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Management Cybernetics

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Complex System Governance

Part of the book series: Topics in Safety, Risk, Reliability and Quality ((TSRQ,volume 40))

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Abstract

The purpose of this chapter is to examine Management Cybernetics as a primary underpinning for Complex System Governance (CSG). The origins of Management Cybernetics and how the Viable System Model (VSM) can be used to model systems (organizations) as a means of understanding control and governance within an organization are suggested. The central tenets of the Management Cybernetics field are surveyed. The essential background for the Viable System Model (VSM) is provided as a critical foundation for CSG. This background includes the historical basis of the VSM, basic laws of cybernetics, the characteristics of the VSM, and the relationship between cybernetics and control for the VSM. The approach to system modeling with the VSM is provided. The five systems of the VSM are presented in detail with respect to their unique role within the model. Additionally, interactions within the VSM are examined. The communication channels within the VSM are explained. The chapter closes with a set of exercises.

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Author information

Authors and Affiliations

  1. National Centers for System of Systems Engineering, Old Dominion University, Norfolk, VA, 23,529, United States of America

    Joseph Sisti

Authors
  1. Joseph Sisti
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Correspondence to Joseph Sisti .

Editor information

Editors and Affiliations

  1. Department of Engineering Management and Systems Engineering, Old Dominion University, Norfolk, VA, USA

    Charles B. Keating

  2. Department of Informatics and Engineering Systems, University of South Carolina Upstate, Spartanburg, SC, USA

    Polinpapilinho F. Katina

  3. Engineering Management and Systems Engineering, Old Dominion University, Norfolk, VA, USA

    Charles W. Chesterman Jr.

  4. Engineering Management and Systems Engineering, Old Dominion University, Norfolk, VA, USA

    James C. Pyne

Glossary of Terms

Algorithm

A comprehensive set of instructions for reaching a known goal [10, p. 401].

Anastomotic

the variety of reticulum expected to see in cybernetics; refers to the fact that the many branches of the network intermingle to such purpose that it is no longer possible to sort out quite how the messages traverse the reticulum [10, p. 30].

Autonomous

A law onto itself; function indicated is responsible for its own regulation [10, p. 103].

Cybernetics

concerned with the general patterns, laws and principles of behavior that characterize complex, dynamic, probabilistic, integral, and open systems [15, p. 19] about the manner of control, all kinds of structure, all sorts of systems [17].

Feedback

The return of part of a system’s output to its input, which is thereby changed. Positive feedback takes an increase in output back to increase the input; negative feedback takes back an output increase to decrease the input—and is therefore stabilizing in principle [10, p. 402].

Feedback Law

“The output of a complex system is dominated by the feedback and, within limits, the input is irrelevant” [15, p. 28].

Filter

A variety reducer [10, p. 94].

Heuristic

Serving to find out; specifies a method of behaving which will tend towards a goal which cannot be precisely specified because we know what it is but not where it is [10, p. 52].

Holistic Systems

Systems whose important characteristics are not ascertainable from the properties of the system components [15, p. 26].

Homeostasis

Wherever one system impinges on the other, it recognizes a match which is normal to their coexistence [10, p. 145].

Invariant

A mathematical term; one thing is invariant with respect to something else; it doesn’t change as the other thing changes [10, p. 87].

Models

More than analogies; they are meant to disclose the key structure of the system under study; a model is good if it is appropriate [10, p. 75, 84].

Regulation

to select certain results from those that are possible [15, p. 70].

Requisite Variety Law

Given a system and some regulator of that system, the amount of regulation attainable is absolutely limited by the variety of the regulator” [15, p. 36].

Self-Organizing Systems Principle

Complex systems organize themselves; the characteristic structural and behavior patterns in a complex system are primarily a result of the interactions among the system parts” [15, p. 26].

Sensorium

anything within a system that can register and classify the existence of a stimulus [10, p. 28].

SIC

Sensory Input Channel.

State

of the system is defined as a particular allocation of forms to events, given a particular configuration of events [10, p. 144].

Variety

The total number of possible states of a system, or an element of a system [10, p. 403]. The measure of the “number of possible states of whatever it is whose complexity we want to measure” [9, p. 23]. The technical expression for complexity of the systems or the number of states a system may have.

ViabilityPrinciple

ViabilityThe ability of a system to maintain a separate existence and depends on a number of necessary conditions [9, p. 199].

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Sisti, J. (2022). Management Cybernetics. In: Keating, C.B., Katina, P.F., Chesterman Jr., C.W., Pyne, J.C. (eds) Complex System Governance. Topics in Safety, Risk, Reliability and Quality, vol 40. Springer, Cham. https://doi.org/10.1007/978-3-030-93852-9_5

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  • DOI: https://doi.org/10.1007/978-3-030-93852-9_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-93851-2

  • Online ISBN: 978-3-030-93852-9

  • eBook Packages: EngineeringEngineering (R0)

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