Social System Stability

The important back story of social system stability to know is that it is computable to a high degree of confidence. Thanks to Rudolf Starkermann, social system stability measurement is straightforward, simple, and breathtakingly reliable. In fact, it is the onset of instability condition that determines when the end of a dynamic simulation run of social behavior has come. We have done thousands of runs ourselves to develop checkpoints in performance. When gain gets too high, performance becomes unstable. It might be counterintuitive to you but it’s boldface reality.

Variety among the individuals in an organization has a great deal to say about the difficulty in creating a stable society. H.S. Dennison, in 1926, covered the subject quite well. Nothing has changed.

Intrinsic Variety

Men vary widely from each other. Anyone who has worked in a large organization will realize that it is by no means a single, completely centralized unit obedient to a single will, but is rather an aggregation of diverse elements with various purposes and wills. In readiness of understanding, in sensitiveness of self-respect, in natural energy, in strength of economic motive, and in speed of response to any stimulus, individual men cover wide ranges.

Their quantitative dispersion over these ranges is not uniform but is like the disposition of their heights and other physical characters—a heavy clustering about a central tendency, or norm, and a running out to highly exceptional cases at either extreme. Along the full range of men, from those who respond most readily to adventure to those who most value security, the men towards the adventurous end of the scale are more actively influenced by chances of profit, accompanied by irregularities of income and risk.

At the other end a steady, safe income wins the most favorable response. For this reason, among others, schemes of profit-sharing or employee investment on the one hand, and of unemployment insurance on the other, will experience a wide variety of reactions. And it is this variety which makes our generalizations so often wide of the mark.

For the small number of workmen, or salesmen, or citizens whom we know really well may be very far from typical of the group as a whole. Besides differing from his neighbors, each man, in response to changes in his environment, himself changes from time to time, not only by growing older but also in other and less predictable ways. The attitudes of both employees and customers are, for example, deeply affected by the swings of the business cycle, responding quite differently in depressions than in times of activity.

Measures which can be easily put into effect at one time may fail entirely at another. Between the two opposite phases of the “great cycle” of prices, as for example, between the last twenty years of the nineteenth century and the first twenty years of this, the differences in the business environment are so many and so great as to demand during the transition period a reconsideration of almost every element of business policy. Recent studies of low-production and high spoilage rates among workers have brought to light some very suggestive examples of the influence which home or other outside conditions can exercise inside the shop; and salesmen and saleswomen are even more sensitive to extra-business influences than factory workers—traveling salesmen most of all.

Good men can go bad and poor ones “get religion” in ways unaccountable when only the influences of the business itself are known. Yet in spite of all their variations, men, like other life forms, can be classified roughly into groups sufficiently homogeneous to be properly subject to general rules, though never so perfectly homogeneous that occasional exceptions need not be made. In a large part of its daily work organization engineering must be making regulations suited to the prevailing characteristics of its group and neglecting the exceptions.

In its fundamental thinking, however, it can never afford to forget that its groupings, departments, and classifications are after all only for its own convenience in formulating its general measures. They do not fully represent the complex natures which actually come under them. Blanket rules—from the laws of a nation to the regulations of a factory—are measures of convenience in management. They are not ends in themselves, but are made to help towards the objectives of the organization.

Even when fitted as well as they should be to the prevailing characteristics of a group, they cannot be supposed to fit all individual cases. Exceptions or individual treatments are not required very often in a well-planned organization, though they are likely to come up anywhere from time to time. An exception may help more than it hurts or hurt more than it helps; management cannot afford to be afraid to think of both possibilities in any given case. The right course of management is obviously to hold between the Scylla of a spineless inconsistency and the Charybdis of a muscle-bound rigidity. Gradually, as this goes on, the “rule of reason” evolves, necessary exceptions become apparent and subgroups are formed.

Rough general classifications give way to finer sub classifications, allowing a progressively nicer fitting of regulation to the regulated. Many early plans of profit sharing dealt with the whole organization in two groups: those of a specified service who participated, and those of less service who did not. Later plans more often divided sharers into manual and managerial workers; and even subdivided each into ranked classes.

Vacations have usually differed as among factory, office, and sales management; now subdivisions along length-of-service lines are common. It is the normal range of variation in these economic and social characteristics of men which is of ordinary daily importance to organization engineering; the exceptional variations form a special field of inquiry for psychiatrists.

Subjected to repeated irritations at home or at work, balked in basic desires, or otherwise out of adjustment, men react in a variety of unexpected ways. Until recent years these have been overlooked or else considered as willful acts to be punished; the possibilities of analysis and removal of causes are now being explored by psychiatry.

Furthermore, newer insights indicate that the mental mechanisms underlying the exceptional or abnormal in behavior are fundamentally the same as those underlying the usual or the normal behavior. The abnormal differs from the normal in degrees only. So far, industrial psychiatry suggests that a considerable increase in organization effectiveness may turn out to be obtainable by appropriate treatment, not merely of the obviously abnormal members, but of those more nearly normal members who suffer some minor maladjustments.

The psychiatrists make persistent protest against wholesale methods of group management, against too much regimentation and rigid regulation. Theirs is a necessary counterbalancing influence to the pressures for economy of time and effort which give rise to blanket rules. They bring management “down to cases.”

The laws of chance and of averages, and the limitations inherent in the conception of the average, are important for the organization engineer to understand. He is in reality dealing with a large number of centers of force, no two of which are exactly alike. He must know and handle “general natures” of groups, “by-and-large” truths, average effects, without overlooking the existence of variability. In organization engineering there are effects to be observed and, when possible, measured, as mass effects or averages. In physics, gas laws can be expressed as if every molecule followed out a line of behavior exactly uniform with every other, and these laws can be correct in the aggregate although not a single molecule actually follows the average course.

Similarly, statements about the general responses of a group of men may be perfectly valid in spite of the fact that one or many contradictory individual responses can be found. But there are discoverable limits within which any group of men can be dealt with as if it were made up entirely of average members. There are cases where not to recognize the essential difference between the conception of average and the reality of heterogeneity is fatal.

More than the physicist, the organization engineer in any but the most elementary organizations needs to know the ranges of variation in the behavior of individuals. If the best effort is to be obtained from each member of a widely varying group, it is clear that there must be a constant refinement in methods of selection and placement; and probably, also, a good deal of readaptation of jobs to the commoner human abilities. Progress must be made in analyzing the demands of different jobs and the strength, dexterity, and temper of the folk who can be set at them.

The individual examination of abnormal cases is also throwing emphasis upon the fact that conditions within any organization are seriously affected by the general influences of the whole social environment. For most organizations, this means that managers must know something of the conditions of the community and adapt themselves to them; and where such conditions are having unsatisfactory effects it means, also, that the organization must be awake to any opportunity to do something towards their betterment.

Social system stability has two components.

Characteristics of the members, attitudes and opinions
Alignment with natural laws, control theory in particular

If copasetic with natural law, organizational stability depends on the psychological states of its membership. The general population is socialized to believe that social system stability is 100% leadership-personality-driven. People don’t consider that attempts to defy control theory end in immediate collapse of social viability. The truth of the stability factor is that control theory sets the limits of stable operations using variables that have no direct linkage to individual characteristics at all. Control theory is an equal indifference employer.

Social stability depends on a handful of variables being within limits, depending upon the values of the other key variables. Every social system dynamic has an exact counterpart in industrial process control. Both are GIGO-disturbed systems. The significant variables include:

Gain
Feedback Lags
Connectance
Quality of control data (good, suspect, bad)
Desynchronization of multiple feedback circuits
Sneak circuits
Unforeseen disturbances

Practical application

History shows that people will live with an abusive regime without complaint as long as it is stable. Each member figures suffering the consequences of dysfunction is better than social chaos. If a society is unstable, for any reason, all cooperation stops in its tracks. For one example, M&A invariably destabilizes both organizations. All work stops with the M&A announcement. Unsurprisingly, over 90% of M&A ventures begin and end in failure. Yet this common performance in no way deters the potentates from throwing their subjects under the M&A bus at the next opportunity to line their pockets. With Nature in charge of social behavior stability, it was entirely appropriate for the distinguished professor of control engineering Rudolf Starkermann to use his expertise to study social behavior. He started work using control theory to understand social behavior dynamics in the 1950s and we joined him in 1986. There is nothing in human social behavior at any scale that does not have a live, running parallel in industrial control. As Starkermann worked with Brown Boveri in factories all over the world, he was well aware of the correspondence.

Social science has measured that fear is the essential lubricant of authoritarians. Accordingly, all tall hierarchies are fear-driven. Although there are many sorts of fears, the paramount fear of the members of a society is instability of their organization. In a mob, prince and pauper have equal social status.

Control theory is a natural law, mathematical physics (Maxwell 1868). Since its mathematics involves matrix calculus, feedback and endless iteration fractal-like, no algebra, most college students avoid taking the subject. As systems become more complex, different branches of control theory come into play. As complexity and multiplicity rise, central control must give way to distributed control. For controlling networks, simple bang/bang hindsight control must give way to preemptive control where regulating action is based on predicting the future. Like mobs, some processes cannot be controlled at all.

The control system itself can cause system instability. If lags are not coordinated or excessive control force is applied (Gain), the control system will go unstable no matter how well system pieces and parts are working. Few autonomous network instabilities are as yet predictable. Why do all the clocks in a mechanical clock shop automatically tick in synch by themselves? Magic?

All ecosystems are under strict control theory regulation. Some parts can act up without making the system unstable. Some parts can fail and take down the whole ecology. The edges of social instability are usually very sharp. Graceful degradation to instability is the exception and not the rule. There is seldom time to patch the dike. In a collective humming along in harmony, all it takes is one member raising his gain above the stability limit and social stability can be lost. Everyone has had the experience.

Sisyphus taking control theory up the mountain, again, By Rob Schouten

History recorded many scenarios when a society destabilized. Everything productivity-wise stops in its tracks. With potentate failure on parade, no one knows who’s “in charge.” With no stable herd sanctuary for security, all members immediately flip into panic mode. Mob behavior is often changing by the hour. Those you looked up to for orders are all frothing at the mouth. The playing field of authority has been pulverized and it is disoriented.

When in danger, when in doubt, run in circles, scream and shout.

All attempts to defy control theory end badly in system destabilization and you don’t have long to wait before the coup de grace is administered. The chances that you can successfully stabilize a large unruly social system without knowing about control theory are zero. That is why predicting social behavior requires a proving ground built out of dynamic simulations running on control theory mathematics (Ashby).

Sooner or later, reality forces you to use intelligence amplification to control for stability. The human brain cannot possibly handle the computational load. The restriction has nothing to do with personality or genius. There are no risk-free short cuts. The Three Mile Island nuclear event was triggered exactly because of false assumptions for making control short cuts. Chernobyl was another control system failure but by allowing manual override.

It is rational to review all the possibilities for system instability and their ugly historical examples and conclude a stable Plan B is impossible. The truth of the matter is that Plan B was first transmuted from Plan A by heavy use of control theory from the start. Plan B viability is maintained by active improvements using control theory. Plan B is stable because of control theory. Because of positive reciprocity, Plan B is impervious to outside attempts at destabilization.

The fact that the population avoids knowing about control theory does nothing to diminish its paramount role in system stability. Navigating without alignment to control theory is the borrowing of trouble for everyone. What doesn’t work for industry doesn’t work for society either.