General Systemantics (retitled to Systemantics in its second edition and The Systems Bible in its third) is a systems engineering treatise by John Gall in which he offers practical principles of systems design based on experience and anecdotes.
It is offered from the perspective of how not to design systems, based on system engineering failures. The primary precept of the treatise is that large complex systems are extremely difficult to design correctly despite best intentions, so care must be taken to design smaller, less-complex systems and to do so with incremental functionality based on close and continual touch with user needs and measures of effectiveness.
The term systemantics is a commentary on prior work by Alfred Korzybski called General Semantics which conjectured that all systems failures could be attributed to a single root cause--a failure to communicate. Dr. Gall observes that, instead, system failure is an intrinsic feature of systems. He thereby derives the term 'General Systemantics' in deference to the notion of a sweeping theory of system failure, but attributed to an intrinsic feature based on laws of system behavior. He observes as a side-note that system antics also playfully captures the concept that systems naturally "act up."
Educator Lawrence J. Peter's widely cited Peter Principle -- "In a hierarchy every employee tends to rise to his level of incompetence ... in time every post tends to be occupied by an employee who is incompetent to carry out its duties ... Work is accomplished by those employees who have not yet reached their level of incompetence."
By "systems", the author refers to those that "...involve human beings, particularly those very large systems such as national governments, nations themselves, religions, the railway system, the post office..." though the intention is that the principles are general to any system.
Additionally, the author observes.
Everything is a system.
Everything is part of a larger system.
The universe is infinitely systematized, both upward (larger systems) and downward (smaller systems).
Once a system is set up to solve some problem, the system itself engenders new problems relating to its development, operations and maintenance. The author points out that the additional energy required to support the system can consume the energy it was meant to save. This leads to the next principle.
The total amount of anergy in the universe is fixed.
The author defined anergy as the effort required to bring about a change. This was meant as a tongue-in-cheek analog of the law of conservation of energy.
Systems tend to expand to fill the known universe.
One of the problems that a system creates is that it becomes an entity unto itself that not only persists but expands and encroaches on areas beyond the original system's purview.
Why systems behave poorly
Complicated systems produce unexpected outcomes [Generalized Uncertainty Principle].
The author cites a number of spectacular unexpected behaviors including:
The Aswan Dam diverting the Nile River's fertilizing sediment to Lake Nasser (where it is useless) requiring the dam to operate at full electrical generating capacity to run the artificial fertilizer plants needed to replace the diverted sediment.
Not only do systems expand well beyond their original goals, but as they evolve they tend to oppose even their own original goals. This is seen as a systems theory analog of Le Chatelier's principle that suggests chemical and physical processes tend to counteract changed conditions that upset equilibrium until a new equilibrium is established. This same counteraction force can be seen in systems behavior. For example, incentive reward systems set up in business can have the effect of institutionalizing mediocrity.
This leads to the following principle.
Systems tend to oppose their own proper function.
What's in a name
People performing roles in systems often do not perform the role suggested by the name the system gives that person, nor does the system itself perform the role that its name suggests.
People in systems do not actually do what the system says they are doing [Functionary's Falsity].
The system itself does not actually do what it says it is doing. [The Operational Fallacy]
The real world is what is reported to the system [The Fundamental Law of Administrative Workings (F.L.A.W.)].
In other words, the system has a severely censored and distorted view of reality from biased and filtering sensory organs which displaces understanding of the actual real-world which pales and tends to disappear. This displacement creates a type of sensory deprivation and a kind of hallucinogenic effect on those inside the systems, causing them to lose common sense. In addition to negatively affecting those inside the system, the system attracts to it people who are optimized for the pathological environment the system creates. Thus,
Systems attract systems-people
Elementary systems functions
A complex system cannot be "made" to work. It either works or it doesn't.
A simple system, designed from scratch, sometimes works.
Some complex systems actually work.
A complex system that works is invariably found to have evolved from a simple system that works.
A complex system designed from scratch never works and cannot be patched up to make it work. You have to start over, beginning with a working simple system.
Advanced systems functions
The Functional Indeterminacy Theorem (F.I.T.): In complex systems, malfunction and even total non-function may not be detectable for long periods, if ever.
The Newtonian Law of Systems Inertia: A system that performs a certain way will continue to operate in that way regardless of the need or of changed conditions.
Systems develop goals of their own the instant they come into being.
Intrasystem goals come first.
The Fundamental Failure-Mode Theorem (F.F.T.): complex systems usually operate in a failure mode.
A complex system can fail in an infinite number of ways. (If anything can go wrong, it will; see Murphy's law.)
The mode of failure of a complex system cannot ordinarily be predicted from its structure.
The crucial variables are discovered by accident.
The larger the system, the greater the probability of unexpected failure.
"Success" or "Function" in any system may be failure in the larger or smaller systems to which the system is connected.
The Fail-Safe Theorem: When a Fail-Safe system fails, it fails by failing to fail safe.
Practical systems design
The Vector Theory of Systems: Systems run better when designed to run downhill.
Loose systems last longer and work better. (Efficient systems are dangerous to themselves and to others.)
Management and other myths
Complex systems tend to produce complex responses (not solutions) to problems.
Great advances are not produced by systems designed to produce great advances.
Other laws of systemantics
As systems grow in size, they tend to lose basic functions.
The larger the system, the less the variety in the product.
Control of a system is exercised by the element with the greatest variety of behavioral responses.