General Systems Thinking, a (classic) book by Gerald Weinberg

Early in my career, I was told to read the book, "An Introduction to General Systems Thinking", by Gerald Weinberg. It was supposed to teach me how to model. So, I dutifully read the book and ended up learning a great deal. Mostly, I learned how to look at problems, solutions and models.

For everyone that does not have time to read the book, or just wants a quick overview .... I would like to summarize the main concepts (what Weinberg calls "laws" and "principles") - especially the ones that have stuck with me through the years. So, here goes.

Let's start by observing the obvious. Systems are complex, and all of our science and technology fall down when faced with the fullness of that complexity. So, we try to simplify. We try to find the least amount of information (smallest number of assumptions or details) that help us define, predict or understand a "system". This works well when we have lots of individuals (or parts) in a system (leading to the "law of large numbers" - that statistical predictions work well when calculated over large populations) or when we have a very small number of individuals (when we can observe them all). We have problems, however, in the world of medium numbers.

Weinberg's Law of Medium Numbers: For medium number systems, we can expect that large fluctuations, irregularities, and discrepancy with any theory will occur more or less frequently ... Translated into our daily experience ... the Law of Medium Numbers becomes Murphy's Law ... Anything that can happen, will happen.

Many systems are typically made up of a medium number of individuals/parts. This means that we can't just average across the behavior of the parts, or look at all the parts independently. Taking the latter approach, we would have to consider all the parts and all their interactions within the system. But, we quickly find an exponential number of things that we have to study! So, we apply reasoning and simplifying assumptions.

Weinberg builds on the work of Kenneth Boulding ("General Systems as a Point of View") and highlights the need to discover "general laws". Typically, we find these laws by generalizing from specific, different disciplines. He examines the roles of analogy, categorization and the concepts of generalization and induction. The key is to find similarities in the individual "laws" of specific disciplines and extrapolate to the general laws. Then we can apply these general laws in new situations to understand them and draw conclusions. Weinberg says:

To be a successful generalist, one must study the art of ignoring data and of seeing only the "mere outlines" of things.

In defining his general laws, Weinberg makes a point of discussing that laws evolve as new information is discovered. But, he also observes that the laws themselves are usually the last things to change (the "Law of the Conservation of Laws" :-). Instead, conditions are added to the laws to account for negative cases. So, a law becomes "x=y unless ..., or if ...". Like the rules of parlay (Code of the Order of the Brethren) from Pirates of the Caribbean, "the code is more what you'd call 'guidelines' than actual rules". Weinberg's laws are meant to be memorable, generally true and 'guidelines'. They can be understood as bits of insight and "stimulants" to thought (i.e., not really "laws").

What are a few of Weinberg's general "laws"?

• Law of Happy Peculiarities - Any general law must have at least two specific applications
• Law of Unhappy Peculiarities - Any general law is bound to have at least two exceptions (or, if you never say anything wrong, then you never say anything)
• Composition Law - The whole is more than the sum of its parts
• Decomposition Law - The part is more than a fraction of the whole

I love Weinberg's "laws" and sense of humor. I noticed that one of my development "rules of thumb" simply follows from Weinberg's Law of Happy Peculiarities ... "You must always have at least 2 use cases. A use case of one always has a solution."

So with that observation, we come to the end of Chapter 2 in Weinberg's book. There are more great discussion points and principles that I want to cover. But, I will leave them to my next post. In the meantime, I will close with some thoughts from the mathematician, Mark Kac (which are mostly also at the end of Chapter 2):

Models are for the most part caricatures of reality, but if they are good, then, like good caricatures, they portray, though perhaps in distorted manner, some of the features of the real world ... The main role of models is not so much to explain and to predict - though ultimately these are the main features of science - as to polarize thinking and to pose sharp questions ... They should not, however, be allowed to multiply indiscriminately without real necessity or real purpose.

Kac implies that there are three activities that involve models - "improving thought processes" (as described in the quote above), "studying special systems" (understanding and translating to the specific from the general) and "creating new laws and refining old" (systems research!).

Amen!

Andrea