The Competitiveness of Nations in a Global Knowledge-Based Economy
F. E. Emery and E. L. Trist
Towards A Social Ecology:
Contextual Appreciation of the Future in the
Present
Plenum,
|
Content
Western Societies as the Leading
Part
The Strategy of Overall
Characterization |
Chapter 4
The General Characteristics of Social Fields -
Environmental Levels
Western Societies as the Leading
Part
It was argued in the first section of this paper that
the future will be largely shaped by the choices men make, or fail to make, and
it will not be moulded simply by technical forces; it was argued that processes
existing in the present can reveal some of the basic choices that will confront
men over the next thirty years; and, finally, it was argued that social science
should consider not only the provision of tools (trained personnel,
institutions, theories and methods) but also the more active role of helping men
to extend their visions.
On this basis I shall seek to identify current
developments which are changing the conditions within which men can make their
future, and shall look at these both in terms of the challenges they pose and
the opportunities they create for further human development. This should reveal the areas within which
growth in social scientific knowledge and capabilities can most help men to help
themselves.
Following the conceptual scheme outlined in chapter 2, I
shall move from consideration of the broader social systems to narrower ones.
Following my own judgement,
I shall start from consideration of the total social field of entities such as
the
38
method of approach will be basically that of trying to
answer the two basic questions of system-field relation posed in chapter
2.
Next, I shall assume that the current leading part in
such systems is the productive system - the complex of interrelated
socio-technical organizations concerned with the social (not household production of material goods and
service. For reasons given in
chapter 3, I think that this method of proceeding is preferable to abstracting
common phenotypical characteristic aspects such as the political beliefs or
values. The next step follows the
same procedure of identifying the information and communication industries as
the leading part of the productive system. Because this last step puts us at two
removed from the social field of modern Western nations I will then go back to
see what effect this elaboration of the production system has on the total
system.
Lastly, I shall touch upon the major boundary conditions
of our primary unit. These appear
to be (a) the relation of the modern Western nations to the more inclusive
international field, (b) the biological inputs of these social fields, and (c)
the natural resources upon which they rely.
Throughout, the concern will be with matters on which
the development of the social sciences might have a
bearing.
The Strategy of Overall
Characterization
As pointed out in chapter 2, if there are predictions to
be made about complex systems they are most likely to be valid if they are
derived from analysis of the genotypical characteristics of broader social
fields. This is, of course, only a
theoretical point: we might have little or no information on which to assess the
larger systems. This is, in fact,
the reason for starting with the more limited strategy of choosing the Western
nations as the leading part, although it is evident that they are part of a
larger social field. Nevertheless,
I do not wish to be like the drunk in the story who knew he had lost his watch
up the dark alley but searched under the street lamp because there he had lots
of light. There is a body of
evidence accumulating about the growth characteristics of the Western type of
society. This evidence is not of
the sort that readily permits of graphical or mathematical extrapolation but it
seems to permit of
39
genotypical analysis. I will devote most attention to this
analysis because it provides the framework within which more detailed
predictions of part processes can be made. A simplified version of this analysis has
been published (Emery and Trist, 1965), but so much weight is being placed upon
drawing inferences that the argument should be spelt out more
fully.
In trying to characterize large complex social systems,
I am reminded that some behaviours of both organisms and organizations are a
function of gross overall characteristics of their environment (Chein, 1954).
We can advance our knowledge of
these behaviours if we can identify the properties that best characterize the
overall environment and the system behaviours necessary for adapting to
them.
This is not a new strategy for the social sciences (see
chapter 2). Thus, in psychology the
Lewinians were able to demonstrate the lawful behaviour of
‘human-beings-in-cognitively-unstructured-situations’ and of
‘human-beings-in-overlapping-situations’ (Barker, 1946). A great deal of so-called learning theory
is of the same kind, that is, the study of behaviour in overly simplified
‘conditioning’ situations, structured ‘meaningful’ situations, complexity
structured or ‘problem’ situations, overly complex or ‘puzzle’ situations. Similarly, Chein (1954) has pointed to
the gain that may be had for psychology from the study of environments that in
overall terms are relatively stimulating or stimulus lacking, relatively rich or
poor in goals or noxiants, cues or goal paths, easy to move in or sticky,
etc.
In the field of economic organization, a similar
scientific strategy has yielded the characterization of markets as classical
competitive, imperfectly competitive, oligopolic, monopolistic. These again are attempts to define ideal
types of overall environments and again have been relatively successful in
showing the lawfulness of some of the behaviour of economic
enterprises.
In the field of military organization, the great
post-war disputes over optimum size of operating units, optimum weapon
capabilities for size of unit, optimum organization of support facilities and
command structures have all centred on the problem of the changes in the more
general characteristics of the battlefield environment following the advent of
tactical nuclear weapons.
The solution we sought appeared to be along these lines.
Therefore we concentrated on those
dimensions of the
40
environment which constitute its causal texture
(Emery and Trist, 1965). By
causal texture we meant, following Pepper, Tolman and
For simplicity of exposition we considered the relevant
variables only as goal objects or noxiants for the constituent systems (i.e.
having different relative values for the systems with the values ranging from
positive to negative) and assumed that there is some sense in which these can be
spoken of as more or less distant from or available to the organization and
hence requiring more or less organizational effort to attain or avoid. Already, it will be noted, something has
to be known about the organization in order to delimit the environment in this
way. We have to know what is of
potential value to it and what are possible courses of
action.
For our purposes, we found it necessary to distinguish
only four levels of organization of environments. 1
The simplest form of environment is that in which goals
and noxiants are distributed randomly and independent through the environment.
That is, a placid, random
environment, placid because of heteronomous processes in the environment of the
system. 2
This ideal corresponds to Simon’s ‘surface over which it
(an organism) can locomote. Most of
the surface is perfectly
l. Any attempt to conceptualize a higher order of
environmental complexity would probably involve us in notions similar to
vortical processes. We have not
pursued this because we cannot conceive of adaptation occurring in such fields.
Edgar Allen Poe did go into this
problem in his short story ‘Into the Vortex’. He intuited that there was a survival
tactic if drawn into a whirlpool - namely to emulate an inanimate object. To strive in one’s own way was to perish.
Folklore and natural history are
full of similar lessons about ‘playing possum’, ‘playing dead’. For our purposes we are inclined to
regard these as survival tactics rather than adaptive behaviour. In case there may be something to the
hunch that a type V environment has the dynamics of a vortex it is worthwhile
noting that vortices develop at system boundaries when one system is moving or
evolving very fast relative to the other - like a Watt County, L.A., and between
the developed and underdeveloped countries.
2. We certainly do wish to convey the meanings
associated, for example, with ‘placid tranquillity’. An old-fashioned mad-house or a Nazi
concentration camp could constitute the kind of environment we are defining.
Our choice of the term was largely
dictated by our need for a contrast with the environmental disturbances that
characterize some of the more textured environments.
41
bare, but at isolated, widely scattered points, there
are little heaps of food’. ... ‘.. - the food heaps are distributed randomly’
(Simon, 1956, pp. 129-38). It also
corresponds to Ashby’s limiting case of ‘no connection between the environmental
parts’ (1960, S,15/4); to Toda’s ‘Taros Crater’ (1962, p. 169); and
Schutzenberger’s stochastic environment (1954, pp. 97-102). The economists’ classical market comes
close to this ideal environment. Thus, although this represents an extreme
type of environment, there has been wide recognition of the need to postulate it
as a theoretical limit. The
relevance goes deeper than simply providing a theoretical bench-mark. This low level of organization may
frequently occur as the relevant environment for some secondary aspect of an
organization and is also quite likely to occur in humanly designed environments
for the reason that such simplified environments offer maximum probability of
predicting and controlling human behaviour, e.g. Adler’s ‘Sociology of the
Concentration Camps’ and the experimental environments of conditioning
theory.
The survival of an organization in a placid random
environment is a fairly simple function of the availability these environmental
relevancies and the approach-avoidance tactics available to the system (I.e. its
response capabilities). So long as
the environment retains this random character, it does not make much difference
if there is more than one need and it is not necessary to postulate any complex
organizational capacity for identifying marginal utilities or substitution
criteria. ‘We can go further, and
assert that a primitive choice mechanism is adequate to take advantage of
important economies, if they exist, which are derivable from the interdependence
of the activities involved in satisfying the different needs’ (Simon, 1956, p.
134). We can go even further and
assert that in the absence of differences in relative value - the nearest goal
object being the best - system behaviour in those environments does not involve
choice.
Given that some environments with which we are concerned
may be judged to be ‘random, placid’ in their causal texturing we may still be
concerned with the effects of different degrees of randomness on
survival.
An indication of the importance of these differences is
given by Simon’s consideration of the effects of ‘range of
vision’.
Increased range of vision in a random environment is
equivalent to increasing the area of non-random environment immediately
surrounding the system. From the
computations he makes for his very clean model of the random environment ‘... we
see that the organism’s modest capacity to perform purposive acts (sic)
over a short planning horizon permits it to survive easily in an environment
where random behaviour would lead to rapid extinction. A simple computation shows that its
perceptual powers multiply by a factor of 880 the average speed with which it
discovers food’ (Simon, 1956).
It is not enough just to characterize an environment and
postulate minimum survival characteristics for systems in those
environments. Environment and
system do not just co-exist side by side. They interact to the point of mutual
inter-penetration. Some aspects of
the environment become ‘internalized’ by the system and some aspects of the
system become externalized to become features of the environment. There are three modes of inter-relation
that we will consider for each level of environment:
(1) instrumentality;
(2) planning;
(3) learning.
The first two are forms of interpenetration of the
system into its environment. What
Trist and I labelled as L12 relations; where L11 relations
represent potentially lawful processes within a system, L22 lawful
processes within the environment and L21, L12 the
influences from environment to system and system to environment, respectively
(Emery and Trist, 1965). The third
mode, learning, may and, hopefully, usually does manifest itself in the use of
instruments and planning. However,
I think we come closer to the core of meaning if we look at learning as an
interpenetration of the environment into the system (i.e., as an L21
relation). Viewed in this way
the main concerns of learning theory should be with (a) the informational
structure of different environments, (b) the kinds of behaviour in these
environments that justify the title of ‘learning
behaviour’.
Again we turn to Simon, this time for a good
consideration of the relevance of instrumentality in placid, random
environments. This appears in his
treatment of ‘storage capacity’. Storage capacity is not a response
capability but it
43
may be instrumental in extending or restricting response
capabilities. In an example dealing
with organisms it is natural to think of storage capacity as intrinsic, like a
stomach or fatty tissue, but in thinking about systems this is an irrelevant
assumption - parts of the environment may just as readily be used by the system
for storage purposes. Simon found
that storage capacity was a highly relevant parameter of survival although not
as much so as reduction of randomness. One would expect therefore to find that
systems exposed to these environments would tend to hoard, and to find that this was
adaptive.
The appropriate planning mode in this environment
has been stated very precisely by Schutzenberger, namely that under this
condition of random distribution there is no distinction between tactics and
strategy, and ‘we find that the optimal strategy is just the simple tactic of
attempting to do ones best on a purely local basis’ (Schutzenberger, 1954).
This aptly describes the marketing
approach of successful traders in
Ashby has suggested that the best tactic in the
circumstances can be learnt only on a trial and error basis and only for a
particular class of local environmental variances (Ashby, 1960, p. 1 7). I agree that the circumstances place
peculiar restrictions on learning but not with the suggestion that the
appropriate learning behaviour is trial-and-error. The experimental environments in which
trial-and-error has been observed to be adaptive have been complexly joined
environments - puzzle situations for the organisms concerned (Thorndike, 1911,
Hamilton, 1967). The classical
learning situation most closely corresponding to the placid, random environment
is that devised by Pavlov and his followers. In this situation sound-proofing,
restrictive harness for the animal etc. are used to create a blank unvarying
environment and the animal is exposed to random encounters (that is, random for
the animal) with some goal objects and some other specific stimuli which are
unrelated to the goal objects, except for co-occurrence in space and time
(Pavlov, 1928). It would be
difficult to devise a
44
better reproduction of a random, placid environment.
The learning ‘behaviour’
observed is conditioning not trial-and-error. Strictly speaking there is no behaviour
involved as there is no element of goal-seeking, the system is just
conditioned. Theoretically the
probability of survival should improve as the system is conditioned to take
advantage of any departures from randomness in its
environment.
A final point is that higher order systems must accept
the degrading of their learning to simple conditioning, their strategies to
simply following their noses etc., if they are to survive in these placid
environments. However, as Zener
found with his dogs (Zener, 1937) and Alder found in reviewing human behaviour
in concentration camps, higher order systems will strive to utilize any elements
of non-randomness to create more order and permit themselves to perform closer
to their level.
More textured, but still essentially a placid
environment is that which can be characterized in terms of clustering of the
goals and noxiants. The goals and
noxiants occur together in space and time with varying probabilities that are
potentially knowable for the system.
This level of environmental texturing was introduced by our discussion of
the significance for placid random environments of any reduction of
randomness. It happens to be the
kind of environment with which Tolman and
The structuring that exists at this level of texturing
enables some parts of it to act as signs (local representatives) of other parts
or as means-objects (manipulanda, paths) with respect to approaching or
avoiding. However, as Ashby has
shown, survival is almost impossible if a system attempts to deal tactically
with each environmental variance as it occurs or as it is signalled (signalling
having the effect of multiplying greatly the density of confrontation) (1960, p.
199). Survival in environments of
this kind requires a second-order of feedback involving some sort of threshold
mechanism so that reaction is evoked less
45
readily and only to the more general aspects of the
environment - to the clustering which will reveal itself only through a manifold
of particular occurrences.
This is the critical feature of adaptation to this kind
of environment, namely that choice of strategies emerges as distinctively more
adaptive than choice of tactics. It
no longer follows that ‘a bird in the hand is worth two in the bush’. To pursue the goal object that it can
see, the goal object with which it is immediately confronted, may lead the
system into parts of the field which are fraught with unforeseen difficulties.
Similarly, avoiding a present
difficulty may lead the system away from parts of the environment that are
potentially rewarding. Adaptation
of these environments therefore requires as a minimum that a system be
goal-directed (Sommerhoff, 1969) - that for each of a number of different
concrete situations it has a course of action that is determined more by the
goal it pursues than by the immediate presenting of goals and
noxiants.
In this sort of environment, it becomes possible to seek
a best strategy where optimality is limited only by restrictions upon knowledge.
Survival of a system becomes
conditional upon its knowledge of its environment. In the extreme case, if enough is known
of the structure of the environment so that ‘the map’s projection has been
changed to that of the really optimal matrix, the distinction between strategy
and tactic (again) disappears’ (Schutzenberger, 1954). This differs from the randomized
environment in that here strategy tends to absorb tactics. Given the omnipotence of a
The objective of a system in this type of environment
also has certain characteristics. In the placid, random it could have none,
apart from tactical improvement and hoarding against a rainy day. In this second type the relevant
objective is that of ‘optimal location’. Given that the environment is
non-randomly arranged, some positions can be discerned as potentially richer
than others, and the survival probability will be critically dependent upon
getting to those positions. So much
of management of organizations is concerned with planning, that it is worth
considering some of the approximations that are appropriate in this type of
environment:
(i) Domain selection. The recognition of clustering itself
so
that, at the level of strategic planning, one is
concerned with relatively few clusters which can be approximately characterized
as units instead of with a multitude of individual objects. This lowers the cost of information
gathering and processing;
(ii) the development of a hierarchy of strategies
as in the rules for trouble-shooting in complex equipment; in this way the
off-putting effects of the unexpected occurring may be buffered by modifying
lower order strategies but retaining intact higher order
ones.
(iii) the assignment of step functions to the
values of goals and noxiants instead of trying to act on a continuous range of
value; the average human being, for instance, tends to break a continuum into
five steps (Jordan, 1968, p. 137).
(iv) the backward determination of the strategic path.
This is by far the least demanding
procedure once the strategic objective is selected (Schutzenberger, 1954). This, however, does require subsequent
adjustments of the strategic objective to fit the available
paths.
‘Planning by approximation’ may represent only that
lowest level of planning which Ackoff calls ‘satisficing’ (Ackoff, 1970). Nevertheless it represents what is
possible and adaptive, given the information structure of a placid clustered
environment. By definition an
environment is only of this type when the system is limited to information about
the relative probabilities of co-occurrence of goals and
noxiants.
Naturally the planning behaviour reflects the
learning behaviour that is possible. Systems are no longer limited to mere
conditioning. This was clearly
demonstrated by Zener (1937) when he duplicated the classical conditioning
experiments with one modification: he freed the dogs of much of the restraining
harness so that they could react to textural characteristics of the experimental
setting, other than just the conditioned and unconditioned stimuli. The learning behaviour he observed, and
filmed, was not conditioned behaviour but goal directed meaningful behaviour.
The major characteristics of
this type of learning have been studied and formulated by
Tolman:
(1) The organism brings to a problematic situation
various
47
systematic modes of attack, based largely on prior
experiences.
(2) The cognitive field is provisionally organized
according to the hypotheses of the learner, the hypotheses that survive being
those which best correspond with reality, that is, with the causal texture of
the environment. These hypotheses
or expectancies are confirmed by successes in goal
achievement.
(3) A clearly established cognitive structure is
available for use under altered conditions, as when a frequently used path is
blocked.
The third relation we have been considering,
instrumentality, is also different in this environment. In the placid random environment the
instrumental relation seems to be limited to variety-reducing forms such as
hoarding and hiding (reducing the effects of environmental variation in goals
and noxiants respectively). In the
placid. clustered environment there is evidence that systems can use parts of
the environment to increase the variety of courses of action open to them, i.e.
to use them as tools. The classical
experimental demonstration of this is Kohler’s work with apes (Kohier, 1927).
As originally reported these
studies suggested that the experimental situation presented such a richly
textured environment for the apes that their successful learning to use tools
must manifest a higher order than just meaningful learning. It seemed that apes were capable of
purposeful problem solving with the insights into causal structures that that
implies. However, the knowledge
that has now accumulated about the innate response capabilities of apes makes it
fairly certain that their tool using was in response to an environment which was
for them only placid and clustered (Chance, 1960).
Disturbed
Reactive Environment
The next distinguishable level of causal texturing is
one that we have called the disturbed-reactive environment. It approximates to Ashby’s
ultrastable system and the economists’ oligopolic market. In this we simply postulate a placid
clustered environment in which there is more than one system of the same kind,
and hence the environment that is relevant to the
48
survival of one is relevant to the survival of the
other. Formally, one could
postulate a placid random environment with more than one system present, but I
do not think that co-presence makes any difference to the concepts one needs to
explain what differences in randomness would occur in that environment (which
might be why the social sciences have such difficulties in linking up with so
called reinforcement theories of learning). Co-presence makes a real difference in a
placid, clustered environment because the survival of the individual
systems requires some strategy as well as tactics. In this environment, each system does not
simply have to take account of the other when they meet at random, but it has to
consider that, what it knows about the environment can be known by another.
That part of the environment to
which it wishes to move is probably, for the same reason, the part to which the
other wants to move. Knowing this,
they will wish to improve their own chances to do likewise, but will know that
they know this. In a word, the
presence of others will imbricate some of the causal strands in the environment. The causal texture of the
environment will, through the reactions of others, be partly determined by the
intentions of the acting organization. However, the environment at large still
provides a relatively stable ground for the arenas of system conflict. Because of this, conflicting systems
‘regarded as a unit, will form a whole which is ultrastable’ (Ashby, 1960, p.
209).
How can competing systems constitute a stable unit in a
disturbed, reactive environment? Given the relatively static nature of the
environment within which the competition occurs, then it is possible (as it was
for the individual organization in placid clustered environment) for strategies
to evolve that limit the disruptive effects of competitive strategies or
competitive tactics. One would
expect these strategies to be broader and take longer to emerge than those
needed in a placid, clustered environment. They would not, however, differ in
principle.
By starting from consideration of the causal texture of
the environment and the way information flows from this, we avoid the dilemma of
the economists’ models of imperfect competition, duopoly etc. As
despite the observable fact that stability is commonly
achieved.
One could maintain that this sort of disturbed reactive
environment makes no difference to the distinction between strategy and tactics
that we made for placid, clustered environments. I am inclined to think that it does.
If strategy is selecting the
‘strategic objectives’ - where one wishes to be at a
future time – and tactics is selecting an immediate action from one’s available
repertoire then there appears in
these environment to be an intermediate level. One has not simply to make sequential
choices of actions (tactical decisions) such that each handles the immediate
situation and yet they hang together by each bringing one closer to the
strategic objective; instead one has to choose actions that will draw off the
other organizations in order that one may proceed. The new element is that of choosing not
only your own best tactic, but also of choosing which of someone else’s tactics
you wish to invoke. Movement
towards a strategic objective in these environments seems therefore to
necessitate choice at an intermediate level - choice of an operation
3 of campaign
in which are involved a planned series of tactical initiatives, predicted
reactions by others and counteraction. At this level the adoptive system is not
just the one that can produce the right tactic for the right occasion (i.e. the
goal directed system) but one that can choose the appropriate
tactic.
If one tries to identify the level of system that is
adaptive to disturbed reactive environments the critical criteria is that a
system must be able, in at least some situations, to choose between two or more
tactical moves either of which could further its ends, i.e. it must be a
purposeful system.
There seems little doubt that even the formulation of
strategic objectives is influenced by this kind of environment. It is much less appropriate to define the
objective in terms of
3. Cf. the use by German and Soviet military theorists
of the three levels – tactics-operations-strategy
50
location in some relatively static and persisting
environment. It is much more
necessary to define the objective in terms of developing the capacity or
power needed to be ab1e to move more or less at will in the face of
competitive challenge. In business
this would probably make it necessary to define objectives in terms of
profitability, not profit. This
formulation has an advantage in this kind of environment, in that there can be a
day-to-day feedback of information relevant to this objective. In the former case, the day-to-day
feedback about approach to a given location (e.g. percentage of market) may be
extremely misleading. It may
conceal the fact that the competitor has made the going easy by conserving his
strength for a later stage (e.g. preparing to introduce an improved
product).
The factors in this kind of environment that make it
desirable to formulate strategic objectives in power terms also give particular
relevance to strategies of absorption and parasitism. It is one thing in a placid random
environment if other things can be characterized as goals or noxiants - they are
either absorbed for the temporary sustenance they afford, or else avoided
because noxious. It is another
thing in a disturbed, reactive environment when the other, itself a system, has
to be absorbed or be absorbed into because it is potentially noxious - because
it is a source of important but unpredictable variance.
So far, with respect to this level of environment, we
have discussed neither learning nor instrumentality. In our discussion of planning it seemed
clear that the strategic objective of maximizing power dictates a corresponding
mode of ‘planning for the best solution’ (what Ackoff calls ‘optimizing’ -
to do as well as possible’,
Ackoff, 1970). We can now ask, what
kind of learning behaviour in this environment enables a system to do this sort
of planning?
The first part of the answer lies, as might be expected,
in the changed informational structure of the environment. A placid clustered environment yields
only information of concomitance (probable co-occurrence of goals and of
noxiants). In a disturbed-reactive
environment, with its independent causal agents, it becomes possible to
distinguish between what is system action and environmental response and what
is environmental pressure and system response. In other words, it
51
becomes possible for a system to ‘learn’ the causal
patterning of its environment. One
further step in learning seems critical in this environment. Given that the other systems can also
learn the underlying causal patterning, and direct their behaviour accordingly,
it is necessary to learn the possible and probable recombinations of the causal
pattern. This I suggest is the sort
of learning that is involved in chess and other such genuine exercises in
problem-solving (De Groot, 1965; Wertheimer, 1959).
As regards instrumentality, it is enough to note that
the adaptive distinctions between strategy, operations and tactics enable a
system to use parts of the environment to change other parts to the status of
too1s: in other words, to act as tool makers. There seems to be no inherent restriction
in these environments to elaborating such tools to the point where they are
fully adaptive to placid clustered environments.
The most complexly textured environments in which
adaptive behaviour is possible, as distinct from sheer survival tactics, are
‘turbulent fields’. These
are environments in which there are dynamic processes arising from the field
itself which create significant variances for the component systems. Like the disturbed reactive and unlike
the placid random and placid clustered, they are dynamic environments.
Unlike the disturbed reactive, we
are postulating dynamic properties that arise not simply from the interaction of
the systems, but also from the field itself.
There are undoubtedly important instances in which these
dynamic field properties arise quite independently of the systems in the social
field (as with some of the earth and water movements in mining). However, in the conceptual series we are
here elaborating, most significance attaches to the case where the dynamic field
processes emerge as an unplanned consequence of the actions of the constituent
systems; that is, those environments that represent a transformation disturbed
reactive environments. Fairly
simple examples of this may be seen in fishing and lumbering where competitive
strategies, based on an assumption that the environment is static, may, by
over-fishing and over-cutting, set off disastrous dynamic
processes in the fish and plant populations with the
consequent destruction of all the competing social systems. We have recently become more aware of
these processes through the intervention of the ecologists in problems of
environmental pollution. It is not
difficult to see that even more complex dynamic processes are triggered off in
human populations.
There are four trends that have particularly contributed
to the emergence of these turbulent environments. Before stating these, however, let me
briefly state that these fields are so complex, so richly textured, that it
is difficult to see how individual systems can, by their own efforts,
successfully adapt to them. Strategic planning and collusion can
no more ensure stability in these turbulent fields than can tactics in the
clustered and reactive environments. If there are solutions, they lie
elsewhere.
The four trends that have together contributed most to
the emergence of dynamic field forces are:
(i) The growth, to meet disturbed reactive conditions of
organizations and linked sets of organizations that are so large that their
actions are persistent enough and strong enough to induce autochthonous
processes in the environment (I am here postulating an effect similar to that of
a company of soldiers marching in step over a bridge or the pulsating budgetary
requirements of the U.S., Soviet military establishments).
(ii) The deepening interdependence between the economic
and the other facets of the society. The growing size and relative importance
of the individual units not only creates interdependence within their economic
environment; it also produces interdependence between what consumers want and
what they think can be produced, between the citizen as consumer, as producer,
as inhabitant, and as a social and political entity. This greater interdependence, when
matched with the independent increase in the power of other citizen roles means
that economic organizations are increasingly enmeshed in public reaction and in
legislation and public regulation of what they do or might think of doing. The consequences that flow from the
actions of organizations lead off in ways that are unpredictable. In particular the emergence of active
field forces (forces other than those stemming from the individual organizations
or the similar organizations competing with it) means that the effects will not
tend to fall off ‘with the square
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of the distance from the source’ but may at any point be
amplified or attenuated beyond all expectation. As a case in point, thalidomide
as a simple cure for morning sickness created a major crisis for the
international pharmaceutical industry and initiated a radical redefinition of
responsibilities in one of the relations between science and the society. Similarly, lines of action that are
strongly pursued may find themselves unexpectedly attenuated by emergent field
forces, e.g. the
For organizations, these changes mean primarily a gross
increase in their area of relevant uncertainty.
(iii) The increasing reliance upon scientific research
and development to achieve the capacity to meet competitive challenge (which
capacity, we suggested, tends to become the strategic objective in disturbed
reactive environments). This has
the effect not only of increasing the rate of change, but of deepening the
interdependence between organizations and their environments. Choices that once appeared to arise from
the marketplace are now seen as being taken by the organization on behalf of the
customer - they are seen as manipulators of desire or, as with thalidomide,
sorcerers’ apprentices. It is not
hard to imagine an organization finishing up in the dock of public opinion
because it chose a line of technical development that appeared to suit its own
needs but eventually left the economy in the lurch. The same trend appears in fields of
public policy-making where competition over the allocation of resources is
increasingly conducted by means of scientific research and
analysis.
(iv) The radical increase in the speed, scope and
capacity of intra-species communication. Telegraph, telephone, radio, radar,
television, gramophone, typewriter, linotype, camera, duplicator, Xerox,
calculator, Hollerith, computer: these names register a century of change that
continues in an explosive fashion. Parallel with these has been a very great
increase in speed and ease of travel, so that recorded communications flow in
greater bulk at greater speed, and even the recording of communications becomes
short circuited as it becomes easier for managers, scientists and politicians
etc. to fly to each other than to correspond. We may recall that Trotter (1916) in
searching for the conditions underlying social reactivity in living populations,
postulated only two critical conditions: (a) some
special sensitivity to their own kind; (b) some
intra-species communication system. The change that has taken place in
intra-species communication is a greater mutation than if man had grown a
second head. The consequences are a
great increase in the information burden and a radical reduction in response
time in the system - a reduction which is unaffected by distance. Reaction takes place almost before action
is formed. Even simple
servo-systems with these properties readily get entangled in erratic ‘hunting’
behaviours. As the information
burden approaches ‘overload’ it invites, in fact demands, radical
counter-measures which tend to be maladaptive and increasingly
unpredictable.
We will probably find that these trends are only part of
the picture. However, they are in
themselves real enough and may explain why we feel that consideration of the
turbulent fields is a matter of central importance and not just a theoretical
exercise.
What is less clear is how our society can adapt to these
conditions. Ashby very wisely
counsels that there may not be a solution to this problem:
As the system is made larger (and is richly joined), so
does the time of adaptation tend to increase beyond all bounds of what is practical; in other words,
the ultrastable system probably fails. But this failure does not discredit the
ultrastable system, as a model of the brain for such an environment is one that
is also likely to defeat the living brain (1960, p.207).
However, as a biologist, Ashby offers us the consolation
that: ‘Examples of environments that are both rich, large and richly connected
are not common, for our terrestrial environment is widely characterized by being
highly subdivided’ (1960, p. 205).
It is my belief that this sort of environment is, in fact, characteristic
of the human condition: that in some areas of his living man has always had to
contend with turbulent environments. What is true is that just as the central
matching process of consciousness has evolved to help protect the human
organisms from information overload (Tomkins, Vol.11, p. 14), so has man evolved
his symbolic cultures to provide a man-made environment of tolerable complexity.
What is significant of our present
era is the emergence of a degree of social organizational complexity and a rate
of coalescence of previously segregated populations that
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defy our current efforts at symbolic reductionism. Larger and larger parts of the lives of
more and more people are being lived in conditions of environmental
turbulence.
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