Introduction          Introduction         Introduction          Introduction         

By definition, a system is composed of interrelated parts. In systems theory, the degree of interrelationship is termed the "wholeness" of the system. If the operation of every part of a system is related to every other part, wholeness is said to be high. And in fact, an outcome measure taken from any part of such a system will represent the effectiveness of every part of the system to the extent that other parts enter into the outcome. Because all parts are interrelated, all of the outcome measures taken from this system will be complex measures reflecting the operation of every other part of the system and will be substantially Interco related.

 For logical purposes, it is useful to contrast a system of high wholeness to a non-system in which no parts are interrelated. Measures of outcome would not reflect the operation of other parts measured and would not be Interco related. This is so obvious that it seems silly. But the converse, stated above, is not so easily grasped: outcome measures from different parts of a system are correlated because those outcomes are jointly determined by common parts of the system.

  What we hope is obvious is that the parts of the system themselves are interrelated but are theoretically independent in their unique operation. The only way to demonstrate this independence is to obtain less complex measures of outcome of that particular part of the system which are free of the effects of other parts of the system. As an example, the quality of the library staff would be one variable contributing to library size, A test of librarianship skills could be devised and administered to the library staff It would certainly be expected that the results of this test would be less correlated with university quality than would be library size. That is, the more molecular the measure, the less intimately it would be expected to he related to global indices of system functioning. However, more molecular measures would give more specific information about system functioning,

 We believe the same holds true for mental ability. Certainly the human mind is a well‑integrated system having a high degree of wholeness. Wholeness is reflected in complex measures of human ability, which explains the high correlations between standard tests of intelligence. Simpler, more molecular measures should be individually less highly correlated with more complex measures but should provide more specific information about the operation of the system.

 Management sciences have learned a great deal about organizations and how they work. Much of this learning has come from adopting the perspective that organizations are entities (systems, defined later), much like people, plants and animals. There are many benefits to leaders who adopt this systems view of their organizations.

 Systems thinking has its foundation in the field of system dynamics, started in 1956 by MIT professor Jay Forrester. Professor Forrester recognized the need for a better way of testing new ideas about social systems, in the same way we can test ideas in engineering. Systems thinking allows people to make their understanding of social systems explicit and improve them in the same way that people can use engineering principles to improve their understanding of mechanical systems.

 Systems thinking are fast becoming a powerful tool for decision-making and organizational change. All employees in a company should be equipped with the skills necessary for systems thinking. It is imperative to have some awareness of the origin of systems thinking and how it can be of benefit to various types of organizational change, such as reengineering, systems integration, process redesign, Total Quality Management, and teamwork. In order to apply systems thinking to challenges that occur in the work place, some of the tools and methodologies used in systems thinking should be taught. Some of the best known strategies used to implement systems thinking include systems modelling, simulations, causal loops, archetypes, and scenario planning. To meet the complex changes that are inevitable, systems thinking can no longer be esoteric knowledge held by few managers, but should be accessed by all.

 The approach of systems thinking is fundamentally different from that of traditional forms of analysis. Traditional analysis focuses on separating the individual pieces of what is being studied; in fact, the word “analysis” actually comes from the root meaning “to break into constituent parts.” Systems thinking, in contrast, focuses on how the thing being studied interacts with the other constituents of the system – a set of elements that interact to produce behavior – of which it is a part.

 The character of systems thinking makes it extremely effective on the most difficult types of problems to solve: those involving complex issues, those that depend a great deal on the past or on the actions of others, and those stemming from ineffective coordination among those involved. Examples of areas in which systems thinking has proven its value include:

§Complex problems that involve helping many actors see the “big picture” and not just their part of it.

§Recurring problems or those that have been made worse by past attempts to fix them.

§Issues where an action affects (or is affected by) the environment surrounding the issue, either the natural environment or the competitive environment.

 System Thinking stresses the systemic pattern of thinking (Systemic is the attribute of thinking derived from systems approach).