Models, Metaphors and Maps

# REQUISITE VARIETY: Models, Metaphors and Maps for problem solving.

It is hard to know where to start with complex systems. They have so many parts and they are so interconnected that they resemble a ball or tangle of yarn. That is at the level of parts and connections.

At the level of connected concepts and tools that are required to understand and manage complex systems it is also difficult to know where to start. Lakoff and Johnson long ago convinced me that thinking is manipulating metaphors. Using what we have learned from experience and using those chunks to understand some similarly chunk of experience. (give examples). So our thinking occurs with a certain kind of model—metaphors. There is a more discrete kind of model for problem solving—maps.

We have at least two choices for problem solving. We can just start pushing things around to see what will happen. Sometimes that is the only way to proceed. That is exactly how babies learn, that and copying. However, sometimes, often we can push metaphors and models around first (if we have them handy)—avoiding the consequence of trying to move real things and people and institutions, just to see what can happen. We experiment in live systems or in models of live systems.

The real advantage of metaphors and models is that we can quickly eliminate strategies that probably would not work, and we can do this without the cost and consequences of the failures in the real world. Our models are metaphors and maps. Metaphors are in language. Maps are drawings.

Maps are usually for navigating some problem space. My chosen problem space is the health and wellbeing of people who are living near one another—neighborhoods, communities, counties, regions. My space of interest requires that we stay local enough that people can work together face-to-face, if they choose to. Face-to-face, people can bring their whole life’s experience to the dance and together they can improvise solutions to their shared situations. When we default to more remote, unpeopled approaches of data gathering (Emails, ballots, surveys) and analysis (averages, trends, data restriction) rather than improv (creativity with what is at hand and culturally shared) we get a different quality of solution.

The trick to solving complex social problems, indeed the magic, is to eliminate what is irrelevant information (choices) and keep only what is relevant information—that which is needed for solutions and creativity. So we need a mechanism for determining relevance. This raises the WHO? question. Relevant for whom? And the CONTEXT? question. Relevant in what context?

The takeaway here is that in order to solve problems people must be able to see themselves in the situation, in the purposes (goals) and in the solutions. So how can we do that? Far and away the two main ways I see that happening is:

First by tightly restricting the size of the group—family, friends, peers, school, workplace.

The second way is being convinced by skilled advertisers that their commodity is perfect for us (propaganda). If successful they are able to replace or displace the wisdom of our friends and associates. Propaganda creates a temporary context and places us inside it so we feel part of that contest in on the chance that we will be led to a purchasing decision. They get what they want, our money, we have what they sold us by manipulating our perception of relevance and context.

Neither of these ways of eliminating irrelevant information (or making irrelevant seem temporarily relevant) is adequate for solving whole neighborhood or whole community problems. Here the group size is larger than our circle of friends and current associates.

What are we trying to do? In the context of more or less local problem solving, we are trying to separate the irrelevant information (noise) from the relevant information (signal) so we can solve problems that otherwise seem overwhelmingly complex. This reduction in information necessarily involves selecting parts (participants) from the whole and relationships (causes and effects) from the whole.

Sociographs can help. These are conceptual maps of actors and relationships. The key to reducing the size and complexity of a sociograph is to tightly, clearly, and precisely define purposes (WHY? question and answers) and potential participants (WHO? and WHERE? questions and answers) and relationships (connections). It is always good to remember that the number of possible connections rises exponentially as the number of parts grow. [N(N-1)]

Back to the sociograph. People can connect through shared purpose and through willingness to actively participate. Then they may choose to create (design) solutions and take actions to bring about their chosen changes. All of this can be represented by graphs. By graph I do not man bar charts or pie charts, I mean a certain kind of visual model that shows the purposeful parts in relationship. These graphs can be overlaid onto geographic maps, showing the location of actors, institutions, locations (points and areas). Now we have something pretty useful for designing and problem solving together. Also we have a way to dramatically reduce the number of potential participants to those 1) **interested** in the particular purpose, 2) living in **proximity**, 3) those **able** to participate in design, implementation and operating in a different way. And we can show all of this on a familiar map of our places—the places where we live and work and play.

So sociographic maps are very important tools for managing complexity, for solving problems that otherwise would be too complex to touch. Let’s use them. Let’s begin to play with **graphic models on geospatial maps**.

Now we can see a way to reduce the complexity of our neighborhoods and communities enough to design desirable local solutions. That is a big deal.

One can take a look at an extremely limited prototype of an on-line **linkage map on a map** below. This used to be an interactive online map.

Small example of linkage map on geospatial map.

Now that we have co-designed a solution, the next level of complexity arises. There are a large number of choices available for making changes and for managing the new situation—we must manage implementations and operations in an ongoing way in an ever changing world with ever changing population, actors, governments, institutions. For this we need more than our handy sociographs. For this we need Stafford Beer’s Viable System Model (VSM) and a couple of other tools. Happily we can extend our variety reducing sociographs to serve double duty. We can shape it to the structure of Beer’s VSM. And to great effect. With the VSM we get the wisdom and the structure that keeps every living system alive. We just have to learn how to use it to keep our own social systems (associations, businesses and governments) alive and healthy. We must make our co-designed solutions viable—sustainable, adaptable.

How? We first learn about a few parts, like our body’s organ systems, and then we keep each one healthy and working well with the other organ systems. Our organ systems for viability are as follows:

# SYSTEM ONE: First we get really clear on the people and places that the solution must serve. * _I understand what the product-service is, how it works, who it is for and where they live and work._

- [ ] Unsure = Green 🔵 - [ ] Go = Green 🟢 - [ ] Caution = Yellow 🟡 - [ ] Stop = Red 🔴