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Figure 6.3.
Beer's classification of systems. Source: S. Beer,
Cybernetics and Man-
agement
(London: English Universities Press, 1959), 18.
first two types (subdividing them further into “deterministic” and “probabi-
listic” systems). Under “simple” came the window catch, billiards, machine
shop layout, penny tossing, jellyfish movements, and statistical quality con-
trol; under “complex” we find electronic digital computers, planetary systems,
automation, stockholding, conditioned reflexes and industrial profitability.
What those examples have in common, according to Beer, is that they are in
principle knowable and predictable, and thus susceptible to the methods of
the traditional sciences. Physics tells us about billiard balls; statistics about
penny tossing; OR about stockholding and industrial profitability—this last,
of course, being especially relevant to Beer. OR was, then, a classical science
of production, a science appropriate to those aspects of the world that are
knowable and predictable, in the same space as modern physics. However,
under “exceedingly complex” systems (which, according to Beer, can have
only probabilistic forms) we find just three examples: the economy, the brain,
and the company. And Beer's claim was that these are “very different” (Beer
1959, 17):
The country's economy, for example, is so complex and so probabilistic that it
does not seem reasonable to imagine that it will ever be fully described. The
second, living, example—the human brain—is also described in this way. More-
over, it is notoriously inaccessible to examination. . . . Inferential investigations
about its mode of working, from studies such as psychiatry and electroencepha-
lography, are slowly progressing.
Probably the best example of an
industrial
system of this kind is the Com-
pany itself. This always seems to me very much like a cross between the first
