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In the narrow sense, systems analysis is the set of methodological techniques used in devising and substantiating solutions to complex political, military, social, economic, scientific, and technical problems. In the broad sense, the term “systems analysis” is sometimes used, especially in English, as a synonym for what is called in Russian systems approach.
The methods of systems analysis are necessary to the solution of the aforementioned problems primarily because in the process of making decisions, choices must be made under conditions of uncertainty that result from the presence of factors not subject to strict quantitative evaluation. The procedures and methods of systems analysis are aimed precisely at setting forth alternative variations of a solution to the problem, identifying the scale of uncertainty for each variation, and comparing variations according to particular efficiency criteria. Specialists in systems analysis only prepare or recommend variations of a solution; the decision-making remains within the jurisdiction of the appropriate official or agency.
Intensive expansion of the sphere of use of systems analysis is closely linked with the spread of the target-program method of administration, in which a program is specially drawn up to solve an important problem, an organization, establishment, or network of establishments is formed, and the necessary material resources are allocated. The first broad program of this sort was the GOELRO (State Commission for the Electrification of Russia) plan worked out in 1920 on the basis of V. I. Lenin’s instructions. The experience garnered in this project was used to carry out the industrialization of the USSR and to draw up five-year plans for national economic development.
In the developed capitalist countries, above all the USA, systems analysis came into use in private business in the 1950’s in solving such problems as the distribution of production capacities for different types of articles, determining future needs for new equipment and particular categories of workers, and predicting demand for different types of output. At the same time, the use of systems analysis is spreading to the sphere of government administration, above all in solving problems related to the development and technical equipping of the armed forces and the exploration of space. Systems analysis techniques were used in the USA in carrying out the programs to build the B-58 jet bomber, in the construction of strategic missiles and air-defense weapons, and in the comparative evaluation of weapons systems.
The International Institute for Applied Systems Analysis (IIASA), which was founded in Laxenburg, near Vienna, in 1972, has 12 member countries, including the USSR and the USA. It works on the application of systems analysis methods primarily to problems requiring international cooperation, for example, the protection of the environment, the development of the resources of the world’s oceans, and the joint use of drainage basins that extends across international borders.
General systems theory and the systems approach are considered the foundation of systems analysis. From them, however, systems analysis borrows only the most general, initial concepts and premises. Its methodological status is very unusual. On the one hand, systems analysis possesses detailed methods and procedures drawn from modern science and specially created for it, which puts systems analysis in the same category with the other applied areas of modern methodology. On the other hand, there is no tendency to shape it into a strict and final theory. Elements of science and practice are closely interwoven in systems analysis. Therefore, the substantiation of decisions using systems analysis does not necessarily involve the use of exact, formalized methods and procedures. Judgments based on personal experience and intuition are also possible, provided this circumstance is clearly acknowledged. The chief principles of systems analysis may be reduced to the following: the decision-making process should begin with the identification and precise formulation of final goals; the entire problem must be viewed as a whole, as a single system, and all the consequences and interrelationships of each particular decision must be identified; possible alternate ways to achieve the goal must be identified and analyzed; and the goals of individual subdivisions must not conflict with the goals of the entire program.
The central procedure in systems analysis is constructing a generalized model or models depicting all the factors and interrelationships of the real situation that may appear in the process of implementing the solution to the problem. The resulting model is studied in order to clarify how close any of the alternate variations of action will come to achieving the desired result, to learn the comparative resource expenditures for each variation, and to establish how sensitive the model is to various undesirable external influences. Systems analysis relies on a number of applied mathematical disciplines and techniques used extensively in present-day administrative activity, including operations research, the expert evaluation method, the critical path method, and the theory of queues. The technical basis used in systems analysis consists of modern computers and information systems.
The methodological means used in solving problems by systems analysis are determined by whether a single goal is being pursued or some group of goals, by whether one person is making the decision or several, and so on. When there is a single, sufficiently clear goal whose degree of attainment can be assessed on the basis of a single criterion, the methods of mathematical programming are used. If the degree of attainment of the goal must be evaluated on the basis of several criteria, elements of the theory of usefulness are used in ordering the criteria and determining the importance of each one. When the development of events depends on the interaction of several persons or systems, each of whom is pursuing individual goals and making individual decisions, the methods of game theory are used.
Although the range of simulation and problem solving techniques used in systems analysis is steadily broadening, systems analysis is not by nature equivalent to scientific investigation. It is not connected with the problems of obtaining scientific knowledge in the strict sense; rather, it is only the application of scientific methods to the solution of practical problems of control and administration, and it pursues the goal of rationalizing the process of decision-making, not precluding the inevitable subjective aspects from this process.
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Novoe v teorii i praktike upravleniia proizvodstvom v SShA. Moscow, 1971. (Translated from English.)
SShA: sovremennye metody upravleniia. Moscow, 1971.
Johnson, R., F. Kast, and J. Rosenzweig. Sistemy i rukovodstvo. Moscow, 1971. (Translated from English.)
Gvishiani, D. M. Organizatsiia i upravlenie, 2nd ed. Moscow, 1972.
Nikanorov, S. P. “Systemnyi analiz i systemnyi podkhod.” In Sistemnye issledovaniia: Ezhegodnik, 1971. Moscow, 1972.
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B. G. IUDIN
systems analysis[′sis·təmz ə‚nal·ə·səs]
The application of mathematical methods to the study of complex human physical systems. A system is an arrangement or collection of objects that operate together for a common purpose. The objects may include machines (mechanical, electronic, or robotic), humans (individuals, organizations, or societal groups), and physical and biological entities. Everything excluded from a system is considered to be part of the system's environment. A system functions within its environment. Examples of systems include the solar system, a regional ecosystem, a nation's highway system, a corporation's production system, an area's hospital system, and a missile's guidance system. A system is analyzed so as to better understand the relationships and interactions between the objects that compose it and, where possible, to develop and test strategies for managing the system and for improving its outcomes.
The term “systems analysis” is reserved for the study of systems that include the human element and behavioral relationships between the system's human element and its physical and mechanical components, if any. Examples of public policy systems are the federal government's welfare system, a state's criminal justice system, a county's educational system, a city's public safety system, and an area's waste management system. Examples of industrial systems are a manufacturer's production distribution system and an oil company's exploration, production, refining, and marketing system. Examples with physical environmental components are the atmospheric system and a water supply system. The direct transfer of systems engineering concepts to the study of a system in which the human element must be considered is restricted by limitations in the ability to comprehend and quantify human interactions. (Operations research, a related field of study, is directed toward the analysis of components of such systems. Public policy analysis is the term used for a system study of a governmental problem area.) See Operations research, Systems engineering
Systems comprise interrelated objects, with the objects having a number of measurable attributes. A mathematical model of a system attempts to quantify the attributes and to relate the objects mathematically. The resultant model can then be used to study how the real-world system would behave as initial conditions, attribute values, and relationships are varied systematically. See Model theory
The systems analysis process is an iterative one that cycles repeatedly through the following interrelated and somewhat indistinct phases: (1) problem statement, in which the system is defined in terms of its environment, goals, objectives, constraints, criteria, actors (decision makers, participants in the system, impacted constituency), and other objects and their attributes; (2) alternative designs, in which solutions are identified; (3) mathematical formulation, in which a mathematical description of the system is developed, tested, and validated; (4) evaluation of alternatives, in which the mathematical model is used to evaluate and rank the possible alternative designs by means of the criteria; and (5) selection and implementation of the most preferred solution. The process includes feedback loops in which the outcomes of each phase are reconsidered based on the analyses and outcomes of the other phases. For example, during the implementation phase, constraints may be uncovered that hinder the solution's implementation and thus cause the mathematical model to be reformulated. The analysis process continues until there is evidence that the mathematical structure is suitable; that is, it has enough validity to yield answers that are of value to the system designers or the decision maker. See Optimization, Simulation
As originally developed, systems analysis studies have been applied to those areas that are “hard” in that they are well defined and well structured in terms of objectives and feasible alternative systems (for example, blood-bank design, and integrated production and inventory processes). The aim of hard systems analysis is to select the best feasible alternative. In contrast, soft systems are concerned with problem areas that involve ill-defined and unstructured situations, especially those that have strong political, social, and human components. These generally involve public and private organizations (for example, design of a welfare system, and structure and impact of a corporate mission statement). The objectives of soft systems and the means to accomplish them are problematical and, in fact, a systemic view of the problem area is not assumed. The aim of soft systems analysis is to find a plan of action that accommodates the different interests of its human actors.
There is also need for further study of large-scale systems, which by definition are most complex. It is important to find ways to describe mathematically the systems that represent the totality of an industrial organization, the pollution concerns of a country and a continent, or the worldwide agricultural system. These are multicriteria problems with the solutions conflicting across criteria, individuals, and countries. The possibility that such systems may be studied in a computer-based laboratory is very promising. But this challenge must be approached cautiously, with the awareness that the methods and models employed are only abstractions to be used with due consideration of the goals of the individual and society.