Systems Thinking and the Internet from Independence to Interdependence

Systems Thinking and the Internet from Independence to Interdependence

Kambiz E. Maani (The University of Queensland, Australia)
DOI: 10.4018/978-1-60566-026-4.ch582
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Abstract

Despite our most impressive advances in sciences and technology, our prevailing worldview and the way we work and relate is deeply rooted in the thinking that emerged during the Renaissance of the 17th century! This thinking was influenced by the sciences of that era and in particular by Newtonian physics. Newton viewed the world as a machine that was created to serve its master–God, (Ackoff, 1993). The machine metaphor and the associated mechanistic (positivist) worldview, which was later extended to the economy, society, and the organization, has persisted until today and is evident in our thinking and vocabulary. The mechanistic view of the enterprise became less tenable in the 20th century partly due to the emergence of the corporation and the increasing prominence of human relation issues in the workplace. Today, this way of thinking has reached its useful life – The futurist, Alvin Toffler declared in 1991 “the Age of the Machine is screeching to a halt”. For well over a century, the western world has subscribed to a way of thinking known as analysis (Ackoff, 1995). In analysis, in order to understand things—a concept, a product, a law, an organization, human body—we break it into pieces and study the pieces separately. This approach tends to overlook the interdependencies and connections between the constituent parts, which are responsible for dynamic change in systems, say aging in human body. On the one hand, this “divide and conquer” approach has served us well in the past. It has enabled efficient mass production of goods and services, which has brought a new social and economic order creating unprecedented wealth and standards of living in the industrialized world. On the other hand, this thinking has resulted in over-fragmentation and has created complexity and cross-purposes within organizations. In the early part of the 20th century, a new breed of scientists, in particular quantum physicists such as Werner Heisenberg (Uncertainty Principle) and Norbert Weiner (Cybernetics) began to challenge the Newtonian precepts (Zohar & Marshal, 1994). In 1968, Austrian biologist Von Bertalanffy (1968) published “General Systems Theory”—a major departure from conventional fragmentation in science. Similarly, Jay Forrester of MIT introduced and demonstrated the applications of feedback theory in organizations (Forrester, 1958). Forrester’s seminal work marks the birth of a new discipline known as System Dynamics. System Dynamics is concerned with applications of systems theory and computer modeling in complex problems in business, economics, and the environment. System Dynamics is the forerunner and the scientific foundation of Systems Thinking. Today, biologist and physicists as well as social and cognitive scientists are working on new fields such as complexity and network theory, and Gaia theory. These emerging fields come under the broader umbrella of “systems theory” or “living systems” and “they are working in the systems sciences and are contributing to advancing the integrated, systemic understanding of life” (Capra, 2007).
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Background

The major intellectual and philosophical precepts that form the bedrock of our modern society, such as free-market economics, mass production, division of labor, and scientific management embed the following machine age characteristics (Zohar et al., 1994):

  • The hierarchy

  • Need for certainty, stability, and the absolute

  • Treating organizations and the society as consisting of isolated, separate and interchangeable parts

  • Relationships based on conflict and confrontation (rationality and self-interest)

  • Desire for control and bureaucratic methods

  • Persistence of “single points of view” leading to friction and polarisation

  • Over-emphasis on specialist expertise, leading to fragmentation and loss of relevance

Key Terms in this Chapter

System Dynamics: Is a scientific tool which embodies principles from biology, ecology, psychology, mathematics, and computer science to model complex and dynamic systems.

Causal Loop Diagram (CLD): A tool that captures the causal interrelationships amongst a set of variables. CLDs reveal systemic patterns underlying complex relationships and highlight hidden causes and unintended consequences.

System: Is a purposeful entity whose parts interact with each other to function as a whole. Thus, a system is not the sum of its parts—it is the product of their interactions (Ackoff, 1993 AU27: The in-text citation "Ackoff, 1993" is not in the reference list. Please correct the citation, add the reference to the list, or delete the citation. ). A system can be part of a larger system.

Leverage: Leverage knows which actions may yield long lasting outcomes. It knows where and when to intervene/influence a system to gain long lasting desired change using minimal effort and energy.

Stock: is the accumulation of a variable such as asset, debt, energy, morale, and reputation. Stock represents the status of a variable at a given point in time, that is, a snapshot of reality.

Systems Delay: Is the time lapse between action and response. Delays often destabilize the system and slow a system down from reaching its goal. Systems delays often mask anticipated outcomes as well as unintended consequences of actions as the intervening time lapse is often longer than expected.

Flow: or rate is the amount of change in a variable over time. Flow represents the change in the status of a variable over a specified time unit.

Systems Thinking: Is thinking holistically and conscientiously about the world by focusing on the interaction of the parts and their influence within and over the system.

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