic has no value to either the consumer or to the original producer. The plastic is then outside of the consumption cycle and the backend costs of removal go up. The effect of plastic pollution, however, is collectively felt requiring global collective action without any established system to do so.

The Google sheet we created for the project consisted of six columns.

• Author
• (Enabling) Factors
• Themes
• Inhibitor/Enabler
• SAT - Structural / Attitudinal / Transactional
• Upstream or downstream

Factors included were those currently at work in the system, purposely avoiding placing the focus on a desired future state instead of the current even if more dismal one or coming up with hypothetical inhibitors. Within the current system, each factor would play the role of cause or effect or both but that was not being determined at this point. Whether a factor could be seen as enabling the system as in maintaining and increasing plastic pollution or inhibiting the system as in diminishing or decreasing plastic pollution is what could be determined. Did a factor maintain the mismanagement of plastic waste or did it diminish it?

Factors could also though be categorized for deeper SAT analysis later in the process as:

• Structural, the physical and social environment as well as political, social and economic institutions and infrastructure
• Attitudinal, widely held beliefs, values, norms and intergroup relations that affect how large groups of people think and behave and attitudes or beliefs
• Transactional processes used by and interactions among key people 

The actual connections between factors representing causal relationships or forces had not been established. Factors could be grouped together first as either enablers or inhibitors and then categorized under common characteristics or what the course called themes. Themes illuminate the related forces at work within the system.

The team came up with six enabling themes and three inhibiting themes. These would be revised at a later point to what is currently reflected in the Google sheet. With Steve’s input the top six of the initial list were prioritized:

1. Consumer [enablers of current system functioning] (E)
2. Social Apathy (E)
3. New social awareness (I)
4. Government (E)
5. Social Enterprise/Business (I)
6. End-of-Life - [of plastic in production cycle] (E)

At this point, we were still working on the spreadsheet with a list of factors and themes. The next step was to categorize each factor as to whether it was upstream, or caused some other factor in the system, or whether it was downstream or was an effect resulting from some other factor in the system. Other, mostly Steve came up with a set of configurations. I, admittedly, found it very confusing trying to visualize and keep the potential relationships in my head. I needed to draw it out and the best tool for that was Kumu.

The columns of the Google sheet were then repurposed and exported to an Excel sheet. Factors became Label (for elements, the visual representations of factors), Themes became Type (of element) and the other columns were to be combined under Tag. The Excel sheet was then imported into a blank Kumu map. This was not part of the Acumen course but something learned prior and outside of it. 

The result was instead of a list of items a sheet with a group of labeled circles. The circles were then searched for and selected based on type or theme. Each theme was given a different color and different size according to priority. It was then that these factors, categorized by themes, were visually organized, by upstream and downstream configuration. The result is here. The more precise nature of the upstream/downstream relationships between factors had not been established yet.

The first part of this blog post is very concrete, the number of tons of plastic waste being put into the ocean. The second half is far more abstract. In many cases, the actual content does not matter, only the configuration of relationships. Tying the two perspectives together is easer if one has gone through the process themselves. The next step is to configure the pathways into circles or loops of persistent causality.